From 07031577fcbd44b1fa9148699635edaceb597697 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Mon, 25 Apr 2022 12:07:22 -0300 Subject: [PATCH 01/19] cli quick lab instructions --- adapter-guide/cli-quick-lab.md | 191 +++++++++++++++++++++++++++++++++ 1 file changed, 191 insertions(+) create mode 100644 adapter-guide/cli-quick-lab.md diff --git a/adapter-guide/cli-quick-lab.md b/adapter-guide/cli-quick-lab.md new file mode 100644 index 000000000..4aa7202aa --- /dev/null +++ b/adapter-guide/cli-quick-lab.md @@ -0,0 +1,191 @@ +# STIX-Shifter CLI Quick Lab + +## Overview + +STIX (Structured Threat Information eXpression) is a JSON structure used to share cybersecurity threat intelligence. STIX-shifter is an open-source python library that is part of the Open Cybersecurity Alliance. It allows data repositories to be queried using STIX patterning and return the results as STIX cyber observable objects. This lab will allow users to test out the various stix-shifter CLI commands. + +## Setup + +### 1. Open a terminal and install the required stix-shifter libraries + +``` +pip install stix-shifter stix-shifter-utils stix-shifter-modules-stix_bundle stix-shifter-modules-qradar +``` + +This installs the core stix-shifter and utils library along with the stix-bundle and QRadar connectors. + +### 2. Store the STIX bundle URL in a bash variable + +``` +BUNDLE_URL=https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json +``` + +### 3. Store the sample result JSON in a bash variable + +``` +JSON_RESULTS=$(cat <Mar 21 01:42:50 microsoft.windows.test.com", + "url": null, + "magnitude": 8, + "filename": null, + "filehash": null, + "sha1hash": null, + "sha256hash": null, + "md5hash": null, + "filepath": null, + "eventseverity": 7, + "credibility": 10, + "relevance": 8, + "sourcegeographic": "Europe.France", + "destinationgeographic": "other", + "domainname": "Default Domain", + "EventID": "529", + "Image": "null", + "ParentImage": "null", + "ProcessCommandLine": "null", + "ParentCommandLine": "null", + "TargetImage": "null", + "GrantedAccess": null, + "CallTrace": null, + "SourceImage": "null", + "PipeName": "null", + "StartModule": "null", + "StartFunction": "null", + "Signed": null, + "Message": null, + "RegistryValueName": null, + "IMPHash": null, + "ServiceFileName": "null", + "RegistryKey": null, + "ObjectName": "null", + "UrlHost": "null", + "ProcessName": null, + "ProcessId": null, + "ParentProcessId": null + } +] +EOF +) +``` + +## Lab Steps + +### 1. Examine the STIX Bundle + +This is a bundle of STIX observed-data objects containing sanitized data from a CrowdStrike instance. + +https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json + +The stix_bundle connector will query the sample STIX bundle and return a subset of data based on the query pattern. + +### 2. Run the execute command + +``` +stix-shifter execute stix_bundle stix_bundle '{"type": "identity","id": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff","name": "stix-bundle","identity_class": "system"}' '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' "[ipv4-addr:value = '12.111.222.0']" +``` + +The execute command runs through the entire stix-shifter flow: + +- Translates a STIX pattern into a native data source query +- Sends the query to the data source via the data source APIs +- Checks the status of the query via the data source APIs +- Fetches the query results via the APIs and, if needed, converts them to JSON +- Translates the JSON results into STIX objects + +Note the bundle of observed-data objects that are returned. Each of these objects contains a numbered set of cyber observable objects (url, network-traffic, ipv4-addr…) which contain the data from the target data source. Given the above CLI example, the ipv4-addr object should contain a value property with 12.111.222.0 + + +## STIX Transmission CLI commands + +The transmission commands use the data source APIs to send a query, check the status, fetch the results, and ping the connection. + +### 3. Run the ping command + +``` +stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' ping +``` + +This command checks that the data source can be reached by the stix-shifter connector. + +### 4. Run the query command + +``` +stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' query "[ipv4-addr:value = '192.168.0.8']" +``` + +This command sends the native query to the data source. + +### 5. Run the status command + +``` +stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' status "[ipv4-addr:value = '192.168.0.8']" +``` + +This command checks the status of the query. + +### 6. Run the results command + +``` +stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' results "[ipv4-addr:value = '192.168.0.8']" 0 2 +``` + +This command fetches the query results + + +## Translation mapping for QRadar + + +### 7. Examine the STIX pattern to AQL mapping file for the QRadar connector + +https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/qradar/stix_translation/json/events_from_stix_map.json + +This file determines how STIX objects and their properties are mapped to the target data source fields. + +### 8. Run the STIX query translation CLI command for the QRadar connector + +``` +stix-shifter translate qradar:events query '{}' "[ipv4-addr:value = '109.0.216.203' AND file:name = 'photos.exe'] OR [url:value = 'blah.com' OR url:value = 'path.com' OR url:value = 'crhs.ca']" +``` + +This command passing in a STIX pattern and returns a list of native data source queries that can later be passed to a query transmission call. + +### 9. Examine the JSON to STIX mapping file for the QRadar connector + +https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/qradar/stix_translation/json/to_stix_map.json + + +### 10. Run the JSON results translation CLI command for the QRadar connector + +``` +stix-shifter translate qradar results '{"type": "identity","id": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff","name": "QRadar","identity_class": "system"}' "$JSON_RESULTS" +``` + +This command passes in a STIX identity object and a list of JSON results (each element in the list represents a row of data). A bundle of STIX objects is returned. The bundle contains the identity object, which represents the data source the data comes from, and an observed-data object for each of the rows that were translated. + From 415e45f53ec4a0007a1d60c5c323402e0aaea39b Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Wed, 27 Apr 2022 06:13:13 -0600 Subject: [PATCH 02/19] reorder step description --- adapter-guide/cli-quick-lab.md | 40 +++++++++++++++++++--------------- 1 file changed, 23 insertions(+), 17 deletions(-) diff --git a/adapter-guide/cli-quick-lab.md b/adapter-guide/cli-quick-lab.md index 4aa7202aa..b3c25ea6c 100644 --- a/adapter-guide/cli-quick-lab.md +++ b/adapter-guide/cli-quick-lab.md @@ -8,20 +8,24 @@ STIX (Structured Threat Information eXpression) is a JSON structure used to shar ### 1. Open a terminal and install the required stix-shifter libraries +This installs the core stix-shifter and utils library along with the STIX-bundle and QRadar connectors. + ``` pip install stix-shifter stix-shifter-utils stix-shifter-modules-stix_bundle stix-shifter-modules-qradar ``` -This installs the core stix-shifter and utils library along with the stix-bundle and QRadar connectors. - ### 2. Store the STIX bundle URL in a bash variable +This is a bundle of sample STIX data that will be used to demonstrate the `stix_bundle` connector. + ``` BUNDLE_URL=https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json ``` ### 3. Store the sample result JSON in a bash variable +This is a list of JSON objects containing sample data that will be used to demonstrate STIX translation. + ``` JSON_RESULTS=$(cat < Date: Wed, 27 Apr 2022 06:52:31 -0600 Subject: [PATCH 03/19] add step for install virtual env --- adapter-guide/cli-quick-lab.md | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/adapter-guide/cli-quick-lab.md b/adapter-guide/cli-quick-lab.md index b3c25ea6c..ea7f7b53b 100644 --- a/adapter-guide/cli-quick-lab.md +++ b/adapter-guide/cli-quick-lab.md @@ -6,7 +6,14 @@ STIX (Structured Threat Information eXpression) is a JSON structure used to shar ## Setup -### 1. Open a terminal and install the required stix-shifter libraries +### 1. Open a terminal and install a Python Virtual Environment + +``` +pip install virtualenv +virtualenv -p python3.9 virtualenv && source virtualenv/bin/activate +``` + +### 2. Install the required stix-shifter libraries This installs the core stix-shifter and utils library along with the STIX-bundle and QRadar connectors. @@ -14,7 +21,7 @@ This installs the core stix-shifter and utils library along with the STIX-bundle pip install stix-shifter stix-shifter-utils stix-shifter-modules-stix_bundle stix-shifter-modules-qradar ``` -### 2. Store the STIX bundle URL in a bash variable +### 3. Store the STIX bundle URL in a bash variable This is a bundle of sample STIX data that will be used to demonstrate the `stix_bundle` connector. @@ -22,7 +29,7 @@ This is a bundle of sample STIX data that will be used to demonstrate the `stix_ BUNDLE_URL=https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json ``` -### 3. Store the sample result JSON in a bash variable +### 4. Store the sample result JSON in a bash variable This is a list of JSON objects containing sample data that will be used to demonstrate STIX translation. From de582d0b4b4094a65b5b80fb36ac99cd593df1e6 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 28 Apr 2022 06:26:15 -0600 Subject: [PATCH 04/19] use venv to create virtual environment --- adapter-guide/cli-quick-lab.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/adapter-guide/cli-quick-lab.md b/adapter-guide/cli-quick-lab.md index ea7f7b53b..36e075b1c 100644 --- a/adapter-guide/cli-quick-lab.md +++ b/adapter-guide/cli-quick-lab.md @@ -9,8 +9,8 @@ STIX (Structured Threat Information eXpression) is a JSON structure used to shar ### 1. Open a terminal and install a Python Virtual Environment ``` -pip install virtualenv -virtualenv -p python3.9 virtualenv && source virtualenv/bin/activate +python3 -m venv labenv +source labenv/bin/activate ``` ### 2. Install the required stix-shifter libraries From 4353c3b32deb00c5b51253177fc465846b85ac8f Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 28 Apr 2022 08:24:31 -0600 Subject: [PATCH 05/19] Explaination on STIX objects --- adapter-guide/cli-quick-lab.md | 155 +++++++++++++++++++++++++-------- 1 file changed, 117 insertions(+), 38 deletions(-) diff --git a/adapter-guide/cli-quick-lab.md b/adapter-guide/cli-quick-lab.md index 36e075b1c..2a50c8f3a 100644 --- a/adapter-guide/cli-quick-lab.md +++ b/adapter-guide/cli-quick-lab.md @@ -4,6 +4,110 @@ STIX (Structured Threat Information eXpression) is a JSON structure used to share cybersecurity threat intelligence. STIX-shifter is an open-source python library that is part of the Open Cybersecurity Alliance. It allows data repositories to be queried using STIX patterning and return the results as STIX cyber observable objects. This lab will allow users to test out the various stix-shifter CLI commands. +### STIX Patterning + +A [STIX pattern](http://docs.oasis-open.org/cti/stix/v2.0/cs01/part5-stix-patterning/stix-v2.0-cs01-part5-stix-patterning.html) is used to query [cyber observable objects](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html). STIX patterns take the format of: + +`[: = 'some value' AND : IN (value_1, value_2)] OR [: = 'some value']` + +The `[ ]` represents one observation. A pattern can have multiple observations joined by the AND or OR observation operators. An observation can be thought of as one instance or row of data. Within the observation is one or more comparison expressions that looks for a value associated to a cyber observable STIX object and its property. This is a sample pattern with one observation containing an comparison operation for an IP lookup: `[ipv4-addr:value = '1.2.3.4']`. The STIX object in this case is `ipv4-addr` and the property on that object is `value`. + +### STIX Observed Data + +STIX-shifter returns a `bundle` of STIX `observed-data` objects. The bundle is just a container object to hold the results. Below is a sample bundle containing one identity object (representing the data source) and one observed-data object: + +```json +{ + "type": "bundle", + "id": "bundle--57d455df-105d-4722-8277-e569110e82ed", + "objects": [ + { + "type": "identity", + "id": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff", + "name": "QRadar", + "identity_class": "system" + }, + { + "id": "observed-data--4db61897-4725-483b-9e68-2874e48650c5", + "type": "observed-data", + "created_by_ref": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff", + "created": "2022-04-28T14:16:41.544Z", + "modified": "2022-04-28T14:16:41.544Z", + "objects": { + "0": { + "type": "x-oca-event", + "action": "Logon Failure - Unknown user name or bad password", + "outcome": "Host Login Failed", + "category": [ + "Authentication" + ], + "provider": "Microsoft Windows Security Event Log", + "agent": "WindowsAuthServer @ microsoft.windows.test.com", + "created": "2021-06-28T19:35:58.000Z", + "network_ref": "2", + "user_ref": "4", + "url_ref": "7", + "file_ref": "8" + }, + "1": { + "type": "ipv4-addr", + "value": "109.0.216.203" + }, + "2": { + "type": "network-traffic", + "src_ref": "1", + "src_port": 3000, + "dst_ref": "3", + "dst_port": 1000, + "protocols": [ + "TCP" + ] + }, + "3": { + "type": "ipv4-addr", + "value": "192.168.1.11" + }, + "4": { + "type": "user-account", + "user_id": "bill_holland" + }, + "5": { + "type": "ipv4-addr", + "value": "0.0.0.0" + }, + "6": { + "type": "artifact", + "payload_bin": "PDEzPk1hciAyMSAwMTo0Mjo1MCBtaWNyb3NvZnQud2luZG93cy50ZXN0LmNvbQ==", + "mime_type": "text/plain" + }, + "7": { + "type": "url", + "value": "www.example.com" + }, + "8": { + "type": "file", + "name": "myfile.exe", + "hashes": { + "SHA-256": "86c5ceb27e1bf441130299c0209e5f35b88089f62c06b2b09d65772274f12057" + }, + "parent_directory_ref": "9" + }, + "9": { + "type": "directory", + "path": "C://filepath" + } + }, + "first_observed": "2021-06-28T19:35:58.652Z", + "last_observed": "2021-06-28T19:36:58.652Z", + "number_observed": 31 + } + ], + "spec_version": "2.0" +} +``` + +Each observed-data object contains a numbered set of cyber-observable objects. + ## Setup ### 1. Open a terminal and install a Python Virtual Environment @@ -51,55 +155,27 @@ JSON_RESULTS=$(cat <Mar 21 01:42:50 microsoft.windows.test.com", - "url": null, + "url": "www.example.com", "magnitude": 8, - "filename": null, - "filehash": null, - "sha1hash": null, - "sha256hash": null, - "md5hash": null, - "filepath": null, + "filename": "myfile.exe", + "sha256hash":"86c5ceb27e1bf441130299c0209e5f35b88089f62c06b2b09d65772274f12057", + "filepath": "C://filepath/", "eventseverity": 7, "credibility": 10, "relevance": 8, "sourcegeographic": "Europe.France", - "destinationgeographic": "other", + "destinationgeographic": "Canada", "domainname": "Default Domain", - "EventID": "529", - "Image": "null", - "ParentImage": "null", - "ProcessCommandLine": "null", - "ParentCommandLine": "null", - "TargetImage": "null", - "GrantedAccess": null, - "CallTrace": null, - "SourceImage": "null", - "PipeName": "null", - "StartModule": "null", - "StartFunction": "null", - "Signed": null, - "Message": null, - "RegistryValueName": null, - "IMPHash": null, - "ServiceFileName": "null", - "RegistryKey": null, - "ObjectName": "null", - "UrlHost": "null", - "ProcessName": null, - "ProcessId": null, - "ParentProcessId": null + "EventID": "529" } ] EOF @@ -176,9 +252,10 @@ stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' re ### 7. Examine the STIX pattern to AQL mapping file for the QRadar connector +This file determines how STIX objects and their properties are mapped to the target data source fields. + https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/qradar/stix_translation/json/events_from_stix_map.json -This file determines how STIX objects and their properties are mapped to the target data source fields. ### 8. Run the STIX query translation CLI command for the QRadar connector @@ -191,6 +268,8 @@ stix-shifter translate qradar:events query '{}' "[ipv4-addr:value = '109.0.216.2 ### 9. Examine the JSON to STIX mapping file for the QRadar connector +This file determines how fields returned in the data source results are mapped to SIX objects and their properties. + https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/qradar/stix_translation/json/to_stix_map.json From 2ea1989cf5c485e958fd6d94d1fb90d2835abecf Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 28 Apr 2022 15:38:24 -0600 Subject: [PATCH 06/19] explaination around cyber observables --- adapter-guide/cli-quick-lab.md | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/adapter-guide/cli-quick-lab.md b/adapter-guide/cli-quick-lab.md index 2a50c8f3a..67f01b057 100644 --- a/adapter-guide/cli-quick-lab.md +++ b/adapter-guide/cli-quick-lab.md @@ -14,7 +14,7 @@ The `[ ]` represents one observation. A pattern can have multiple observations j ### STIX Observed Data -STIX-shifter returns a `bundle` of STIX `observed-data` objects. The bundle is just a container object to hold the results. Below is a sample bundle containing one identity object (representing the data source) and one observed-data object: +STIX-shifter returns a `bundle` of STIX `observed-data` objects. The bundle is a container object to hold the results. Below is a sample bundle containing one identity object (representing the data source) and one observed-data object: ```json { @@ -106,10 +106,17 @@ STIX-shifter returns a `bundle` of STIX `observed-data` objects. The bundle is j } ``` -Each observed-data object contains a numbered set of cyber-observable objects. +Each observed-data object contains a numbered set of cyber-observable objects. The properties on the cyber-observable object store the data returned from the data source. See the [STIX 2.0 standard](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html) for more on cyber observable objects. ## Setup +### Prerequisites + +* Python 3 +* pip +* venv +* Ability to run bash commands + ### 1. Open a terminal and install a Python Virtual Environment ``` From aa852b430a4e3b2980d2f2773ef89d4d8a260ba4 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 25 Aug 2022 07:06:42 -0300 Subject: [PATCH 07/19] Add jupyter notebooks for tutorials --- .../STIX-Shifter Connector Tutorial.ipynb | 863 +++++++++ notebooks/STIX-shifter CLI Quick Lab.ipynb | 1660 +++++++++++++++++ 2 files changed, 2523 insertions(+) create mode 100644 notebooks/STIX-Shifter Connector Tutorial.ipynb create mode 100644 notebooks/STIX-shifter CLI Quick Lab.ipynb diff --git a/notebooks/STIX-Shifter Connector Tutorial.ipynb b/notebooks/STIX-Shifter Connector Tutorial.ipynb new file mode 100644 index 000000000..ca681e46c --- /dev/null +++ b/notebooks/STIX-Shifter Connector Tutorial.ipynb @@ -0,0 +1,863 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "9e68b07c", + "metadata": {}, + "source": [ + "# Setup\n", + "## Prerequisites\n", + "* Python 3\n", + "* pip\n", + "* venv\n", + "* Ability to run bash commands\n", + "1. Open a terminal and install a Python Virtual Environment\n", + "\n", + "`python3 -m venv labenv`\n", + "\n", + "`source labenv/bin/activate` Do I need to create this in Jupyter?\n", + "\n", + "2. Install jupyter notebook\n", + "`pip install notebook`\n", + "\n", + "3. Run jupyter notebook\n", + "`jupyter notebook`" + ] + }, + { + "cell_type": "markdown", + "id": "347e7f76", + "metadata": {}, + "source": [ + "### Fork repo, clone project, create working branch" + ] + }, + { + "cell_type": "markdown", + "id": "523d4cd8", + "metadata": {}, + "source": [ + "### Clone the STIX-Shifter Project" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "cab2798e", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Cloning into 'stix-shifter'...\n" + ] + } + ], + "source": [ + "%%bash\n", + "if [ ! -d \"stix-shifter\" ]\n", + "then\n", + " git clone https://github.com/delliott90/stix-shifter.git\n", + "else\n", + " echo \"STIX-Shifter project has already been cloned\"\n", + "fi\n", + "# git clone https://github.com/delliott90/stix-shifter.git" + ] + }, + { + "cell_type": "markdown", + "id": "00b77153", + "metadata": {}, + "source": [ + "### Create environment variables for the project path" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "97e5ec3b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "env: STIX_SHIFTER_PATH=/Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter\n", + "env: IDENTITY_OBJECT={\"type\":\"identity\",\"id\":\"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\"name\":\"STIX Demo\",\"identity_class\":\"system\", \"created\": \"2022-04-07T20:35:41.042Z\", \"modified\": \"2022-04-07T20:35:41.042Z\"}\n" + ] + } + ], + "source": [ + "%env STIX_SHIFTER_PATH /Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter\n", + "%bookmark SS_PATH /Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter\n", + "%env IDENTITY_OBJECT {\"type\":\"identity\",\"id\":\"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\"name\":\"STIX Demo\",\"identity_class\":\"system\", \"created\": \"2022-04-07T20:35:41.042Z\", \"modified\": \"2022-04-07T20:35:41.042Z\"}\n" + ] + }, + { + "cell_type": "markdown", + "id": "b9f742de", + "metadata": {}, + "source": [ + "### Generate required libraries used by STIX-Shifter" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "b36fc48e", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "requirements_files: ['stix_shifter/requirements.txt', 'stix_shifter_modules/onelogin/requirements.txt', 'stix_shifter_modules/reversinglabs/requirements.txt', 'stix_shifter_modules/mysql/requirements.txt', 'stix_shifter_modules/mysql/stix_translation/json/stix-shifter/stix_shifter_modules/onelogin/requirements.txt', 'stix_shifter_modules/mysql/stix_translation/json/stix-shifter/stix_shifter_modules/reversinglabs/requirements.txt', 'stix_shifter_modules/mysql/stix_translation/json/stix-shifter/stix_shifter_modules/mysql/requirements.txt', 'stix_shifter_modules/mysql/stix_translation/json/stix-shifter/stix_shifter_modules/datadog/requirements.txt', 'stix_shifter_modules/mysql/stix_translation/json/stix-shifter/stix_shifter_modules/sumologic/requirements.txt', 'stix_shifter_modules/mysql/stix_translation/json/stix-shifter/stix_shifter/requirements.txt', 'stix_shifter_modules/datadog/requirements.txt', 'stix_shifter_modules/sumologic/requirements.txt']\n", + "install_requires: ['adal==1.2.7', 'antlr4-python3-runtime==4.8', 'boto3==1.21.21', 'colorlog==6.6.0', 'datadog_api_client==1.2.0', 'flask==2.0.3', 'flatten_json==0.1.13', 'jsonmerge==1.8.0', 'mysql-connector-python==8.0.25', 'onelogin==2.0.1', 'pyOpenSSL==21.0.0', 'python-dateutil==2.8.2', 'requests_toolbelt==0.9.1', 'stix2-matcher==3.0.0', 'stix2-patterns==1.3.2', 'stix2-validator==3.0.2', 'sumologic-sdk==0.1.13', 'uuid==1.30', 'xmltodict==0.13.0']\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://pypi.org/simple\n", + "Requirement already satisfied: adal==1.2.7 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 1)) (1.2.7)\n", + "Requirement already satisfied: antlr4-python3-runtime==4.8 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 2)) (4.8)\n", + "Requirement already satisfied: boto3==1.21.21 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 3)) (1.21.21)\n", + "Requirement already satisfied: colorlog==6.6.0 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 4)) (6.6.0)\n", + "Requirement already satisfied: datadog_api_client==1.2.0 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 5)) (1.2.0)\n", + "Requirement already satisfied: flask==2.0.3 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 6)) (2.0.3)\n", + "Requirement already satisfied: flatten_json==0.1.13 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 7)) (0.1.13)\n", + "Requirement already satisfied: jsonmerge==1.8.0 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 8)) (1.8.0)\n", + "Requirement already satisfied: mysql-connector-python==8.0.25 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 9)) (8.0.25)\n", + "Requirement already satisfied: onelogin==2.0.1 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 10)) (2.0.1)\n", + "Requirement already satisfied: pyOpenSSL==21.0.0 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 11)) (21.0.0)\n", + "Requirement already satisfied: python-dateutil==2.8.2 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 12)) (2.8.2)\n", + "Requirement already satisfied: requests_toolbelt==0.9.1 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 13)) (0.9.1)\n", + "Requirement already satisfied: stix2-matcher==3.0.0 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 14)) (3.0.0)\n", + "Requirement already satisfied: stix2-patterns==1.3.2 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 15)) (1.3.2)\n", + "Requirement already satisfied: stix2-validator==3.0.2 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 16)) (3.0.2)\n", + "Requirement already satisfied: sumologic-sdk==0.1.13 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 17)) (0.1.13)\n", + "Requirement already satisfied: uuid==1.30 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 18)) (1.30)\n", + "Requirement already satisfied: xmltodict==0.13.0 in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 19)) (0.13.0)\n", + "Requirement already satisfied: astroid==1.6.2 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 2)) (1.6.2)\n", + "Requirement already satisfied: attrs==17.4.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 3)) (17.4.0)\n", + "Requirement already satisfied: autopep8==1.3.4 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 4)) (1.3.4)\n", + "Requirement already satisfied: coverage==4.5.1 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 5)) (4.5.1)\n", + "Requirement already satisfied: flake8==3.5.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 6)) (3.5.0)\n", + "Requirement already satisfied: isort==4.3.4 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 7)) (4.3.4)\n", + "Requirement already satisfied: lazy-object-proxy==1.3.1 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 8)) (1.3.1)\n", + "Requirement already satisfied: mccabe==0.6.1 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 9)) (0.6.1)\n", + "Requirement already satisfied: more-itertools==4.1.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 10)) (4.1.0)\n", + "Requirement already satisfied: pluggy==0.6.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 11)) (0.6.0)\n", + "Requirement already satisfied: py==1.10.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 12)) (1.10.0)\n", + "Requirement already satisfied: pycodestyle==2.3.1 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 13)) (2.3.1)\n", + "Requirement already satisfied: pyflakes==1.6.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 14)) (1.6.0)\n", + "Requirement already satisfied: pylint==1.8.3 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 15)) (1.8.3)\n", + "Requirement already satisfied: pytest==3.5.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 16)) (3.5.0)\n", + "Requirement already satisfied: pytest-cov==2.5.1 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 17)) (2.5.1)\n", + "Requirement already satisfied: six==1.11.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 18)) (1.11.0)\n", + "Requirement already satisfied: wrapt==1.10.11 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 19)) (1.10.11)\n", + "Requirement already satisfied: requests_mock==1.7.0 in /usr/local/lib/python3.9/site-packages (from -r requirements-dev.txt (line 20)) (1.7.0)\n", + "Requirement already satisfied: requests<3,>=2.0.0 in /usr/local/lib/python3.9/site-packages (from adal==1.2.7->-r requirements.txt (line 1)) (2.28.1)\n", + "Requirement already satisfied: cryptography>=1.1.0 in /usr/local/lib/python3.9/site-packages (from adal==1.2.7->-r requirements.txt (line 1)) (37.0.4)\n", + "Requirement already satisfied: PyJWT<3,>=1.0.0 in /usr/local/lib/python3.9/site-packages (from adal==1.2.7->-r requirements.txt (line 1)) (2.4.0)\n", + "Requirement already satisfied: botocore<1.25.0,>=1.24.21 in /usr/local/lib/python3.9/site-packages (from boto3==1.21.21->-r requirements.txt (line 3)) (1.24.46)\n", + "Requirement already satisfied: s3transfer<0.6.0,>=0.5.0 in /usr/local/lib/python3.9/site-packages (from boto3==1.21.21->-r requirements.txt (line 3)) (0.5.2)\n", + "Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/local/lib/python3.9/site-packages (from boto3==1.21.21->-r requirements.txt (line 3)) (1.0.1)\n", + "Requirement already satisfied: certifi in /usr/local/lib/python3.9/site-packages (from datadog_api_client==1.2.0->-r requirements.txt (line 5)) (2022.6.15)\n", + "Requirement already satisfied: urllib3>=1.15 in /usr/local/lib/python3.9/site-packages (from datadog_api_client==1.2.0->-r requirements.txt (line 5)) (1.26.11)\n", + "Requirement already satisfied: click>=7.1.2 in /usr/local/lib/python3.9/site-packages (from flask==2.0.3->-r requirements.txt (line 6)) (8.1.3)\n", + "Requirement already satisfied: Jinja2>=3.0 in /usr/local/lib/python3.9/site-packages (from flask==2.0.3->-r requirements.txt (line 6)) (3.1.2)\n", + "Requirement already satisfied: itsdangerous>=2.0 in /usr/local/lib/python3.9/site-packages (from flask==2.0.3->-r requirements.txt (line 6)) (2.1.2)\n", + "Requirement already satisfied: Werkzeug>=2.0 in /usr/local/lib/python3.9/site-packages (from flask==2.0.3->-r requirements.txt (line 6)) (2.2.2)\n", + "Requirement already satisfied: jsonschema in /usr/local/lib/python3.9/site-packages (from jsonmerge==1.8.0->-r requirements.txt (line 8)) (4.12.1)\n", + "Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.9/site-packages (from mysql-connector-python==8.0.25->-r requirements.txt (line 9)) (4.21.5)\n", + "Requirement already satisfied: defusedxml>=0.6.0 in /usr/local/lib/python3.9/site-packages (from onelogin==2.0.1->-r requirements.txt (line 10)) (0.7.1)\n", + "Requirement already satisfied: deepmerge>=1.0.1 in /usr/local/lib/python3.9/site-packages (from stix2-matcher==3.0.0->-r requirements.txt (line 14)) (1.0.1)\n", + "Requirement already satisfied: simplejson in /usr/local/lib/python3.9/site-packages (from stix2-validator==3.0.2->-r requirements.txt (line 16)) (3.17.6)\n", + "Requirement already satisfied: cpe in /usr/local/lib/python3.9/site-packages (from stix2-validator==3.0.2->-r requirements.txt (line 16)) (1.2.1)\n", + "Requirement already satisfied: requests-cache in /usr/local/lib/python3.9/site-packages (from stix2-validator==3.0.2->-r requirements.txt (line 16)) (0.6.4)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: colorama in /usr/local/lib/python3.9/site-packages (from stix2-validator==3.0.2->-r requirements.txt (line 16)) (0.4.5)\n", + "Requirement already satisfied: appdirs in /usr/local/lib/python3.9/site-packages (from stix2-validator==3.0.2->-r requirements.txt (line 16)) (1.4.4)\n", + "Requirement already satisfied: setuptools in /usr/local/lib/python3.9/site-packages (from pytest==3.5.0->-r requirements-dev.txt (line 16)) (63.2.0)\n", + "Requirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.9/site-packages (from cryptography>=1.1.0->adal==1.2.7->-r requirements.txt (line 1)) (1.15.1)\n", + "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.9/site-packages (from Jinja2>=3.0->flask==2.0.3->-r requirements.txt (line 6)) (2.1.1)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING: jsonschema 4.12.1 does not provide the extra 'format_nongpl'\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.9/site-packages (from jsonschema->jsonmerge==1.8.0->-r requirements.txt (line 8)) (0.18.1)\n", + "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.9/site-packages (from requests<3,>=2.0.0->adal==1.2.7->-r requirements.txt (line 1)) (2.1.0)\n", + "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/site-packages (from requests<3,>=2.0.0->adal==1.2.7->-r requirements.txt (line 1)) (3.3)\n", + "Requirement already satisfied: url-normalize>=1.4 in /usr/local/lib/python3.9/site-packages (from requests-cache->stix2-validator==3.0.2->-r requirements.txt (line 16)) (1.4.3)\n", + "Requirement already satisfied: pycparser in /usr/local/lib/python3.9/site-packages (from cffi>=1.12->cryptography>=1.1.0->adal==1.2.7->-r requirements.txt (line 1)) (2.21)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n", + "DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://pypi.org/simple\n", + "Requirement already satisfied: python-dotenv in /usr/local/lib/python3.9/site-packages (0.20.0)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n" + ] + } + ], + "source": [ + "%%bash\n", + "cd $SS_PATH\n", + "python3 generate_requirements.py\n", + "pip install -r requirements-dev.txt\n", + "pip install python-dotenv" + ] + }, + { + "cell_type": "markdown", + "id": "31f347eb", + "metadata": {}, + "source": [ + "### Set sample ReaQta results JSON to environment variable" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "c9d6707f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "env: REAQTA_RESULTS=[ { \"eventId\": \"847102109500309505\", \"endpointId\": \"842028663686823936\", \"payload\": { \"localId\": \"847101972854081537\", \"process\": { \"id\": \"842028663686823936:2222:1648564483636\", \"parentId\": \"842028663686823936:1111:1648485432579\", \"endpointId\": \"842028663686823936\", \"program\": { \"path\": \"c:\\\\users\\\\reaqta\\\\downloads\\\\test.exe\", \"filename\": \"abcd.exe\", \"md5\": \"d05807b758e56634abfdb7cd62798765\", \"sha1\": \"adb328949df38cece2fc7ad818788d12ej311a9a90\", \"sha256\": \"a4693a722a69bb5b58e02bd1b28369a123459047bd37bda4836b97a6a6c65432\", \"size\": 73802, \"arch\": \"x32\", \"fsName\": \"test.exe\" }, \"user\": \"DESKTOP-TEST\\\\ReaQta-test\", \"pid\": 2222, \"startTime\": \"2022-03-29T14:34:43.636Z\", \"ppid\": 1111, \"pstartTime\": \"2022-03-28T16:37:12.579Z\", \"userSID\": \"S-1-1-11-00000000-1111111-222222222-9999\", \"privilegeLevel\": \"MEDIUM\", \"noGui\": false, \"logonId\": \"0xxx1s1\" }, \"incidents\": [], \"triggeredIncidents\": [], \"data\": { \"addressFamily\": 0, \"protocol\": 0, \"localAddr\": \"192.168.1.2\", \"localPort\": 443, \"remoteAddr\": \"192.168.2.3\", \"remotePort\": 8443, \"outbound\": true }, \"eventType\": 8 }, \"happenedAt\": \"2022-03-29T14:40:48.722Z\", \"receivedAt\": \"2022-03-29T14:41:21.301Z\" } ]\n" + ] + } + ], + "source": [ + "%env REAQTA_RESULTS \\\n", + "[ \\\n", + " { \\\n", + " \"eventId\": \"847102109500309505\", \\\n", + " \"endpointId\": \"842028663686823936\", \\\n", + " \"payload\": \\\n", + " { \\\n", + " \"localId\": \"847101972854081537\", \\\n", + " \"process\": { \\\n", + " \"id\": \"842028663686823936:2222:1648564483636\", \\\n", + " \"parentId\": \"842028663686823936:1111:1648485432579\", \\\n", + " \"endpointId\": \"842028663686823936\", \\\n", + " \"program\": { \\\n", + " \"path\": \"c:\\\\users\\\\reaqta\\\\downloads\\\\test.exe\", \\\n", + " \"filename\": \"abcd.exe\", \\\n", + " \"md5\": \"d05807b758e56634abfdb7cd62798765\", \\\n", + " \"sha1\": \"adb328949df38cece2fc7ad818788d12ej311a9a90\", \\\n", + " \"sha256\": \"a4693a722a69bb5b58e02bd1b28369a123459047bd37bda4836b97a6a6c65432\", \\\n", + " \"size\": 73802, \\\n", + " \"arch\": \"x32\", \\\n", + " \"fsName\": \"test.exe\" \\\n", + " }, \\\n", + " \"user\": \"DESKTOP-TEST\\\\ReaQta-test\", \\\n", + " \"pid\": 2222, \\\n", + " \"startTime\": \"2022-03-29T14:34:43.636Z\", \\\n", + " \"ppid\": 1111, \\\n", + " \"pstartTime\": \"2022-03-28T16:37:12.579Z\", \\\n", + " \"userSID\": \"S-1-1-11-00000000-1111111-222222222-9999\", \\\n", + " \"privilegeLevel\": \"MEDIUM\", \\\n", + " \"noGui\": false, \\\n", + " \"logonId\": \"0xxx1s1\" \\\n", + " }, \\\n", + " \"incidents\": [], \\\n", + " \"triggeredIncidents\": [], \\\n", + " \"data\": { \\\n", + " \"addressFamily\": 0, \\\n", + " \"protocol\": 0, \\\n", + " \"localAddr\": \"192.168.1.2\", \\\n", + " \"localPort\": 443, \\\n", + " \"remoteAddr\": \"192.168.2.3\", \\\n", + " \"remotePort\": 8443, \\\n", + " \"outbound\": true \\\n", + " }, \\\n", + " \"eventType\": 8 \\\n", + " }, \\\n", + " \"happenedAt\": \"2022-03-29T14:40:48.722Z\", \\\n", + " \"receivedAt\": \"2022-03-29T14:41:21.301Z\" \\\n", + " }\\\n", + "]\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "566f291c", + "metadata": {}, + "source": [ + "### Translate ReaQta results into STIX with CLI command" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "8ff1a0c6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"type\": \"bundle\",\n", + " \"id\": \"bundle--7f6d556f-eebc-4af4-bef2-5b756bc67bd9\",\n", + " \"objects\": [\n", + " {\n", + " \"type\": \"identity\",\n", + " \"id\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"name\": \"STIX Demo\",\n", + " \"identity_class\": \"system\",\n", + " \"created\": \"2022-04-07T20:35:41.042Z\",\n", + " \"modified\": \"2022-04-07T20:35:41.042Z\"\n", + " },\n", + " {\n", + " \"id\": \"observed-data--67989789-d5da-4f04-a80c-0bd05ed2ac1c\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2022-08-23T15:40:38.775Z\",\n", + " \"modified\": \"2022-08-23T15:40:38.775Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"code\": 847102109500309505,\n", + " \"file_ref\": \"6\",\n", + " \"user_ref\": \"7\",\n", + " \"process_ref\": \"3\",\n", + " \"parent_process_ref\": \"4\",\n", + " \"network_ref\": \"9\",\n", + " \"category\": \"8\",\n", + " \"action\": \"Network Connection Established\",\n", + " \"created\": \"2022-03-29T14:41:21.301Z\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"host_id\": \"842028663686823936\",\n", + " \"ip_refs\": [\n", + " \"10\"\n", + " ]\n", + " },\n", + " \"2\": {\n", + " \"type\": \"x-reaqta-event\",\n", + " \"local_id\": \"847101972854081537\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"process\",\n", + " \"extensions\": {\n", + " \"x-process-ext\": {\n", + " \"process_uid\": \"842028663686823936:2222:1648564483636\"\n", + " },\n", + " \"windows-process-ext\": {\n", + " \"owner_sid\": \"S-1-1-11-00000000-1111111-222222222-9999\"\n", + " },\n", + " \"x-reaqta-process\": {\n", + " \"privilege_level\": \"MEDIUM\",\n", + " \"no_gui\": false,\n", + " \"logon_id\": \"0xxx1s1\"\n", + " }\n", + " },\n", + " \"binary_ref\": \"6\",\n", + " \"creator_user_ref\": \"7\",\n", + " \"pid\": 2222,\n", + " \"created\": \"2022-03-29T14:34:43.636Z\",\n", + " \"parent_ref\": \"4\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"process\",\n", + " \"extensions\": {\n", + " \"x-process-ext\": {\n", + " \"parent_process_uid\": \"842028663686823936:1111:1648485432579\"\n", + " }\n", + " },\n", + " \"pid\": 1111\n", + " },\n", + " \"5\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"c:\\\\users\\\\reaqta\\\\downloads\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"parent_directory_ref\": \"5\",\n", + " \"name\": \"abcd.exe\",\n", + " \"hashes\": {\n", + " \"MD5\": \"d05807b758e56634abfdb7cd62798765\",\n", + " \"SHA-1\": \"adb328949df38cece2fc7ad818788d12ej311a9a90\",\n", + " \"SHA-256\": \"a4693a722a69bb5b58e02bd1b28369a123459047bd37bda4836b97a6a6c65432\"\n", + " },\n", + " \"size\": 73802,\n", + " \"extensions\": {\n", + " \"x-reaqta-program\": {\n", + " \"arch\": \"x32\",\n", + " \"fsname\": \"test.exe\"\n", + " }\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"user-account\",\n", + " \"user_id\": \"DESKTOP-TEST\\\\ReaQta-test\"\n", + " },\n", + " \"8\": {\n", + " \"type\": \"x-ibm-finding\",\n", + " \"extensions\": {\n", + " \"x-reaqta-alert\": {\n", + " \"incidents\": [],\n", + " \"triggered_incidents\": []\n", + " }\n", + " },\n", + " \"src_ip_ref\": \"10\",\n", + " \"dst_ip_ref\": \"11\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"network-traffic\",\n", + " \"extensions\": {\n", + " \"x-reaqta-network\": {\n", + " \"address_family\": \"IPv4\",\n", + " \"outbound\": true\n", + " }\n", + " },\n", + " \"protocols\": [\n", + " \"tcp\"\n", + " ],\n", + " \"src_port\": 443,\n", + " \"dst_port\": 8443,\n", + " \"src_ref\": \"10\",\n", + " \"dst_ref\": \"11\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.1.2\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.2.3\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2022-03-29T14:40:48.722Z\",\n", + " \"last_observed\": \"2022-03-29T14:40:48.722Z\",\n", + " \"number_observed\": 1\n", + " }\n", + " ],\n", + " \"spec_version\": \"2.0\"\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "cd $STIX_SHIFTER_PATH\n", + "python main.py translate reaqta results \"$IDENTITY_OBJECT\" \"$REAQTA_RESULTS\"" + ] + }, + { + "cell_type": "markdown", + "id": "efdec47e", + "metadata": {}, + "source": [ + "### Navigate to the MySQL module" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "b2e3a222", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(bookmark:SS_PATH) -> /Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter\n", + "/Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter\n", + "/Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter/stix_shifter_modules/mysql/stix_translation/json\n", + "from_stix_map.json \u001b[34mstix-shifter\u001b[m\u001b[m/ to_stix_map.json\n", + "operators.json \u001b[34mstix_2_1\u001b[m\u001b[m/\n" + ] + } + ], + "source": [ + "%cd -b SS_PATH\n", + "%cd stix_shifter_modules/mysql/stix_translation/json\n", + "%ls" + ] + }, + { + "cell_type": "markdown", + "id": "3ad97409", + "metadata": {}, + "source": [ + "### Load the operators.json file for editing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "12228a3d", + "metadata": {}, + "outputs": [], + "source": [ + "# %load operators.json\n", + "\n", + "{\n", + " \"ComparisonExpressionOperators.And\": \"AND\",\n", + " \"ComparisonExpressionOperators.Or\": \"OR\",\n", + " \"ComparisonComparators.GreaterThan\": \">\",\n", + " \"ComparisonComparators.GreaterThanOrEqual\": \">=\",\n", + " \"ComparisonComparators.LessThan\": \"<\",\n", + " \"ComparisonComparators.LessThanOrEqual\": \"<=\",\n", + " \"ComparisonComparators.Equal\": \"=\",\n", + " \"ComparisonComparators.NotEqual\": \"!=\",\n", + " \"ComparisonComparators.Like\": \"LIKE\",\n", + " \"ComparisonComparators.In\": \"IN\",\n", + " \"ComparisonComparators.Matches\": \"LIKE\",\n", + " \"ObservationOperators.Or\": \"OR\",\n", + " \"ObservationOperators.And\": \"OR\"\n", + "}\n" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "b1333d92", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overwriting operators.json\n" + ] + } + ], + "source": [ + "%%writefile operators.json\n", + "\n", + "{\n", + " \"ComparisonExpressionOperators.And\": \"AND\",\n", + " \"ComparisonExpressionOperators.Or\": \"OR\",\n", + " \"ComparisonComparators.GreaterThan\": \">\",\n", + " \"ComparisonComparators.GreaterThanOrEqual\": \">=\",\n", + " \"ComparisonComparators.LessThan\": \"<\",\n", + " \"ComparisonComparators.LessThanOrEqual\": \"<=\",\n", + " \"ComparisonComparators.Equal\": \"=\",\n", + " \"ComparisonComparators.NotEqual\": \"!=\",\n", + " \"ComparisonComparators.Like\": \"LIKE\",\n", + " \"ComparisonComparators.In\": \"IN\",\n", + " \"ComparisonComparators.Matches\": \"LIKE\",\n", + " \"ObservationOperators.Or\": \"OR\",\n", + " \"ObservationOperators.And\": \"OR\"\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2313037b", + "metadata": {}, + "outputs": [], + "source": [ + "# %load from_stix_map.json\n", + "{\n", + " \"ipv4-addr\": {\n", + " \"fields\": {\n", + " \"value\": [\"source_ipaddr\", \"dest_ipaddr\"]\n", + " }\n", + " },\n", + " \"ipv6-addr\": {\n", + " \"fields\": {\n", + " \"value\": [\"source_ipaddr\", \"dest_ipaddr\"]\n", + " }\n", + " },\n", + " \"url\": {\n", + " \"fields\": {\n", + " \"value\": [\"url\"]\n", + " }\n", + " },\n", + " \"file\": {\n", + " \"fields\": {\n", + " \"name\": [\"filename\"],\n", + " \"hashes.'SHA-256'\": [\"sha256hash\"],\n", + " \"hashes.MD5\": [\"md5hash\"],\n", + " \"parent_directory_ref.path\": [\"file_path\"],\n", + " \"created\": [\"file_created_time\"],\n", + " \"modified\": [\"file_modified_time\"],\n", + " \"accessed\": [\"file_accessed_time\"]\n", + " }\n", + " },\n", + " \"user-account\": {\n", + " \"fields\": {\n", + " \"user_id\": [\"username\"]\n", + " }\n", + " },\n", + " \"directory\": {\n", + " \"fields\": {\n", + " \"path\": [\"file_path\"],\n", + " \"created\": [\"directory_created_time\"],\n", + " \"modified\": [\"directory_modified_time\"],\n", + " \"accessed\": [\"directory_accessed_time\"]\n", + " }\n", + " },\n", + " \"network-traffic\": {\n", + " \"fields\": {\n", + " \"src_ref.value\": [\"source_ipaddr\"],\n", + " \"dst_ref.value\": [\"dest_ipaddr\"],\n", + " \"src_port\": [\"source_port\"],\n", + " \"dst_port\": [\"dest_port\"],\n", + " \"protocols[*]\": [\"protocol\"],\n", + " \"start\": [\"entry_time\"],\n", + " \"end\": [\"entry_time\"]\n", + " }\n", + " },\n", + " \"process\": {\n", + " \"fields\": {\n", + " \"pid\": [\"process_id\"],\n", + " \"name\": [\"process_name\"],\n", + " \"arguments\": [\"process_arguments\"],\n", + " \"created\": [\"process_created_time\"],\n", + " \"binary_ref.name\": [\"filename\"]\n", + " }\n", + " },\n", + " \"x-mysql\": {\n", + " \"fields\": {\n", + " \"system_name\": [\"system_name\"],\n", + " \"severity\": [\"severity\"]\n", + " }\n", + " }\n", + "}\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "4c0c00ac", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "env: PATTERN=[url:value = 'www.example.com']\n" + ] + } + ], + "source": [ + "%env PATTERN=[url:value = 'www.example.com']" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "4286f88e", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[37m 2022-08-22 15:54:09,334 stix_shifter_modules.mysql.stix_translation.query_translator INFO Converting STIX2 Pattern to data source query\u001b[0m\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"queries\": [\n", + " \"SELECT * FROM demo_table WHERE url = 'www.example.com' limit 10000\"\n", + " ]\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "cd $STIX_SHIFTER_PATH\n", + "python main.py translate mysql query \"$IDENTITY_OBJECT\" \"$PATTERN\" '{\"table\": \"demo_table\"}'\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "926953e5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(bookmark:SS_PATH) -> /Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter\n", + "/Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter\n", + "/Users/danny.elliott.ibm.com/Documents/IBM_Documents/jupyter/stix-shifter/stix_shifter_modules/mysql/stix_translation/json\n", + "from_stix_map.json operators.json \u001b[34mstix_2_1\u001b[m\u001b[m/ to_stix_map.json\n" + ] + } + ], + "source": [ + "%cd -b SS_PATH\n", + "%cd stix_shifter_modules/mysql/stix_translation/json\n", + "%ls\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b1c274f", + "metadata": {}, + "outputs": [], + "source": [ + "# %load from_stix_map.json\n", + "{\n", + " \"ipv4-addr\": {\n", + " \"fields\": {\n", + " \"value\": [\"source_ipaddr\", \"dest_ipaddr\"]\n", + " }\n", + " },\n", + " \"ipv6-addr\": {\n", + " \"fields\": {\n", + " \"value\": [\"source_ipaddr\", \"dest_ipaddr\"]\n", + " }\n", + " },\n", + " \"url\": {\n", + " \"fields\": {\n", + " \"value\": [\"url\"]\n", + " }\n", + " },\n", + " \"file\": {\n", + " \"fields\": {\n", + " \"name\": [\"filename\"],\n", + " \"hashes.'SHA-256'\": [\"sha256hash\"],\n", + " \"hashes.MD5\": [\"md5hash\"],\n", + " \"parent_directory_ref.path\": [\"file_path\"],\n", + " \"created\": [\"file_created_time\"],\n", + " \"modified\": [\"file_modified_time\"],\n", + " \"accessed\": [\"file_accessed_time\"]\n", + " }\n", + " },\n", + " \"user-account\": {\n", + " \"fields\": {\n", + " \"user_id\": [\"username\"]\n", + " }\n", + " },\n", + " \"directory\": {\n", + " \"fields\": {\n", + " \"path\": [\"file_path\"],\n", + " \"created\": [\"directory_created_time\"],\n", + " \"modified\": [\"directory_modified_time\"],\n", + " \"accessed\": [\"directory_accessed_time\"]\n", + " }\n", + " },\n", + " \"network-traffic\": {\n", + " \"fields\": {\n", + " \"src_ref.value\": [\"source_ipaddr\"],\n", + " \"dst_ref.value\": [\"dest_ipaddr\"],\n", + " \"src_port\": [\"source_port\"],\n", + " \"dst_port\": [\"dest_port\"],\n", + " \"protocols[*]\": [\"protocol\"],\n", + " \"start\": [\"entry_time\"],\n", + " \"end\": [\"entry_time\"]\n", + " }\n", + " },\n", + " \"process\": {\n", + " \"fields\": {\n", + " \"pid\": [\"process_id\"],\n", + " \"name\": [\"process_name\"],\n", + " \"arguments\": [\"process_arguments\"],\n", + " \"created\": [\"process_created_time\"],\n", + " \"binary_ref.name\": [\"filename\"]\n", + " }\n", + " },\n", + " \"x-mysql\": {\n", + " \"fields\": {\n", + " \"system_name\": [\"system_name\"],\n", + " \"severity\": [\"severity\"]\n", + " }\n", + " }\n", + "}\n" + ] + }, + { + "cell_type": "markdown", + "id": "c20dc152", + "metadata": {}, + "source": [ + "%%writefile from_stix_map.json" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eb4a9707", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/STIX-shifter CLI Quick Lab.ipynb b/notebooks/STIX-shifter CLI Quick Lab.ipynb new file mode 100644 index 000000000..5eaa02035 --- /dev/null +++ b/notebooks/STIX-shifter CLI Quick Lab.ipynb @@ -0,0 +1,1660 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8ee0344c", + "metadata": {}, + "source": [ + "# STIX-Shifter CLI Quick Lab\n", + "\n", + "## Overview\n", + "\n", + "STIX (Structured Threat Information eXpression) is a JSON structure used to share cybersecurity threat intelligence. STIX-shifter is an open-source python library that is part of the Open Cybersecurity Alliance. It allows data repositories to be queried using STIX patterning and return the results as STIX cyber observable objects. This lab will allow users to test out the various stix-shifter CLI commands.\n", + "\n", + "### STIX Patterning\n", + "\n", + "A [STIX pattern](http://docs.oasis-open.org/cti/stix/v2.0/cs01/part5-stix-patterning/stix-v2.0-cs01-part5-stix-patterning.html) is used to query [cyber observable objects](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html). STIX patterns take the format of:\n", + "\n", + "`[: = 'some value' AND : IN (value_1, value_2)] OR [: = 'some value']`\n", + "\n", + "The `[ ]` represents one observation. A pattern can have multiple observations joined by the AND or OR observation operators. An observation can be thought of as one instance or row of data. Within the observation is one or more comparison expressions that looks for a value associated to a cyber observable STIX object and its property. This is a sample pattern with one observation containing an comparison operation for an IP lookup: `[ipv4-addr:value = '1.2.3.4']`. The STIX object in this case is `ipv4-addr` and the property on that object is `value`.\n", + "\n", + "### STIX Observed Data\n", + "\n", + "STIX-shifter returns a `bundle` of STIX `observed-data` objects. The bundle is a container object to hold the results. Below is a sample bundle containing one identity object (representing the data source) and one observed-data object:\n", + "\n", + "```json\n", + "{\n", + " \"type\": \"bundle\",\n", + " \"id\": \"bundle--57d455df-105d-4722-8277-e569110e82ed\",\n", + " \"objects\": [\n", + " {\n", + " \"type\": \"identity\",\n", + " \"id\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"name\": \"QRadar\",\n", + " \"identity_class\": \"system\"\n", + " },\n", + " {\n", + " \"id\": \"observed-data--4db61897-4725-483b-9e68-2874e48650c5\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2022-04-28T14:16:41.544Z\",\n", + " \"modified\": \"2022-04-28T14:16:41.544Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"action\": \"Logon Failure - Unknown user name or bad password\",\n", + " \"outcome\": \"Host Login Failed\",\n", + " \"category\": [\n", + " \"Authentication\"\n", + " ],\n", + " \"provider\": \"Microsoft Windows Security Event Log\",\n", + " \"agent\": \"WindowsAuthServer @ microsoft.windows.test.com\",\n", + " \"created\": \"2021-06-28T19:35:58.000Z\",\n", + " \"network_ref\": \"2\",\n", + " \"user_ref\": \"4\",\n", + " \"url_ref\": \"7\",\n", + " \"file_ref\": \"8\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"109.0.216.203\"\n", + " },\n", + " \"2\": {\n", + " \"type\": \"network-traffic\",\n", + " \"src_ref\": \"1\",\n", + " \"src_port\": 3000,\n", + " \"dst_ref\": \"3\",\n", + " \"dst_port\": 1000,\n", + " \"protocols\": [\n", + " \"TCP\"\n", + " ]\n", + " },\n", + " \"3\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.1.11\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"user-account\",\n", + " \"user_id\": \"bill_holland\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"0.0.0.0\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"artifact\",\n", + " \"payload_bin\": \"PDEzPk1hciAyMSAwMTo0Mjo1MCBtaWNyb3NvZnQud2luZG93cy50ZXN0LmNvbQ==\",\n", + " \"mime_type\": \"text/plain\"\n", + " },\n", + " \"7\": {\n", + " \"type\": \"url\",\n", + " \"value\": \"www.example.com\"\n", + " },\n", + " \"8\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"myfile.exe\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"86c5ceb27e1bf441130299c0209e5f35b88089f62c06b2b09d65772274f12057\"\n", + " },\n", + " \"parent_directory_ref\": \"9\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"C://filepath\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-06-28T19:35:58.652Z\",\n", + " \"last_observed\": \"2021-06-28T19:36:58.652Z\",\n", + " \"number_observed\": 31\n", + " }\n", + " ],\n", + " \"spec_version\": \"2.0\"\n", + "}\n", + "```\n", + "\n", + "Each observed-data object contains a numbered set of cyber-observable objects. The properties on the cyber-observable object store the data returned from the data source. See the [STIX 2.0 standard](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html) for more on cyber observable objects.\n", + "\n", + "## Setup\n", + "\n", + "### Prerequisites\n", + "\n", + "* Python 3\n", + "* pip\n", + "* venv\n", + "* Ability to run bash commands\n", + "\n", + "### 1. Open a terminal and install a Python Virtual Environment\n", + "\n", + "`python3 -m venv labenv`\n", + "\n", + "`source labenv/bin/activate`\n", + "\n", + "### 2. Install jupyter notebook\n", + "\n", + "`pip install notebook`\n", + "\n", + "### 3. Run jupyter notebook\n", + "\n", + "`jupyter notebook`\n", + "\n", + "### All remaining steps take place in the jupyter notebook" + ] + }, + { + "cell_type": "markdown", + "id": "f8d1892a", + "metadata": {}, + "source": [ + "### 4. Install the required stix-shifter libraries\n", + "\n", + "This installs the core stix-shifter and utils library along with the STIX-bundle and QRadar connectors." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "4d2049c2", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://pypi.org/simple\n", + "Requirement already satisfied: stix-shifter in /usr/local/lib/python3.9/site-packages (4.2.5)\n", + "Requirement already satisfied: stix-shifter-utils in /usr/local/lib/python3.9/site-packages (4.2.5)\n", + "Requirement already satisfied: stix-shifter-modules-stix_bundle in /usr/local/lib/python3.9/site-packages (4.2.5)\n", + "Requirement already satisfied: stix-shifter-modules-qradar in /usr/local/lib/python3.9/site-packages (4.2.5)\n", + "Requirement already satisfied: stix-shifter-modules-mysql in /usr/local/lib/python3.9/site-packages (4.2.5)\n", + "Requirement already satisfied: stix-shifter-modules-reaqta in /usr/local/lib/python3.9/site-packages (4.2.5)\n", + "Requirement already satisfied: 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If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n" + ] + } + ], + "source": [ + "%%bash\n", + "pip install \\\n", + "stix-shifter \\\n", + "stix-shifter-utils \\\n", + "stix-shifter-modules-stix_bundle \\\n", + "stix-shifter-modules-qradar \\\n", + "stix-shifter-modules-mysql \\\n", + "stix-shifter-modules-reaqta" + ] + }, + { + "cell_type": "markdown", + "id": "174f0aa9", + "metadata": {}, + "source": [ + "# Lab Exercise 1: Using CLI tools with the STIX-Bundle connector" + ] + }, + { + "cell_type": "markdown", + "id": "5f60b5e5", + "metadata": {}, + "source": [ + "## Examine the STIX Bundle\n", + "This is a bundle of STIX observed-data objects containing sanitized data from a CrowdStrike instance.\n", + "\n", + "https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json\n", + "\n", + "The stix_bundle connector will query the sample STIX bundle and return a subset of data based on the query pattern.\n", + "\n", + "Note the bundle of observed-data objects that are returned. Each of these objects contains a numbered set of cyber observable objects (`url`, `network-traffic`, `ipv4-addr`…) which contain the data from the target data source. Given the above CLI example, the `ipv4-addr` object should contain a value property with **12.111.222.0**" + ] + }, + { + "cell_type": "markdown", + "id": "b13ae679", + "metadata": {}, + "source": [ + "## STIX-Shifter Transmission CLI commands\n", + "The transmission commands use the data source APIs to send a query, check the status, fetch the results, and ping the connection." + ] + }, + { + "cell_type": "markdown", + "id": "0257bd78", + "metadata": {}, + "source": [ + "### Set environment variables to be used in the CLI" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "4844548d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "env: BUNDLE_URL=https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json\n" + ] + } + ], + "source": [ + "%env BUNDLE_URL https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "8867db72", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "env: IDENTITY_OBJECT={ \"type\":\"identity\", \"id\":\"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\", \"name\":\"STIX Demo\", \"identity_class\":\"system\", \"created\": \"2022-04-07T20:35:41.042Z\", \"modified\": \"2022-04-07T20:35:41.042Z\" }\n" + ] + } + ], + "source": [ + "%env IDENTITY_OBJECT \\\n", + "{ \\\n", + " \"type\":\"identity\", \\\n", + " \"id\":\"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\", \\\n", + " \"name\":\"STIX Bundle\", \\\n", + " \"identity_class\":\"system\", \\\n", + " \"created\": \"2022-04-07T20:35:41.042Z\", \\\n", + " \"modified\": \"2022-04-07T20:35:41.042Z\" \\\n", + "} " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "340b792b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "env: BUNDLE_AUTH={\"auth\": {}}\n" + ] + } + ], + "source": [ + "%env BUNDLE_AUTH {\"auth\": {}}" + ] + }, + { + "cell_type": "markdown", + "id": "e407e416", + "metadata": {}, + "source": [ + "### Run the ping command\n", + "This command checks that the data source can be reached by the stix-shifter connector." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "a1916a50", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"success\": true\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" ping" + ] + }, + { + "cell_type": "markdown", + "id": "533c714d", + "metadata": {}, + "source": [ + "### Run the query command\n", + "This command sends the native query to the data source." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "5191d11e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"success\": true,\n", + " \"search_id\": \"[ipv4-addr:value = '192.168.0.8']\"\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" query \"[ipv4-addr:value = '192.168.0.8']\"" + ] + }, + { + "cell_type": "markdown", + "id": "a5496cbf", + "metadata": {}, + "source": [ + "### Run the status command\n", + "This command checks the status of the query." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "d76d8a2f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"success\": true,\n", + " \"status\": \"COMPLETED\",\n", + " \"progress\": 100\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" status \"[ipv4-addr:value = '192.168.0.8']\"" + ] + }, + { + "cell_type": "markdown", + "id": "a94dde00", + "metadata": {}, + "source": [ + "### Run the results command\n", + "This command fetches the query results" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "41c53984", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"success\": true,\n", + " \"data\": [\n", + " {\n", + " \"id\": \"observed-data--05baca02-9154-45e3-a41d-f10366ad8dc0\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--fa188421-a904-4e95-a3a4-309a558b9295\",\n", + " \"created\": \"2021-07-23T14:24:43.723Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.723Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-06-17T11:36:21Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"CustomIOAWinHigh\",\n", + " \"outcome\": \"A process triggered a high severity custom rule.\",\n", + " \"severity\": 70,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"powershell.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", + " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"powershell.exe\",\n", + " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 25952186719,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"suspicious_activity\",\n", + " \"tactic\": \"Custom Intelligence\",\n", + " \"tactic_id\": \"CSTA0005\",\n", + " \"technique\": \"Indicator of Attack\",\n", + " \"technique_id\": \"CST0004\",\n", + " \"confidence\": 100,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:25769826315\",\n", + " \"agent_local_time\": \"2021-06-17T11:30:47.357Z\",\n", + " \"agent_version\": \"6.24.13806.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-06-17T11:30:53Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", + " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", + " \"pid\": 25925279935\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-06-17T11:36:21Z\",\n", + " \"last_observed\": \"2021-06-17T11:36:21Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--d3e1a58a-ecd5-4cd8-bd67-8b220fc455ce\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--fa188421-a904-4e95-a3a4-309a558b9295\",\n", + " \"created\": \"2021-07-23T14:24:43.724Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.724Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-05-10T18:45:39Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"UACBypass2\",\n", + " \"outcome\": \"A malicious process launched that's likely attempting a User Account Control (UAC) bypass. Review the process tree.\",\n", + " \"severity\": 70,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", + " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22472903178,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"privilege_escalation\",\n", + " \"tactic\": \"Privilege Escalation\",\n", + " \"tactic_id\": \"TA0004\",\n", + " \"technique\": \"Bypass User Account Control\",\n", + " \"technique_id\": \"T1548.002\",\n", + " \"confidence\": 80,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", + " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", + " \"agent_version\": \"6.22.13607.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", + " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n", + " \"pid\": 22456494518\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-05-10T18:45:39Z\",\n", + " \"last_observed\": \"2021-05-10T18:45:39Z\",\n", + " \"number_observed\": 1\n", + " }\n", + " ]\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" results \"[ipv4-addr:value = '192.168.6.242']\" 0 2" + ] + }, + { + "cell_type": "markdown", + "id": "49f1244e", + "metadata": {}, + "source": [ + "## STIX-Shifter Execute CLI command\n", + "\n", + "### Run the execute command\n", + "The execute command runs through the entire stix-shifter flow:\n", + "\n", + "* Translates a STIX pattern into a native data source query\n", + "* Sends the query to the data source via the data source APIs\n", + "* Checks the status of the query via the data source APIs\n", + "* Fetches the query results via the APIs and, if needed, converts them to JSON\n", + "* Translates the JSON results into STIX objects" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "0a0ce7c6", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[37m 2022-08-23 14:45:15,272 stix_shifter.scripts.stix_shifter INFO Translated Queries: \n", + "{\n", + " \"queries\": [\n", + " \"[ipv4-addr:value = '12.111.222.0']\"\n", + " ]\n", + "}\u001b[0m\n", + "\u001b[37m 2022-08-23 14:45:15,731 stix_shifter.scripts.stix_shifter INFO STIX Results (written to stdout):\n", + "\u001b[0m\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"type\": \"bundle\",\n", + " \"id\": \"bundle--7bac91c6-368d-40f4-8659-97f2f268e844\",\n", + " \"objects\": [\n", + " {\n", + " \"type\": \"identity\",\n", + " \"id\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"name\": \"STIX Demo\",\n", + " \"identity_class\": \"system\",\n", + " \"created\": \"2022-04-07T20:35:41.042Z\",\n", + " \"modified\": \"2022-04-07T20:35:41.042Z\"\n", + " },\n", + " {\n", + " \"id\": \"observed-data--05baca02-9154-45e3-a41d-f10366ad8dc0\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.723Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.723Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-06-17T11:36:21Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"CustomIOAWinHigh\",\n", + " \"outcome\": \"A process triggered a high severity custom rule.\",\n", + " \"severity\": 70,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"powershell.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", + " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"powershell.exe\",\n", + " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 25952186719,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"suspicious_activity\",\n", + " \"tactic\": \"Custom Intelligence\",\n", + " \"tactic_id\": \"CSTA0005\",\n", + " \"technique\": \"Indicator of Attack\",\n", + " \"technique_id\": \"CST0004\",\n", + " \"confidence\": 100,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:25769826315\",\n", + " \"agent_local_time\": \"2021-06-17T11:30:47.357Z\",\n", + " \"agent_version\": \"6.24.13806.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-06-17T11:30:53Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", + " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", + " \"pid\": 25925279935\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-06-17T11:36:21Z\",\n", + " \"last_observed\": \"2021-06-17T11:36:21Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--d3e1a58a-ecd5-4cd8-bd67-8b220fc455ce\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.724Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.724Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-05-10T18:45:39Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"UACBypass2\",\n", + " \"outcome\": \"A malicious process launched that's likely attempting a User Account Control (UAC) bypass. Review the process tree.\",\n", + " \"severity\": 70,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", + " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22472903178,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"privilege_escalation\",\n", + " \"tactic\": \"Privilege Escalation\",\n", + " \"tactic_id\": \"TA0004\",\n", + " \"technique\": \"Bypass User Account Control\",\n", + " \"technique_id\": \"T1548.002\",\n", + " \"confidence\": 80,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", + " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", + " \"agent_version\": \"6.22.13607.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", + " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"pid\": 22456494518\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-05-10T18:45:39Z\",\n", + " \"last_observed\": \"2021-05-10T18:45:39Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--5b858b41-d98a-4912-bd7d-6e8bc2a0d9a3\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.724Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.724Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-05-10T18:45:39Z\",\n", + " \"process_ref\": \"2\",\n", + " \"outcome\": \"This file meets the machine learning-based on-sensor AV protection's high confidence threshold for malicious files.\",\n", + " \"severity\": 70,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"file_ref\": \"12\",\n", + " \"action\": \"library load\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", + " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22472903178,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"NGAV\",\n", + " \"tactic\": \"Machine Learning\",\n", + " \"tactic_id\": \"CSTA0004\",\n", + " \"technique\": \"Sensor-based ML\",\n", + " \"technique_id\": \"CST0007\",\n", + " \"confidence\": 70,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", + " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", + " \"agent_version\": \"6.22.13607.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", + " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n", + " \"pid\": 22456494518\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " },\n", + " \"12\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\"\n", + " }\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-05-10T18:45:39Z\",\n", + " \"last_observed\": \"2021-05-10T18:45:39Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--30a91c57-fc2b-4dea-986d-885088490592\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.725Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.725Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-05-10T18:45:49Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"IntelDomainMedium\",\n", + " \"outcome\": \"A domain lookup matched a CrowdStrike Intelligence indicator.\",\n", + " \"severity\": 50,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"network_ref\": \"13\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", + " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22472903178,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"intel_detection\",\n", + " \"tactic\": \"Falcon Intel\",\n", + " \"tactic_id\": \"CSTA0007\",\n", + " \"technique\": \"Intelligence Indicator - Domain\",\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"technique_id\": \"CST0018\",\n", + " \"confidence\": 80,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", + " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", + " \"agent_version\": \"6.22.13607.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", + " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n", + " \"pid\": 22456494518\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " },\n", + " \"12\": {\n", + " \"type\": \"domain-name\",\n", + " \"value\": \"catsdegree.com\"\n", + " },\n", + " \"13\": {\n", + " \"type\": \"network-traffic\",\n", + " \"dst_ref\": \"12\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-05-10T18:45:49Z\",\n", + " \"last_observed\": \"2021-05-10T18:45:49Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--7819a74a-5f9f-499c-bf8c-eb50a6a37b32\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.727Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.727Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-05-10T18:45:53Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"MaliciousPowershell\",\n", + " \"outcome\": \"A PowerShell script related to this process is likely malicious or shares characteristics with known malicious scripts. Review the script.\",\n", + " \"severity\": 50,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"powershell.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", + " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"powershell.exe\",\n", + " \"command_line\": \"powershell -ep bypass -c \\\"(0..61)|%{$s+=[char][byte]('0x'+'4765742D576D694F626A6563742057696E33325F536861646F77636F7079207C20466F72456163682D4F626A656374207B245F2E44656C65746528293B7D20'.Substring(2*$_,2))};iex $s\\\"\",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22475614444,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"suspicious_activity\",\n", + " \"tactic\": \"Execution\",\n", + " \"tactic_id\": \"TA0002\",\n", + " \"technique\": \"PowerShell\",\n", + " \"technique_id\": \"T1059.001\",\n", + " \"confidence\": 80,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", + " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", + " \"agent_version\": \"6.22.13607.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", + " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", + " \"pid\": 22472903178\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-05-10T18:45:53Z\",\n", + " \"last_observed\": \"2021-05-10T18:45:53Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--77382665-4552-427a-a011-641f40e50e7f\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.728Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.728Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-05-10T18:46:24Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"Destructive\",\n", + " \"outcome\": \"A suspicious process, associated with potentially destructive malware like ransomware, launched. Review the process tree. \",\n", + " \"severity\": 90,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"powershell.exe\",\n", + " \"parent_directory_ref\": \"3\"\n", + " },\n", + " \"2\": {\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"powershell.exe\",\n", + " \"command_line\": \"powershell -ep bypass -c \\\"(0..61)|%{$s+=[char][byte]('0x'+'4765742D576D694F626A6563742057696E33325F536861646F77636F7079207C20466F72456163682D4F626A656374207B245F2E44656C65746528293B7D20'.Substring(2*$_,2))};iex $s\\\"\",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22475614444,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"data_loss\",\n", + " \"tactic\": \"Impact\",\n", + " \"tactic_id\": \"TA0040\",\n", + " \"technique\": \"Data Encrypted for Impact\",\n", + " \"technique_id\": \"T1486\",\n", + " \"confidence\": 80,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", + " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", + " \"agent_version\": \"6.22.13607.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", + " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", + " \"pid\": 22472903178\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-05-10T18:46:24Z\",\n", + " \"last_observed\": \"2021-05-10T18:46:24Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--a57280d3-dec4-46af-9869-0d96090cc2d1\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.736Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.736Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-06-15T21:12:34Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"CustomIOAWinHigh\",\n", + " \"outcome\": \"A process triggered a high severity custom rule.\",\n", + " \"severity\": 70,\n", + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"powershell.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", + " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"powershell.exe\",\n", + " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22807129300,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"suspicious_activity\",\n", + " \"tactic\": \"Custom Intelligence\",\n", + " \"tactic_id\": \"CSTA0005\",\n", + " \"technique\": \"Indicator of Attack\",\n", + " \"technique_id\": \"CST0004\",\n", + " \"confidence\": 100,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21476796844\",\n", + " \"agent_local_time\": \"2021-06-15T19:35:43.749Z\",\n", + " \"agent_version\": \"6.24.13806.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-06-15T20:33:15Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", + " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", + " \"pid\": 22345196996\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-06-15T21:12:34Z\",\n", + " \"last_observed\": \"2021-06-15T21:12:34Z\",\n", + " \"number_observed\": 1\n", + " },\n", + " {\n", + " \"id\": \"observed-data--47c347bd-9eec-44ec-b5c5-08b85d7d82b5\",\n", + " \"type\": \"observed-data\",\n", + " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", + " \"created\": \"2021-07-23T14:24:43.764Z\",\n", + " \"modified\": \"2021-07-23T14:24:43.764Z\",\n", + " \"objects\": {\n", + " \"0\": {\n", + " \"type\": \"x-oca-event\",\n", + " \"created\": \"2021-06-15T21:15:58Z\",\n", + " \"process_ref\": \"2\",\n", + " \"action\": \"CustomIOAWinHigh\",\n", + " \"outcome\": \"A process triggered a high severity custom rule.\",\n", + " \"severity\": 70,\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \"parent_process_ref\": \"7\",\n", + " \"host_ref\": \"9\",\n", + " \"provider\": \"CrowdStrike\"\n", + " },\n", + " \"1\": {\n", + " \"type\": \"file\",\n", + " \"name\": \"powershell.exe\",\n", + " \"parent_directory_ref\": \"3\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", + " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", + " }\n", + " },\n", + " \"2\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"1\",\n", + " \"name\": \"powershell.exe\",\n", + " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", + " \"creator_user_ref\": \"5\",\n", + " \"pid\": 22824166752,\n", + " \"parent_ref\": \"7\"\n", + " },\n", + " \"3\": {\n", + " \"type\": \"directory\",\n", + " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", + " },\n", + " \"4\": {\n", + " \"type\": \"x-crowdstrike\",\n", + " \"scenario\": \"suspicious_activity\",\n", + " \"tactic\": \"Custom Intelligence\",\n", + " \"tactic_id\": \"CSTA0005\",\n", + " \"technique\": \"Indicator of Attack\",\n", + " \"technique_id\": \"CST0004\",\n", + " \"confidence\": 100,\n", + " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21476994700\",\n", + " \"agent_local_time\": \"2021-06-15T19:35:43.749Z\",\n", + " \"agent_version\": \"6.24.13806.0\",\n", + " \"ioc_value\": \"VMware, Inc.\",\n", + " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", + " \"last_seen\": \"2021-06-15T21:13:15Z\",\n", + " \"platform_id\": \"0\"\n", + " },\n", + " \"5\": {\n", + " \"type\": \"user-account\",\n", + " \"account_login\": \"admin\",\n", + " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", + " },\n", + " \"6\": {\n", + " \"type\": \"file\",\n", + " \"hashes\": {\n", + " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", + " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", + " }\n", + " },\n", + " \"7\": {\n", + " \"type\": \"process\",\n", + " \"binary_ref\": \"6\",\n", + " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", + " \"pid\": 22345196996\n", + " },\n", + " \"8\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"12.111.222.0\"\n", + " },\n", + " \"9\": {\n", + " \"type\": \"x-oca-asset\",\n", + " \"ip_refs\": [\n", + " \"8\",\n", + " \"10\"\n", + " ],\n", + " \"hostname\": \"WIN10-1S\",\n", + " \"mac_refs\": [\n", + " \"11\"\n", + " ],\n", + " \"os_version\": \"Windows 10\",\n", + " \"os_platform\": \"Windows\"\n", + " },\n", + " \"10\": {\n", + " \"type\": \"ipv4-addr\",\n", + " \"value\": \"192.168.6.242\"\n", + " },\n", + " \"11\": {\n", + " \"type\": \"mac-addr\",\n", + " \"value\": \"00:0a:11:f1:00:0x\"\n", + " }\n", + " },\n", + " \"first_observed\": \"2021-06-15T21:15:58Z\",\n", + " \"last_observed\": \"2021-06-15T21:15:58Z\",\n", + " \"number_observed\": 1\n", + " }\n", + " ]\n", + "}\n" + ] + } + ], + "source": [ + "%%bash\n", + "stix-shifter execute stix_bundle stix_bundle \"$IDENTITY_OBJECT\" '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \\\n", + "\"$BUNDLE_AUTH\" \"[ipv4-addr:value = '12.111.222.0']\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1ee0bf52", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From e83ca07f4dba3141138379809d0a7fbecb9affe2 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Sun, 28 Aug 2022 21:27:57 -0300 Subject: [PATCH 08/19] Add descriptions around STIX bundle exercise --- notebooks/STIX-shifter CLI Quick Lab.ipynb | 1462 +++----------------- 1 file changed, 157 insertions(+), 1305 deletions(-) diff --git a/notebooks/STIX-shifter CLI Quick Lab.ipynb b/notebooks/STIX-shifter CLI Quick Lab.ipynb index 5eaa02035..2ba8094a2 100644 --- a/notebooks/STIX-shifter CLI Quick Lab.ipynb +++ b/notebooks/STIX-shifter CLI Quick Lab.ipynb @@ -1,6 +1,11 @@ { "cells": [ { + "attachments": { + "Screen%20Shot%202022-08-26%20at%202.42.41%20PM.png": { + "image/png": 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" + } + }, "cell_type": "markdown", "id": "8ee0344c", "metadata": {}, @@ -115,6 +120,10 @@ "\n", "Each observed-data object contains a numbered set of cyber-observable objects. The properties on the cyber-observable object store the data returned from the data source. See the [STIX 2.0 standard](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html) for more on cyber observable objects.\n", "\n", + "### STIX-Shifter CLI commands\n", + "\n", + "The CLI tools, and by extension the connector logic, is broken up into two types functions: `translate` and `transmit`. The translate functions convert a STIX pattern into a native data source query, and convert JSON results returned from the data source into STIX objects. The transmit functions implement the data source API calls for making queries, checking the query status, fething query results, pinging the data source, and deleting a search (if supported by the APIs).\n", + "\n", "## Setup\n", "\n", "### Prerequisites\n", @@ -124,7 +133,7 @@ "* venv\n", "* Ability to run bash commands\n", "\n", - "### 1. Open a terminal and install a Python Virtual Environment\n", + "### 1. Open a terminal and install a Python virtual environment\n", "\n", "`python3 -m venv labenv`\n", "\n", @@ -134,11 +143,21 @@ "\n", "`pip install notebook`\n", "\n", - "### 3. Run jupyter notebook\n", + "### 3. Install ipython kernal to use virtual environment\n", + "\n", + "`ipython kernel install --user --name=labenv`\n", + "\n", + "### 4. Run jupyter notebook\n", "\n", "`jupyter notebook`\n", "\n", - "### All remaining steps take place in the jupyter notebook" + "### All remaining steps take place in the jupyter notebook\n", + "\n", + "### 5. Change the Kernel to use the virtual environment\n", + "\n", + "This will cause every notebook cell to run in the virtual environment.\n", + "\n", + "![Screen%20Shot%202022-08-26%20at%202.42.41%20PM.png](attachment:Screen%20Shot%202022-08-26%20at%202.42.41%20PM.png)" ] }, { @@ -146,102 +165,17 @@ "id": "f8d1892a", "metadata": {}, "source": [ - "### 4. Install the required stix-shifter libraries\n", + "### 6. Install the required stix-shifter libraries\n", "\n", "This installs the core stix-shifter and utils library along with the STIX-bundle and QRadar connectors." ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "id": "4d2049c2", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Looking in indexes: https://pypi.org/simple, https://pypi.org/simple\n", - "Requirement already satisfied: stix-shifter in /usr/local/lib/python3.9/site-packages (4.2.5)\n", - "Requirement already satisfied: stix-shifter-utils in /usr/local/lib/python3.9/site-packages (4.2.5)\n", - "Requirement already satisfied: stix-shifter-modules-stix_bundle in /usr/local/lib/python3.9/site-packages (4.2.5)\n", - "Requirement already satisfied: stix-shifter-modules-qradar in /usr/local/lib/python3.9/site-packages (4.2.5)\n", - "Requirement already satisfied: stix-shifter-modules-mysql in /usr/local/lib/python3.9/site-packages (4.2.5)\n", - "Requirement already satisfied: stix-shifter-modules-reaqta in /usr/local/lib/python3.9/site-packages (4.2.5)\n", - "Requirement already satisfied: antlr4-python3-runtime==4.8 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (4.8)\n", - "Requirement already satisfied: xmltodict==0.13.0 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (0.13.0)\n", - "Requirement already satisfied: flask==2.0.3 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (2.0.3)\n", - "Requirement already satisfied: python-dateutil==2.8.2 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (2.8.2)\n", - "Requirement already satisfied: flatten-json==0.1.13 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (0.1.13)\n", - "Requirement already satisfied: boto3==1.21.21 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (1.21.21)\n", - "Requirement already satisfied: stix2-matcher==3.0.0 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (3.0.0)\n", - "Requirement already satisfied: jsonmerge==1.8.0 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (1.8.0)\n", - "Requirement already satisfied: requests-toolbelt==0.9.1 in /usr/local/lib/python3.9/site-packages (from stix-shifter) (0.9.1)\n", - 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"text": [ - "DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\n" - ] - } - ], + "outputs": [], "source": [ "%%bash\n", "pip install \\\n", @@ -253,6 +187,16 @@ "stix-shifter-modules-reaqta" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "4b91ed03", + "metadata": {}, + "outputs": [], + "source": [ + "%pip list" + ] + }, { "cell_type": "markdown", "id": "174f0aa9", @@ -290,42 +234,38 @@ "id": "0257bd78", "metadata": {}, "source": [ - "### Set environment variables to be used in the CLI" + "## Step 1: Set environment variables to be used in the CLI\n", + "\n", + "### STIX Bundle URL\n", + "This points to a publicly aviablable, static JSON file of STIX data. " ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "4844548d", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "env: BUNDLE_URL=https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json\n" - ] - } - ], + "outputs": [], "source": [ "%env BUNDLE_URL https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json\n", " \n" ] }, + { + "cell_type": "markdown", + "id": "495c68af", + "metadata": {}, + "source": [ + "### STIX Identity Object\n", + "The identity object represents the data source the STIX results are taken from. As we will see, the identity object is passed into some of the CLI commands so that STIX-shifter can prepend it to the top of the bundle of STIX results." + ] + }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "8867db72", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "env: IDENTITY_OBJECT={ \"type\":\"identity\", \"id\":\"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\", \"name\":\"STIX Demo\", \"identity_class\":\"system\", \"created\": \"2022-04-07T20:35:41.042Z\", \"modified\": \"2022-04-07T20:35:41.042Z\" }\n" - ] - } - ], + "outputs": [], "source": [ "%env IDENTITY_OBJECT \\\n", "{ \\\n", @@ -338,20 +278,21 @@ "} " ] }, + { + "cell_type": "markdown", + "id": "33cae353", + "metadata": {}, + "source": [ + "### Authentication object\n", + "The CLI transmission commands require that connection and authention details are passed in so that the connector can talk to the target data source. In this case the `\"auth\"` object is empty since the STIX bundle we will query is publicly available and doesn't need any access credentials." + ] + }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "340b792b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "env: BUNDLE_AUTH={\"auth\": {}}\n" - ] - } - ], + "outputs": [], "source": [ "%env BUNDLE_AUTH {\"auth\": {}}" ] @@ -361,26 +302,16 @@ "id": "e407e416", "metadata": {}, "source": [ - "### Run the ping command\n", - "This command checks that the data source can be reached by the stix-shifter connector." + "## Step 2: Run the ping command\n", + "The `ping` command checks that the data source can be reached by the stix-shifter connector." ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "id": "a1916a50", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"success\": true\n", - "}\n" - ] - } - ], + "outputs": [], "source": [ "%%bash\n", "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" ping" @@ -391,27 +322,16 @@ "id": "533c714d", "metadata": {}, "source": [ - "### Run the query command\n", + "## Step 3: Run the query command\n", "This command sends the native query to the data source." ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "5191d11e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"success\": true,\n", - " \"search_id\": \"[ipv4-addr:value = '192.168.0.8']\"\n", - "}\n" - ] - } - ], + "outputs": [], "source": [ "%%bash\n", "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" query \"[ipv4-addr:value = '192.168.0.8']\"" @@ -422,28 +342,16 @@ "id": "a5496cbf", "metadata": {}, "source": [ - "### Run the status command\n", + "## Step 4: Run the status command\n", "This command checks the status of the query." ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "d76d8a2f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"success\": true,\n", - " \"status\": \"COMPLETED\",\n", - " \"progress\": 100\n", - "}\n" - ] - } - ], + "outputs": [], "source": [ "%%bash\n", "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" status \"[ipv4-addr:value = '192.168.0.8']\"" @@ -454,242 +362,16 @@ "id": "a94dde00", "metadata": {}, "source": [ - "### Run the results command\n", + "## Step 5: Run the results command\n", "This command fetches the query results" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "41c53984", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"success\": true,\n", - " \"data\": [\n", - " {\n", - " \"id\": \"observed-data--05baca02-9154-45e3-a41d-f10366ad8dc0\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--fa188421-a904-4e95-a3a4-309a558b9295\",\n", - " \"created\": \"2021-07-23T14:24:43.723Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.723Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-06-17T11:36:21Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"CustomIOAWinHigh\",\n", - " \"outcome\": \"A process triggered a high severity custom rule.\",\n", - " \"severity\": 70,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"powershell.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", - " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"powershell.exe\",\n", - " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 25952186719,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"suspicious_activity\",\n", - " \"tactic\": \"Custom Intelligence\",\n", - " \"tactic_id\": \"CSTA0005\",\n", - " \"technique\": \"Indicator of Attack\",\n", - " \"technique_id\": \"CST0004\",\n", - " \"confidence\": 100,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:25769826315\",\n", - " \"agent_local_time\": \"2021-06-17T11:30:47.357Z\",\n", - " \"agent_version\": \"6.24.13806.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-06-17T11:30:53Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", - " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", - " \"pid\": 25925279935\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-06-17T11:36:21Z\",\n", - " \"last_observed\": \"2021-06-17T11:36:21Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--d3e1a58a-ecd5-4cd8-bd67-8b220fc455ce\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--fa188421-a904-4e95-a3a4-309a558b9295\",\n", - " \"created\": \"2021-07-23T14:24:43.724Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.724Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-05-10T18:45:39Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"UACBypass2\",\n", - " \"outcome\": \"A malicious process launched that's likely attempting a User Account Control (UAC) bypass. Review the process tree.\",\n", - " \"severity\": 70,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", - " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22472903178,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"privilege_escalation\",\n", - " \"tactic\": \"Privilege Escalation\",\n", - " \"tactic_id\": \"TA0004\",\n", - " \"technique\": \"Bypass User Account Control\",\n", - " \"technique_id\": \"T1548.002\",\n", - " \"confidence\": 80,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", - " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", - " \"agent_version\": \"6.22.13607.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", - " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n", - " \"pid\": 22456494518\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-05-10T18:45:39Z\",\n", - " \"last_observed\": \"2021-05-10T18:45:39Z\",\n", - " \"number_observed\": 1\n", - " }\n", - " ]\n", - "}\n" - ] - } - ], + "outputs": [], "source": [ "%%bash\n", "stix-shifter transmit stix_bundle '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \"$BUNDLE_AUTH\" results \"[ipv4-addr:value = '192.168.6.242']\" 0 2" @@ -700,9 +382,7 @@ "id": "49f1244e", "metadata": {}, "source": [ - "## STIX-Shifter Execute CLI command\n", - "\n", - "### Run the execute command\n", + "## Step 6: Run the execute command\n", "The execute command runs through the entire stix-shifter flow:\n", "\n", "* Translates a STIX pattern into a native data source query\n", @@ -714,923 +394,95 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "0a0ce7c6", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[37m 2022-08-23 14:45:15,272 stix_shifter.scripts.stix_shifter INFO Translated Queries: \n", - "{\n", - " \"queries\": [\n", - " \"[ipv4-addr:value = '12.111.222.0']\"\n", - " ]\n", - "}\u001b[0m\n", - "\u001b[37m 2022-08-23 14:45:15,731 stix_shifter.scripts.stix_shifter INFO STIX Results (written to stdout):\n", - "\u001b[0m\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"type\": \"bundle\",\n", - " \"id\": \"bundle--7bac91c6-368d-40f4-8659-97f2f268e844\",\n", - " \"objects\": [\n", - " {\n", - " \"type\": \"identity\",\n", - " \"id\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"name\": \"STIX Demo\",\n", - " \"identity_class\": \"system\",\n", - " \"created\": \"2022-04-07T20:35:41.042Z\",\n", - " \"modified\": \"2022-04-07T20:35:41.042Z\"\n", - " },\n", - " {\n", - " \"id\": \"observed-data--05baca02-9154-45e3-a41d-f10366ad8dc0\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.723Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.723Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-06-17T11:36:21Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"CustomIOAWinHigh\",\n", - " \"outcome\": \"A process triggered a high severity custom rule.\",\n", - " \"severity\": 70,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"powershell.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", - " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"powershell.exe\",\n", - " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 25952186719,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"suspicious_activity\",\n", - " \"tactic\": \"Custom Intelligence\",\n", - " \"tactic_id\": \"CSTA0005\",\n", - " \"technique\": \"Indicator of Attack\",\n", - " \"technique_id\": \"CST0004\",\n", - " \"confidence\": 100,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:25769826315\",\n", - " \"agent_local_time\": \"2021-06-17T11:30:47.357Z\",\n", - " \"agent_version\": \"6.24.13806.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-06-17T11:30:53Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", - " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", - " \"pid\": 25925279935\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-06-17T11:36:21Z\",\n", - " \"last_observed\": \"2021-06-17T11:36:21Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--d3e1a58a-ecd5-4cd8-bd67-8b220fc455ce\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.724Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.724Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-05-10T18:45:39Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"UACBypass2\",\n", - " \"outcome\": \"A malicious process launched that's likely attempting a User Account Control (UAC) bypass. Review the process tree.\",\n", - " \"severity\": 70,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", - " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22472903178,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"privilege_escalation\",\n", - " \"tactic\": \"Privilege Escalation\",\n", - " \"tactic_id\": \"TA0004\",\n", - " \"technique\": \"Bypass User Account Control\",\n", - " \"technique_id\": \"T1548.002\",\n", - " \"confidence\": 80,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", - " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", - " \"agent_version\": \"6.22.13607.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", - " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"pid\": 22456494518\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-05-10T18:45:39Z\",\n", - " \"last_observed\": \"2021-05-10T18:45:39Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--5b858b41-d98a-4912-bd7d-6e8bc2a0d9a3\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.724Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.724Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-05-10T18:45:39Z\",\n", - " \"process_ref\": \"2\",\n", - " \"outcome\": \"This file meets the machine learning-based on-sensor AV protection's high confidence threshold for malicious files.\",\n", - " \"severity\": 70,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"file_ref\": \"12\",\n", - " \"action\": \"library load\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", - " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22472903178,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"NGAV\",\n", - " \"tactic\": \"Machine Learning\",\n", - " \"tactic_id\": \"CSTA0004\",\n", - " \"technique\": \"Sensor-based ML\",\n", - " \"technique_id\": \"CST0007\",\n", - " \"confidence\": 70,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", - " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", - " \"agent_version\": \"6.22.13607.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", - " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n", - " \"pid\": 22456494518\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " },\n", - " \"12\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\"\n", - " }\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-05-10T18:45:39Z\",\n", - " \"last_observed\": \"2021-05-10T18:45:39Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--30a91c57-fc2b-4dea-986d-885088490592\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.725Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.725Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-05-10T18:45:49Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"IntelDomainMedium\",\n", - " \"outcome\": \"A domain lookup matched a CrowdStrike Intelligence indicator.\",\n", - " \"severity\": 50,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"network_ref\": \"13\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", - " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22472903178,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"intel_detection\",\n", - " \"tactic\": \"Falcon Intel\",\n", - " \"tactic_id\": \"CSTA0007\",\n", - " \"technique\": \"Intelligence Indicator - Domain\",\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"technique_id\": \"CST0018\",\n", - " \"confidence\": 80,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", - " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", - " \"agent_version\": \"6.22.13607.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"f95b7ba752c6452da9d83f84ca7307ae079d220718bcb2babf145903bac894dd\",\n", - " \"MD5\": \"b5a6d2fb3f4521c37d613de52ab3467d\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"C:\\\\Windows\\\\SysWOW64\\\\DllHost.exe /Processid:{3E5FC7F9-9A51-4367-9063-A120244FBEC7}\",\n", - " \"pid\": 22456494518\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " },\n", - " \"12\": {\n", - " \"type\": \"domain-name\",\n", - " \"value\": \"catsdegree.com\"\n", - " },\n", - " \"13\": {\n", - " \"type\": \"network-traffic\",\n", - " \"dst_ref\": \"12\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-05-10T18:45:49Z\",\n", - " \"last_observed\": \"2021-05-10T18:45:49Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--7819a74a-5f9f-499c-bf8c-eb50a6a37b32\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.727Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.727Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-05-10T18:45:53Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"MaliciousPowershell\",\n", - " \"outcome\": \"A PowerShell script related to this process is likely malicious or shares characteristics with known malicious scripts. Review the script.\",\n", - " \"severity\": 50,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"powershell.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", - " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"powershell.exe\",\n", - " \"command_line\": \"powershell -ep bypass -c \\\"(0..61)|%{$s+=[char][byte]('0x'+'4765742D576D694F626A6563742057696E33325F536861646F77636F7079207C20466F72456163682D4F626A656374207B245F2E44656C65746528293B7D20'.Substring(2*$_,2))};iex $s\\\"\",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22475614444,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"suspicious_activity\",\n", - " \"tactic\": \"Execution\",\n", - " \"tactic_id\": \"TA0002\",\n", - " \"technique\": \"PowerShell\",\n", - " \"technique_id\": \"T1059.001\",\n", - " \"confidence\": 80,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", - " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", - " \"agent_version\": \"6.22.13607.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", - " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", - " \"pid\": 22472903178\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-05-10T18:45:53Z\",\n", - " \"last_observed\": \"2021-05-10T18:45:53Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--77382665-4552-427a-a011-641f40e50e7f\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.728Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.728Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-05-10T18:46:24Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"Destructive\",\n", - " \"outcome\": \"A suspicious process, associated with potentially destructive malware like ransomware, launched. Review the process tree. \",\n", - " \"severity\": 90,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"powershell.exe\",\n", - " \"parent_directory_ref\": \"3\"\n", - " },\n", - " \"2\": {\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"powershell.exe\",\n", - " \"command_line\": \"powershell -ep bypass -c \\\"(0..61)|%{$s+=[char][byte]('0x'+'4765742D576D694F626A6563742057696E33325F536861646F77636F7079207C20466F72456163682D4F626A656374207B245F2E44656C65746528293B7D20'.Substring(2*$_,2))};iex $s\\\"\",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22475614444,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"data_loss\",\n", - " \"tactic\": \"Impact\",\n", - " \"tactic_id\": \"TA0040\",\n", - " \"technique\": \"Data Encrypted for Impact\",\n", - " \"technique_id\": \"T1486\",\n", - " \"confidence\": 80,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21477405166\",\n", - " \"agent_local_time\": \"2021-05-10T16:53:04.627Z\",\n", - " \"agent_version\": \"6.22.13607.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-05-10T18:21:42Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16\",\n", - " \"MD5\": \"73b7a0103cb74d7f763ff7f43b95168a\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Downloads\\\\6252822930423808\\\\e99613d7a57a80ea3ec27c8aa8dbb37a6d80f2adeb7f02ede03c7861bd448f16.exe\\\" \",\n", - " \"pid\": 22472903178\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-05-10T18:46:24Z\",\n", - " \"last_observed\": \"2021-05-10T18:46:24Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--a57280d3-dec4-46af-9869-0d96090cc2d1\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.736Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.736Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-06-15T21:12:34Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"CustomIOAWinHigh\",\n", - " \"outcome\": \"A process triggered a high severity custom rule.\",\n", - " \"severity\": 70,\n", - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"powershell.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", - " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"powershell.exe\",\n", - " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22807129300,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"suspicious_activity\",\n", - " \"tactic\": \"Custom Intelligence\",\n", - " \"tactic_id\": \"CSTA0005\",\n", - " \"technique\": \"Indicator of Attack\",\n", - " \"technique_id\": \"CST0004\",\n", - " \"confidence\": 100,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21476796844\",\n", - " \"agent_local_time\": \"2021-06-15T19:35:43.749Z\",\n", - " \"agent_version\": \"6.24.13806.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-06-15T20:33:15Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", - " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", - " \"pid\": 22345196996\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-06-15T21:12:34Z\",\n", - " \"last_observed\": \"2021-06-15T21:12:34Z\",\n", - " \"number_observed\": 1\n", - " },\n", - " {\n", - " \"id\": \"observed-data--47c347bd-9eec-44ec-b5c5-08b85d7d82b5\",\n", - " \"type\": \"observed-data\",\n", - " \"created_by_ref\": \"identity--f431f809-377b-45e0-aa1c-6a4751cae5ff\",\n", - " \"created\": \"2021-07-23T14:24:43.764Z\",\n", - " \"modified\": \"2021-07-23T14:24:43.764Z\",\n", - " \"objects\": {\n", - " \"0\": {\n", - " \"type\": \"x-oca-event\",\n", - " \"created\": \"2021-06-15T21:15:58Z\",\n", - " \"process_ref\": \"2\",\n", - " \"action\": \"CustomIOAWinHigh\",\n", - " \"outcome\": \"A process triggered a high severity custom rule.\",\n", - " \"severity\": 70,\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \"parent_process_ref\": \"7\",\n", - " \"host_ref\": \"9\",\n", - " \"provider\": \"CrowdStrike\"\n", - " },\n", - " \"1\": {\n", - " \"type\": \"file\",\n", - " \"name\": \"powershell.exe\",\n", - " \"parent_directory_ref\": \"3\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"de96a6e69944335375dc1ac238336066889d9ffc7d73628ef4fe1b1b160ab32c\",\n", - " \"MD5\": \"7353f60b1739074eb17c5f4dddefe239\"\n", - " }\n", - " },\n", - " \"2\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"1\",\n", - " \"name\": \"powershell.exe\",\n", - " \"command_line\": \"powershell.exe Invoke-WebRequest -Uri pastebin.com\",\n", - " \"creator_user_ref\": \"5\",\n", - " \"pid\": 22824166752,\n", - " \"parent_ref\": \"7\"\n", - " },\n", - " \"3\": {\n", - " \"type\": \"directory\",\n", - " \"path\": \"\\\\Device\\\\HarddiskVolume4\\\\Windows\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\"\n", - " },\n", - " \"4\": {\n", - " \"type\": \"x-crowdstrike\",\n", - " \"scenario\": \"suspicious_activity\",\n", - " \"tactic\": \"Custom Intelligence\",\n", - " \"tactic_id\": \"CSTA0005\",\n", - " \"technique\": \"Indicator of Attack\",\n", - " \"technique_id\": \"CST0004\",\n", - " \"confidence\": 100,\n", - " \"detection_id\": \"ldt:0a3e7f1d15874c09ad37dae363774e50:21476994700\",\n", - " \"agent_local_time\": \"2021-06-15T19:35:43.749Z\",\n", - " \"agent_version\": \"6.24.13806.0\",\n", - " \"ioc_value\": \"VMware, Inc.\",\n", - " \"first_seen\": \"2021-05-10T16:45:12Z\",\n", - " \"last_seen\": \"2021-06-15T21:13:15Z\",\n", - " \"platform_id\": \"0\"\n", - " },\n", - " \"5\": {\n", - " \"type\": \"user-account\",\n", - " \"account_login\": \"admin\",\n", - " \"user_id\": \"A-2-3-4-333-444-222-1001\"\n", - " },\n", - " \"6\": {\n", - " \"type\": \"file\",\n", - " \"hashes\": {\n", - " \"SHA-256\": \"3656f37a1c6951ec4496fabb8ee957d3a6e3c276d5a3785476b482c9c0d32ea2\",\n", - " \"MD5\": \"975b45b669930b0cc773eaf2b414206f\"\n", - " }\n", - " },\n", - " \"7\": {\n", - " \"type\": \"process\",\n", - " \"binary_ref\": \"6\",\n", - " \"command_line\": \"\\\"C:\\\\Users\\\\admin\\\\Desktop\\\\dns.exe\\\" \",\n", - " \"pid\": 22345196996\n", - " },\n", - " \"8\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"12.111.222.0\"\n", - " },\n", - " \"9\": {\n", - " \"type\": \"x-oca-asset\",\n", - " \"ip_refs\": [\n", - " \"8\",\n", - " \"10\"\n", - " ],\n", - " \"hostname\": \"WIN10-1S\",\n", - " \"mac_refs\": [\n", - " \"11\"\n", - " ],\n", - " \"os_version\": \"Windows 10\",\n", - " \"os_platform\": \"Windows\"\n", - " },\n", - " \"10\": {\n", - " \"type\": \"ipv4-addr\",\n", - " \"value\": \"192.168.6.242\"\n", - " },\n", - " \"11\": {\n", - " \"type\": \"mac-addr\",\n", - " \"value\": \"00:0a:11:f1:00:0x\"\n", - " }\n", - " },\n", - " \"first_observed\": \"2021-06-15T21:15:58Z\",\n", - " \"last_observed\": \"2021-06-15T21:15:58Z\",\n", - " \"number_observed\": 1\n", - " }\n", - " ]\n", - "}\n" - ] - } - ], + "outputs": [], "source": [ "%%bash\n", "stix-shifter execute stix_bundle stix_bundle \"$IDENTITY_OBJECT\" '{\"url\": \"'\"$BUNDLE_URL\"'\"}' \\\n", "\"$BUNDLE_AUTH\" \"[ipv4-addr:value = '12.111.222.0']\"" ] }, + { + "cell_type": "markdown", + "id": "04c029bb", + "metadata": {}, + "source": [ + "# Lab Exercise 2: Using CLI tools with the MySQL connector\n", + "\n", + "This connector relies on running a local or remote MySQL database. The transmission calls interface with the datasource using the source APIs, in this case [mysql.connector](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_transmission/api_client.py#L1). This is differenct from the STIX bundle connector that searches against a static JSON of data." + ] + }, + { + "cell_type": "markdown", + "id": "f0a0f72c", + "metadata": {}, + "source": [ + "## Step 1: Set environment variables to be used in the CLI and load MySQL\n", + "\n", + "### Load the variables\n", + "This will set variables for the database user, password, host, and name." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4511cc31", + "metadata": {}, + "outputs": [], + "source": [ + "%env DB_USER root\n", + "%env DB_PASSWORD giveamanafish\n", + "%env DB_HOST localhost\n", + "%env DB_NAME demo_db" + ] + }, + { + "cell_type": "markdown", + "id": "d156958d", + "metadata": {}, + "source": [ + "### Load the Jupyter notebook MySQL extension" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6a2d97d9", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext sql\n", + "%sql mysql+mysqldb://$DB_USER:$DB_PASSWORD@$DB_HOST/$DB_NAME" + ] + }, + { + "cell_type": "markdown", + "id": "bc87c97e", + "metadata": {}, + "source": [ + "## Step 2: Examine the demo table contents\n", + "\n", + "This will be the data the MySQL connector will query against." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3c949717", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "\n", + "SELECT * FROM demo_table;" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "1ee0bf52", + "id": "b4956816", "metadata": {}, "outputs": [], "source": [] @@ -1638,9 +490,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "labenv", "language": "python", - "name": "python3" + "name": "labenv" }, "language_info": { "codemirror_mode": { From 4399b59e10b24e5ce82688a8cb4c7e6d1d4f3495 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Tue, 30 Aug 2022 15:56:04 -0300 Subject: [PATCH 09/19] fix time range qualifier for MySQL translation, updated sample SQL data --- .../scripts/mysql_populate_script/data.csv | 24 +++++++++---------- .../stix_translation/query_constructor.py | 2 +- .../test_mysql_stix_to_query.py | 14 +++++++++++ 3 files changed, 27 insertions(+), 13 deletions(-) diff --git a/stix_shifter/scripts/mysql_populate_script/data.csv b/stix_shifter/scripts/mysql_populate_script/data.csv index 5fdf0c5fb..2e03d39ee 100644 --- a/stix_shifter/scripts/mysql_populate_script/data.csv +++ b/stix_shifter/scripts/mysql_populate_script/data.csv @@ -1,14 +1,14 @@ source_ipaddr,dest_ipaddr,url,filename,sha256hash,md5hash,file_path,username,source_port,dest_port,protocol,entry_time,system_name,severity,magnitude varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),int,int,varchar(100),double,varchar(100),int,int 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b/stix_shifter_modules/mysql/stix_translation/query_constructor.py index c75536d83..02e5fd1c4 100644 --- a/stix_shifter_modules/mysql/stix_translation/query_constructor.py +++ b/stix_shifter_modules/mysql/stix_translation/query_constructor.py @@ -63,7 +63,7 @@ def _format_start_stop_qualifier(self, expression, qualifier) -> str: qualifier_split = qualifier.split("'") start = transformer.transform(qualifier_split[1]) stop = transformer.transform(qualifier_split[3]) - qualified_query = "%s AND (entry_time >= %s OR entry_time <= %s)" % (expression, start, stop) + qualified_query = "%s AND (entry_time >= %s AND entry_time <= %s)" % (expression, start, stop) return qualified_query @classmethod diff --git a/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py b/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py index 41a5fa823..f698b4d16 100644 --- a/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py +++ b/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py @@ -87,3 +87,17 @@ def test_all_mappings_stix_2_0(self): def test_all_mappings_stix_2_1(self): _test_mappings(FROM_STIX_MAPPINGS_2_1, "2.1") + + def test_start_stop_qualifiers_with_one_observation(self): + start_time_01 = "t'2016-06-01T01:30:00.123Z'" + stop_time_01 = "t'2016-06-01T02:20:00.123Z'" + unix_start_time_01 = 1464744600123 + unix_stop_time_01 = 1464747600123 + stix_pattern = "[url:value = 'www.example.com'] START {} STOP {}".format(start_time_01, stop_time_01) + query = _translate_query(stix_pattern, {"table": "demo_table"}) + where_statement = "SELECT * FROM demo_table WHERE url = 'www.example.com' AND (entry_time >= {} AND entry_time <= {}) limit 10000".format(unix_start_time_01, unix_stop_time_01) + assert len(query['queries']) == 1 + assert query['queries'] == [where_statement] + + + # AND (entry_time >= 1548678241009 OR entry_time <= 1548680041009) limit 10000 From a2d29ad31f2b664aad0be0c19437cc88bd499018 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Wed, 31 Aug 2022 14:39:26 -0300 Subject: [PATCH 10/19] add offset and length support for MySQL connector --- .../mysql/stix_transmission/api_client.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/stix_shifter_modules/mysql/stix_transmission/api_client.py b/stix_shifter_modules/mysql/stix_transmission/api_client.py index 625f21d8b..c0a6d0045 100644 --- a/stix_shifter_modules/mysql/stix_transmission/api_client.py +++ b/stix_shifter_modules/mysql/stix_transmission/api_client.py @@ -58,13 +58,19 @@ def run_search(self, query, start=0, rows=0): cursor.execute(query) result_collection = cursor.fetchall() results_list = [] + row_count = int(rows) # Put table data in JSON format - for tuple in result_collection: + for index, tuple in enumerate(result_collection): + if index < int(start): + continue + if row_count < 1: + break results_object = {} for index, datum in enumerate(tuple): results_object[column_list[index]] = datum results_list.append(results_object) + row_count -= 1 response["result"] = results_list From 2fe93d3c4eb3fac201f9e38d668161229a052b71 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 1 Sep 2022 14:32:24 -0300 Subject: [PATCH 11/19] add labenv to gitignore --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.gitignore b/.gitignore index 02b52b7c9..0ac11a073 100644 --- a/.gitignore +++ b/.gitignore @@ -62,6 +62,8 @@ coverage.xml venv/ ENV/ virtualenv*/ +labenv/ +labenv*/ # mkdocs documentation /site From 14580c1621d7a53b43a3c9f546d2d85c5d579c56 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 1 Sep 2022 14:40:01 -0300 Subject: [PATCH 12/19] add results translation and execute to cli tutorial --- notebooks/STIX-shifter CLI Quick Lab.ipynb | 498 ++++++++++++++++++--- notebooks/set_virtual_env.png | Bin 0 -> 146242 bytes 2 files changed, 446 insertions(+), 52 deletions(-) create mode 100644 notebooks/set_virtual_env.png diff --git a/notebooks/STIX-shifter CLI Quick Lab.ipynb b/notebooks/STIX-shifter CLI Quick Lab.ipynb index 2ba8094a2..bad9d4951 100644 --- a/notebooks/STIX-shifter CLI Quick Lab.ipynb +++ b/notebooks/STIX-shifter CLI Quick Lab.ipynb @@ -1,11 +1,6 @@ { "cells": [ { - "attachments": { - "Screen%20Shot%202022-08-26%20at%202.42.41%20PM.png": { - "image/png": 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" - } - }, "cell_type": "markdown", "id": "8ee0344c", "metadata": {}, @@ -16,7 +11,7 @@ "\n", "STIX (Structured Threat Information eXpression) is a JSON structure used to share cybersecurity threat intelligence. STIX-shifter is an open-source python library that is part of the Open Cybersecurity Alliance. It allows data repositories to be queried using STIX patterning and return the results as STIX cyber observable objects. This lab will allow users to test out the various stix-shifter CLI commands.\n", "\n", - "### STIX Patterning\n", + "## STIX Patterning\n", "\n", "A [STIX pattern](http://docs.oasis-open.org/cti/stix/v2.0/cs01/part5-stix-patterning/stix-v2.0-cs01-part5-stix-patterning.html) is used to query [cyber observable objects](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html). STIX patterns take the format of:\n", "\n", @@ -24,7 +19,7 @@ "\n", "The `[ ]` represents one observation. A pattern can have multiple observations joined by the AND or OR observation operators. An observation can be thought of as one instance or row of data. Within the observation is one or more comparison expressions that looks for a value associated to a cyber observable STIX object and its property. This is a sample pattern with one observation containing an comparison operation for an IP lookup: `[ipv4-addr:value = '1.2.3.4']`. The STIX object in this case is `ipv4-addr` and the property on that object is `value`.\n", "\n", - "### STIX Observed Data\n", + "## STIX Observed Data\n", "\n", "STIX-shifter returns a `bundle` of STIX `observed-data` objects. The bundle is a container object to hold the results. Below is a sample bundle containing one identity object (representing the data source) and one observed-data object:\n", "\n", @@ -120,10 +115,31 @@ "\n", "Each observed-data object contains a numbered set of cyber-observable objects. The properties on the cyber-observable object store the data returned from the data source. See the [STIX 2.0 standard](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html) for more on cyber observable objects.\n", "\n", - "### STIX-Shifter CLI commands\n", + "## STIX-Shifter CLI commands\n", "\n", "The CLI tools, and by extension the connector logic, is broken up into two types functions: `translate` and `transmit`. The translate functions convert a STIX pattern into a native data source query, and convert JSON results returned from the data source into STIX objects. The transmit functions implement the data source API calls for making queries, checking the query status, fething query results, pinging the data source, and deleting a search (if supported by the APIs).\n", "\n", + "The `execute` command runs through the entire query flow:\n", + "\n", + "* Translate a STIX pattern into a native data source query\n", + "* Send the query to the data source via the data source APIs\n", + "* Check the status of the query via the data source APIs\n", + "* Fetche the query results via the APIs and, if needed, converts them to JSON\n", + "* Translate the JSON results into STIX objects" + ] + }, + { + "attachments": { + "set_virtual_env.png": { + "image/png": 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lbnNpb24+MTQ1ODwvZXhpZjpQaXhlbFhEaW1lbnNpb24+CiAgICAgICAgIDxleGlmOlBpeGVsWURpbWVuc2lvbj42Nzg8L2V4aWY6UGl4ZWxZRGltZW5zaW9uPgogICAgICAgICA8dGlmZjpSZXNvbHV0aW9uVW5pdD4yPC90aWZmOlJlc29sdXRpb25Vbml0PgogICAgICAgICA8dGlmZjpYUmVzb2x1dGlvbj4xNDQvMTwvdGlmZjpYUmVzb2x1dGlvbj4KICAgICAgICAgPHRpZmY6WVJlc29sdXRpb24+MTQ0LzE8L3RpZmY6WVJlc29sdXRpb24+CiAgICAgICAgIDx0aWZmOk9yaWVudGF0aW9uPjE8L3RpZmY6T3JpZW50YXRpb24+CiAgICAgIDwvcmRmOkRlc2NyaXB0aW9uPgogICA8L3JkZjpSREY+CjwveDp4bXBtZXRhPgrJVmfHAABAAElEQVR4AeydCbxvU/n/173udV2za8iUqaRCqJukzEKKpBAK6ReKSNEkGTI3avgbQiJKChVJqAwppKSQKDJEyXC5hntd9/tf761ne/Y6e3+/+zud8z3nfJ7X65y9v3uvtfba773W2ms/61nPmtCIEiQiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiMKAEJg5ovpQtERABERABERABERABERABERABERABERABERABERABEcgISJGtgiACIiACIiACIiACIiACIiACIiACIiACIiACIiACIjDQBKTIHujHo8yJgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAhIka0yIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiMNAEpMge6MejzImACIiACIiACIiACIiACIiACIiACIiACIiACIiACEwajwjmzJkTbrzxxvDAA/8Kiy8+Lay33nph6tSp4xGF7lkEREAEREAEREAEREAEREAEREAEREAEREAEREAEBp7AhEaUgc9lDzP4/PPPh1NOOSX885/35qkuvPDC4YAD9g8LLrhgfkw7IiACIiACIiACIiACIiACIiACIiACIiACIiACIiACg0Fg3LkWuemmmwpKbB7DE088ES6//PLBeCLKhQiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIQIHAuFNk406kTO6//4GywzomAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIwwgRGtSK78dyzoTFndlsIp01brDT8YostWnpcB0VABERABERABERABERABERABERABERABERABERABEaWwLAu9jh79uxw6223hYUWWii8/GUvq33njWefDLPuuSXMvjf+/fPP4fkZ/w5zn5kR5j73ghJ74rzzhYlTFwnzLLZ0mLLCmmHeldYK88bthHnnH3KN6dOnh2uv/U3mTsROTpo0KWy00cb2U1sREAEREAEREAEREAEREAEREAEREAEREAEREAEREIEBIjBsiz3OnDkzfOGLXwwzZszIbn/jjTYK2223XVMUs+/5U3j6xovCM7ddFeY+P6dp2PTkxMlTwtQ1Ng0LrPvOMHm5VxZOP/744+Gyy34RHnjggYCF9qabbhpWWGGFQhj9EAEREAEREAEREAEREAEREAEREAEREAEREAEREAERGAwCw6bIvuKKK8LFl1yS3/U888wTjvr858PUqVPzY7Yz+5+3hBk/+2qY/eBddqir7ZSXrhEWedsBYfKyq3WVjiKPPgL/+c9/wlJLLTX6Mq4ci4AIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAI5ASGzbUI7ju8zJ07N/DnZe7Tj4cnLv1meOpPl/nDXe/Puu8v4eFT9w4LTH9HWHjzD4YJ8y3YdZpKYDAJUKZuuOGGcPPNN2d/Dz74YLjgggsCAycSERABERABERABERABERABERABERABERABERCB0UmgqF3u4z2su+664brf/jZgIYtsFF2LLLDAAvkVn3vwzvDoOZ8Kc554OD/Wy51GVHDOvOHCMOvvN4bF33t8mGfxl/YyeaU1IARwXXPssccOSG6UDREQAREQAREQAREQAREQAREQAREQAREQAREQgV4QGDbXImSWxR7/cffdYb755gsrrbhinv9Zt10THr3g82Hu7GfzY/3cmTh1oTDtPUeGKSu/rp+XUdojQOCxxx4Le+yxR+HKssgu4Ojbj0ajkQ1U3XvvveG5554Lyy23XPaXzsboWwaUsAiMIQLMLnn00UezOvXf//43WyR55ZVXDosuuugYusv2bsWY/Pvf/w6PPPJI5prsJS95SeY+in6FRAREQAREQAREQAREQAREQAREYGwTGDaLbDDOO++84ZWrFf1Uz/rrNeGRHxwasJhuJpMWnBbmmbZ8mDRt2TBx/kXChMnzhYlT5g8hKs/mzn4mNJ57Jsx9akaY8+gD4fn4N+epxyqTm/vMk+HRsz8Rpu32pTBlpbUrw+mECIhAcwJPPvlk+M53vhO+9a1vhVtuuaU08CqrrBI22WST8KlPfSq8/OUvLw1z3XXXhTPPPLP0XDcH119//Xxg46c//Wngz2TPPfcM6623XvbzvvvuC5+PPvu9rBbbqo9//OP+UMv9f/zjH+G4444rhDvwwAPDq171qsKxkfxx++23h6985St5Fvbbb7/wmte8Jv/d6c4RRxyRLaBL/OnTp4e99tqrMqk5c+aEs88+O3sed9xxR4D/kksuGXbYYYch/CoTGYMn4HLZZZdl7pDOP//8QP1KZaGFFsqe17ve9a6MsZ/ZlIa131dffXX47ne/az/DlltuGYjfjfDcvvSlL+VJ+LqWH+zBDgPgv/jFL8IPfvCDrMxUJfna17427Lrrrtl9regGyqvC9+s4z8y3G+SJGWj9lD/84Q/h5JNPzi9x8MEHh1VXXTX/3c+dfpStXuf3mmuuKZSdww8/PCy77LK9vozSEwEREAEREAEREAEREAERGAYCw6rITu/nuftvD4+ef2SpEnveZV4e5nvZumHyiq8JU1ZYM0yIVtTtSOPpGWH2PbeEWffeEp696/rw3H/uKUSfO+e58Oi5nwlL7nVSmLTEi9bhhUD6IQIiUEoA5dLRRx+dKUTLlG0+Espd/k4//fRMqYzCc4UVVvBBsvMow3stt912W67I/uUvf5kp3O0aKG9Nkb388ssHLMlRInpZZ511wqabbuoPVe5jLfrBD34wcB0TFho9/vjj7edAbB966KEChw033LAnimwUjfBGrr/++kpF9uOPP54p9tKBD8oRAxpeUOzyh+DnfvLkyf70mNq/9tprw957750zrLo5OP3mN7/J/g477LDwuc99Luyzzz5hwQWr1374bXTr5evXEkss0bUim2ft08RqfI9kNkzVPdQ9/s9//jMb3LjxxhtbRkGZyx9K5NNOOy184AMfaBmnHwFmzZpV4MLAQ78V2QwE+Wfx9re/fdgU2f0oW71+LnfeeWeBz+677y5Fdq8hKz0REAEREAEREAEREAERGCYCE4fpOkMu8/zM/4ZHzvlkmPvcrPzcpIWXDItssmdY+oBzwpIfOiMstMU+Yb7V1m9biU2CE6LV9pRXbxAW3mrfsNR+Z8W/74SFN3pfmLTAYvn15j47Mzxy1sGh8exT+THtVBN45plnqk+OozMoLMezcP8oiY488shSi9FmbLC6xjobZeYgyYQJEzLlF0onLyimn376aX+ocv/UU08tKLEJiNXxYou92OZURh5HJw466KBK632PAQX2tGnTMvcRU6dOrVSM+zijcR+XPIccckjYYIMNWiqx0/tDqY317Zve9KbwxBNPpKdH9W+ssNdcc81QR4md3uj//d//Bf7q1t00vn6LgAiIgAiIgAiIgAiIgAiIgAgMJoERs8iecfFXw/NPvaDMmrzES8NCG7w3TF3rLSFM7E+WJi+1cpi82QfDghvtHp69+efhiWvOCXMeezDMefyh8MQvTgqLbHtQX57QhRdeGLzic+ONNw6LL7545bXOOeecwrm3vvWtmTKncLDiB1N8//Wvf+Vn11hjjcBflVx66aX54puEwUrJy1//+tdw+eWXhz/96U8B39MolrCIXHrppcMb3vCGzFIVP8jNBMvBBx54IA+C1eDWW2+d/66z88c//jFgUWWSpsG0YSzSkGefHepn/fvf/35AUZnKTjvtlFl5psfT31gFcg2s/R5++OFMYTT//PMHrBpxm7H55ptnCpc0XtVvFDT4vkVQ0L3jHe/Ig3Icy9Zbb70148b08EGz6P3EJz5RcFNA5lEAo9zGwhmftVhsY+H8u9/9LrPEzm8w7mCdvdtuu4WLLrooTJz4wljawgsvHF796lf7YEP2sfi0xWLtZKs47bgYwCr7m9/8ZpY3S5+8HnXUUeGYY46xQ6Vbwn3oQx8qnMNKdosttigcG+8/aEOwzPeyzTbbZIMb1AVff1HwtrL29+mMxn3u8YADDghf//rXh2T/Fa94RWbh/MpXvjJra2iDKWdY/HsXOUTEuv3d7353dnzKlClD0hpNB55//vmsvmFpngpMaDtgQjszc+bM7J33s5/9LPzoRz8qBKecoQTnHUw7LREBERABERABERABERABERABERj9BPqjNW7BZdZfrw3P3HZ1mDjv1GglvXtY4E079k2BnWZlwqR5w9Tp24b51t4qzLz6u2HmteeEp276aVSibxHmjW5Mei0opln4zgRfuVWKbBTeKDG9oBjEKrGOXHXVVeH3v/99HvQ973lPU0U20/j99H4UuyyYNWPGjPDlL3853HzzzXlatsO9oDTmDwXBdtttF3bZZZdQtaDfU089FVLlPL5MUYbXFax477nnnjw4yn0vKJlxZVAlKVMLh49Y3BVUCVbDTFEn/VSw9ENRy9+vf/3rbBo3lpEoV1oJ4VFUI4ssskiuyOb5/b//9/8KyrxBs4In794vLvfwvve9L/PPinI/FawicSXysY99rFC2UcRhwYyyF9l2222zvzS+/33xxRcHlJ4mb3vb2wLHeincCwqxH//4x3myxx57bKBurLXWWvkxv0O9xXLbC0rxE044wR8a8/v4XbZ6/bKXvaz0fv/+978XjlMHf/jDHxaOjacflLUyJTZtFv7Cy+SjH/1o1m7jc57BSBMGHSmHZ511lh0alVtmevCXCuVk++23Lx2UxN89C0DCzLfXvN/e+MY3BgZlh2tmBAOt1AV771etC5Den36LgAiIgAiIgAiIgAiIgAiIgAi0JvCCOWTrcL0L0ZgbHr/062HeZVeN7j7ODAtssMuwKbH9TaDQXmjTPTMXJpMWf2mYcenX/Olxsc/im16whsTiDwvBMiW2D8s+lnMoYlgkDwvcMmG6PMpxL7/61a/8z6b7WHN7JTaBN9tss6ZxenESDh/5yEcKSpFm6WIxzqJ+3nK8Kry3mDRlB5aDJ554YkGJXRV/JI+zsKMXFDZnnHFGKFNiWzis9lGuURa8YEU5iHLSSSdlFuY+byjKzFezP85+mUsRBm9SNyVpvLH2m8GvK6+8MvuDSZngP9jL61//ev9zXO1T9z/5yU8W7pkywyyGKiW2Bca/OzMaGMzxgisb2q7RKgzEpkpsY8KgR9nMGrtXBhGZ7cLAqhdmcfBOGy7hfffzn/88rwvpTI3hyoeuIwIiIAIiIAIiIAIiIAIiIAJjkcCwK7Jn3X5NmLL86mGJ/zspzLPoMiPOdNKSK4Yl9zk1zLPg4nFxyD+NeH6GMwOpIpsPfqxPmcKO4EZk+vTpmTUqH+MoV1ZaaaXsnP+H0vuLX/yiP5Tv4y4gVWBi1VtXcE3i5aUvfemQRaxYONDcqKy22mo+eLa/+uqr5+ctHFtza5FGwJXIoYceWvA5iwsLXGqwoNb3vve98I1vfCPzwbrkkkvm0bE+9/zyE8mOV+wzAIDV9Ve/Gl3txIGBQZcbbrihkMX3vve9ldb4PiDK+1QJTjnAtcKgyTLLLDPE/QVuZXjmqaA0TBVVWJ+zgKKkNYG0DWodY+yEYADIK51ZGBQ3TrhtqiOww3IbdxtemCkzWuXDH/5wIevMbMC1VF0mtK0o8xlU9MKx9F3iz2tfBERABERABERABERABERABERgdBAYdtcic6Nf7EXffWhcjXGoz+KRQjZh3vnDtJ2PDs/86bIQVip3HzBSeevndVFUe/nKV76S+yDGUhKfxyj1vKC4RJmJUg8XJCa49sB366abbmqH8i1+gpn2bvLQQw9lU73xc9pKUuVDmTU2eTJBCb/HHnvYz2yLxXgzFyI+MMpkLEvxvWqy6667hh13jO5vnGCBjFKd+8V/8l/+8pfs7COPPJJZHzezAPTcsfLFPYZdb9FFFw0777xzwAUN7AfNtYj5IjcUqRLNjpdtV1555Uzp9re//S07jf9j9ssGH8riD+cxBm145t4tDcox/JlzH0iZSxF4UN76LX/+858z9zQMuuC3HfdDWKTi2mOjjTYKuDfoRHDPcMUVVwTSpSzj+gaXKvyVDWL5a+Cf36zWF1hggdyFEu2EtRWk64X6inseE5S53A8DHOksDwaKfFhcNHGdZsLgHANtDETgKgjFKANf1NtWjMiH1b/0WnfffXemGOV+uOfDDjusWTaGnKO+pz6gsc62sjUkQsUB2qH9998/7LfffnmIc889N3z84x/Pf4+WHd4r6cKODAxWuampui8GKInHrAjvU593FotieqFM+EUyl1122ZYDc4T3i9VS5/yADO8Qvy5EWnb89f0+ZcnWuaDu8S6gPFBe11lnnaazXnw6dfaZDfDggw8WglKWWPdhEAVXXr/97W8zf+j3339/1jaxrgLtHusgUJ9btQVV90XbxPubdoJnQJrMImI9E97xEhEQAREQAREQAREQAREQgcEiMOyK7KnTo4/bAVJi549jnklh6tpb5j/Hw06q3LWFIvkobKaIXXfddcPRRx8d8NFqClh4YfWGEi1NF+UeSjDvIgT3Iq0U2albEdLl47KfcsEFFxTyiT/uVIntr8/HMxzw9WwssDRGEYpSpExSS/DzzjsvC4a7AKy+vUsKryApS2u4j2GB7hfgwx8t5aGuYL1sC9XxPNOyUjed4QjHwo/4IPb3S/5xG4CUuRShDjRzs9JtvnHlw+wH3E80ExSbBx10UKbkaRbOzqHUos6ff/75dmjIloEtBrt8+fSB3vKWt4TbbrstO8RAmFnvw/GQQw7xQfN9lP5e8U+7UhWWvPn8ffazny3EzRONO5dccklWJ1F6lQn3gPUv1/YDSz4s6xOYxTRK5uOOOy6w4Oi+++5bGOBA+d6uIhvf+17JSn7wJ9+JsBaCV2SjtEfZiqJvNEnqjgauzdreZvfGDBCemVfos+gv5df8uBP/a1/7WuHZ8bxbDSYws4TBAxN4o2g2YXDGLzLL+wHFepXgN/79739/UzdWlA8GPvbaa6+unytKYbhSR7x8+9vfHjII7M+PxD59ANaNwI+8b4fL8sL6BgxW1C33d911V+aGJh088Wmb66yqd7kPq/1qAgyQ3n777ZmfevqCDJBKREAERGAsEsDFHsYYfEun33tj8X51TyLQLQGMs/gOxYhPBgTd0hxf8ScO++1OGP5L1r7HicOu16+dtX4ELFMionRGUdNKaGiwVPby6KOPhmuvvdYfyvexyvZCOLPe9Mf9fmqNjbKgnwt2mXW05QGFZOpv1c75LUqGTTbZJD+EpS4LN1ZJ2rHBOo4POxSPpDXI4u+TfKJkSBfwa5Z/FqozP8r4sx3khdCwTvzud79buJ3LLrsss/TEIjd1KYKiqR2lfiHhGj9Qhr373e9uqcQmKRQ6b37zm4dYXZZdhueHVbxXEpeFO/3008Paa6+dWUOWnffHUl/Y/lyzfbOAbhbGzqUW2xzHzz+W829/+9tDlRKbcCjFjj/++KwNMz/1HPfi02ef2QhY9HorfR++nX3Kvhfc0dRVwPl47GPxy0eT/+s0rTTt4fxtA1x2Tdw7dTOQx8BL2p5WvZ/smv3Y+nKUps89817zC1SmYfhNeWUxYdxk2YBzWbhWxxhsZcHcVImNu6w9kplMrdLq93kGvlkYmhlPrZTY5IVBxM033zx3jdYsf7TjpN1MiU18wvF8Wg0cNrsW55iFRhvL32c+85lWwcfEeVwcMWBiM4XoO/D+YKYB/UcGOBlUKRNjRZhBFga1La9+ttCg5pmBPPIr12e9fUKjrRz09u6VmifAotS8h/iO5ltQMrwEGPy2Nrmd9bg6ySXuAe1arfQZnaQ/nuKwIDuGA8xI51tGIgJ1CQywVrnuLShcpwRShSrpvPOd72w5tdqux8uajxIvqfLZzmFJ7ZUSfFC3+ohM02J0u5/C1GU/ZZwP/roKIaxRvZg1qj9m+2XcGRQYDVZK6QcQFowoo3HHwkDGWJNtt9027L777oXbQoG91VZbFY5hTd9PBQUK9bL08d1O2StbNBFFLvls1cE6/PDDhyiKSBdFTyo8b6xY25Eqi+d20qgTlvtEWYK/+VS4HwbpUkF5T92rUmZbeNJGKWNucex4J1vSwtLfC+3ueBYGhryFOiy8y6hO2NCepmlcd911nSTVlziUU9qXMiUtZbWs/lGnmSVUFqdVJnm30R7gAswLZRGr/kESXKvwUZOWCfLI4AR9AdrcVOhTlNX/NBwzMVKGq6yySuZ6KA1LHt74xjeGn/zkJ+mp2r9xN0PbwR/WyYMquJWiDcXwwPeF2skvg4kslL399ttng6Nlz5ByzCwSZj9gqZ2KsRr0PgXuriyvrd4h6T2OxG/aWfJ7xx139OzyX/rSl7Iyw2yR8SqDVg7o01CPTz755PH6SEbkvpmNZYZg1ItJk8aXcdyIQE8uiqswa5OrBkqTKB3/5HnbtaR87RhjFpHF3OnTofdh9qREBOoSkCK7LqlxEA6lbd1FtcCBYhplrxdzLeCPsY8LjvXXX79wuNloKVZnWGSZ4M+2nbxZvHa2+Mj0wkKXdQU/pt7C3Xzn1olPvJRNnXgjEQZL1zKFIFP4sQxF0X3CCSdklvl07seCYMWEmwMTFCB0XrxgDYg7g35JagWMUhXLg1tvvTVg3cvACZ0qrIy93HLLLYEpW3WEe8QCEWtq0r3pppsy6+tUkX/kkUcW/Aq3ShvFv3X2Uqtb3C7YObYoQOw3efCCstfOsWUGgxdcU6SWk1iR05klLT7e6eR6VybER5mN9W8zwbWBTxtf27gywEr+zDPPbBZ1yLnUzzwBaD/Gs9gaA8aAspgOktq5drZYy3j5/e9/73+O2D4WuumClJQplMoo7yir1D9mKND+eKFON3NV4sPaPi5xWF/CDw6jEGbwNh2UszgjuWXgjjpuQnmgjeUYdZhZPSyMShvIugVemvUrfDj2YYA1OspWZqZQN3k2LOqcCgqKTmeapGkN6m/KCa7RWNPE+46vm1+eDbNWmBGEwBd3abjEuvPOO7O1Ck455ZTAoAECd5TmPEfJ6CSAix7KTDo4OzrvprNce+OUCQPgOpO+Cs+EhZIlw0cAF3O0aRtssEE2K3D4rqwricDoJkAbyuw7hJnb/R6EGN20lHtPQIpsT2Oc77OollfG1sGBPyMvKPmqLI5S9yJ8qKdWUZaW/+DmGArSfo9ueyU8Skk+tvx0/Wb75NErXrDA4oO4jqy66qpDpsDXiTcSYVgIiw5ymTKb/DBFHt+0dOQYfHjd616XKQlZxGy0KgFwZ4MSpUpQKpVZB1aFb/c4rglSBTCKntRvK+UPpQGWIF5g30qw/sQyjjrqZ07wvFEGpxbfXsnUKm3KAWWcv1Rhi4LKzrFNf/u0sbD1YfHXbsLHA0pxExQoKE723HPPMHXqVDuczbDAtzYKPC+4yKnr1oRBG9I+66yzsmtiIduOMODghbz202WSv9ag7qNA88Jz7oWk/q6r3k29uFY7aTDY54UZAyyYjFLZl4X55psv69Sn7Y+tq+DTqNrH7yBrV+DL24R6Rh3AD/wgSqqMxooc63rKhVcU0QYyEMX9mPAOaubOxcIRB1czWKP7tgRXGPirhw910wQrYvyIS6oJMDPLyhl9BAYbGFzFOpuZW7hpwXKXacQ2AAFXXCtJ+k+A2VcYiKRGG/2/8ti+wtZbb51xhW36zhnbd667MwIMQGPwgKg9MyraikB9ArSj6F34npNVdn1u4z2kFNnjvQS4+/eLYLnDTXfL4mCVUyb491xuueXyU0yxr/JZmiqysSbrp6B49r5HUboy1WW77bar/cd0aC+2+KM/VrbvP8LLzg/asWWWWSagHEVp2kr4qD3qqKMyRQpKGTp4o9H6CgUvVtCp8LGeWganYbr9XTbFu2oAiGulvutb+d8lDtPxUVqXCYNbLIzoxdcVf3yk9lmI0TPB/Ukz/+so8LxlNnF//OMft8z+ueeemy22SVnuVNLp8r1S2naan0GIl7advWLiF13kPlHqjrSguEutrCl76cCUzydKXO9qBBc/ddwDYGGMr3w/SEubxQwO3seDKPQLvPsTBtGa5RXXRVgBe6nz7mUmRbMBSNoIBri8YHGH64yRFgbd6LO0I3UH6tpJ04flncBsHYTZBViFVin1eGZ8qBIOYcaRb7+zgyX/uAfKR7tSZ2CjLM3hHnwnn51MUSdOnXvkHU+bSB+ujnD/nfCuk3YnYbjHfrhw4R6b+TPmms3OY/gCV/78QFvVPXK94S5bVXmx43XKj4Wts6V96qStpCx384xHiqvNzGPws5+znODTrrUq7WYn7Uon75k6ZaMsTKfljzLWyb2V5SE91mlZouy3+4y4dje8O2mru6lrtGHt9kF4xs3eJ7SdNgMYg6x+Pdf0Oev36CYgRfbofn49zb2fHlc3YdxJpD5wm32QpFbZqeUV1+WDCF9+JlhxNlNKWbhutnU+fLtJv1nc0eAbO80/VmtYWqFkZRox/kzrCAocPl6xam32QquT1nCGoYNRZsWEZTKKqX6Ktxa067AIKcqsMuHZ8CFgf61GtrGe56+ZpBb4g6AQ9Pn1i6vyIWGdIR8m3U+tZpjy3kxQJPbCl3A3H2nN8jeaz6VMWGi3F9LOu6kX16uTRjpIS9tZ5/32xS9+Meyzzz75X9WAseUBVxm4rPLtBGWYweNUwW9xBmHLe+ELX/hC5t8VH6+pu6Q0j4RPmaZh0t9Y/dR5Z+200065spU0sBQq8+mcpt/r37j5YOFDZjjhAo76wQw12vq99967NE98SJ900klZHD4QicOWQQFmET388MN5NpkhgDWUH9zj3jlWZ8CahPxzYnaMn1mQX8jtMBjoB0hxa1UmWG/vtttu+X1Tp/FZfsEFF5QFz46hdKQ9xwc9vFA0MqsPRXvqssongjKAsmfxyCOM6bcy2NRMmenTsX18jsOQP4wirG/MYDPHeD62cPRaa62V5ZP+INfHur2Zcoe+FxbWKM2Iwz2SBrMJ/PvQ8sL2tNNOy66LWywvuIwjPxgoMPjFM6escf9VvO0e7DnQD7J79Ytk47bLjl988cX+si33qdsXXXRRdo88B+6RGWM8U3imiya3SpAFuckLdQkFGOUdX9LcIzPaSNMG0TjPVHfOc00G9HFVRR+W/qAX2lS7Rz/I769H2aLeUZa4Hmypi1wj7QtT5i09XEmVCYORhOHZMdMIAxGLY20+bpPsGLMjvHRaR3wa6T55oq6ymCvtE7PhaHMYTKWsV9Uf2jfeb/CnLMMb4yXqAHE4zn2UPW+UabwnWAid68KVLe3XmXGwcriUYbYwLfWCPJhY3TrnnHPsUGGLC0Z7Rv57mEUjOU59RoiPMQ18cNXJPTK7JTUCICz3zJoOxLf3Bd/3xMF9nx/YJrxJO+8ZX0bt3i0dv7V8kJfUrR5uiXgHWNtHHX//+9+fzXZM64RPk3aVcNRHyhj3Rr1KZ676OHX2u2n/yS8D39wLZb/VMyI/7fC2/Ft5aqettrh2zU7rGvllMJ93KW0Y73jq5oknnljoT/jrYczGs7L2m3jsU195jqmYwRhltM5s4jS+fo9DArHBk/SRQLTqbcROaf4XO9GVV4sv5DycxYkNfWX49ETspBfiR+vBNEjhd3z5FMLHjn/hfN0fsVNcSCf6ZauMGj++G3GaaSF87PgVwkfrnML5Cy+8sHC+2Y9o7ViIC8f4gmkWJTsXO+FD4tkz6HRLmmUSp58VrhVdN5QFG3XHYue+ET+gGrGz3oi+0xtRocjSw5V/sRPWiJ3U2vcZOymFtN72trfVjkvA6HerEJ/nUFeiu5RCXH9fcSHTWmUsvrQb0a1Frb/Y6S9kLSquS68fp2c3oj/XRuxUNmg/6kj8UCukBZdWEjsjhThl7KJ7hDxMtHQsTTJ+TOVhYBg/VErDcTB+xBfC7rHHHqVhoxK0EC4q5TMeMGn1F2dDFOL68hgHXArn2mmHSjP6v4PRH3QhXepJvyVarBeu+elPf7rrS0YFRiHN6MO84zTjh2ghreiupeO0fMT4EVVINyow/enGEUccUTgfFQCF82U/orV/IQ51w0tUEBbOxwETf7oRFReF87zvupWo7CmkefTRRzfSsk19iwqXbi81JH4/ytaQiyQHqPPU7ehypeHbHWuX48d9IQbvWDvHNiorC+eb/UjLSHRl0ix46Tn6Anb96O6oNEzVQfo0Zfdo6bGlDYlrIeRJRIVpg3bQh0n34+BkI7r0yeLQh0vP2+9oEZ+n22yHNp845CUaBjQLWjhHO8+f76fZteNCxpX5IkxUwBfS4kd06daIgxRN40W3MUPixXVNGtyrXbtsSxvn8xmVTXn4tK+e9leiS7b8mlY3ea7N+kk8Q+4nFfKfvp/S/EYlaoN64iUqsbL8cn0vFpd2gzbSfqdbz9vuIQ3Db/9+oS23MGm/xuch3ac/06xcWpqtvnN8uvQZicd3WbOyFRWyTcsQ+fJSVQ7seoSnr2Z5Trfp+y66mcrD+nLjr/mzn/0sD0Pdj0YV+e80fX5HH+Z59E7rSJ5AyU4cJGl6ffIQB2KHxIwK+Ia1HWX5jmus5OlG106F+MSNC//m58vi8y1i7Vwhcg9/UPft2mke7Tjf52USB6TyuL5+RGVjdpx6zvvK0km31MP0fRcNhSrDW/y4MHIhO+2+Z2hbrA0gj77v7BO2OkBY3x7x7ra8lG355vHhSZO2N30fp3F9vY4DZz4rTfc7af/tGZEHylmaF/td9oza5W2ZtzTbaastbjd1jfLS7N3Auyx9V6XfCJZ3v/Vl3vJp70S+uyUi0IrApFigJANMID7AAc7dC1lLp9AwAlwlnGPRRm9BFTtqYeedd86j+HNYQURFYX6uXzt+BJ1rMPUynf7d7rW9b952447G8DBkpJY/BEsKRmMZkceawKxE7N5YnA/LwM985jN2aCC31113XcHaLM0k5Rer9AMOOCA9VfjNAlreaq1wMvkRO4aZ5aUdxnUGFuGpJQVWYuYSI778M6sELBNiZ65yWrelads61qAWdhC390S/lF5wpfLKV77SH6q9j5Wr93XvI2JV1AtZaaWVCslgpceMEHyJj1dJ3drUcZtRh1WaTt0p9XXS7jQMltJeWJui13LIIYeUJrn//vtnLh+wihktQv+CRcvwWY1VIRaKVVaKde+pHdc16WyU9PnVvWan4fbbb7+83Y9Kgcw6de21184WvcTqGCs02hB89pvvdRarNJdSvAtYqJKyj9Usflx5ZzGbKH4MZ1aPWEex3glxbNE+1rrA+q9OncEq0p4JLlmwRqsrzcoi70xkhx12yFy9YVWOT3TzGY/lMBaLZv1Nf5lZM9wfEhWImX9u4mGljPUrgkU3+V1zzTWz31FBkr0zbe0H+pxYdNJWkxb9F9jFwcyMGZa2zYQ8mmUZ72WujX/wVOx9zkwJ1nPAwpA2i74R+eN5sKA6/vOxbEWw+CX/JpxnhhZtKBaxtnAx1udYMLfTv7J2ow5v1prgvXVmtHqFG/cZFdhZtnrhe/+MM87InzMugMgT6VJeKPO2Fgh9I//9YFyabVl8FIlK0BAHyDO3Tlh+2yKl6667bnae53LwwQdnLhF5HtRFhPIHq3Qx4exkyT8rr9wH/UT6dyxYG5U4Wd2lzmEJTn46Fdw20r+kLtozJ//UbcT6eZ3WkWb5YpaDWQ5HpV3GlGdF2xEVYBkr2igsp2lz7H2P1Tvfg9QthLJMvVliiSWysnxYtP6EUZlwn4TnGwOJirRsAWXep9QhZlbwzUFZoXyUWXOXpdvJMb4RTHo92wk2lEHqV1TiZlb8LOBOG0G9Y5YQbTqsEBa0trrBzCOO0x/GmpbZmax5gzBr0c9Oafc9g9UxbRb1jzzS9vAsvbAezCWXXJIdop4RB6FNpW1GKC+0pzw/ZhXgFpAygxs/LPPjwEAWjn/cs90nPJjZS12l3867gjbD3hl5pBo7vWj/KWd1nxFZapd3ehvttNXE7aauYfVP20QdRnjH8D3EbAJmDvCseJfx7U9fjfctTFkbw4S+CS7g0AvwPuT9gcSBqhAHiDMrbQtL/4x6TbtI+ZKIQFMCrTTdOt8dgXYssrlSnKZRsNZNrb2a5aZbi+yykbFm1+NcmQU0FmnNJCrkCvcYp8bmwaPLgsK5OPUvP1dnpyw/jOK2EiyCvOV1/BhqFaXj81iz+muNFYvsZkB4Blhqx8ao8MdIdV2JHYVCXEb625FOLLKxLEtHoePLuFFmIR2nnDfNTjOr7pQLFg6pRIVOo46lhaVFGcb6N5XUIhvLiFZCO2Tpsh0ki2xvmeTz2Ml+XMQxR8Ez8GlUWZzkEdrYodz7tFuVnVZJx0G3RvwAzP+wfPcSO4OF63mLOR+unf3U2qIbi2ws4DwP9lNrnHbyZmE/8IEPFNKl3npJrXuGwyKb9sPfK1Yy3Upqke3TT/ex5Oml9KNskb977723gTV7mv86v1MLtdQiO7VGa8Yjurwo5IEy1a7ED/08jXYssnlvxo/jLC71OxXqiL2fouIoP21WcLBK6xF9najgytLEKttLdEWQ5xMLtboSBxPzeGVWl3XTsXD+Gcc1NuxwvvXvQWY6mURFTZ6PsneUb2f8c+QdaNeMCpchzKL7j/w8bbe9C8oscb/zne/kYXmH+HeK5dO3/1iPpxbsUWFQsAj2loW+TaMuW14sbWYqWJnhnuhTm7SyyCZ8O7xJl+dNvLI+C+fpt/FtwR95qyu8TyxdeKTCjD7O85fyS8Pab18v4roDQ56ztx7HGj6tO1FRll+T959JWTngnL8e+1GZZFGyrZ8xFBV0+blOLLLzyHHH2gQYpdJpHUnT8b+pa/YsosLfn8r2sZq381HRmJ+PSsr8OHU6LcueA/EJb+LrbFRoN6JSzU5lWyydmS1p16Wf2C/xZTGt73b9Ti2yiU97kc5cju5k8nujT2ESldj58bKZJwceeGB+3tqGTt8zzASw+4uDipaFfOufkekyeP9gvUs8ymlqLU+d411n6caB4yw9nq+1m7Rvll5+sbgTB3PzeMT37aYPl+77fLbT/nuL7HaeUae8ybdxYdtOW91NXfOzIniHpuLrPywR/671M3ksru+zxoFFO5xt46Blfp+t9EmFiPoxLgnIR3ZsDQZJUksW/ODVlXbClqUZlcBlh5sew8eVF0YkGU1vJviQwkeSCf52zSc2lideurFQ8Om02sfKw6x6CIsVGCPdkhcJ3HTTTQHfh/aX+gl8MeTQPSzr8ZuJdbYXGKcWtf78SO8zapxakscOQWY1QFn3gm/A2EHxhwr7jFITp85f7BQV4vIDC398m8WOci2/5FhfrLHGGpk115DExtCBdDZFN7eG1UKZYJVpFnFl59s9xnPxgrVpNxI7ktmCaSyaVnfhtG6u1+u4vBNSwWqnW8GKzstGG23kf47IftpuNrNI7TaDWHCl1qNY8qRcur1Or+NjVcbaGPhILRPa0Khoyvxr0h5jkdqONGun03TMiiw9Phy/saLDyikq2EJUYA65JHljnRKEsCZm8cjvn//853Y421LeaC+wPsVCPyqPCuc7+eF9n/q+XSdp+ThROZpZI/pj7PsFjb1PYrNExBLV+9+2+CwcalbDWCZanxnrTRNm4qXPHMtsLJyj4iWbOYNP4jLBehRLRwQLQ/qzZglbFp5j+JdN+/3MzvF+Z3leCJZxZlGJdS9W8+l7CSthX2+wmK4r7fKuky4+Xc23f10LZtJlbRDKfTRAKJ2t5L8z0lmhdfJFWUmf8+abb55Hpd1Mz9PmmFjZsd+ttpQrLOS94Kff+pG+Dvkwvd7vtI40ywf9e54VixLbLAcf3toojmHFb2KzXmFA/UrLMta2ZgVvcWzr6yx1hf61F2aT+Dpk1/JherUfB/3ypPBD3WvBKjWdGcM3QnRXk12KbwITP6OQ2ZpYrnuhzaft58/OdfqeoR9LW4vQzqTvEqx1EdpCm5GCH3CbiYL1tS8bhKXO+UWW48AghzPLbvsmP+igg/L0spP/+4eVN+WwXfFlqdP2v51n1Clvf1/tttVW/tuta1hh815DmAHFOzQVZnzZcWZdIH5mPn0Q3z/hPM/JyiH34oX3rIl/v9sxbUXAE5BrEU9jAPbpwNr0DbJDx7WOxGGYIQsp1Innw6Cw40XUzqKPqeI5VdD49P0+0139gjAocljhnpXuTWhwbYqfHWu1TTtChOee6Gi1EjpgfnEBPqZZoELyAgFeYrYQDkd4XkwVakd4efFcfRmHMx+KgyYo0r761a8WssUHpU1LZxob011NmA5HZ8amTNlx2/JhlCqV7Fw7Wz6M+aPzwAccAwxMbWTqpH8+liZ1jY62H6ixc2Nhm079Z7qp7wjXvUfaiPRjweKWLbhp5zrZkmf/rCg3KEDaaXvtutGiZchgCwt1jSZhCinl1E8LZSqiVyw0ux8Gw9I2hEX5qJNeeqHIhnc3Qt2N1kR5EnTUe12+SJyPBNoIBmcY1DK3CZxj8R3etf1UonOdToTpxdF6sRCVdwaLVFFGcKvhP9YJ2K5iHqVRXfcH6YcUz2+4hDY7XSAPJTzlnfLNoFVaxskbU3WjZVSWTdpDuKH0YPFP+jls+euVeGUEhgm9Euo/bUMq/kOX6c0I/TxjQfmociXg+4j0O3HFZeUHRUhatuzaTKc2tx12zG9ZyM+UzBzH7cuyyy7rgwzZx1CjyrUQx1F0sggm07URbziCcriqX8t9fPCDH8zimNIo+9HiXzu8WyTV9Wn4eeEbh7JFucctB7w7FZQuZcYC/tmXuSfzypl2rs21rN/o41G2bRq9V/D6ML3c77SOtFIO4h6APy+4lcDFB/37Mpd60fI2r3cMTKWKaEsLFz+8y7yggLU6Sx+8SnmMAhU3Qb+Offl0sUufXrf71ubxnNPBim7TJr4fQPHpUUZRVvvBcf/NSr8S4yHcLdH3oV9IP4l+gZdO3zOkwQAr/RmUzNEKN3+v4u7D3B6a2xnC+/aIfKcDrYRBYEmauJdgQN4r65u5EqLdM/dYL6TU/L8vS920/+08o254292001Z3U9d8vxFWVc9r6aWXzrKGa1iU1gxaUv943nzr0M5hcEC+rf1Ny6HdG7oFExu8sN/aikBKQIrslMgI/0aRYi9FskJH23ycNcsa/nNZcddLVSfXh/H7rGJPp6Ou8pjGyvuzJi0bnfXplu2zIjUratuIMApxPri8T1MskVKLiLK0/LGyjx6Upt5CyYf3+4wYe0U2HQA+JNrl6NMcS/v44POCIqRdRTbPkxcZviZNhssSxa5XZ0vZplPjhY6K76xTL1EY+HvhQxcljFkf+Pj92KfzT774wzoruhLJlO/+g5ryz7Nq9THSj/wNR5qpsgBFTzrC320+OlEwN7smSiWzXCAcnUU636kCr1kadi5d+RulVS+t1O06/d6iyPeKbPYZpGmllIcj9ZKPNgbbTFFlFiiWbwYP2rEItHjpNk6PTw+19TtVkDCAXGaRniYKC7OM4Rztz1ZbbZUGy35jYWQfCZQF/Cd7xS0fnigXqgbdShMdpoP41PQfL1ie8i5u5nvU+hF1s4gyrK54P6LEqVI81k2vk3C06zxDFDKmrG2WDlaw+Mk1n9DUJatbDApQbqJLt0A/rBfin43NrquTLkpom41CO86Hr5d0cMqfS/ejK5r8EB/OfqAwP5Hs0Nf2/e0yZWMSpfKnf+cSKLrFyQaYm/Vh0/tNE6fNQpFNfUDR6ZU5zfKKMg1lP21LO+1VO7zTvPbjN5bvzLjgWVr57cV1Ugt4S9PeHfwuU0j68xanzrbZs6oTv1dhOq0jda6PUpIBU/ox+MD1bXhZfPOLzTmvuErDlvXl/DcDvv2bCedpN8kP/fpOByOaXSMucped7kX/ouw6ZQzKwnEMhSLf1tHdSWYwhCLRG9Cg2KevhVIx/V5u9z3D9RhIsL4GFtjWz/AKTwYjTLiGiTcEsmPp1tpn3/b5900avt33s6VPOt3U03aekeW5E94Wt522upu65vtKzOawGR2Wj7ItTKlnGCsyiGK+3DEMM+MwW/eAmVOpfobZeCbdGo5YOtqOXQITx+6tjc47Szu2WGD4l3bZXTHahnVoKp0oYGl4/Ohumqb/TQfTT+ljKhcvyTpCw+UVFFgY0VH1H6QoPNsVPtpTpZN/UTVLD2Wgt8ggHosYSF4gkL7ko8+5gJVMu5J+iFdZwbabbi/DoxT2L3/SpryndQpLERQDXpheWeWiwoeru88iRFg98IdVop/GmKbBjIi4enwWzp8zZYE/Nlb2+bi0zjP3dO211wasgeoIyh462fxF34F1ovQkDIqkdBAICzPf/tW5EB9m6SKjw+WOqU7+2gkT15MYUpewxGnGhI9mG1zCdRGdZhQ+KPdZ8M4LaaWSKitaWcUxSOIXdkrTq/M7teilXakj5513XmbxicKMv2bW1OksBRZhQsnvhUE3s2rzx0d6H6suLyjbm324EtYsVn28ZvtMOU8H/svCR3+eQ/pWzZQuZWl0e4znhBU1gxP27uQjkLLOrAX6LalQNlhUDStEyr03MGBgk8UI6V9Rdzp5h6fXY0DVLFwZNK3DljQwHGDgjT+z3vNpp305fy7dT6/Je7nVH/1X7yKiSsGZXqvq9x577JEPGPOsWn30N6vDXMMrwckrFrUmaV/EjtvWFg/GMrKutMO7bpqdhmNAC6UcrmBMiY1yHoMX3tvmwqXT9IczXqvn3ElefFmoG7/TOtIqfQavUKyx+B9tC0pj2gP6IriywG1IKnW/M9M8k47vE7SqB7jkM6l7TQtfd2sKYZsdUjce4eq0v63uMb0e7wYGsPg+wRjLC0p9ZmSxYCz9R5NO3jPEZTYZBj0Is4Ds2diCqlzfG5vwTjVp1T5z3th6d2C+XbS0bJv26ex41bZX7X+7z6hT3nYf7bTVdct9WV3zz4tr13lmNuMagy76ZuhRGDghrgl9TxjQbvjBDTtv2zr1w8JqOz4JSJE9YM/dK3cta0yxs5eDHbMtDRQfKn6k3c510gCgJMOKJ228LE3bMvKeWrzEhSrzl46Fa7ZlSqcX0jShw+qnj9rxVlsa99RHIz656gidTZQpXhhhJl+dsPTpjIV988dm98Lzj4tx2s9aW15YqYI4VZDXSqiPgZiS7K1luRSKj7KRfjpo+HnzggXE4Ycf7g91tW8DVQxW0TFNp5qXJU4n1ctYL7/eMpVOFL7EWwltHcpj8yuduhBoFb/b82YtaekwuwWFuh8ctHNVW5R8qeWTfVRUxRnU4wxCptPFWQkeq50qJqnSk2eJdTOKMS+8S8pmNqWzTFpZL/KhlrZf/jp19nGN4YV79DOR/Dnb5/6xsvLCqvHtSFxMbMg7lVknrd717VyjF2FTpXSr2S18EF1zzTWFS7dq76gzKc9CAv/7gXLV1y+UM6uvvnpZ0L4c410UF3TK0mZwggEaPjZRUJP/gw8+OPsQrLo4Cm+s8bDmZ3AP615vBcd7zlvOVaVT5ziDJQjtbx22hPX1t1u3P76/SL8EJU2rP/zveuuvZnUbhTBlkz/eyalggc0AEwNo9sHO4Fpq0e/jpetv+HPs42bHBIWRd6HQzMAFJacNUpX5LLY0B3WLFR6zCkwY7KP8xoXfstkZDNJ0W14s7dG69e1S3XvotI60Sp9+i+WHQQa+R7GmxwXMiSeemA26pWmgwDJpZpxRVkf8e7vVDBBvyZt+G9r1u93aQKu/Vt00mQndD+HbBEtp2ncMaxhgjAtq5pdiVpb1t7p9zzCAh1AGuA4GAQxoIOmAk5+RRvhWbTR1HvHfiWYBn51I/jVrw5Og2c9etf9laVcd65Z3VbpVx7upa94ogm/+Vs+L89OnT8+zwiA3rmDOOeecbNCY72PWcDALdvoLDIB58fos77bMh9G+CBiBYVdkz7rnZrv2wG1n3f2i38qRyhwdjbTjGVcGztwG8DHCRwwfaTTkfAAzLYPzCK44vLQ7Ym9WA3SA8b/HR1NqWWpKuvRDhY87FNntCEp730j50cBUEdFOuv5FSTysObBmo3PMgAAvz6oX4bbbbjvELQT3yuISfCxXjWzyUcEINFZv9jzayfNoCMtHcTq6j3KEjmrZh116TyiJ0qnMpFk2eJPGHa7ffCylLkWwKqE+VAkdtZQL0/ZTtztV8VsdT32Z0glopXRNfcSl1r+trjkI59NpvM2srLFKNuUBeUdJnLZR/p5Q3jG13guW9MMptNdpuaENYVZLq1kkKFXwO2iLgFm+KRv9mt5q1+jnlnqWWpjiuod2o+yDj/aHGQheyj58UUCXWfH4D2LSwD2Jt/zx6dKuo5jqVni/YzHlhfdOM8UUH6D+A40B13Ytj/igYEEmL7zry/yX+jDDvZ/O0EkV2z4/MPGKWTtXNfBh59lilUYfqkqY2bHjjjsWTlPevIVf4WQffmA9Z2L1wCzU7Diz2bxQflH0MZjKPZgw2wzjAQZ7vM/ZbmcYWPre4h8FSasBEvpj3mK5234A/Vf76Pb3bfmzLeUJK1/+UBQzBdqsyRm4qOo3m2U71u3eV7WlS18cQwraFPpEJpSzqjaF61W917DutPc4/STeh342R7MBbT+wMxrfB7g4NMGQB0WZny3JuWbtpcUdrVv7FiP/VeskNWsXq+670zpSlR7HUVzZTBHea7Q9fsCFMH5Aht+In8XB+7nqG6JsViyD3qaUZ2ZoVXtP3bI21Baje+Hqvf1v7QdKOW/h66/y6KOP+p/5vg045Qe63MEFFW0/TE3oKzDQiIGH9xVubGxL+LrvGUubLf1Y63/Th0VRa8IMCi/++9yvFeLDsM8MJNpo67N4QyJcjVXJBRdcUHWq9Hiv2v/SxCsOdsu7ItnKw93UNT+AkK6J5i8Id54XfSSEdxDlkNkYZljA+xFXP8x+xXjD6g3tB3XHxA9O9WP9GLuOtmODwLArsuc8eFd45uafDxy9p373ozD38X/3PF9WgdtJmI6v78gQl5FeGgQ+rPiIRQnDB7y9HDfZZJOw/fbbFy5T1XkuBHI/mGpqrk3oPKEkoWOCry0URSzIQUOVdqAY+UXR285UFy5L+DL3IXRSuJ9OJVWWkg6dIVwzwI7FIHjZVwlKA/sgsjB8uNAJYHoMyhYsoWDCsyJNLHtIk8a5mQWOpTdat3C0DqTdA6vKM7qK1TKc/OAHnVNG6LFWwve6WW1YXP/BZ8dGcks+0zxSz5qVbT4wve9ay/9uu+1WWKHdjre75cPYM0dRh7KPDp7vNJsVFmXSd2K5Xmqh3W4eRiI8ikfrHHN9PvpR1DLlmEE2r9jjI5cPKC/UVVigqOFjC6FNpBNJu4N1ogkdqnSGiJ3r57ZMiUinDqtdlKrUJ1OsMNDHRw/PHRcyqU9Wm8ZbJ7+4mqE9a/ev3/WV6ZmUXbPWsHuhDeGeUZBhoWNMUPYwiJoqHC0eW+pmOhhk51Pf1HxY8R41RRUDn+zjbxtlUto2WDrtbs3K1uLhQxArFmb/mHUabSeD15TLdIYI7+FOhHaDd5UXLHb9x60/18l+t2UrXaODZ4t1lylG2TIoSt1BYeIXI7L8Uk/q9L0YQOD+KV8oQ2gfYEE5TwdUaCNSyyG7Xr+2Zo1G+t6qyq6HwtaUltbfo91klhCKV9qQMmGwzKRKMW91zMK12jJDwNZh4Jmg3KhS0sKafpR9vNLnandgpiw/9FER2navTLGwMGIAEC782QLIpmzh3VqmOEPpbj73aZta+eVF8WqDlLTntLNVkr63LBxl0PjYwBfXtkFp6kQ6K5K49L/ox5jQPx1JYdCdPjF/9r3SKj/WBhLO930sHoOa9DdN2i2rFm9Qt95y2M9UtfzCJx3EtnN+WzaTt9M64tP1+35AwSu9LAzPBhdIJv5Z8W2JUM7Nd66FY4uvbdxdlokZHvBOrqpfKNWsDtl9l6XV7TH/veitSUnXztFfszbarsc7vsztip3vZEubQNuPNXaZgp+BdOtXo+BEOnnPki+PBgAAQABJREFU+LzRdtuCjljeYjiG0A6aiyMLz7vHrn/IIYeUDmDQ12dglDbajM54t1g82syyvhiGdp0s9N7r9t/utWrbLe+qdJsd77Su0RZZfwEDoTIjG77FeM/wvMyNJfdIOaQO2kCXzx9lz9LluNd5eUW2t5j38bUvAjmB2NkfVpn77FONfx21ZWPGpd9oNJ6fM6zXLr3YnNmNxy46ofHgcds05j43qzRINwejO4ZG/FjK/6JCulZyUdnSiB/UeTyfRrofP9Qb8YXYiFO5CuFPPfXUpteKHcFC+Kiwa0SFTyO+QArH0+v533EaWRan6YWanIydoCHXIl/dSuzkDUnX5zt+vDa9RFQaNWLHqpE+P59G1X70+9Q07TRvsYPTNPygnYwfJDjGbvoXP/obsdPRNEz82Gzr1qL1XCG9uDBeW/Gjwr0Qn+fgJU2fe4zWQD5I0/1o5VZIn/jRB2nTOHVPRmXFkLTtGcA5fuBWnqc+e4kd3ULYqDj0p0v3o4KvECdlR6Q4CJaHiUq/0nSikigPQ/6jYro0nB2MVjSF8HbPbKMfcwuWbeNsiUb8yK8M36w8RoVhIS1+eKZRqTXkfK8ORMv9yjz7+222T32LH7eVWYodzK6vYde3i0QLjEKa0aWJnep6y71EBUYhfbu+bbln22+2JV/Rgr0yT9E9S6107BrpdakbXqKSpZBeVCr50/l+7OQXwln6rbZRSZmnYTvRj34hrfghaKeGbHnH+7LN9aivvPM6kV6XrfghVLgXzyNl78+V7UcFZHZLvGPLzrdzLFrAdoInixM/9PLr05bE2SIt/+JHeSO6yMjjRcVvg7IVlSGN+KGXtZ0+/7RvUVGYXS/OKsrj8Q6i3xmVWtkfbXD8gMzP824x4R4tzThY0og+rLO4dr7VNi46nscnnajEadA/jRa2jahgbcAhWtNlx+06vDeiwqWQtJ2LSp7CcfsRB3Dz65C+CWXbt/PR4rsRB6Ky9OlTR2OGPB48TaLyKT/OtaPSuhEt3bN+NbziDMH8fLQUtGiN6HouP851vPCM7D7Yxhkd+em0HJMv2hHeYTx33yZxP9yXSbSKK6RLexAtXhtxUK/Bs6Qu23WjIsmiZdu4xkZ2jut7sfDt8iYN+hcWn75EHFxpRCVTnnxUQOXn/bPKA5TsRAVmHieuf9GIA1eNqABtRKVWI1p8Dnk30GZQL1oJfUbySvkvk+i+Lb+uvwcLyzG7V8KaVJWDVtcjfrTwz9KMA3aWXHYvvoxERW2DbyXqN227P0d+fNnyafIOjRbLDfoY1D+k0zqSRS75R5k1JpRV+pe0NbxzKQtxgD0/T7io1M7qFUlxP76+8q6MriAbPM84UFmIR9zoYibPAel7DlFRl5UT3mPRhWEjDv7k8eFg958n0MMdvmWMQfqeiAYV+TnaHOo5dZV6nPZXff3gmVuacfC2NLf0gQkDQxNfhnnXwBL9AEK/yn8HRYVwdrzT90wW+X//aOMtv7aNrmV8kHyfNtTCUL9ptyiX5I/8++caBxfzeD6f9GHijJWsDEXlaiMO+BTKEumnzyJPKNnptP3v9Bn5+2jnvU62jVu7bXU3dS0O9OfX5dnQ3sGcNKMFf4NyZvmib4PEwez8GHHoo1LuEeLxbW1xaCO8WJtI30AiAq0IYLUy7PLkr89q3H/oBo2HT9mnMfvBYudvODMz+77bGv/5f3tmeZn5ux/1/NK8UFNlJw1mXYmrxTaipcqQNCxNXvrR2jBPLvqlKoRFEdtMyhTZhKcTQkMVLUoL6dl12Uarruwjp1n6dc7BCEWDT7uZQqZOmoSh0xtH8htxlLCQtl0nWlTXSiqOKjaiFWAjTl8uTcfSY8vzoBHnA6aZjHZFNvfGi82/vOyFVGdLp4sOSLuSKpp7qchG4eE7T9wHH6+Uo7rCh1TaMSWddhX2VdfzH0t1OBMmVfaS9mhSZEfruLyzk95zqqDn3ujwM7iWhm32mw+9MvHKPsp6P4UP0bKy0yzfdo4Pk2j52DR7vVY2crF+KrJJnzoZZ8+09SyNSbpFoYaCqEy4jnWc03jpb9oEr+zjfKeKbPKCUsZ/yKfXS39Tn8vapHYU2Vw3utsawhXFeifSj7LlP3RTBulv6k36brAwKL6QVJHNoH3a3lucdIsSBGVmN+IV2Wn6Vb8Z5KszaJwqiiiPXK/O/aHsMSUH94fCO80Pg4ntCEpHP6iZpud/Uy9ROqViYdr9WCcd3ret6hTKXq8cJp5XANn10y313ytM/Ts5VWSTZrQOzHnSxhjrOs+Ga1f1lejbp3lLf/POwrjFSz8U2SgX02szCGLSiSIbhQdlI03X//bpcrxsgM/yYNtWimVfBkZSkU1++U7w95vuowCzY6kimwEMO2db3+futI4Yx3Rbdj27Ltv0WwEDIRMU183qK0ZHlhbfdF5axSUedS364vfRer4frb7zPGLQ4oX22PJfto2W5fn5Xiiy6QPH2SB5mmXX5BhttL0fO33P+Ptk37f7cPdtpQ9L/ea7vypvdjw1siEe3/R2vtW2riKbvPm6X5Vu2v53qsjuhrflrZN3Y6v60qyuRWvsltzpr3shj5bfZlsGW7xYexBdkPjD2heBUgIjoshuPP9c4z9f3y1TID9w2EaNGRd/pTHniYdLM9iPg3Mee7Dx2IXHNR743Ib/U6jvjeaz55fiA9krOtnHoqZdQZnKh1qcUt6I03Yaccpkg2NlQkNvf60srKoU2ZYuCm1ewljQ8EKJvhUbcUp/NhJnYbrdolTzjOI0lG6TLMRHwUOeUYjxxwc/1pdYEbQjfIDE6coZ+zilM3sOPBMslrBCiq5YaifHc8ECyf6qRttrJziCARlJr9Np4iXGBzHlKLW+qpv9VFnRS0V29H075IWLRVa7wuBT+sJGEdIrod6jzLIXfXot+x39djeqrCFSi660s1iWV5QTljZbbxlj4b0itq5FdqtZI6TNxwtpp/dcpsi2vKCoo1ymcfw9MHOCNrpKvCK73bJWlWaz47S3tFHeWtLnN90nHG1PHemVspGPE5N+K7LtOnRyvYVpysH/ppxQnqMrjkJ5tTBYppUJbTLlwcKlW+4b5SrvAT4G/Pl0lhUKMn++yiLb8oHSEastX958fPYpf1WKeNJJFdPNLLLtut461a6XKr4sbLNtP8oWynr6G80GGOxZ87FMeAab7T5sa/dDWnaMLZaC9A1o96vaCD7KGbBvNUjUjI2dIx/++nX2TSFC/8UrCCwulmz0STCO8PdgAysoVqsGgihrfJiaYtXyyRZlCu8su067imzSoA/KR2gzZSQWl1VWknZtylaZVFlkW1iMIeJ08fweLD22KFmr+msMWKRKN+LAl4GFNL/0jS3tMiMV2nSfnj1T2hPi7b///kMs1C093l9p22L3xxYLSJ+2xePZYWlZ9mxNkZ32SSxuJ7zpv1JPfBmsUmQzgFRX6OuY4tnyx5a8M4CA+PahjiLblGewLRPeHXYtrAZT4ZidR/FlUlUOWl2P+HYP3iKb45Sdsll+3D/WjAwAWV5SRTZlMS3/XpFN+p3WEeKmQn2nDFh+bEuZiH5ys7KI8ZAd94ps0iK/vI98e0H7zswIlK0Wr0wxiWUoA3K+/BGe3yjYy55jmv9e/DbebFOhL56+38kfzKinlnevyPYDGWV1mWuUWWRznD4IA9OWrvEzLtGf/5BBrk7fM1zPhBkwdi0MSpoJ7+z0XWNxeedUGQBRL7Dqpx5YeLsvrPKjG4v8eFl5aZandtv/bp5Rp7ztnjtpq7n3buoaM2V4NpYH2/I+o00qK6e0k2X9F+LSZ7P+ij0XnoGlW1UGLKy2IgCBCfyLhWbYZfb9t4b/nrZviF8g2bUnTpocpq65eVjgDduHycuu1pf8zL7/L+Hp314Qnr71ly9ed55JYYl9TguTX7JKz6+Jn0B8KZvg/5OFdsoWnbIww7nFl1RsKPJLRoVy5kc6P9DnndgBDnHaa7YIo10K31f4QpWMLgL4VI+K38y/6913350t7rLIIotkPkxjBy7zc+gXKhpddzd4uY0f1NliR/ifjB39zL+YLVoSO3hD/NIN3h0MX45YaChaQGQXpO3F1yy+db1PtuHLTb0rRWuwbLFQ/NGxz+KO5Dl+6GULfq288so98SlbLzeDESoOPmZM8MkJlzgIkflMpH3hD/+cvo2JHeQQP5hzX+rxoy5biHfFFVesvKHYEQ9xMCpEpXGg/YpK0iztODATeH/3W6LSNLt2VOIEFrmhLlNee+E/uN9571f6sOCZR4V/1q7RP6D8lz0PwuA/m3U28H/OM28l8cM48z3P+4t6Rh3zfkRbxR+O83TT4wdo9l7F5ygL+PkyQd1g7RIWxPL+dclbHDjO4vGewB92/OjM2pJ0Md1+3UdUqmT1jn4B9ZQ6yroqzdad6FVeorIk65fwDuCa+Nus0+5T76MSOfPxTXvBAqS9zC/PiHY9KrLzhSEpf5TfadOmZWWw7ncCeY2DFtl6GSykli6K2CuWI5UOnCj71FN8k9PPMeH5Uu65Z9rK4SrTdv3h2PJOok3j3UC9T+t3t3notI6UXRd/1NaOUs+XXnrpQjDKKe0Rz7GqHtIGc878N7Omia2ZxNoHtM1VwnsiKuizskB9H06JiskQLXazS1JmyxapiwOamT9q2mDa6n6XV9oG2j76Szxna/v9u8Mz6uY949Npd59yQ7+LNo/2dvHFF6+VRBykyOoG7TP9pF7x7Hf7bzc3Urzt+p3WNXQ3rAfGc4M79bzZ+5H7pP9BOYyDXmGJJZbI+gJl/bM4AJKthUN7jg6trJ9n+ddWBCAwYopsLv7U9ReExy/5KrsFmbz48mHqGpuEKS9bN0xe/lVhwqR5C+fr/mg892yYff9tYdad14dn/vKrMOfxh4ZEnbb9IWHq2lsOOd6LAyiJ/cIDNNDRaqAXSfckjZFWZEfrw3xRCG6ID1QU2RIREAEREAER6JYAi4KxUFqc+ROiJXWIVuzdJqn4IiACItAVgTJFdlcJKrIIjEIC0fVAtog3gxNxVlGpkReLL0c/vNndMShWpvwahFtHWcc3LIPgLM689957D0K2lAcRyAiMhrrGYCUDUAwEoSuLM4j09ESgJYFJLUP0MQDW189H5fKTv/l+4SrPPXJ/eO6qs+OSxWcHLLUnL7NamLTkSmHytOXCxGnRkmOBRcLEyVNDmBL/MCif/UyY+1z8mzkjPP/oA2EOf/+5O8x+6G8hzs8qpO1/LLLpB/qmxOY6ceqfv1w2Als4MI5/sIptnB6YE2AkNU4Dy39rRwREQAREQAS6IYBVFAPK0QVLmD59ejdJKa4IiIAIiIAIiECPCDD7hZlTCJaYcRG8fKYJSq3o7itXYkc3HAOrxCb/fMNGH8PZwHl0fRHe//73h3nn7cwIj/QkItBLAqOhruGxACU2g1VxjbZe3r7SGsMERlSRDdeFt/xwaERF9Mwbf1yKee6c58Ks+/6S/ZUG6PDgwm/eJSy48e4dxm4djemw0RdzIeBGG21U+D1ef0R/boEXPR0Vk8022yybGm6/tRUBERABERCBbgkwXVVK7G4pKr4IiIAIiIAI9I7A1ltvHXDbhcuQuAZFZskcF68NuC6I6xhkrgu4GoqtQw45pHcX7lNK0c95iH6TMxdo0TdwiAty9ulKSlYE2iMw6HUtrlMT4rpH2U3Fxbkz137t3aFCj1cCEwfhxhfZ5uNh0bfuHyZM7H92Jkaf2NO2+1RYaIv+vWDiglLhqKOOKihq8eG09tprDwLuEc0DfsRgQ0fFBH9Je+65p/3UVgREQAREQAREQAREQATGHAFZao65R6ob6oAALkXwgW2zcfG5GxcqDnFhylyJjWswfOWm/rY7uFzfo2CVjSIbOeywwzJ/4H2/qC4gAjUIDHpdO/PMM7M1IuJiqSEuAlnjjhREBF4gMKI+stOHMOuuG8PjP/lCqS/rNGwnv/G9vWhUYs+74ms6iV4ZxxbLYKEJ/HCy+IgXnNUzZWr11Vf3h0d8fzh9ZNMROe+884a4W1lggQXCMcccE1aKCwZIREAEREAEREAEREAERGCsEmDhPha9o/871hZnHKvPTPfVXwLUCVyAsTgh38ws9saCiBg6jTZ55JFHAguy4wu/7qKto+0eld/RS2AQ6xrvQ/K12GKL5Qu9jl7CyvlwEhhx1yL+Zqe8/PVhqY+cHWZe9Z0w87rzAm5FeiETJ08JC23wvrDgBjuHMM/kXiRZSIMX1oEHHlg4Zj9YyXX33XcfOCW25W84tldddVX48pe/PORSrEzNdDEpsYeg0QEREAEREAEREAEREIExRoCPdf4kIiACLxCgPmyyySZjAsfiiy8+Ju5DNzE2CQxiXZt//vmlwB6bxa3vdzVQimzudgJK5833CvNP3zY8fcNF4ak//iw8/9TjHYGYtNDiYf7Xvj3Mv+47wjwL9W9Ulwq44IILhpkzZxbyudRSSwUWqFhrrbUKx8fbj9VWW23ILTNS/fGPfzyUnRsSWAdEQAREQAREQAREQAREQAREQAREQAREQAREQATGNYERUWSj8L3xhhsDrjgmzjMxm37zhje8IeDDx2SeRZfO/FgvtNn/hWduvybM/sdNYda9t4Q5D/8zNBoNC1bY4mN78lIrhykrrhWmvOx1Ycor1g/xAoUw/fqBYpb7wvfdq1/96rDhhhuGjTfeOJsi1a9rdpsuq9g+88wzeTJM4+qH4Nts+eWXz/wfMWUMNnvvvXeYOnVqPy6nNEVABERABERABERABERABERABERABERABERABMYYgWH3kT3zyZnhoouipfVTTxVQ4mbiXe9+V8uVShvPPhnmzHg4zH1mRpg78/GA644w/yJhYvybtPBSYcJ8CxTSHa4fDz74YKa0njZtmnxilUD/6U9/mi3wyNQxGElEQAREQAREQAREQAREQAREQAREQAREQAREQAREoC6BYVdkX3nlleGuO+8qzd+yyy0bWLFUIgIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAJGIJozD6/cd+99lRd86MGHwpw5cyrP64QIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiMD4IzDsiuznn3++kvLcuXNDs/OVEXVCBERABERABERABERABERABERABERABERABERABERgzBIYdkU2iyJWySKLLhKmTJlSdVrHRUAEREAEREAEREAEREAEREAEREAEREAEREAEREAExiGBYVdkT3/99BcWaCyBve6665Yc1SEREAEREAEREAEREAEREAEREAEREAEREAEREAEREIHxTGDYF3sE9n333Reuufqa8OSTT2bsp06dGt64/hvDqquuOp6fhe5dBERABERABERABERABERABERABERABERABERABESghMCIKLItH48//nhoNBph0UUXDRMmTLDD2oqACIiACIiACIiACIiACIiACIiACIiACIiACIiACIhATmBEFdl5LrQjAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAhUEht1HdkU+dFgEREAEREAEREAEREAEREAEREAEREAEREAEREAEREAESglIkV2KRQdFQAREQAREQAREQAREQAREQAREQAREQAREQAREQAQGhYAU2YPyJJQPERABERABERABERABERABERABERABERABERABERCBUgJSZJdi0UEREAEREAEREAEREAEREAEREAEREAEREAEREAEREIFBISBF9qA8CeVDBERABERABERABERABERABERABERABERABERABESglIAU2aVYdFAEREAEREAEREAEREAEREAEREAEREAEREAEREAERGBQCEiRPShPQvkQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREoJSBFdikWHRQBERABERABERABERABERABERABERABERABERABERgUAlJkD8qTUD5EQAREQAREQAREQAREQAREQAREQAREQAREQAREQARKCUiRXYpFB0VABERABERABERABERABERABERABERABERABERABAaFgBTZg/IklA8REAEREAEREAEREAEREAEREAEREAEREAEREAEREIFSAlJkl2LRQREQAREQAREQAREQAREQAREQAREQAREQAREQAREQgUEhIEX2oDwJ5UMEREAEREAEREAEREAEREAEREAEREAEREAEREAERKCUgBTZpVh0UAREQAREQAREQAREQAREQAREQAREQAREQAREQAREYFAISJE9KE9C+RABERABERABERABERABERABERABERABERABERABESglIEV2KRYdFAEREAEREAEREAEREAEREAEREAEREAEREAEREAERGBQCUmQPypNQPkRABERABERABERABERABERABERABERABERABERABEoJSJFdikUHRUAEREAEREAEREAEREAEREAEREAEREAEREAEREAEBoWAFNmD8iSUDxEQAREQAREQAREQAREQAREQAREQAREQAREQAREQgVICkx566KHSEzooAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAoNAQBbZg/AUlAcREAEREAEREAEREAEREAEREAEREAEREAEREAEREIFKAhMaUSrP1jhhFt2LLbZYjdAKIgIiIAIiIAIiIAL9J/DYY4/1/yK6wqgkoD7rqHxsyrQIiIAIiIAIiIAIiIAIBFlkqxCIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAgMNAEpsgf68ShzIiACIiACIiACIiACIiACIiACIiACIiACIiACIiACUmSrDIiACIiACIiACIiACIiACIiACIiACIiACIiACIiACAw0ASmyB/rxKHMiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAJSZKsMiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIDDQBKbIH+vEocyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAlJkqwyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAgMNAEpsgf68ShzIiACIiACIiACIiACIiACIiACIiACIiACIiACIiACUmSrDIiACIiACIiACIiACIiACIiACIiACIiACIiACIiACAw0ASmyB/rxKHMiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAJSZKsMiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIDDQBKbIH+vEocyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAlJkqwyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAgMNAEpsgf68ShzIiACIiACIiACIiACIiACIiACIiACIiACIiACIiACUmSrDIiACIiACIiACIiACIiACIiACIiACIiACIiACIiACAw0ASmyB/rxKHMiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAJSZKsMiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIDDQBKbIH+vEocyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgApOEQAREQAREQAREYGwQaDQa4cEHHwz//ve/wxJLLBFe8pKXhHnnnXds3JzuQgREQAREQAREQAREQAREQAREYFwTGBOK7EcffTR89rOfbetB7r777uENb3hDuPHGG8O3v/3tLO7hhx8ellpqqWz/+9//frj66qvDggsuGE444YS20lbgEM4666zwu9/9ri0U73jHO8KWW25ZO85vf/vbcPbZZ2fhv/CFL4QFFlgg2//Rj34UrrzySj27CpK33357+PrXv56dXWONNcKHP/zhipAvHn7ggQfC0UcfnR1YaaWVwr777hs++clPhrlz54ZddtklvPnNb34xsPaGncDPfvazcPHFF2fXPfDAA8Oqq6467HnQBUeOwPPPPx8uvPDCcPPNNwfqKr+9LL744mHHHXcM6623XpgwYYI/1fH+zJkzwyc+8Yksvm8Dqt6pHV9olEZ8/PHHw/HHH5/lfq211grvec97Ku+EwYdzzjkn3HrrrVkYBh4++tGPhsUWW6wyzmg88eMf/zjrF/CubrfPNhrvtyrPvn/k+51V4elLEQd573vfG9Zff/2qoLWOV9XdWpEVSAREQAREQAREQAREQARGmMCYUGSjTKNj3o4888wzWXC2FnfOnDl5Eo888kh2fNasWfkx7dQnMGPGjJxr3Vh8+Lcj9oyIQxkweeihh0qf3WOPPRaOO+64LNhuu+0WVl99dYsyrrYrrrhi/mz4QN5zzz3DfPPN15TBddddl8dZbbXVAvXiiSeeyOJYXWqagE72lQB1x9qx2bNn9/VaI5W46m85+f/+97/ZYCvtXpXQVp500knhggsuCEceeWSYOnVqVdDaxylnVuZ8G1D1Tq2d8BgJyDvpqaeeyu6G92GVoMRmMJ1BCGTixIlhr732GnNKbO6NOgyTsdpGcY91xPeP0kGnsvi+TlmZKgtX91hV3a0bX+FEQAREQAREQAREQAREYCQJjAlFtge46KKLZlZn/ljZPso8hI9Gk15Zqll62r5A4E1velNYaKGFWuLAOrif8txzz2VT7rkG0+7HqyJ7/vnnz+7drP/++Mc/hje+8Y1N0f/mN7/Jz2+wwQb5vnZEYLgIqP4OJX3XXXdlMyVMGbbwwgtndfmVr3xlWHbZZTPF4U033RR++ctfZlbatHvHHHNMOOyww8KkSWPu9T8U0IAfQdl9xhlnhFtuuSXL6eTJkwMzKpZffvkBz7myJwIiIAIiIAIiIAIiIAIiIAIjQ2DMfcni9oBpznUF9yI2Dd/citSNq3D1CGy77bZhmWWWqRe4B6He9773hXe/+90BpYCknMDGG2+cT2NHSd1MkY2rAtz3ICussEKYNm1aZgGPOxeEwSOJCIjA8BLAkveUU07J3YjwHjv44IMLsytod1/96leHrbfeOhxyyCHh6aefDv/85z/DpZdeGrbZZpvhzbCuViCAEvtb3/pW3g5PmTIlfOxjHxvWd2UhQ/ohAiIgAiIgAiIgAiIgAiIgAqOAwIvmyKMgs/3IIspOFsPir1OLbO+SpB95VJovEKjr5gWrRJ4nCldJOYHXvva1YZ555slOYg3YbKo3bkVMUIAjzGSweoMCppWojrQiNPznn3322YAytK7wDM3yt24cwhHHu/5pJy75wxJbMpQAboGwsEZe/vKXZ4rqKhdB+Mj+9Kc/nSfC+g+tRHW2FaHOz1MfGISwWTG4emHNgboDvt08mzr1iXdtO20DJLinTut55yQVs4xAN+WjLD2O9SPNqmvpuAiIgAiIgAiIgAiIgAg0IzDmLLKb3WzZub/85S/hvPPOy06xuBIf/HUEK1X8jd55550B/7QoxF/1qlcFFnXadNNNcyVhnbQUppwAH9KXXHJJ+MMf/pBZEfIBjvKVafMsXFYlLHzHQpAs1IlygMXHfvKTnxSUtT/84Q/Dr371q2zw4nOf+9y4m2ZPeUWZDRsE9yLMTigT71bELLex7Dz22GOz4CzSOX369EJUe3a///3vs2eHMnPppZcOa665ZsA1CTMnTFgQDV+7iyyySDjooIPscL7Ft++//vWv7DfPk+fq5YorrghXXXVV9ixR1vXC/69PfzTv33vvvZnVJ/eAte59990XLr/88vDXv/41s86lPr30pS8Ne+yxR1hllVWG3CrtGwu0sUCoKcAoOzw/rHxf97rXDYnDAfy4UsdQ1OG7mesQh+dP+5ha8Z966qlZ3jbccMPwlre8JVx77bXhhhtuyOK/4hWvyMqHH2wZ7/UXxrbQLfssAOfdZHEsFdxp8awpAyjA8Zudvu9wQ0J9uvvuu7PywaAgLp9e//rXVz7r9Dr63ZwAbSFt2t/+9rcsIAsfsmhmq4UdGXC85pprAnUan8m462K9grXXXju85jWvKVyU53f++ednbSL9GnwyE5f6+J///CdbhJJZNiwwiXzoQx/K3G7RjuKuhvQpT8stt1z2rjVXbIWLxB+8B3hH33HHHVm6xKGM0RdiAWDKj2R4CPSi7uKnncWyEd6l9JGuv/76rM2g3NJuM/Njiy22yMre8NyZriICIiACIiACIiACIiACRQLjXpHNxxxTrZG6Fr986NsK8oYTJQ8fmvyheEUhZxavFkbb+gRQbH7pS18Kf//73wuR+JjiYxwfr3xklwkf8TxTFG4ICht7xhae9G2hMhRk49Ff7EYbbZQrslFWlymyUSCbWxF8iqN0QbDmNaYs4OWF3zw7FC5eUGjyhyL1U5/6VObygPPUE0sLJYt38cN1GJQw4dmn+bzyyisDA0souKXENlIvbM2VBL+wrD/33HMLAahP99xzTzj88MOzNssrxFAmo2BOhbYOBfeJJ54YdthhhyEuKlBqfeUrX8mUXBaX61CX+cNf8+c///mC4g5FudVTrsm1TWiXrXzYsfFef/1icSgZywYhjJXfHnXUUblVvX8/YW155plnhtRSmwVdKTf8vetd7woMWkk6J0A9+OY3v5kpi0kFxSB9hWYKX57ND37wg4AFvpcnn3wyMFDI39ve9raw5ZZb5qcZXL///vuz39QdFOc2EGWBUFZbGNK48MIL7VS2xbqaQQ/achTdKKe9UJepq6RjQhyuxx/vFBT0DFBK+kegl3WXAS5ra2mjea96oVwx+M3frrvuWihzPpz2RUAEREAEREAEREAERKCfBMa9IrtduFismBIbRSn+n1EkPPzwwwFLYJQxKNtQ5JRZl7Z7vfEaHiWZKbFRUG622WZh5ZVXzixzsSx78MEHh3xkVbHCovCtb31rtvCZKQOwZDPlz7zzzlsVdUwfhwtlGAXHn//852xryn+7cW+NjeK7lWCJfdxxx+WLanKN9ddfP/PbyzWw8EIIc8QRR2TPlMVAGQBCsAz3ChmzWsxOxn+k4RXZKFHsY9sft/DavkjAlNhYPTMogTL417/+daasIhQWvub3HIWbV2K//e1vz+LwfHlWP//5z7OEsfrE8tKsSVGw8myJj2B9TRlgQIKyRNuIchR/zV/+8pcL/pwJj0IN5TuCopUFC7E4xQqQARLV3wxNXr/4hQ/suoL7rLJBu+9973u5Ehsrbaztl1xyyWyQ46c//WnWNmCpyUKxWMxL2ieAwhEltr3XGBRkhokNDlaleNFFF+XlnnrGuxC3WSihGRSk/cYqmkE86nYqp59+ehaG4yjMmRnjBzE4bkrs9dZbL7O0ZUYFgxc2E4YZEIceeihBM0GJ/vWvfz13JUIbwDuVQSdmUtBuE4a2gEGyOu6nLG1t2yPQr7pr71Xe37ThCO9fG1jGmp9yyGwNiQiIgAiIgAiIgAiIgAgMJ4Exp8hG0bzXXns1ZdjMmrdZRD5ETzvttCwIH/S4RPDWRihtOMa0fZQ9KFvr+rxsdt3Rfu6zn/3skA/n9J4YDEC5hTC1GatOhA+lI488MrdYwx0GSulvfOMbgam0dWT55ZcPO++8czb12RRhuMjgeY1nYRo4H6lMJ0fxSN1JP0pNkY3iI3UfUsaOtCj3yPbbbx+22267PBjxud7RRx+dHUN5wuJm66yzTh6G2QxekY3rHy+m8LZjfFiboISRNCfA4Jq3ukYpuf/++2fukbDGQxGF0ok6aIIS27vyQamBm5CTTz45C4JyGkUWwiCfKbGpzyi3TAiDUg6XTCjRGZBKlaKmxN5qq63CTjvtVGg3sNZX/X2BpimZ+IVishuhvqIQRXDbhHLVFJ0MImyyySbZMZ4NAxebb755x+tJdJPP0RwXZTODs2btyr0wCMdfM0U2Zd6s5PGDvu++++bPhnrIICBW9qTDgANum9K1PlBKo8DeZ599Au/CKuG8HxRBKc67m4EnBuqZuWSDvpQD84dN+0HeTNZdd91soIuBfa6Na4oyBbuFH+/bOv2j1JremPW77lLe/AAxbTh9MAZkEJTZvNfTMmf501YEREAEREAEREAEREAE+kFgYj8SHek0sf5r9meKlnbziaKPjzpkj+hT1iuxOcbHPx1/k1/84he2O663fIQ1ex6cY8qqyWWXXWa7Ged02jWc99577/yDPg+snbYJeCtrU1pbIt6tCB+rZZacFta2+FNGGIAoc0OAYnPjjTfOwlCfUGiyQB0KNARLPl8/UZIiKNQQyglWvyZYcCNYkuNLWVJNAMWXV2JbSBSVJuZGhoE6ExijkPKCsgpXE/wtscQS2SkUneZzHcWVV2JbXMqE+WWuah/Jzy677KL6bdBKtrbII6fS91BJ8KaHzLqeQB/+8IeHcCf9PffcM0uDttrqXNNEdbJAgHbNK7E5iSIYlx++vStEij9ww2NCn8MGGOwYfrLf8573ZD8ZhEoH/iwcLj6aKbFpf70S2+KhKDcxF1IozWm7EQYPvRLbwjIYabM0GNyUVBOo0z+qKiP9rLu8c70S2+6AY/Y+5n1x22232SltRUAEREAEREAEREAERGBYCIw5i2wUaLYgXRXBTj/8/Yco1kmmtEmvY+4a+Njbfffd09Pj7jdKLT64mwnPzcT8dsKRxTPLBOUnyjSb5loWRsdaE0AJgesWFMp/+tOfArMOTGHN1HITr/C2Y+kWtxO41kGY5o6biDLx1lt8BPMcsdRmJgMf7PhfRrHCBz4+WhFc+GB9zXmU24RHyDNCGj7d7KD+FQhU1SXcd5igqERYsI0BJAbusP7F6pLBDKznUVCjpEoHKqzeEh8lXVX7SPtLOUEZi4I8tUh95zvfSRKSJgT8O8wPAjaJUnnK3msoSal7ZeIX2qTOYZUpaZ8AymRmjLFQLgphLJ1x2eJnPPhUrU4xe+Yf//iHP5Xve2td2kYWVPVC25gOBvvz7JcpsTnurf1RlCM244Z96rkptfnthXc+ym/ukUEuPzjmw433/Tr9I54raxmk0s+6y4KOVcJAhT13yiiuqiQiIAIiIAIiIAIiIAIiMFwExpwie4UVVsimpPcDoH00kLa5GGl2ndSKsVnYsXyOhajacbHCdGoES89mykmvgBvL/Pp9b0wXxrILJTFKqte97nXZJW3BPQYN6nyoeitRlJ/4UG0lZgGMS5MzzjgjC457ERTZ5h8bBdvLXvay7Bgf9LgXQZFNOUEBj7QavMoCjfN/fhHNOigOOOCAzNc/jFGWMWhkA0csUodl3jbbbJMryfzinpQdKz/NrsXz94pslF2kLWlOwLen1l42j/HC2f/+97/5Iqy4c8I63vwgU//r1FmzzK1zPYV5kQCDhli8M1DIjKKvfvWr2UnqCYpk80P8YoyQDfbwG4WxtY/+fLpvM8b8cdrOVmKzKlqF47x3a4M/bP5aCYMtUmSXU6rTP2JtiW9/+9tDEuhn3fVtTHph3/eyPKRh9FsEREAEREAEREAEREAE+kVgTLoW6RcsrFVNUK61+sOKStI+AT7akVb8zF9n+1dQDE/AW1ub8tG7FUFp3GxAwdLyloEca1U/OG8WwCgzbfFNc11g0+RRAHF9c4thfrItHOnUUbRbPsfrtlV9SrmwwCILMu4RXRrAF84mKKZwAYSy++67784O+/aRA3Wev/nEtnTN7Yj91racgFcy2YBPecjiUVz/oEDlzyxrUWCb1HlmvhxYPG2bE+B57bfffvlsF9o6fI2boKT0LpPsuL0L+U39rfNncW3rZzvZsXTbTtuQ1vM6ecL6XNJ7Av2su83quc3a4o7sHd77u1OKIiACIiACIiACIiACIlBOYMxZZJffZm+OMi3YlGunnHJKvvBRb1JXKkZgySWXDA899FA2LdmOlW2ZsizpnsByyy2XWWbi7oHpwnwct+tWhFx45RpTj3fddde2ModVNdPnsex+8skn87pmCmyzWMRCGEteLLcR/HU2++huKxMKXCCANT6LovKH6xhcveAyBCU2CgzKyte+9rXMctv74GURT/OjWkiwxQ9ZbbYA9L/TWNdT5uHPwpxYyVKPWwnue0zMhzlpER83EieccIKd1raHBFAmp8piFlFlhgkDCgwC0qc4+OCDC4OGWEpznmfEooCdCG6eeim+ncdNirXLvbyG0qpHoJ91l/5V1ewYZnaYePczdkxbERABERABERABERABEegnAZkMt0EXtyUmVb5EOf+DH/wgnH766Zmyx8JrW5+ATVvFWtOsPdPYKNV+97vfpYf1u0MCtgAjijEsns0ymw/ZlVdeuVaqWGnhbxu5/fbbK+OgeKN+8Oc/iP3CUjfddFO+OJr5fMVvM37TEVygmCWq3IpUou74BGXgrLPOCmeffXamwCYhrOJpA1ngEeW1PQsGQKirXpHqFaZpJihbPPvvfOc76Sn9rkkAJfZb3vKWPPQPf/jDfL9qh0Eqc//j6xL7iPkyLovP4JHVWRvMLQunY/UJoNhGEWwKbnwNX3LJJYUETGlMO1ll1YwLs+9973vZX7N6V0i4ix+WJ5KgLa8SXI6Qr/PPP78qiI53SaCfddcPZqfZvP766/NDUmTnKLQjAiIgAiIgAiIgAiIwTASkyG4DNJahZvmJkiedYktSdP4vvvjicNVVV7W0KG7j0uMqqHd1AWeUq6lcccUVuX/k9Fyd337Kdp3wYz0MfrJNGIgx39X+Wdj5ZltTKuMvuWyxR57lN77xjax+UEdM8U2aKM1NGUoeEOobvnxNXvWqV2W7LJBm5aITy19LT9tyAliBUscuv/zycMcddwwJhKW2973LIAYLQJqSC4ttK0M+MsrSU089NXv+NhDhz9fdV/0NYbvttsvfRwz8YNFbxQXuJ598co4Xa2ATWziV+nTeeefZ4cL2u9/9bl5n67gZKkTWj0oCuNLZZZdd8vO/+MUvCsph1g5AeK4/+clP8nB+h7bQ/NcPx7NhodGXvOQlWRZ+/etfl/ZzGNyizJCvv//97z672u8hgX7WXZ4tM+NSoV3nvYDwfrYZU2k4/RYBERABERABERABERCBfhGQIrsNsgsvvHDYeuutsxgoej75yU9m7g+wRmTBLRbMw2rNpF0loMUba1uU+yxW1OrPrNzXWWedXKHJR/Dhhx+eWfjOmjUrYLX2/e9/P7MUbZeTn2KNVSgWit0o09q9/iCHR6Fi1l1+Ma8NN9ywrWxjrWuDPVjtYimKv22eHVbUJ554Yq7gZFFJFKJe7MPcFnF8xSteUZhqv9Zaa2XBbVEzfDfLV7on2Jt973P8C1/4QjZAZ75QcfvCYJ1ZfzL4YM9gj+hPG0EpipuEq6++OnvexKHOkZaJ9xFsx5ptVX+LdHDDstNOO+UHf/Ob34TPfe5z4corr8xcwDDQiisYntUnPvGJzGqewK997WsLi6MyEGSDRbTR+EXHxc/s2bOzLe2tWWdyTRYmlPSOwLrrrhts1gmpMiBhC0VTD81lD8+XQSAWnebZsMXnuQ0YUj9oL4dDdtxxx+wyKNiPOuqobHYUfvPJN5bYJ510Up6NDTbYIN/XTm8J9LPu0oZ/+tOfzttwni1l7TOf+UzmCoc7eetb31pYrLe3d6fUREAEREAEREAEREAERKCcgHxkl3OpPLrNNttkSlWm1GLlVuVTdLfddsutEysTGycn+NiuIyhNWWAO+chHPhKOOeaYgMKSD/Zjjz22ThJNwyy00EKZOwT8kaKoQWGDYKko37wh4F4EVxImKCjxV96OwHHfffcN3/zmNzNlJlaEZZaEWF9/8IMfHJL0euutV5iKnlp7pf5YzQJ8SEI60BUBlGdbbLFFwEKU+uKtedOE3/e+9+WHsJhHuXHppZdm8U477bT8nN9BmbrJJpv4Qy33VX+HItpqq60yS3ieD4onZkI0c9mCwhp3Fql86EMfyttbBvj4S4UBqk996lOFgaU0jH53RoA6dNhhh2XuQxj0O+OMM7J3IKntvvvumSsfWzegzLUL7klYTHI4LLLJE+9p/Ob/8pe/zOr5ueeey+EhgoL+TW9605DjOtA7Av2qu7iOou2vasNZhHnbbbft3Y0oJREQAREQAREQAREQARGoSWBMWGSbBSj37PfrMDA/r4T1K7FbXH+eY1iQHnrooWGHHXYoVX5i2br//vuHdq0N7XpjZVvGsp17w082gwQovNJnwO93vvOdwazCqtJN4xGOZ8MzkgwlgBLZC4rtOpI+6+nTp4fjjz8+rLLKKqXRSRcrvrLBAxTnXnnuLRVJDNcV3oqba0mKBPzzqNovxij/9d73vjdze8BMlDJhsUAsgFML3Z133jkcdNBBpfWMOkm9ZaCqTHx+y86r/g6lgm95Bvp4HmVtHjGoMyiwP//5z5fWO9rbL37xi4E2oCwNBiiOOOKIsNJKKw3NQDzin5uP74+XRhzDB31fxO+X3TLPZ++9985PMTsJtxwIbjyoZ2XvQs6jVGb2g82o4ZiXqmfg81QVxqeT7uPaZp999skGUtJzlAGUnHvuuWd6KvvdyfVKExqlB/39+/2q2/F1Kg3Ty7rr02ZxUWZNpcJ7m2dLP9i/i9Nw+i0CIiACIiACIiACIiAC/SIwIS6a1+gmcfOhh3/U8Si4FcEKjo9CVpDHf6Sk9wRw3cIfVsLjtaz1nmr/U6R5oY1g9sISSyyR1ZE6H+79z5muUJcAz/Cxxx4L+L1lwTms6XmWZQMRaZrm3oJ2EoUcg0jDZTWa5mW8/MaHLTNOmM3CwA+KrnbfSzxvXAzhw57F3Earwor7GGsyY8aMgGuzBRZYIGtPp0yZMuK3SD3HhRTuh2gbeEcPej0fq/2Ibuouaxucc845WXnCDRiMeKa4KGKmAIv9Vg1sjnghVAZEQAREQAREQAREQATGDQEpssfNo9aNioAIiIAIiMD4ITAWFdnj5+n1907HqiK7G2pliuxu0lNcERABERABERABERABEegHgYn9SFRpisD/Z+884K0ozv89AiqiURRUFFGiCGrEBjZsWGOJhYiaqLFr7MafMcYSWzS2RP3bezf23qNRFDWxF2LHDmIBAUUslPz5TvJu5u7d3bOn3dOe+XzOndlpO/Ps3j17vvvuOxCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIFApAgjZlSJJPxCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIFAVAgjZVcFKpxCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIFApAvjIrhRJ+oEABCAAAQhAoG4IlOMju8x1sOuGAQNJJoCP7PZctLDjlClTfMECCyzgOnXC1qU9pebNqfcFWpuXPDODAAQgAAEIQKBYAl2KbUB9CEAAAhCAAAQg0AwEEKyb4Sgyh0oQ6Nq1q9OH0JoE0q6FCNyteT4wawhAAAIQgEA9E0DIruejw9ggAAEIQAACECibQJpIU3bHdAABCECgiQmkXTsRuJv4oDM1CEAAAhCAQJ0TQMiu8wPE8CAAAQhAAAIQKJ5AmgBTfE+0gAAEIACBkEB4fUXUDsmQhgAEIAABCECg2gQQsqtNmP4hAAEIQAACEOgQAqG40iE7ZCcQgAAEWpxAeN1F1G7xk4HpQwACEIAABDqAAEJ2B0BmFxCAAAQgAAEIVIdAKKJUZw/0CgEIQAACeQiE12NE7TzEqAMBCEAAAhCAQLEEELKLJUZ9CEAAAhCAAATqgkAomlR6QNXsu9Jjpb/iCHBsi+NF7eYlUE2xWf9n1ey/eY8KM4MABCAAAQhAIIsAQnYWHcogAAEIQAACEKhLApUSIyvVT11CYlAQgAAEMghkXf8qIUIjZmfApwgCEIAABCAAgZIIIGSXhI1GEIAABCAAAQjUikCW+FJoTOW0LdQ35RCAAASahUD8WlmqsI2Y3SxnBPOAAAQgAAEI1AcBhOz6OA6MAgIQgAAEIACBDAJxUSWjalRUSpuocZCoVD9BlyRrSIDjWUP47LouCJQiSsf/b4rpI2xbTLu6gMUgIAABCEAAAhCoKwII2XV1OBgMBCAAAQhAAAIhgVAACfPT0lbf4rR6lp+3ntUnhgAEINDoBApd9/KIzWEfeeobM2tXTBtrSwwBCEAAAhCAAAQQsjkHIAABCEAAAhCoSwImeOQdXJ76eerE91dKm3gfbNcPAY5n/RwLRlIbAoVE5KT/kaw2Vj+rTnymalNM/Xh7tiEAAQhAAAIQaE0CCNmtedyZNQQgAAEIQKCuCZgwkmeQWXVLLcuzX+pAAAIQaEQCWddFm09cZA7bxMusjeqklVmdMC62ftiWNAQgAAEIQAACrUkAIbs1jzuzhgAEIAABCNQtgVAwyRpkVr20srT8cD956oT1STcWAY5vYx0vRlt9Aknic/z/JKwTloX5GmlWWdJMVD/eR1I98iAAAQhAAAIQgIAIIGRzHkAAAhCAAAQgUDcEQhEka1Bp9ZLyk/LUd1p+1n4pa3wCHPfGP4bMoHgCWWJx0v9EvH5YJyyz/DDPRqeypHwrtzhvPatPDAEIQAACEIBA6xIoW8jWzYluPrgBad2TiJlDAAIQgAAEOpKA7jnioZy8eF9Z20n7yapPWf0R4BjW3zFhRPVDwITn+P+J5WukVhbPC7dtRqqblG/lxBCAAAQgAAEIQKAYArPNurlo/2uwiB4mTpzovv/+e9epUyc377zzcqNSBDuqQgACEIAABCDwPwJ5bkmS6sTztD169Oio46TyqDBIxOsFRQWT5bQt2DkVIAABCOQkUI5onNS2UF6/fv3a/f4r1CZpKkltkuqRBwEIQAACEIBAaxMo2yJ7nnnm8UL2zJkz3aRJk1qbJrOHAAQgAAEIQKBkAoXE4KTyMC9Mf/XVV65z584lj4WGEIAABCCQTWDGjBlORk0WQjE6TCeVW14YJ7UJy0lDAAIQgAAEIACBsoXs2Wef3fXo0cNNmTLF/fDDD9GrZqCFAAQgAAEIQAAClSIQitTWZ5gXT9v2kCFDrDoxBCAAAQhUiMDTTz/dzr2krrsmRodp22VSnpURQwACEIAABCAAgTwEyhaytROJ2fPPP3+e/VEHAhCAAAQgAAEItCNgwnO7glkZSWWWZ7G1s+2vv/7adelSkdsc65oYAhCAAAT+S6Bnz55u+vTprlevXj7HBGxtpKX/27RNueVZHLa1PGIIQAACEIAABCBgBDpZghgCEIAABCAAAQjUgoCJz0n7TiqzPIvVTmnbDtNJfZIHAQhAAALlE7BrrnrKk7Y9hnUtz+KsMqtDDAEIQAACEIBA6xJAyG7dY8/MIQABCEAAAjUnkCVaJJVZnsWaQFI6zKv5JBkABCAAgSYkoOusfTS9eNqmzPXYSBBDAAIQgAAEIFAuAYTscgnSHgIQgAAEIACBDiFgYojF2mk8re0wr0MGxk4gAAEItCgBu95aLAyWtjjMM0xhmeVZnFVmdYghAAEIQAACEGhNAgjZrXncmTUEIAABCECgoQgkCRthntK2HaYbapIMFgIQgEADEbBrbRjb8MPrcTzPtokhAAEIQAACEIBAsQQQsoslRn0IQAACEIAABKpOwEQQ7SgpHc+z7Xhc9YGyAwhAAAItSiB+vdW25YVIkvJUnpYftiUNAQhAAAIQgAAEQgII2SEN0hCAAAQgAAEIdBiBYkWMpPrKs/wwtnSHTYYdQQACEGgxAknXXyGw66/FaXlZuMK2WfUogwAEIAABCECgtQggZLfW8Wa2EIAABCAAgbogkCVShGVh2gZueRYr39KKLW31iSEAAQhAoDoEwmtuPK09FroeZ5VnlVVnNvQKAQhAAAIQgEC9E0DIrvcjxPggAAEIQAACLUQgTbiw/KQ4zLN0CyFjqhCAAARqSkDX3fDaG6bDgVm+xWEZaQhAAAIQgAAEIJCHAEJ2HkrUgQAEIAABCECgYgTyihiF6oXlStt2mK7YoOkIAhCAAATaEAivtZZOug5bXpvGwUah8qAqSQhAAAIQgAAEWpxAl0rMf+rUqW7cuHHuq6++csaYxrkAAEAASURBVDNnzqxElzXvo1OnTm7eeed1iyyyiOvWrVtR42k2HuWwmDx5sj83vvvuOzdjxoyiOFIZAvVAoHPnzq5r167+WjDffPMVNSTO/6Jw1WVljn91DkuaaFEo38qzYpXp8/HHH7u55prL9e/fvzqToFcIQAACLU7ArrfCMNtss3kadn0Oty2tCirXtsW+UcafvPUyumioomb7HZkFv5zfmFn9UgYBCEAAAs1NYLZZNwf/LmeK+rJ96623mkbAjrPQF+yAAQNyi9nNzKNYFhLxRo8eHUfKNgQalkC/fv1cXjGb879hD3PqwDn+qWiKLki79SiUb+WKLa2d27bFyjMhe9iwYdokQAACEIBABQnccccd7ttvv3V9+vSJRGwJ1PaxXYXbSitYbHUsLjbf2tUiroYI28y/I7OOUbG/MbP6ogwCEIAABJqfQNkW2bLElhV2jx493GKLLea6dCm7y7qgPn36dDdmzBg3YcIEb1G81FJL5RpXM/Ioh4Wg9e7d2/Xs2bNpzo20E+GFF17wRYMGDUqr0lT5rTJfnf/jx493Y8eO9deCvEK2rgUKzX7+N/t5wPGv/GUrFKDjvYdlls6KVWYf9WVpxXPPPbebZ5554rtgGwIQgAAEKkRA11oFxSZCW55tx8t9gyL/hP0X2bRq1fX7d9KkSf6N5GKMnrIG1Iy/I7PmW+pvzKw+KYMABCAAgeYnULbqLHciCs0kYms+EuQ1JwnZNkflFwpWt5l4lMpC7kQUWkHELnReUN64BHT+6xyWkG3ndJ7ZWF3O/zy06rcOx78+j40JJeHolBf/hOWkIQABCECgcgT0W2fKlClu8cUXj6ywJV7HP7ZHE7bTYtWzMmsTxlllYb2OSkvI1u++iRMnFmX0lDW+ZvwdmTXfUn9jZvVJGQQgAAEIND+BsoVs84mtL6JmCzYnm2Oe+Vlda5unTSPUsfnY/PKM2XxiW9s8bagDgXokYOewndN5xmh1rW2eNtSpTwJ2DO2Y5hml1bW2edq0ep0kcTrOJKyTJFrHy+Pt2YYABCAAgcoQ0PebPrPPPnumeC0B2j7aswnS8TgsSxqh1U8q6+g8+/7p3r27F7JNgC53HPY7q5XuHWyuNvdyGdIeAhCAAASan0Dzqc/Nf8yYIQQgAAEIQKAlCJgwbbEmHaZDCJav2NJhOWkIQAACEKgcgTnmmCNVyDbh2mLtNSsdjipNsE7LD9t2VFrfMRJe5RpDARG2o8izHwhAAAIQgMAsDxpAgAAEIAABCEAAAvVEoJAQbeUWa+xKh596mg9jgQAEINBsBMwiW7FEZi3YZ2J1GGveSduWH8bxtLYtqI96CfquQbyul6PBOCAAAQhAoNUIIGS32hFnvhCAAAQgAIE6IxAK0mlDi9exbcWWTmtLPgQgUJ8ERo0a5UaMGOGmTp1alQF269bNDR061A0cOLDk/hthjCVProyGoTidJTIn1bP68VjDsbz40NLy4/U6YtvG0rlz547YHfuAAAQgAAEIQCAg0ClIk4QABCAAAQhAAAJVI1CK4By2CdNJg1R5+EmqQx4EIFA/BKopYmuWEsi1j3JCI4yxnPmV07aY663VLbQ/1WuEYGJ2I4yVMUIAAhCAAASaiQAW2c10NJkLBCAAAQhAoMEJmIhhcXw68Xxt2yesG68XlpGGAATqg4BZYh9xxBFVGdBpp51WtrV3I4yxKvCK7DS85hYSeVW3UJ347ktpE++DbQhAAAIQgAAEGp8AFtmNfwyZAQQgAAEIQKClCEjQsE984mn58XpsQwACEIBAeQTSrreWH8ZJe1K5gsVJdciDAAQgAAEIQAACIQEsskMapCFQ5wR0o//BBx+4cePGJY50ySWXdL169Uosq9fMKVOmuFdffbWs4S233HKue/fuZfVBYwhAoH4J5BU5wnphun5nxsggAAEIND4Bu94Wa2Xd+DNnBhCAAAQgAAEIdDQBhOyOJs7+IFAigbffftsdf/zxTnFa0IrxV155pfvJT36SVqWu8vW67pZbbum+/vrrssY155xzunvuucctsMACZfVDYwhAoH4JmFCSNEKVheVhOqk+eRCAAAQgUD4Bu/aagK1tS6f1nqdOWlvyIQABCEAAAhCAQN0I2RMnTvSLsfzwww9FH5U+ffq4QYMGOYlZrRLeeust9/LLL/vp6oZx8ODBTta4hOYk8Prrr7sDDjggEnyHDx/u4iulv/fee+65555zL7zwQsMI2W+++WY0Jx05ncOrrrpqroP4yiuvOLVX+P777522119//VxtqdS4BN5//31/nuuHsB7YLL/88o07mRwjv/POO91aa63lFlxwwRy1W7OKzoUwxLfDMtIQgAAEIFBdAnYNThK0VZaUX90R0TsEIAABCEAAAs1EoG6E7AMPPNBJnC01LLroou7kk092AwcOLLWLhmk3ZswYt/POO7exPpt99tnd/fff7+aff/6GmQcDzUcgFLElXs+YMcMdeuih7R7cSPCSkN3I4Wc/+5nbZZddck1B8z3ppJOiuvbDKcposYQeAj766KNO18IVVlihKWf/+OOPu8MOO6zN3H7zm9/462GbzCba0DnetWtX96tf/cr/b8w111wNO7tS/kfjbWw7HhsUy9d2mLbyeo1nzpzpfvGLX7jp06e7lVZayR177LH1OlTGBQEIQKAdAbveIlK3Q0MGBCAAAQhAAAIVJlA3QrZEbPm43XvvvZ0sS2+77bZ2U91kk03ciiuu6PO/+uord/HFF/s2q6++unvooYe8xep5553XtCKOAZFrCbthtLxp06Y5WSo2q5Ct+f7jH//wbjW+/fZbt/jii7uVV17Zi3bGoBnjUMTef//93d/+9jc3evToZpyqn9O9997rPvvss1zzkwU24T8Exo8f737961+7Dz/80Gf8/Oc/d0ceeWTTWT3dd9997Q658vRgr5nDd9995y699FJ3++23u/32289ttdVWTm6EOjJccskl7sEHH8zcZZcuXZzekOrbt6/bZpttfDqzQYmF9v1nsXUTbodpK6/nWOPVvY9C7969KzbU6667zo0cOdJ/Zx599NEV67eRO/ryyy/99VFz0JtOzfrgr5GPEWNvHALxa622Tcy2dDwuZ3bWVzl90BYCEIAABCAAgcYmUDdCtjD+6Ec/cjvssIN7+umnE4VsWWsOGTIkIi4hW21kia3F3s466ywny+5WELMjCC2Q+OKLL9wRRxzRbkFACTkbbbSRP+ayQm22EBex99hjDy9kN9s8w/lIyDExJ8wnnU4gLmKrpgRPhWYTsyXoxkNSXrxOs2xPmDDBv4Vwww03uEMOOaTN92G15yjx76OPPiq4G/3/ynL+6quv9qL7nnvuWbBNJSpI3LAQpi2vVeOPP/7Yu5tSTPgPAT34lwsuBS2cjJD9Hy78hUCpBLLEZSuzONxHUl5YThoCEIAABCAAAQgkEagrITtpgHnzdtppJ18VMTsvscap98c//jESseedd17Xq1cvpx/lssyWhfJLL73kzj///KJ8hMsn+1VXXeX9TMuas94WCUwSsfMesU8//dRdc8013oe6XlOPB1ntS1ySVXszBb2a32ohScQ2Bs0qZtv8Wjl+99133cEHH+zWWGMNL2gvvfTSHYpD37fzzTdfu31OmjTJjRo1yn9UeOGFFzqNbd11121XtyMyJJIQIAABCECg+gQQpavPuJg9aDH1W2+91T3//PPFNCu6rn6TyS0W6zQVjY4GEIAABCBQBoGmEbLFIC5mX3TRRd5Suww+NK0xAVkBykJf4be//a3bbrvtvPgsf8B33323F7Blsb3XXnu5m2++2fXs2TNzxGona8abbrrJ96UbbwnZ8rMr1zX1EN55551oYUe5E5EldjFBHAoFWaT96U9/KlStocr/8pe/uKWWWsr9+Mc/bqhxlzrYLBHb+kTMNhLNGf/zn/90zz77rNPbSnI50lELQm6//fap7i90TdV37+WXX+6hX3vttQWF7CTBOSkv7SiGdcN0Wv1mydf3mdZNiC/8W+789P2gdTdKCRrTHHPMkdpUx0f9Z9VJbZyjoJyx5+ieKhCAQIxA0jVXeeZeJFadzQ4icOONN7oLLrigQ/Ymg6JbbrmlQ/bFTiAAAQhAAAIi0FRCtiYUitnHH3+8Fyy5mRKZxgwSsi2sueaa0Q92/QgePny4W2211fwiaPKZLv/Ku+22m1VvE+um+uGHH/Y3dWojv6GywtaP7g8++MC9+eabdSNkn3DCCe7rr7/2PnDvuecep48FWVvLD22ScCFryDD87ne/c2IWBrkmkOivuNGCjpeJY+HYZX1+xx13OD3QkJ9ouRxqdjE7j4htjBCzjURzxnoTQQ/1dH3TgpD61HJBSH3fbrvtttH/qn7gaox5fXoniSJZR06L3yaJl8X2k7WPWpfpQasY6vtN/rP1IFYPMPS9paBFrnXcN9hgg2ioxxxzjNP3otX5/PPPvRW/Kmy66aZu8803j+oqof70Haq1B8aOHeut62Txv/baa/vv2bCy1jTRW1A6pqeffrrTG07yVa91LHS8n3jiCSef6nIzY/vSQrRPPvmk/2y99db+Ya3Na7PNNnP6xIPeupJbMQUtAjx48GCfloWhrvsKp556ql8jRe5sXnzxRScrRL0FoPVU5Etebucs6KG4xJ3vv//esvz3hcauuZxxxhklC/hRhyQqTuD666/33+9ZHev+IO9C0Vn9lFqm80/nflbQwyGNUS4RCRCoNgFd0xUuu+wy16NHj6rtTt81r732mv8f7aiH6VWbDB1DAAIQgEDDEGgoIVvinoUwbXkWS8x+6qmn/A8z/ZCSlSahMQno2Mn/9SeffOJ9rh577LFtJiL3GFrYTlZ/EnKShOxXX33VnXnmmf7Hg2J7/U2isMRe/eDVgk/1ECQgmPAg4SLu11Q/hGRBLjE7DPoRJStI/RgXM1l1yzpdC6+FYc455/SbjSjy2EJy4XyUth+FAwYMcBJYml3MLkbENlaNJmZPmTLFzTPPPDb8kuJK9FHSjmvUSKKfxEMd63333bcmC0La1BdaaCEvJuo6pGBCth4ayv2XgtazSHKJIrdKmocEcf1AtgWMlffGG294v+CyQJcgKT/Hzz33nO9PC0xuuOGGfp2NvKK5b9gAfyQAK6y00kpODzr1PREGuXPRd5nczZiYJxEjfBCs+vZ2k66VFvQQQC5gTBi2fN076fPXv/7V9y0rfAt6EGp96Rgfeuih7fYlUVnHUsf4nHPOade/+rJ5pfmo1kMK2896660XCdnya235hx12WHQO2Pg0Jn30Wv1xxx3nttxyS1+ka6e1s7ry+26+35MeiFg94toR0EMYGR1kBdWpZdA5GT4gSRqLyvXbxe5Zkuo0ep7uLc14KEzXw7wktv7kJz8paSiyNtYboY0U7D5fv6H0nVyt0LVrV9+17a9a+6FfCEAAAhCAQEigrRoWltQwnSZgHH300U6fMKTVlUWmfsh99tlnDSlky6JJvqFl6ZQ37LPPPolV9YRcC2KussoqieX1nGnWfeeee663OtTCbvqxLp9sChJIdIwV4q9CS/xWO/0Yl+VXaJ38zDPPeL4HHXSQ++lPf+rb18Mfm8s222zjRZw8Y5KILas1sTjxxBPd22+/7X/EZ7W1HxpZdRqtTH6/ZU0o661mFbNLEbHtODaCmC0h6ZRTTnH333+/9+Gut2pCi0qbS1as/3sJoBL31lprLf8/Id/6rRJ0jpx00kle6NWCkOF1r6MY6FpkYqsWaLYHb998800kJO66666Jw5k8eXJUR2+ZSMjWD2Q9pJIrFfnm1nf7yJEj27SXSK43NvTgstncJtlE7TVxLXIs62sJCI888oj/f1EdCcb67tD5ruuhrJP1Ro+E2m7durndd9/ddyULbgtaK8JEbP2vydepRA99b8qST2K4rK7nnntut8UWW1izKP7DH/4QidgSrfUg1Y63Kml8di5oDNr3sssuG7UvN2EPMnbccUd/j6NzRZaxEuAVJPzLGlHnoR4E6KG1hHg9CFEQSxP24/cQvgJ/ak5A1zFdO0wo04MXBZ3jejtP9zO1Fof1f6Mx6uGLgha71f/f+uuv75ZZZhmfp98rzfaQzU9s1h8dm0rcV4b9hGnbT6mxhGh9JGTr4VYxQdcQieC6PpYqhBezv2rU1YOgddZZx1/rdL3XQ0T9LtIbmnrwrWu83BJeccUVfvFbvTWjN3oee+wx9+GHH/q3rPRbSb8l5Z5Rrvz0eyP+Zk81xk6fEIAABCAAgSQCdSlk64eOXk3WDxS7cU0avG4K5Re0GYMsiYoRsbMYyOWCRKxGFLI1L1mYaQ764anFHfWKss4R/TiV1ZdZnY0ePdqddtpp/hVr8VNd+ZfWjZf9eND5pB/ueoX67LPPdv369ctCV/dlcRFbr3FLyG7VIMtAhWYUs8sRse18qHcxWwKsXvNXkJAm0UkuDPKK2RKx9RBD1nEK+rGmB1/6n2+1oOuhHtTVYkFIuW6SiKMgV06VDA8++KDvTtduuZfSmydyNXHnnXf6BYAlckvIlGjZjCG+boIW0pRbBTFX0Bs9Yr7DDjv4bb15JCFb90smZPuCWX/0/yJXTAobb7yxfwBibqvkxkPChb5/JUTr/1DuP+y71Dea9Ud9S8DW96y97WRlik3E1rj18ML6D+uUm5aAL6HagsRDnff631fQAwA90NEbXGKgB8YmZKtuPT3MtjkQ/4+AzrkkoVoPbKrla/1/e8+f0sMeC/YwRw9vWulBqs3f4rxidN561m+xsayp9YaIBGkJ03nFbBOxJWA3qogtVvof0vXPjIB0XuqNze7du3uUemCsbbOulgsrO2/1gE9ltgaRDA4UCr0l4SvxBwIQgAAEIFAlAnUpZOup/pFHHlmlKTdGt4VeUSx2Fo18w6HzQQs96gZM1gKyEoj7Iuzfv793raF6EjfkXkbWBbpZsyBrGbkm0Q2zrGXSrPmtfr3HSSJ2vY+5I8bXjGJ2JURsY1+vYrYeVj3wwAM2TB/rNey8YnZcxLaO/vWvf/nrxcorr2xZLRXbgpByr6AHv/ZjtBwIcukhK60w6G0ZWbrqQaNZyUpglUBa6SDRUg899ANb1t8SXfVw86ijjvK7kjW+hGxd65spyFJavrDjQQKzCdm6VuQNEv8tyDVJXGSW9bve9pEgLNcNemCQ9GBCFrImiFh/YSzL2WIXLQ7bZ6XlBzsUsa2u8mRVeNddd3lxX+dEmgsTa0MMAQiUT6DaonSpI5R4bcJ0HjHb6pZixV3qGKvVTg9WwsUYZdiktWUs7L333k4fC/b2j7blmiSsa3WIIQABCEAAArUkUJdCdi2BsO/6JSDf0LLUl6W1rA31w1ouZJZYYgkvcP/5z392sj6TUCdrwPA14Xfffdf/IJfFsn5UV+IVyFqSktW1BIbp06f7171lOWG+P80Crpbjq8W+5XrArElWX31172ZEIqaEUD3UaNQHF7J+kZVxXDg0xrJ0lEuF+MMvCYj6f5CAEw/6H5FIJTb1EmQRJDHM3rCwcYVituXF4zQRW/UkzsV9xcfbN/u2xF4Jerp2ytd0ua4d9EpxoaBFAvVQaeGFFy5UtehyCauyxAyFaonZWuRS1/5a+8stekI5G+i6Fn6vWTNZz1mQr/S8Qd+jCnrgK//jSSG8riQJ2bLYzhKx1afcLlQrSMhOCyZkq1zXT4TsNFLkQ6B8AvUqYIczyytmN5OIbfPX20r6zaAgwyC9QaPvSn0P6J5A92D6baEH0vqukRW32ujeWW/F6V5M95Ny40WAAAQgAAEI1JoAQnatj0DK/hdbbDG/kFVKcdHZ6q8ZgoQK/TiNB/m5lE9x/SCXj0ItTCXxTxYGEm9UJoszW/Qp3r7RtmUtYTekcsVg7hjCeWSJd6EAFLZpxLTNU2JuUtCNul4jly/ARgwjRoxIFbElROtV+aS56zXn8847z7uXkN/geLjppps8E1sANF7e0duyGNIbE4cffrizV1dtDCZmJwlmKgvdiVgbi//v//6vIlbI1l+jxro2yrVDR7lTktsnPUDUg8ZKBll5638+fg2TwKvvOf0Ql3V4M4ZFFlmkotOyhYUl/psbjqwdSOCIh0JufySySyCpVghF/Pg+wvue+MLJ8bpsQwACrUGgkJjdjCK2HkjK6MGC1liQX2y56pJrJq0rovUV5Ptab1xpnRIZO6iN7hl0D603rfQ7igABCEAAAhCoBwJ1K2TrCbG+TIsJ+tEiP4hxH47F9FEvdSVQ6XWuuHWixjdmzBj31FNPtRuqbky0sGM86HXkn//85/Hsht2WMCmBRK4I+vbt64WSiy66yMn69rDDDnP6sa9FTGQReOaZZ3q3AhK0L730Ul+3GayyJExK1E+zRtNrg/JbmhYa3SI9nJcWIJPwmWSxLOvEu+++2y8AF7ZppHSaEGgidtZcJGZrwVP5So6L2bLIqRcR2+ag/1n9uNKPpSQxW6J1PGhBQH2SglwNma/gpPJWyNP3oX6gakEnicCVCFpIT99PYZCwrGuyHrzoQZvEUR1HPUis1H61v1CcDPffCulK39vYw1CxC91wpbGMux5RPd1fZIVyjlf8YUXSfswXcaGyZn24kTRv8iDQkQTy/J8mjUftanUvmiZmN6OILfZ60CuXi3bNN3/f+j2keyRbkFTrBchVo97ytDb2VpUsuMP7KWuTdGzJgwAEIAABCFSbQF0K2RIqtQK9XocuNsiiL03cK7avWtbXD3+5wEgK8kGaJGTr9d1GXdAxaZ7xPFmPXXbZZU6+oeM3zgMGDPAWA3IvIQtVWRKIk268ZK2q19D16rl8qOrcksV2IwdZV2iOsl5t9aBjm3Y8dS2RkB2+Ht9ovPSjQpa08utu4cADD3S77babbWbGZpmtNiZm6yFIva5DsM4666SK2ZkTjRXqoVY1XRrEdleXm2uttZY75JBDEhfhK2fAOqeSXPVoQTZdc7WOgflsHjlyZOJbNGn7L/S9nyVcpvVJfjKBpZZayj8sl/94PegtJRQSwJMW6cu7nzwLXusan2bxrQcrFrIst60OMQQg0DEEaili2wzjYrbytRhkM/jEtjlarIegtn6M5SnWWhLhwshxo6ewjQyH+M0R0iMNAQhAAAK1JFCXQrassfVjVqLshhtumIvPe++952677TYnIZPQfASeeOIJ9/vf/77NKtn6AS2rPwUdd1mo6oevLAbkA1jWuMcff3y0qr1egb7yyiu9mC3r7aOPPrruLFKb78gxo0oQkEW1fBjqIY4sZmS5XEzQ/4rcjNx6663+jQ4JvBIc6zVIzD7ttNO8H/i4ZXaeMUvE/uUvf5mnalPW0cMPvZWStDBfR0w4XHxQb88UE5LeQkprH3+gmVaP/GQCErL1uri+P/VdmiRK6y0Ie4im604oeiT3WnyuHnwkBfPhnVRmeXoDQA+yk4IeoliIv0Fg+cQQgEDrEgjFbFFoRhFb89Jv6v/3//6fX7NCxjzycx0u/qg6hYLYbL755v4t10ceecS7asQquxA1yiEAAQhAoFoE6lLItsnKNUL4GpPlJ8Va6E5CNqH5CMj6XFYA8n2tH6PydSyf2PrR/frrr7uTTz7Z/xDXD+4bbrjBvw6nRSHvuece799NLlfURq/KyXLr/PPP96LeHnvs4S0/sdRqvnOmGWekc16fUoP+X7QwW6OEddddtyQxu5VFbLl52G+//dzPfvazmr2yrfNLi/BaCN2+hNbUYb7VVZz3YXQhEbtQebjPVk2vv/76/k0midgSq3XuxIMsteVKRkH/k5UMiy++uPvoo4/cnXfe6d8cCF2X6BX4PFbi119/vRdU4kK1/HnbuHXtk9V5UtB9BaG1CejhmZ0HukcMr1OtTaY1Zm9itmardDMGGQToWil/1xKyZfyldVKKCfotJSFbCz6qrX6jI2QXQ5C6EIAABCBQSQJ1LWRXcqL01bgE5BpEPzJkkSoRWoK0BVlZ68e4xA/VkU83Bb1Gp0UhN954Y3fNNdd4FwO/+tWv3Hbbbed/pGhhK7kekd9YuVgYMmSIdVnT2Hyg6sFM1uJbpVip1nRi7BwCJRAoVszWwo6taIktoU7uZ3beeee6eMtE7n7kHksCUShYh76yH374YacfxmEYN26cu/nmm8OsxDQidSKWxEy5gVGQCw4t4KUHtxKQJdgNGjTIf/fp+0bfs+PHj/fflfLLrzUHlG9isNotv/zyifsoNVPf3xKyJaTLN75ea9e+ZcWv9S3eeeedgl2rrd4w0dtXK664oj//9cbVKaecEq0xogfZoSscuVayIMtCPQASJ91jEFqPgM4BC7qfTFprxsqJ8xHQNbpW/q/zjbBtrWYVsG2WWg9Fa1fYdXDVVVf1izxaeZ5Y66oobLrppl4Q53qZhxp1IAABCECgWgQQsqtFln4rQmDs2LGRX18t3BaK2NrBDz/84FfdVlo3ZvEggUditX4gSwSXhb/cNAwdOtSLKHKvoAXJJLbI0qDWQa/umYgg4aFaASGoWmTpt9IE8orZErFladRKQQ++Kr2QY6X4de/e3QuJ4SKsPXr0iARuiUe63m2yySZefHz55Zf92zWV2j/9/IdAaB2vNUQUtI6EXHEp6PtP/zuy0Lvrrrv8xxcEf/Q9etZZZ1V8IW09XH7wwQf9nvRGXfytOn0nS3zPCvbARPNIChIm42so6D7C2sltmT4KijVXQn0RuOKKK7zbuPiozjnnnEgs1THVot61Cg899JB/Q9B8/Nuiejp/VaagNw5sDZdajZP9ti6B0NWY1i4o1YBHD/4KLfLbupSZOQQgAAEIdBQBhOyOIl3B/ejJelKQFVyzhVBwjVt3jBkzxumHuXy9qUwW2GlBN11ajfyNN97wP8jlgkSLmKh/Wd8U68c1bT/l5suiXH7rPvnkk3YLWoZ953W5E7apx3QznrP1yLnRx2RitsQqEwjCObWiiF2thRxDruWktRitgh5GatE9XWclvGsR4zPOOMOXyWenPmHQQ0etcdDKwd4sijNIy4/XC7flr1zfe/fee2+0pkRYvthii/m3luRD/29/+1tkxWx19KBhn332cVroKykUGlPWNV6+rS+88EL/On/44FZistzjyE2QfGDL6jotqL2s+OMiuCzI9QbWTjvtFImdYR+nnnqqO/vss734GOaTrj8C33zzTeJ139yBaMRZ50gxM4rfZ+ZtqzVZZFgRD7rHtO8sidyNvPB0fG5s1zcBGcW88MIL3rVi6Lap0qPWtVvf93p4TYAABCAAAQh0FAGE7I4iXcH9yPJYC2G++OKLvlfdeOvJul7TbbawyCKLOH30yvmBBx7o59mnTx+nRaDkO1s/DCSOHHPMMakLPoVM9CrcJZdc4n8cSwQ3C5lyfA+H/VcirflIXMgKpf7Ysj7LbW/9lBvrnJUgp1fYw4cW5fYbb1/NvuP7Yrs6BCRmy/1AXMxuNRG7Vgs5hoJkIfFSZ8AKK6zgF4VSWouMmv/l4cOHKysSs/3GrD/ycSz3KGqXJGTbPsNxWNtmiPVd9PzzzydOJS3fKut18bQ68ver/5k0i2X10bVrV6c3nvSRO5iPP/7YyWJP372hGw7bn+430vZndeTSK0/Q/YysVrVfPZyWyxN9/9l3lFlLp/Wl+nIPpgfTeqgtoVBW6PG3t+LtdQ+Vd4zxtmx3LAG9RVfNIIv9J5980hsQ6HwqJejNGAIE6omAXI3pjSiJ2dUMCy+8sH/Dp1m/m6vJjr4hAAEIQKB0AnUjZOuHmH48DR48OJqNFpModjGKeBvzBxZ12gQJ3SxIjG2FoB/3sqSWv2hZ3IS+DDV/vR6sH7F6fbiYMHSWaxF9CLUlINE+bpGZNCKJ3eUEE0XK6aOe28paMr5IXpoFZT3Po9DYJGb/5S9/8R9ZwOlVclnwtkLQWyUSg7fYYouKu3jIw08PDPTJGyQ+JQlQ+p+XcKTjJuHxq6++8u6UzH+2Hjo9++yz0YMtewgln8cK2rbX9+Njufjii31ZVp14G7bbEtBxsGPRtqS6W+XuV2I8C49V9xg1a+8TJ070xhLyk15Ny9Vm5ce86pOA1kLQdyIBAhCAAAQg0IwE6kbI1g9kraic9GpeKeAlXMnSZ+DAgaU0p00dEZDllF4blvWUFn+SgCWrbD300OvHrWoFoNdV9fCnmDBhwoRiqtdV3VabbzHwjzjiCHfZZZf580FCoa59w4YNK6aLhqmrhxqyCJVYqbk2e+jXr5/TGyOyrpJY1yxBlsKam4KJ1c0yN+YBAQg0DgEZSOga1IxvNTbOUWCkEIAABCAAAQhAID+BuhGyt9pqK6cPAQJJBPTq2uGHH55U1JJ5WjRNfrRLFSvVvpFCq8232GMjdwxa+KpVgh5UNruVvR3LG2+80ZLEEIAABCBQYQI9e/b01vxypUOAAAQgAAEIQAACEKh/AnUjZNc/KkYIgfohIP/eWuDqu+++K3pQ8gGpBdcaKbTafBvp2DBWCEAAAhCAQKMSKNY1XaPOk3FDAAIQgAAEIACBZiGAkN0sR5J5tBQBuVUJ/ck3++Rbbb7NfjyZHwQgAIFSCWy88cZu9dVX9827d+9eaje0gwAEIAABCEAAAhCAAAQakABCdgMeNIYMAQhAAAIQgAAEWpGAfMU3k7/4VjyGzBkCEIAABCAAAQhAAAKlEmj+lbJKJUM7CEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQqAsCWGTXxWFgEBCAAAQgAAEIQAACEGgtAt26dXNTp051p512WtUmrn2UExphjOXMj7YQgAAEIAABCECgkQhgkd1IR4uxQgACEIAABCAAAQhAoEkIDB061JUrNGehUN/aRzmhEcZYzvxoCwEIQAACEIAABBqJABbZjXS0GCsEIAABCEAAAhCAAASahMDAgQOdPvUcGmGM9cyPsUEAAhCAAAQgAIFKEsAiu5I06QsCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQqTqBsIbtTp/90MX369IoPrtYd2pxsjnnGY3WtbZ42jVDH5mPzyzPmzp07+2rWNk8b6kCgHgnYOWzndJ4xWl1rm6cNdeqTgB1DO6Z5Rml1rW2eNtSBAAQgAAEIQKBxCMyYMcMPtpjfR1mzs35a6d7B5mpzz+JDGQQgAAEIQEAEyhay5513Xk9yzJgxzr6ImgGt5qI5Kdgc88zL6jYTj1JZdO3a1SMbP358U50bec4D6jQPAZ3/OocV7JzOMzury/mfh1b91uH41++xYWQQgAAEIACBWhGYNm2a++yzz/zu7fdfuWOxfprpd2QWk1J/Y2b1SRkEIAABCDQ/gdn+PSuUM02tNP7WW2+5mTNnltNN3bbV0+EBAwbkXoimmXkUy2Ly5Mlu9OjRdXtsGRgEiiXQr18/N9988+VqxvmfC1NDVeL4l3e40m43kvItT7F9bO+63wjzlA7zbFtCQPfu3d2wYcOsKTEEIAABCFSIwB133OEmTZrk+vTp42abbTZnFrWWVhz/2K7DfOVpOx6S8tLqxtt25Haxv4+yxtbMvyOz5l1Jhln7oQwCEIAABJqDQNkW2VoNXEKvfizaDUwzoNFcNKdiRGzNuxl5lMpCgp+En7nnntvZa/bNcG4wh9YioHNX53AxIqYIcf43x3nC8W+O48gsIAABCEAAApUkUOrvo6wxNOPvyKz5VoNh1v4ogwAEIACB5iBQtkV2c2BgFhCAAAQgAAEIVJOALKWTQphv6TBWOtyOW1+rzPLCWG8E9ezZ0/Xv3z9pt+RBAAIQgEAZBN5++23vem3ppZeOLLLN0loCpdIWW75ZWSdtayhWHk+HwwzrhPmkIQABCEAAAhBoDQJlW2S3BiZmCQEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAArUigJBdK/LsFwIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABHIRQMjOhYlKEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgUCsCCNm1Is9+IQABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBcBhOxcmKgEAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACtSKAkF0r8uwXAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEchHokqsWlSAAAQhAAAIQgAAEIAABCFSQwKhRo9yIESPc1KlTK9jr/7rq1q2bGzp0qBs4cOD/MotMNcIYi5wS1SEAAQhAAAIQgEDDEsAiu2EPHQOHAAQgAAEIQAACEIBA4xKopogtKhLItY9yQiOMsZz50RYCEIAABCAAAQg0EgEsshvpaDFWCEAAAhCAAAQgAAEINAkBs8Q+4ogjqjKj0047rWxr70YYY1Xg0SkEIAABCEAAAhCoQwJd3nvvvTocFkOCAAQgAAEIQKCZCPz73/9OnE6YH6ZVWdv2se2ZM2f6PNtWueVZXW1/8skn7ttvv3X9+/dXVQIEIAABCFSQwMcff+wmTpzo5phjDjfbbLO1+XTq1KnNdliuIcS3bVjKtxCmLU9xWn5YhzQEIAABCEAAAs1LoItuNAgQgAAEIAABCECgmgQkMieFMD9Mq64J05afFId5ErBN5FDMPU4ScfIgAAEIlE/AxGqLdc21T1KelWnPllYchnA7TKfVCfNJQwACEIAABCDQGgRQsVvjODNLCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAINSwCL7IY9dAwcAhCAAAQg0DgEzHI6PuIw39IWyyJPadsOY6WtXH2GZbIGNIvA+P7YhgAEIACB8gno+mvX2ay0ysKP9mzbNgptW348z7Yttrq2TQwBCEAAAhCAQGsRwCK7tY43s4UABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQg0HAEuvBUu+GOGQOGAAQgAAEItCyB8L7FrLItz2LBUTrcrmdgEyZMcHvvvXfBIc4///yub9++bpVVVnGbbrqp69y5c8E2VIAABCBQDQJ2jU2Ltc+ksjDfxmXXaoutjpWHcVgnzCcNAQhAAAIQgEBrEEDIbo3jzCwhAAEIQAACTUEgScSwPIvNzYht1/vEZ8yY4T766KOCw1SdV155xd11113u8ssvd+eee67r3bt3wXbVqnDMMce4L774wm2yySZu2223rdZu2vX75ZdfuiOPPNLnH3DAAW6FFVZoV4cMCECgugTs+qo46aO9F8q3EYZ9xfNs22Kra9vEEIAABCAAAQi0FgGE7NY63swWAhCAAAQg0NAE4iKGWWVrUlam2D6NNtmll17abbzxxu2GPX36dDdmzBg3YsQIN3XqVC98S8yVoD377LO3q98RGaNGjXJjx451SyyxREfsLtrHtGnT3AsvvOC3x40bh5AdkWn+xMyZM/0k5Zu5noP+X7t06VLPQyx7bHaNTYrVeVK+8sIyv/HfupYfz7Nti60P2yaGAAQgAAEIQKC1CCBkt9bxZrYQgAAEIACBhiaQJWJYmWL7NNpkl112WbfHHnukDvvzzz93w4cP92L266+/7l599VU3aNCg1PoUQKAZCHzyySfugQcecHLDo7DAAgu4n/70p65Pnz51M73vvvvO3X777U5j1VsW88wzj1t99dXd4MGD62aMlRyIXWOLjTUGa2Pj0bblx/Ns22Kra9vEEIAABCAAAQi0FgGE7NY63swWAhCAAAQg0DAEQmtrG3SWiGFliu1j7ZolXmihhdwWW2zhbrnlFj+l0aNHZwrZEtTEohgLVlk8q36lfXCrX42lFEtVnQtqP8ccczTLoWQeOQl8+umn7vrrr3dmja1mErRvuOEGt9NOO9XUvY5N4fvvv3eXXXaZ++abbyzLTZkyxf3973/3orYE7WYLdo0tNhYHtcmKwzJfMfhjbYMskhCAAAQgAAEItBCBDhOyzV9lC7FlqhCAAAQgAAEIQKDiBNZcc81IyJaAFg8S06677jr3/PPPu5deesl169bNrbrqqt4yVItEatHIeHjzzTfdTTfd5J566iknH9QKsnpdaaWVvAX4aqut5vNkEX7SSSf5tNyKKDz44INOYqPCgQce6Pr37+/TEtFHjhzpbrvtNvfWW29F/dp4tttuO7fGGmv4uvbn7LPPdu+9955fzHLzzTd3jz76qHvyySf9R5atEgfDOV988cXuvvvu88L7GWecUTM3KzZ+4soTuOOOO7yILQvnXXfd1Yug1157rZs8ebJTmc65Wgedp/q/k8gqcX3hhRf256X+r+QOSH7c55prrloPk/1DAAIQgAAEIACBhidQVSE7FK95et7w5woTgAAEIAABCNScQNb9hJXF45oPusID+Oyzz6IeV1555SithNyNyHe2iczKk0/txx9/3H8k/F100UVepFaZwmOPPeYOP/zw/2wEfyVoS6DTR31qQUe5T3j66aeDWv/p3/J+8YtfeCFb1rMnnHCCu//++9vU1UY4npNPPtm7iLBKL774op+DfIWfc8457pprrrEi3872Y5laANMWypTFdq38hdt4iCtLQIuJfvXVV75TnVsSsxV23HFHd+GFF3rxWK48Fl10UZ9fiz/6vaP/O4X11lsvshDfaqut3AcffOD/Z5599llfVovxVWuf4XVW6bwfjSdsm7Qd5ikdBmsb5pGGAAQgAAEIQKB1CFRsFZJQtG4dfMwUAhCAAAQgAAEIdByB8ePHe2tr26N8aluQheq+++7rBV/l7bXXXt6i+ttvv/UuDmQ5LWtn5f/1r391Xbt29W4PQhH74IMP9m0kREtUvuCCC3z3p5xyilt//fWdXJuojqytzz//fF+2zDLLuA033NCnzWfx3XffHYnYEqU32mgjN3DgQO9W5IknnojmcNVVV7URsn0ns/488sgjkRgvC261HTJkiFtxxRW9W4kbb7zRV1W/AwYM8GlEbKPXPLHOQQWdAz169IgmNu+88zp9JHKrTi2F7Pfff99pcUcFnZ8WJLjq3NeiqK+99lrTCdk2T2IIQAACEIAABCDQkQRKtsiOC9c8He/Iw8a+IAABCEAAAq1JIOl+Q/ckyreyMN1olGRtHbc6lqgswU7+sG+99dY2QnXob1oWqrJ2VpAl83LLLRdNXyK03Bucfvrp3oJZVtZy3SGXHxYkUO+yyy626QXtpZZayh122GE+7+WXX3YbbLBBVOfOO+/0YrP2s/vuu0ftlJCLEgUJ35dffrkXIn3GrD+rrLKKH6cWxnvnnXechPa42wWzKN9///29O4nQX7cYmZCteWnRP0JzEpg0aZKf2GKLLdZugnpoIoHY6rSr0EEZ5opH57AeDoVB/z8SsnWON2Owa20Ya57hdjxt5VlxWKZ0GNQfAQIQgAAEIACB1iVQtJBtAjY3Ea170jBzCEAAAhCAQK0IJN1/KM/EbI1L2/ap1ThL3e8zzzzj9CkUfve73zn5mLYgAVsit4LE6FDEtjqqf++993o3CPJbLSF77rnntmL3j3/8w7sPCfNkBa19Kcjvb94gP9xqK9/asqaNh+7du0dZclcSF7JVuOeee7o99tgjqkei9QjIJ7pCeE4aBXMzYnUsv6NjvQmhEBexlWdjNItt5TVLsGtsGGtu4XZS2upkxWGZ0mFQnwQIQAACEIAABFqXQBcTplMRzLJyqmZQ79yOVJMwfUMAAhCAAATqgEDa/USYb+msWGVJH00xLb8Opl/pIWgBxC233DISgD/88MNoF7Lgjlt1W2HPnj198pVXXvH+hZdYYgm35JJLepcjzz33nBs2bJhfaFECtMRwLfi4/fbbW/Pc8VFHHdWmru435RZFbhi0nyuvvLJNedKGfCITWpuAvWGQJBLbww89CKllMCF9zjnnbDeM8CGO5hJut6vcaBnh9VZj17ZEZsu3vEabF+OFAAQgAAEIQKCuCWRaZHuRu8pPvRGx6/r8YHAQgAAEIACB+iKQdF9i4omVKbZPfY2+4GhkJW0W0GHl77//3ovNZ555pnfHIaH64osvdr/5zW98NQnEFq677rrIB7XlJcUSlmXp+sc//tEv5qhFE+UmQf6z9VEw/9ay5pZP4mKC+pKvbAnXeazMw7579+7tZNVNaG0CEoclAGshz3j44YcffFatfaObyJ41Rg00SeiOz6mhtu0aG8aaQLidlLY6WXFYpnQY1CcBAhCAAAQgAIGWJZAoZJuVNq9utex5wcQhAAEIQAACdUFA9yTh/UiYtgHG87RtH6vTKLF8Xps7gnDMytNid+edd17kE1o+pk3IjrsuyGP5+c033/hdaLFECdePP/64GzlypNNijGYJKx/W+lx99dXeilo+f/MEWYzb2Ky+xGm179evn/v888+9mxMri8dJPpHjddhufgJ60DJx4sTofAxnbOdoktuRsF610/PNN5/fhR42xYP9j3Xq1MmFft7j9Rpx266xFmsOls6Kba5Wx9qFcTxtbbLywzqkIQABCEAAAhBoXgJd4lMzETueX+3tWu232vOifwhAAAIQgAAE9Lb5rNfOE0KYb+msWGXFfBJ22dBZErPXW289LzpLyNNCd/I3vfjii0fzuuiii9zgwYOj7TwJWZVq0UR95JpErkrkM1vW3RKdta8TTjjBLyJZqD+NKRSxjzvuODd06FD3ox/9KGoqS235604LYd20OuQ3PwE7D3QOxsOnn37qs6xOvLyjtk3Ilmit/x2J1hY++eQTn5xjjjksq2ni8DqsSUmYTrt2xycd1o2XsQ0BCEAAAhCAAASyCER3WnYzklW5lDLrt1BcSt+0gQAEIAABCEAAAq1GYNlll42m/NVXX/l0KGT/61//isrjiUcffdRbdcsticJLL73kLrnkEnfppZdGIpSEuB//+Mduxx13dLL6lp9shddffz3RMtYXBn9Uz4J8ZcuXd1xs/Oyzz6wKMQRSCfTv39+XyQ1O+NaBBGM7h6xOaicZBXJ/88UXX/hP2H9Gk3ZF8jGvoN86oYsf5b311luK2jxo8hn8gQAEIAABCEAAAhAoiUAnPRFXsNe7yo3joyimv3hbtiEAAQhAAAIQgAAE2hJYeOGFo4zJkyf7tMTmQYMG+fQVV1zhF1aMKv03IatW+d++6qqr3Kuvvupzx4wZ44VsCduhAG1tZalt/SpPrk/iYcaMGW2yzFJWmUkuQuQq4pZbbonaSAAsNcT3XWo/tKtPAssss4wzH9ihBf8DDzzghWO561h++eVLHvwjjzziHnvsMf/ReVlKkO/rPn36+KYal0R2hTfffDP6PxwyZIjP4w8EIAABCEAAAhCAQHkEOpXz40G7jltax4cTL8/ajrdlGwIQgAAEIAABCECgLYFw0UWzSlWNgw46yFeUGxBZU8v6esKECU5W2yNGjHBHH3101NHWW2/t0yuuuGKUd+ihh3qXJd99953PUztZZD/88MN+e9VVV3WhiwSzsn7++eedFp+UOK4F+Pr27Rv1eeGFF3o3Jbr/k/WrxrTbbrv5tFUaO3ZsJP5ZXlY811xzRcUSIrX/N954I8oj0VwE1llnHT8hWTfLbY4euthbB2uttZY3xqn1jDfYYAM/DrkXOeecc7w/ebnPUZBv+PDhU63Hyv4hAAEIQAACEIBAIxNIXOwxz4T0g0TBLLqtjeXbdlJ5PM/qEkMAAhCAAAQgAIGQgO4rwvuGMG314nnato/VaaY4XAzyxRdfdBtttJGfnixTDzjgAHf++ed7oVjW10lh2LBhbpNNNvFFckmy7777eoFQQvNhhx2W1MTn7b///m3Kll56aW91KiH64IMP9mUS8VZZZRXvSuGjjz5yo0aNcttuu22bdtqQharEb4Xdd9/dHX744W6HHXbw24X+SMiXBbrGq4Up9VFQnGeRy0L9U15fBPQA5dtvv/U+2+0NBI1Q+WuuuWbFBhu/jhTTca9evdx2223nbr31VqdFH82nt/L1UKkZg11jLdYcLZ0VGwurY+3COJ62Nln5YR3SEIAABCAAAQg0L4H274cWmGtcqFb1pLy0bnTTkhSK6SOpPXkQgAAEIAABCNQvgbTv+TDf0lmxyor51C+R/40sdNdhbhT+V9o+tdRSS0WZN998sxeizUpborCsrM8+++x2rkIk/kq0Nmts62SvvfZyCy20kF/Y8b333rPsKJZQrn4HDBgQ5SmhviQsmpBshXJHcu6557ozzjjDPfnkk5btY1mnHnLIIU4WrDvvvLMXwttU+O9GaPmdVH7qqacmzjGpLnmNT2Ddddd1a6yxhnv33Xf9ZOSXWi49yg3bb7+9P0e1KOP8889fVnfyK68HQVooVW8zaNv+L8vquE4bh9dhDVG/8dKu3fEphHXjZWxDAAIQgAAEIACBLAK5hWy7MQk7S8oLyy2dt16p9a0dMQQgAAEIQAAC9Ukg7V4gzLd0VqyypI9mnZZfn0T+NyoJzHKPkTd07949s74soq+55ho3bdo0L6rJ1cgiiyzievTo4bSQY1LYaqut/KKMckWihfVkAav9yCVCmpWzys4888yk7rw7BYnpspqWz2z5DZawN/fcc0f1NUa5i5CLEgncCsrLE2yOeepSpzkI6OFGuNBpJWYlv9jjxo3z56X8bZcbbKHUcvtphPbh9Vbj1bYJ1Epbnk/wBwIQgAAEIAABCFSIQC4h225GbJ/xbcu3OK08Ld/aJcVpFtxJdcmDAAQgAAEIQKC5CSTdF5h4YmWK7dPcNLJnJ+vufv36ZVcKSsWsZ8+e/hNkl5WUSK9PUpDoV2lhMmk/5EEgjYB8rOv3yXLLLZdWhfwUAnaNDWNVDbeT0lYnKw7LlA6D+iRAAAIQgAAEINC6BDKF7LjwHN8OscXL4tuqW+yNh/pI6ifcL2kIQAACEIAABOqfQNr3eZhv6axYZUkfEUjLr386jBACEKgFAT24WWaZZfwbC7XYfyPvM7zeah7a1m89y7e8Rp4jY4cABCAAAQhAoP4IpArZugkJQ3zbysL8MK3yJOE6Xsf6SYqLqZvUnjwIQAACEIAABOqDQNp3ephv6axYZfGPZhjPsz7qY/aMAgIQqEcC66+/fj0Oq2HGZNddDdiuuSZmh3kNMyEGCgEIQAACEIBA3RNIFLLtRkSjD9PhbML8MB2K12G+tU3KC8vC9pZPDAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAq1LoJ2QHQrNYdoQhXmWDsVny1P9MG3tk+KwXphOqkseBCAAAQhAAAKNRyDt+z3Mt3RWrLI8HxGyfhqPFiOGAAQgUN8E7Poaj8NRW1mYRxoCEIAABCAAAQiUQ6BLXIS2bd14WNp2YHl2U6Jyq2N5VlexlSmdVJ6Up7oECEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgIARiCyyQ1E5TFtFy7PYRGrbttjqKw7zwnRYJyldTN2k9uRBAAIQgAAEIFBfBNK+28N8S1usGSht25YuJq4vCowGAhAICXTr1s1NnTrVnXbaaWF2RdPaRzmhEcZYzvxKbRteh9WHXafD/pLyrFy/JbPKrR4xBCAAAQhAAAIQCAlEQrZlJt1QWJ7F4Y2H5cXbx/Pj5Wnblp8Wx/s1QT2tPvkQgAAEIAABCNSeQPz720YU5lvaYtVR2rYtXUxs+yGGAATqj8DQoUPdiBEjvJhdjdFJhNY+ygmNMMZy5ldq2/A6rD7sOh32l5QXlpOGAAQgAAEIQAACxRLwQnbWTYaVWRwXsZUfzwsHYe2UF6bDOvF03nrF9BnfB9sQgAAEIAABCHQcgbTv9jDf0hZrdErbtqXDOKwT5lu642bIniAAgWIJDBw40OlTz6ERxlgLfnaNVaxgsdL22zDMUz4BAhCAAAQgAAEIlEugS3iDEabVsW0rNsvnME910m5U4vVU14KVpW1bPjEEIAABCEAAAs1BIP7db7MK8y1tseoobduWDuOwjuUn9W15xBCAAAQgUD6B8Lqs3mw7TId55e+RHiAAAQhAAAIQgIBzkWuR+I2GbVssWErHty3fYMbrJJVb3aRw/G5DAABAAElEQVQ47D+pnDwIQAACEIAABBqPQNr3e5hvaYs1S6Vt29IWh+WWF48bjxQjhgAEIFD/BMJrrUarbQtKm7GT5RFDAAIQgAAEIACBShCIhOywM7sRsdhuRGxbdZWOb1u+9RWvE+ZbOt4mzDcr8DCPNAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCLQWgVQf2SZSm4gdYokL1Hm2rX3Yr+Ul7UNlVtfqpeWF5aQhAAEIQAACEKg/Aknf6RplmB+mrUx5lq945syZbbbDPJUpKA7r+Uz+QAACEIBAxQiE1151qmuuftOZIZKl47Hqhnnatmu8tbU6iuMhrBMvYxsCEIAABCAAgeYn0M4i224kNHXdKNh2GFtadZS27TBtZWFsNy1hPWuregQIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQJxAm8UerTAuLtt2KECrbrgdT1t5XLy2vmxfVi/cTsuL12EbAhCAAAQgAIHGIJD0/a+Rh/lh2sqUZ/mKQ0trK7O8+LbyCRCAAAQgUHkCdt1VbL/3LNbeLB2P42XhyFTXQpi2PMVp+WEd0hCAAAQgAAEINC+BNhbZ9kNR09VNgv0gVBy/abCy3r17Ny8dZgYBCEAAAhCAQEUIhPcYYYdhvqXDWOlw28QTy1dseWE8bdo017Nnz3BXpCEAAQhAoEIE+vTp4+aaay63xBJL+N+JnTp18rF+M1raYuXZR7u3tGLbDuN42lf67x9rE+aRhgAEIAABCECgdQh0ik9VPwjjNwjath+Mqh+m4+3ZhgAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhUkkAkZEucDkMoVmelwzakIQABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAKVJhAJ2eo4LmZn7SwUt7PqUQYBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQKIdAGyFbHWW5EQnF62JE73IGSFsIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhBobQJeyM4rSlu9eNzaCJk9BCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIVJNAZJFt4nR8Z5ZvscrDdLw+2xCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBShKIhGx1muRWJL4zE7EVWzpeh20IQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQKUItBGy0zoNRetQvJbwTYAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIVJNAp1CYLrQjqxsK24XaUA4BCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQKIdAqkV2HrHahO1yBkBbCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgEAWAS9kS5DOchOSJFhn1c/aIWUQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgWIItLHITrLCDkVsS8fjYnZIXQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAMQS65K0cF69tO2976kEAAhCAAAQgAAEIQKAVCei+eezYsW7cuHFuoYUWcosssoibY445WhGFn/PEiRPd559/7iZPnuzmnntut8ACC7hevXplviHasrCYOAQgAAEIQAACEIBARCC3kB21mJWQWxGE7JAIaQhAAAIQgAAEIFAagQkTJri99967YOP555/f9e3b162yyipu0003dZ07dy7YhgrpBD788EN30003ubfeest9//33rk+fPm6zzTZza6+9tuvUqc1Li+mdZJTMmDHD3Xjjje6f//yne+WVV9zUqVPb1F5uueX8cdf+4i77vv76a7frrrv6+gcddJBbf/3127Rt1I2HHnrIMxk1alS7KUjgHzZsmJ93K4v87cCQAQEIQAACEIAABCAQEZhtljXELE36Pz6yFZtAPXPmTF/J8sJYBbatH1QECEAAAhCAAAQgkEXA7i/idcJ8S4ex0uG27k8sz2LLC+PRo0e7nj17uv79+8d3WXfbskzdfPPNixrX4osv7s4991zXu3fvotpVsvIxxxzjvvjiC7fJJpu4bbfdtpJdZ/b15ZdfuiOPPNLXOeCAA9wKK6yQWT+p8Nlnn3X7779/UpHbeOON3cknn1yWmC0uRx11lHvppZcS9xFmrrjiiv5YduvWLcrWw42f/vSnfvuEE05wW2yxRVTWiAk9KDj99NPdXXfdVXD4EvhVVxbalQzXXXedGzlypNP/ztFHH13Jrsvqq17HVWhSb7/9ths/frxbeuml/YMYPfzRAxl9LG2x5dsDm6Rt7c/K4+lwLGGdMJ80BCAAAQhAAAKtQaCgRbb9eIzjSMuP12MbAhCAAAQgAAEIQCAfAYlCElLjYfr06W7MmDFuxIgR3rL3o48+8mLu5Zdf7mafffZ49Q7ZllWt3GUsscQSHbI/28m0adPcCy+84DflqqNYIVsPPCTCW5B1+8ILL+zuueceJ5H84Ycf9hbQEuhLCbLwloW9WWAvueSSXpQeOHCgW2yxxZxE6n/84x9OAqbqyFr797//vTvzzDNdly4Fb81LGVJN24jpwQcf7N58800/Dgn222yzjT9uOt91DHUuift7773nXn/9dbf99tu78847r+hjmzXRjz/+2J83iusp1Ou46okRY4EABCAAAQhAAAJGIPFuOUmktjzF9iTc8qwzYghAAAIQgAAEIACB0gksu+yybo899kjtQNbbw4cP9wKoBL9XX33VDRo0KLU+Be0JSDiUuKqw9dZbuz/84Q8+LavyrbbayqcllJciZOveWNbEJmJvsMEG7sQTT3Rdu3b1/erPoosu6iRqy43GXnvt5R8GPP30095auSMt26MBVTlx8cUXRyK2rKElUIuBBT0IWWONNdwuu+zijjvuOPfII494fjout912W1OK+zZ3YghAAAIQgAAEIACB4giU5AAQAbs4yNSGAAQgAAEIQAAClSAgP8Khmwm5UMkK8tMsC+Rigiye1a7SQf3KsryUoHvPH374oZSm7dp89913Ud7qq68epSWuatFBhW+++SbKLyYh1xWysFaQX+tTTz21jYgd9rXgggu6s846K8q6//77o3SxCbEtNui8KIdpnrbvv/++F6M1NonYV111VRsROxzznHPO6f70pz9FbnZk7S8r+VqHPPOs9RjZPwQgAAEIQAACEGgVAu0sshGpW+XQM08IQAACEIAABBqRwJprruluueUWP3T5Ho4HibByW/H88897H81y5bDqqqu6wYMH+0UitWhkPMjtgxY+fOqppyJrZYm6K620krcAX2211XwTWYSfdNJJPi2hUeHBBx90n376qU8feOCBkV9yieESdmVVK3cbZgVt49luu+28Ja5v+N8/Z599tncvIXcf8hv+6KOPuieffNJ/NP4pU6b4hRmtjax977vvPu+T94wzzsjlZiW0BpZQapbX8mdtY1xmmWVsF0XFGr+FffbZp6CfbbkdkZj+zDPPeAFcvrUlcBcKEqHvvPNOz0XHWRbgK6+8stNx2nDDDZ36TQqvvfaaP85qo2NpQX66tdDlz3/+8zZjlriu46v+fvOb3zi1lwsQWZDLyvyaa66xLhJjHR8Lsj6fd955bTMxlk/lfffd15mof+GFF/pxmUW7xqC5a6z6xMO3337rjjjiCJ8tC2+dM3Ij89VXX0VW4Zq3XJ0o2Hk2ceJEbw2uPL0RoQcD8udt7nP0AEmLrOrhhPjGw0UXXeRdovTr1y/qO15HlvpyD6T/31/+8pe5xhXvg20IQAACEIAABCDQ6gTaCdlyG5ImZqfltzpE5g8BCEAAAhCAAAQ6isBnn30W7UriZRjkbkQLIZrIrDKJnI8//rj/3HHHHU6im1keq/yxxx5zhx9+uJJtgkRdCcn6qE+5vZA1s0TMMKh/y/vFL37hhWyJjVqk0ATJeH0bjxZVtEUNVefFF1/0gqB8J59zzjlthNJwP9affIXroyDxMY+/8B/96EdesL399tu9r2oxWWqppdwhhxzi+5HQbi5GfEbOP5MnT47GMmTIEL8IXp6mWrRTvBQ6d+5csImOi1xwyM92GCTE6yPx+Morr/TuS8JyCbN//OMfw6woLStyfd55551oIU0Vyme1jq32Kf/sv/3tb6M2WpQxK+h3g9yEKOh8S/L9ntReDxr0EEPnjvarMdi+9FBDIc0vuh6e2Lm43nrreSFbC3uqnzBYnQEDBvhsPSCxPInh8UU6JX5L0Ndnhx12cIceemgblyd6EKT2SQ+WbL9yA6R6c889txey84zL2hJDAAIQgAAEIAABCPyHQJcscdrKLAYaBCAAAQhAAAIQgEDtCIwfP95bW9sI5FPbgoRUWbNK8FWQBawsqiXM/f3vf/cinERB5f/1r3/1FrUS/kIRW5aqaiNhVaLyBRdc4Ps65ZRTvDWqLFNVR+3OP/98XybrZbNS7dOnj8+7++67IxFbovRGG23khVUtZvjEE09Ec5CriVDI9o1n/ZEAamK8hGX5lJY4LMthLZZ44403+qrq18TIPCK29X/AAQd4YVYCp8T0MMiqupDlcFjf0rK2tRB/wGD5SbGskPXJE3RProcKttilBF/54ZbFso7XFVdc4bvZfffdPSNZCCvouJuILVH5Zz/7mWfas2dP/+BAx1LnjaznxSY+fz0sOPbYY31f+qPjsdZaa0XbSQmdqxbWXnvtXA8ZrL58ZttDEHE1IdvKi4n33HNPPzdZ32seOp/ER0HziAcTsWV9rY946QGRzlUx0psL6kOcygnFjqucfdEWAhCAAAQgAAEINAuBdhbZxUwMgbsYWtSFAAQgAAEIQAAC2QRkbW2WoVZTorJcI8gf9q233tpGqJYwbEFuGEzElsuHUPyTICcrVrk3kJgnK2uJoHL5YUECtdwxWJCgLUvlww47zGe9/PLLXjS1OnJtIbFZ+zFh0NrKRYmChO/LL7/cC39WJhcNGqcsomUBLKF9rrnmsmIfm4i9//77u1133bWNpbIYmZCteSUJ4W06S9jQ/rRIptxkWOjdu7eTe5L+/ftbVlGxWYarkfqqRtB4TcT+3e9+57bffvtoNxJ/hw4dGh3DG264IVrIUq5ELOjhhAncypOY2717d3f00Uf7KrIaNlcy1sbOK1lVS0iPC91WL4y1qKaFxRZbzJK54pDfhx9+mKtNWiVZUCvI/Y2O0TzzzNPufI233Xvvvd2vf/3rKFtsNXflyTpbFu96+6BHjx5RnWITpYyr2H1QHwIQgAAEIAABCDQbgejXj0TpPMJ0luuRZoPDfCAAAQhAAAIQgEBHEpCvZH0KBYmY8jFtQUKjRG4FCc2hiG11VP/ee+/11qWyvJWQLTcHFuSqQu5DwjxZQWtfCgsvvLBVLRjLD7faShCV9Wo8SDi1IHclcSFbZbJYlb/iSgdZJ8tFRig8ax9yOaIFCRV0T2zibcjDF6b8GTduXFQSzi/KrEBCvs8VZAU/fPjwdj3aQwUJrXIlIp/SmpcsvnU8NK5QxLYO5ptvPktG844y/puQ4C3L/LwhtMgulkcoEH/yySd5d1mRenr4orcW4kFvG8gHvFmm639JD1kIEIAABCAAAQhAAAIdR8AL2YjTHQecPUEAAhCAAAQgAIFyCchX8JZbbhkJwKHVqiy441bdtj+5klCQP2QtCrnEEkv4hfwk7j733HNu2LBhfgE8CdASReVWIbT6tX4KxUcddVSbKhKGJWy+//77fj8SWgsFWbxWOrzxxhveqtZEalnYalwS9mWJfOKJJ3pXI7JU33nnnf3u5VJi+eWXLziUcBFNLR5Y6aDjKhcXChKn//nPfybuQvf1FrRYoQRsid5x4VtW/jpvxERzLBSKfagQitdff/11oe7blE+aNCnalrDckUGc0nyVyyrbhGydywQIQAACEIAABCAAgY4lEFlkd+xu2RsEIAABCEAAAhCAQJyArKTNAjos0yJyEpvPPPNM745DQrUW9ZPFrUIoqslq1yx3wz7iaQm4sjaW72S5i5CFsnxGy3+2Pgrm31rW3HncSYT7UF/ylS2BPI+VedhWriVCYTgsKzU9ffp0v0iiidjnnXeek8sI+fuWuxI9HPjb3/7mLZYl4FvIO47QHUZonW39pMVyVfHBBx/44h//+MduwQUXTKwq1xgWxFSfQiG0itY59NBDD/mHHPKnHV8AsVBfsgIvJpi/dLUp1qo6rK+HLR0ZzCo/aZ/yw65y/a/o/5EAAQhAAAIQgAAEINCxBBCyO5Y3e4MABCAAAQhAAAKpBOTzWj5840F5crcg8dV8QsvHtAnZEmnDkOTOIyxXWhbZClosUcL1448/7kaOHOkXYzSxVz6s9bn66qu9X2D5zM4TJArb2Ky+hF61l2sLibdyzZAWivWpnNZPmC8rdBMf5QNZIraCrG9POukk75JFAqV8SJuQLY6LLLJI2E1qOhSyX3vttdR68YKbb745soiWP/E0IXvatGltmuY5xnLboiBheLfddmsjXmuOOh76yHr6oosuatN/fMOYxPPTtkNXNBLdZVGed1FL+WO3EArilpcW53GTmNbW8kO/85YXxlZubMMy0hCAAAQgAAEIQAAC1SWAkF1dvvQOAQhAAAIQgAAEKkZAYvZ6663nRWeJzXLBIBEytCKVIDl48OCi9tm1a1cvkEskl+AolxPymS3LbonO2tcJJ5zgtIhkoaAxhSL2cccd5xchlDsMC7LUzhKyw7rWptz43XffjbpYZ511orQSelBwzjnnuB133NHP1ayVZSGfV3zt1auX9wcuVo899pjTYod5RNiXXnopGsuyyy4bpeOJUCjfb7/9vA/xeJ207d///veRiC0XIfKFHgrNEvCzhGyJ5mnuNtL2KW6rr766t8ZX/3q4se6666ZVj/LFXuK+gva75JJLRmWFEpVw6SLr/KxglvF5jm3Yj/6PCBCAAAQgAAEIQAAC5RHoVKh5kmVDUl6hfiiHAAQgAAEIQAACECifQCh2ys+xQihk/+tf/0rdyaOPPuqtuuWWREEi6iWXXOIuvfTSaNFvCZBycSFRV1bfZokr/8xmqZ26g1kF5sdZdeQrW76848J0IbEwq/9Sy7799tuoqcT6eJAV+Nlnn90me+jQoW22szYk9Mrq2cK1115rydT4hRde8P7KVUGi7xxzzJFaV5bAdpxDi+V4A/n3luW+PhJPZXlvx2STTTZx+++/fxsRW+2/+OKLeDcV2d53332jfi677DL3ww8/RNtpifBhiUT3pMU27byP9zF69Oh4VtHbci+TFl599dXofyB0eWIif5qQPmHChOhBQlrf5EMAAhCAAAQgAAEIFCZQUMgu3AU1IAABCEAAAhCAAAQ6ikBoSTt58mS/W4nNgwYN8ukrrrjCL2AYH49ETfnf1sJ+EuQUxowZ44VsCdsmdobtZKlt/Srf3CqEdeRjOgxmsaq8JBchEvtuueWWqEk5BhLxfUedJiRCC9o77rgjoYZz4dhVQT7Jp0yZklg3KVMLVJrLDz0EOOuss7yFe1JdHQ8tLmkhz+KWm222ma8ua/mkxR7FQz7PdYz1kV/z8KGBCeG2T8US9eU6xkKSyG9lxcYDBw50G2ywgW+m8+uggw5yaSK09iurePPvrnN6hx12aLNLG/+dd97pfZuHhXKvowcy5Qa5oHniiSfadaP+JcZb0JsRFux/Uq5rksR0uYwhQAACEIAABCAAAQiUTwAhu3yG9AABCEAAAhCAAAQ6jEC46GIoUkokVJDVtKypZX0tS1AJhyNGjHBHH310NMatt97ap1dcccUo79BDD/UuS8z3r9pJjH344Yd9nVVXXbWNxbBZWT///PN+AUGJ47K47du3b9TnhRde6N2USKyWywiNSVbL5rpDFceOHZsq9kYdBYm55por2nrkkUec9v/GG29EeWmJtddeO7Iuv+uuu7yILPcfGvOoUaO8BfOxxx7bprmESS2EGfdB3qZSsCER+7e//W2Uc/3117tDDjnEPfDAA56D+pHbFnEdPny4n7sqDxs2zMXdnUSdBImddtopEsoPPPBAp/71MEILOWoBxz/96U/uzTff9C3kPkQPIsKHCfKFLl4SjWWpLdH2gAMO8MfPdqP+inlAYO3SYp2XZtUvC3Qdf7kOkbAt9uJx//33u//7v/9r47pG1vzhsVb/yy23nN+NzvHTTz/dyfpc56t8kv/617/2/tzTxmGW3XqAoP1p7mkW1BqL2Nr5of6POOKIiNOQIUNc+L+jRVEtnHHGGf4hg46J5nbyySdHrlKsThgXM66wHWkIQAACEIAABCDQigTwkd2KR505QwACEIAABCDQsATCxSAlXm600UZ+Lssvv7wXJc8//3wvFMv6OilINJWLCQVZuMr9g/wjS1w+7LDDkpr4PLmkCIPEO4mmEqIPPvhgXySL2lVWWcX3K7/IEoglqMaDhMCnn37aZ+++++7u8MMPb2d9G29j2xLyJYxqvLKcNetZxWYNbXXDWG47jj/++Gis8tOtTzzIAl2LP0rU1iKFsn6WaCphNU/Yaqut/PhUX4Kr2uuTFsRCDxHyBM1PY9GxVd+y+NYnHnRsJKAraN5y73LPPff4NqG7D2u38sorezcz2tYxlMj7l7/8xYrLimUJf9NNN7ljjjkm8petOaSFhRZayFvCL7PMMu2q/OpXv3IPPvigz7/tttucPmGQT3OJ1ElB7nIs2AMLnXsS8pNCGlv9z8T/t2Qpr4c2Oicl1usTBvn5nm+++SLGYVmx4wrbkoYABCAAAQhAAAKtRqCgRfZss83WakyYLwQgAAEIQAACEOgwAqG7jtlnn73gfpdaaqmojixbQ1cNEubk89osV6OKsxISfyWuauG/MOy1115etE1bVE9CuaxT5SYiDBJEkxbvkxXwueee62QBHQ9asFAipsTSJKHS6mf5iladU089NXGO1j4tlmh86623OlmXx4MEyl122cWPfcEFF3SnnXZa5JNaFtT65A2a+4033ugfMpg1crytBFtZ74pFlgAfPyfWWGMNb+GbxF770DkgVzFhn7Im3n777eND8HX22Wcf/yBDc69WmH/++f089cAj6dzUfsV/u+2289zSzo0BAwZ4wVjswqC5an5aWDScd1hHYrPqpJVbXVm16yFAvJ629RBIrk9CK3e10zl/5ZVXOj0QiAedc3pQ1LNnz3iR3847rsTGZEIAAhCAAAQgAIEWIzDbrFdS/y2xWq98mo9CSyfF4mO+8xSn/ehpMY5MFwIQgAAEIACBDAJ2jxGvEuZbOoyVDrd172F5FlteGMtPrYSj/v37x3fZMtvTpk3zrg1kubvIIou4Hj16OC3kmBbEU65Ixo8f77QwYvfu3f2igHFBL619Ur4sVOV3WsdGlqfmRkF1lSfXEHJRIoG7o40n5PpB54k46X42dNmSNJdy8sRU+5JPc81VVsqy0C03iOG4ceP8oo4S33v16pXox9z2o3Phk08+8X6/NQadE2GQKw256tCxCh+whHUqkZZLkffff9/JdYvGLAvy8E2DPPvQuSU3KBLJJSyXc/5o3hKpFfSgRX69xfaDDz5wkyZNcosuuqgfZ95x6W0EuUXp16+fs4Ug87RtpDpvv/22v1bo2Im9ri2Kw3SYZ2Wao6UV23YYx9O+0n//WJswjzQEIAABCEAAAq1DANcirXOsmSkEIAABCEAAAi1EQJa8EtLyBglEEv/TLEfz9hPWkzVymkWyRK5ll102rN6h6TnnnNP95Cc/6ZB9VpqrDVoMJYzrkyfooUTWOREuiJmnv1LryOJe1tX6lBqyzq1S+wzbiW0pBjvVHlc4RtIQgAAEIAABCECg1Qikm+W0GgnmCwEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAnVJACG7Lg8Lg4IABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEjgJBtJIghAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCECgLgngI7suDwuDggAEIAABCEAAAhCAAAQ6goAWc7z//vv9rqq56GdHzIV9QAACEIAABCAAgWYmgJDdzEeXuUEAAhCAAAQgAAEIQAACmQQ6d+7sFlpoocw6FEIAAhCAAAQgAAEI1J4ArkVqfwwYAQQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCGQQQMjOgEMRBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEI1J4AQnbtjwEjgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgQwCCNkZcCiCAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACB2hNAyK79MWAEEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkEEAITsDDkUQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQewII2bU/BowAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEMgggZGfAoQgCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAARqTwAhu/bHgBFAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBABgGE7Aw4FEEAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgEDtCSBk1/4YMAIIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhDIIICQnQGHIghAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEKg9AYTs2h8DRgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIZBBCyM+BQBAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAArUngJBd+2PACCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQCCDAEJ2BhyKIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAoPYEELJrfwwYAQQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCGQQQMjOgEMRBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEI1J4AQnbtjwEjgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgQwCCNkZcCiCAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACB2hNAyK79MWAEEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkEEAITsDDkUQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQewII2bU/BowAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEMgh0ySijCAIQgAAEIAABCECgygQmTJjg9t5774J7mX/++V3fvn3dKqus4jbddFPXuXPngm2okE7gww8/dDfddJN766233Pfff+/69OnjNttsM7f22mu7Tp1Ks/W45JJL3IMPPpi+01klXbp08fvSsdxmm218OrNBnRaeeOKJ7uWXX/aj0/m4zz77pI7066+/drvuuqsvP+igg9z666/v008//bT785//7NMXXHCB69WrV2ofFEAAAhCAAAQgAAEIQAAhm3MAAhCAAAQgAAEI1JDAjBkz3EcffVRwBKrzyiuvuLvuustdfvnl7txzz3W9e/cu2K5aFY455hj3xRdfuE022cRtu+221dpNu36//PJLd+SRR/r8Aw44wK2wwgrt6hTKePbZZ93+++/fptqbb77pHn74Ybfxxhu7k08+uSQxW2PLcyzfe+899/jjj7urr77a7bfffm7PPfdsM5Z63/j888/d3XffHQ3zuuuu80L1nHPOGeWFiR9++CHiMnXq1Kjou+++i/KnT58e5ZOAAAQgAAEIQAACEIBAEgGE7CQq5EEAAhCAAAQgAIEaEFh66aW9kBrftUS+MWPGuBEjRjgJgRJLJeZK0J599tnj1Ttke9SoUW7s2LFuiSWW6JD92U6mTZvmXnjhBb85bty4ooXsmTNnOonwFmRNvPDCC7t77rnHSYiWmC2LYQn05YSddtrJzTfffO26mDRpkhM7fRQuvPBCp+O+7rrrtqtbrxkPPPBAm6HpnJQwXy6zNp2yAQEIQAACEIAABCAAgRgBhOwYEDYhAAEIQAACEIBArQgsu+yybo899kjdvSxhhw8f7sXs119/3b366qtu0KBBqfUpaE/g448/9oK1Srbeemv3hz/8wVeSVflWW23l0xLKyxVlt99++1SL+X//+9/uoosu8g8itMNrr722YYRsPQi4/fbbPachQ4Y4WbLrAcAdd9xRNjPfKX8gAAEIQAACEIAABCCQQqA0B4ApnZENAQhAAAIQgAAEIFA9AgsttJDbYostoh2MHj06Sicl5LZEwmMxQRbPalfpoH5LdR8h4VfuKSoR5M7Cwuqrr25Jt+iii7oFFljAb3/zzTdRfjUSs802Wxt3LC+99FLRx6mYcel4VoqfxipLfAX5+N5yyy19+rnnnnN6SECAAAQgAAEIQAACEIBAtQhgkV0tsvQLAQhAAAIQgAAEqkBgzTXXdLfccovvWYsUxoNEWPksfv75551Ex27durlVV13VDR482C8SqUUj40FWtVr48KmnnoqslSXqrrTSSt4CfLXVVvNNZBF+0kkn+bSJmVrc8NNPP/V5Bx54oOvfv79PSzwdOXKku+222/yCirLaVbDxbLfddm6NNdbwefbn7LPPdvIfLXcfm2++uXv00Ufdk08+6T8a/5QpU/zCjFb/4osvdvfdd5/3Z33GGWfkcrMiwdqC3ImY5bVY2RiXWWYZq1K1WA8l5FLknXfe8fvQAwctMvnBBx+4M8880+dpYUTViYfXXnvNae6qf+yxx0YCvKy8ZamvBSslMl9//fX+PHjmmWd8F0suuaRnq4UXS10sVD7aFXQcZZEtP+3y9f3/2TsTeKum9o8vSihDKSolU4VQSsYSkSFzJPISUcmUOZlCeJGpV5J5+huSDCVFZaZMGfIqIpnSrPIaKuHvt953Hevsu/c++9x77r3nnvN9Pp/TXvNe67vP3d37289+lkzXom/fvjbNPxCAAAQgAAEIQAACEMg1AYTsXBNlPAhAAAIQgAAEIFCOBObPn58avXXr1qm0EhIxFTvbicwqc/GLFcNY4R8kdjrPY9W//PLL5oILLlAyzSTqSkjWR2Mq9Ia8mSdPnpzWTuO7smOOOcYK2RJlr7zySjNu3Li0tsr489Gmivvvv3+qzfvvv2/XIPH21ltvNQ899FCqzj+PK1SscLe5ojy+k8QLX3fddc0RRxxhw2NMmTLFMtlyyy3NWWedZYeVQOtCjLjzlMdRjNx1kiBcvfp/fy3XgwjH88QTTww99bJly1JtlixZkrqeeiChvrVr1zYSr3XNfdNDgttvv918+OGHlq9flyT9448/pq5p586dzVprrWW22mor06RJE3sdFHKkV69eqbUkGZM2EIAABCAAAQhAAAIQSEoAITspKdpBAAIQgAAEIACBSiawaNEi623tpqGY2s4kbsobVoKvTIKiPKp//fVX8+KLLxp5TkvIVPmjjz5qRUh5Tfsidr9+/WwfiawSlSV6yq699lq7AaK8iNVG/YYNG2br5L28zz772PQmm2xij2PGjEkJnhKlO3XqZLbffnsrcL722mupNTzwwANpQrbt/Nc/kyZNSom8EpbVV2Jvq1atzOLFi82IESNsU40rIVWWRMS2Df/65/TTT7cbZ0qsl5jum7zC11tvPb+oXNLymnfXynm85+pE7gGC2Hfv3t3our3zzjtm1KhR9pwSuxUKRJ762diECRNSzeU170yxxocOHWo92vVwYI899nBVHCEAAQhAAAIQgAAEIJAzAgjZOUPJQBCAAAQgAAEIQKBsBORt7bxx3UgSleUJq3jYTohUXdDzdfjw4SlhVJ7MLVq0cENYEbply5Zm8ODB1nNWXtYK3fHZZ5+l2kig7tGjRyovEVyeyuedd54tkxfv3nvvnWrzzDPPWLFZ5+nZs2eqnxIKUSKTgHrvvffaMBS24K9/2rRpY+cp712F1ZDQvvbaa7tqe3SeyqeddpoJhsEQIydkd+zYMVQITxssJKPzaZPMiRMnpmoVIkPhSVxolFRFKRPaMPLrr79O6y2Pdgnx4i8hWSbv+H333TetXS4yCi+i612jRg07nMK46Jqee+65Nq9QKtkK2QoTI9N11UMFZ5q/hGyZvhcI2Y4MRwhAAAIQgAAEIACBXBJAyM4lTcaCAAQgAAEIQAACZSCgcBAunnHcMP379zeKMe1Mnr0SuWUSo30R27VR+7Fjx9rQHRIkJWTXqlXLVRt50ip8iF8mL2idS1a/fv1U20wJxeFWX3kay6M6aAp94UziblDIVt3JJ59sTjrpJNcsZ0d5pZ9//vmpkCRuYIUcUYgMmTaXdN7SPg/XNslx0KBBGZtJbD7nnHOyYptx0P81kGDtRGzXR/HVdT20NhfX3NVlOs6YMSMVz1vxtxWf25nijkvY/uijj2w4E8VSl9iNQQACEIAABCAAAQhAIJcEELJzSZOxIAABCEAAAhCAQAUQ0AaIhxxySEoA9j1/5cEd9Op2U6pXr55NSnBULOZNN93UaANAibvyEO7SpYvdDFACtMRweQt369bNdU98vPjii9PaShhWWJTZs2fb89x///1p9WEZxdvOtUmMPeWUU1IitdKal4R9xZeW+KxQI/JUP+644+zpFf5ku+22y/VU7HgK3zJr1ix7HXJ5Al03J8r74yr8isq1VnnCZ2PaGNOZ2yDT5XU8+OCDrZCt9Pjx460nvdIYBCAAAQhAAAIQgAAEckUAITtXJBkHAhCAAAQgAAEIlJGAvKSdB7Q/1IoVK6zYfPPNN1uvWAnVd955pzn77LNtMwnEzhR7WZ9MJgFX3sZXXXWV3cxRmyYqZrTiZ+sjc/Gt5c2dbdxojaVY2RLIk3iZ+/NVmA95defSVq1aZS6//PKUiH3bbbcZhdtQvG+FK9HDAcWAbtq0aWrzRJ2/tPMQQ3kq+yZBf+HChTY+t+KPyzNa11vn9Tfg9PuUJu1ilZemb1gfid4jR45MVXXt2jWVDks8/vjj5vjjj0/z2g5rRxkEIAABCEAAAhCAAASyIYCQnQ0t2kIAAhCAAAQgAIFyJFC9enWzzjrrlDiDyurWrWskvu6///62XjGmnZAtkda3sHAefr3S8siWabNEia6vvvqqef311402Y3RhNRTDWp8HH3zQyItaMbOTmERhNzfXXuK0+ksoVugJhTmJssaNG0dVlbpcXujyPJf17t3bithKV6tWzVx99dU2JIvEfAnMTlQWx4YNG6pZ1qaHBGHXUiFM5AWvuOfugYO4a8PEpCav+zjT9yiX9vLLL2c1nK6vvM3btm2bVT8aQwACEIAABCAAAQhAII5Abn/LjTsTdRCAAAQgAAEIQAACZSIgMXvPPfe0orPE5qVLlxrFm/bDSNxxxx1ZC4hrrbWWFcglkkskVagSxcyW0CpRUue68sorjTaRzGSaky9iywt6r732MhJwnclTO07I9tu6PmU9KoSHs+BmhBKcb731VnPsscfatcqbXCYPeT8WtOufi2Pnzp1TQrY/tyRju/klaZuLNk8//XRqmMsuuyySybfffmvuu+8+21bXGCE7hY0EBCAAAQhAAAIQgEAOCCBk5wAiQ0AAAhCAAAQgAIGKIrDNNttYIVvnk1dvUMj+97//HSkgvvTSS3azR8VKVnzoDz74wIb+WG211UyvXr2MjhJuN998c/s54ogjzKGHHmpDjkyfPt2KvJm8vdXOmWJlK5Z30BTKo6LNjwkd5tEsL/AhQ4aYPn36pKYmAb68TIydSfx35ntT++WuXkfF8K4o00MNfU9k++67b6znuN4MGDFihP2ejBs3zpx33nlm/fXXr6ipch4IQAACEIAABCAAgQIn8Pd24wW+UJYHAQhAAAIQgAAECoFA/fr1U8tYtmyZTSsUxo477mjT8ohV/OugybNa8Zi1eeG0adNs9XfffWfuuusuG2/bF6BdX3lqu3FV5ousro1iTPs2b968VDYsRMiSJUvME088kWqjuNGlteC548bx40b7HsZ+H3/uKldM8p9++slvkrN0jRo1UiFMfMHahTXRiRQ7O2hz5841ikFdUeZ7zoc9lPDnoe/H4Ycfnip64YUXUmkSEIAABCAAAQhAAAIQKCsBhOyyEqQ/BCAAAQhAAAIQqEAC/qaLvmfzmWeeaWehMCAKkSHv68WLF1uv7VdeecVccsklqVm6eMytWrVKlZ1zzjnW03v58uW2TN7eisM9ceJEm99pp52MxFdnLvzHe++9Z7T5pMTxlStXms0228w1McOHD7dhSiRWKxyG5nTiiSfatGs0Z84cG87E5TMd11577VSTSZMmGZ1/xowZqbKoRPv27VPC8ejRo82gQYOMQmFozh9//LGNPz5w4MC07oqpfdFFF5lgDPK0RmXIyJteJq9nZwof48Rsrc+Fd9H1UPzyE044wTUt9+Nvv/2WEs3lib/zzjtnPOcBBxyQajNq1KhUmgQEIAABCEAAAhCAAATKSoDQImUlSH8IQAACEIAABCBQgQT8DQS1oV6nTp3s2bfbbjtz+umnm2HDhlmhWN7XYdalSxez33772SrF1u7bt69RXG0JzQoFEWWnnXZaWlWzZs3Mp59+aiRE9+vXz9YpznSbNm1szG5tnCiB+Mgjj0zrp8zuu+9uxW+le/bsaS644AJz9NFHK5vRJORL6NV8JezqI9MxLuyJRPgrrrgiNVfFcNYnaPJA1+aPErXfffddGyt88ODBRmFScm0u7IYYLly40Gy44YY2tIvCvOicMoU70cc3MX3yySf9onJJK0662/iza9euoR75wRO3aNEidf31IOCTTz4xDRo0CDYjDwEIQAACEIAABCAAgawJ4JGdNTI6QAACEIAABCAAgdwR8MN1KHZ1Jttyyy1TTUaOHGk9rl2BRGGFCpGYGDSJvxJjBwwYkFYl0VSi7RZbbJFW7jISyh955BGz/fbbuyJ7lADeoUOHtDJlFI5k6NChRh7QQWvUqJEVaCV4b7311sHqVN73/E4VeonrrrsudI1ek9CkBHR5Ccu7PGgS9Xv06GHnLkH5+uuvT22iKc90fTKZP+8k17Jly5apIX3vZYnGYQ8ixE/XMEr0d+f055E6QSkS48ePT/XS5pRJTXHVnQXDo7g5qj7b774bkyMEIAABCEAAAhCAQHESWO2vV1L/1MY+euXTxSh06bCjMLkNcnSM+qOnOHGyaghAAAIQgAAEwgi43zGCdX65S/tHpf28fvdwZe7oyvzjF198YerVq2eaN28ePGXR5BUWQiEr5FHbsGFDo5AV2sgxysRToUgUX1sbIyrsheJxx3k5R43lyuU1rbjTujba3LBWrVquypZp00KFKJFAq99HK9JWrFhh9D0RJ/0+64dsqch5xJ1LIU2++uor+7BCIVtcyJG4PtRBoCIIzJw5094r9GaG2yRWRz+t+40rc0fNzaV1dHn/GEzbRv/7x/Xxy0hDAAIQgAAEIFA8BAgtUjzXmpVCAAIQgAAEIFBEBOT52rRp08QrlkAk8V+fXJmE1yjxVSLXNttsk6tTZT3Ommuuabbddtus+1VkB3ksZ3MNK3JunAsCEIAABCAAAQhAAAIVTSDaLaeiZ8L5IAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIhBBCyQ6BQBAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAvlDACE7f64FM4EABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIEQAgjZIVAoggAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgfwhgJCdP9eCmUAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgEAIAYTsECgUQQACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQP4QQMjOn2vBTCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQCCEQPWQMoogAAEIxBJYuXKl+fbbb81XX31lP19++aVZvny5ady4sf1ssskmplGjRqZhw4amenVuM7EwC7Ry8eLF5uuvvzazZ882+n7MnTvXrL/++mnfD31HateuXaAEWBYEIAABCEAAAhCAAAQgAAEIQAACuSSAwpRLmowFgQIm8Oeff5qJEyea66+/3rz00kuJV9quXTvTvXt306VLF7PxxhvH9pP4efLJJ8e2Ka/KevXqmXvuuSc1/FtvvWWuu+66VD4scfnll5vWrVvbKvG58MILzcyZM8OappXddNNNZsstt0wry5T5+eefzUknnWRWrFgR21Tz0bwqw+bPn2+GDx9ubr75ZvOf//wn0RTWXXddc9xxx5muXbuaPffc01SrVi1RvzfeeMPceOONkW179OhhjjjiiMj6slRMmzbNDBw4MHKI3XbbzX4XIhsEKvRQaMaMGeaLL76wHz0g0gOgmjVrWvG/adOm5swzzwz0IgsBCEAAAhCAAAQgAAEIQAACECguAgjZxXW9WS0EsiawatUqM2rUKHPttdcaCXjZ2ptvvmn0OeOMM8yAAQOswBflhSuv7tGjR2d7ipy0lze5b++9917GuWhNzlZbbTUjIT7J/MV07Nixrmui41VXXWVGjhyZsW2vXr0ytsl1g1mzZpkhQ4aY2267LeuhJXhL/NanZcuWdpyOHTtmHGfKlCmxrNu3b59xjNI2yHSda9SokWjoZcuWmSuvvNLccsstse2bN2+OkB1LiEoIQAACEIAABCAAAQhAAAIQKAYCCNnFcJVZIwRKSWDRokXWS3b69OmlHCG9mzychw0bZiZNmmR23nnn9MoCyMnTWgL1ggULYlfz3HPPmaeeeiqxx/AHH3xgPeFjB/2r8sQTTzQHH3xwpmY5rZcAfdppp+VkTD0o2XvvvU2fPn3s96SQw9K88sor5uijj874XYkC+8ADD9jQLVH1vXv3zvgGRFRfyiEAAQhAAAIQgAAEIAABCEAAAvlIACE7H68Kc4JAHhD46aefzIEHHmhyJWK7JckDd5dddjHjxo0znTt3dsUFcZSn+f/93/+Z/fffP+N6Tj31VLPvvvsahdaIM3lvJ/Gy3mijjWxIj7ixcl33xBNP5EzE9ud21113mTlz5lgPdIXXKDRbsmRJmURs8dD3LC7Ez6GHHoqQXWhfHNYDAQhAAAIQgAAEIAABCECgyAmsXuTrZ/kQgEAIAW3mqJjF7777bkhtbookkismcKHZfvvtZyRSZzJ5bStcSCYbOnSoef/99zM1M/LQrVOnTsZ2uWogr/pu3brlargS48hr/YILLihRXggFCrGTyWu/ENbJGiAAAQhAAAIQgAAEIAABCEAAArkkgJCdS5qMBYECIXDKKaeYF154odxXc/zxxxt5HBeaaUPMYMztsDXecMMNsXHHZ8+ebc4999ywrmll2iCzIr3bP/74Y+tNnjaJcsjcfvvtZvz48eUwcuUNKU9zeZxjEIAABCAAAQhAAAIQgAAEIAABCGRHgNAi2fGiNQQKnsBnn31mvXuTLHSPPfaw4UcaNGhg5MU9b948K8w++eSTSbqbt956y4ZHkBdzIZnChTz88MNmr732yrgsPTTQZpirr57+XPHPP/80p59+esb+Cily4403ZmyXywYS4JOYOChu99Zbb23WWWcdo5jr33//vXn88cfNd999l2QIc/nll1eoSJ9kUvXr149tttlmm0XWz5gxI7LOVbRp08YoNMjaa69tFIpHRwwCEIAABCAAAQhAAAIQgAAEIFDsBBCyi/0bwPohECBw//33B0pKZiWePv/886Z169YlK/8qmT9/vhkyZIjR5o6ZTIKvE7Lr1atnunTpYpYvX56pm63P5K0rIbV9+/aJxtKacml77rmnOeecc8wtt9wSO6zEfDGXV7VvI0aMSOSNrFjJis1dUbZ48WIbnznT+S688EIzcOBAExbjevDgwebVV1+1sb+//PLL2KEU3kYPV7baaqvYdhVZ2aJFC6MHDaWxTz75JLbbTjvtZCZPnmwKeaPLWABUQgACEIAABCAAAQhAAAIQgAAEIgggZEeAoRgCxUogbgM5x2TKlClmiy22cNkSR3msXnvttVaMu/rqq0vU+wUSYiXkVqtWzay55prmqaee8qtj06uttlpsvURBbSpZWaa1jx492mQSayV4ywN3ww03tFOV57I8tTNZ3759Uw8BMrXNVX2SuOlnnHFG7EMMeZ937NjRvPjii3bjz0zxoseOHZtXQnZZWGaKC69wO4jYZSFMXwhAAAIQgAAEIAABCEAAAhAoVALp77IX6ipZFwQgkJjAp59+Gtv2kEMOiRWx/c6DBg0y8l7NZAsXLszUpErWyxv5kUceyTh3hY/QBoDOtMmhyuJMMbgVi7uiLUlIEIUTSWIKwXHnnXdmbPr1119nbJO0wYoVK8ysWbNsCBx5ev/6669Ju+akXaaY8ArTk08mz/OlS5eazz//3Cg2usIH/f777xU+xT/++MN8++23Zvr06eann36q8PNzQghAAAIQgAAEIAABCEAAAhCofAJ4ZFf+NWAGEMgbAhL5Mgmom2yySeL5ymP64IMPtuJTXCeFIsk3AS9uvtnU7brrrlakzhRm5b777rPxpHUNHnjggYynUJv11lsvY7tcN1CM60zWpEmTTE1S9QrBksmSiOdxY8jDXaFa5Pn//vvvl2gqz33Fe9eGmZ06dSpRHyz45ptvTFwc+KZNmxo98JH4qtA5CsfibOrUqS4ZenzuuedKxA8Xo2nTppklS5ak+mR6c0JvOrzyyiup9kooZntUOCC/oYR+ecFrja+//rpflUrrQcoRRxxhunfvbr3qM70d4TpqvPfee89l047idtBBB6XKFGJID4L0sOODDz5IlSshHptvvnlaGRkIQAACEKg4Avr/cp999jGnnXYa9+OKw86ZIAABCEAAAkVPACG76L8CAIDA3wSCGw7+XfN36o033rACXZK26iXxbPjw4X8PEEhpI7v1118/UFpYWW1YOGbMmIyCfteuXRMtXH806o/HyrAkgqViPB922GGJplenTh3Trl07K0xGdWjevHlUVcZyhaqRh3jcAxqFS9Hn5ptvNvvvv7+59957TaNGjSLHltB77rnnRtYfddRRVsiWEHvCCSdEtgurePDBB0sUK954tt73YbHZ9b0ZNmxYifFdgR4Y6LuqhyqZTG1vvfVW+9FbF5p327ZtM3WzIWeiYtsrXJETsvXzcuqpp5qosDOV4RWecXE0gAAEIFBEBPSWjB6q69OvXz/Tv3//0H0xiggJS4UABCAAAQhAoAIIEFqkAiBzCghUFQJrrLGG0QaJcSZPSAmD8nJNYvJy/fHHHyM/8sZWiIlCtrXWWss89NBDGZco0S5KuHOd5QmbybvbtS2P48Ybb5xxWMV5lkdvUtPDkbjvSGnXe8UVV5gjjzwyVsQOzvGFF14wHTp0MHPmzAlWVVq+tBtLBiccN448uPW2RRIROziuwn3Iq10iuLzQy2rywNZ1y/SzUNbz0B8CEIAABHJDQA82dd/23xzKzciMAgEIQAACEIAABNIJIGSn8yAHgaInsO2222ZkINFLGxP26tXLTJgwocLjDGecYB422HHHHY2E1bKaQlVkethQ1nPE9d90003jqm2dvJ8VWqNVq1bWA1gezBVtCiNy5ZVXluq02pyztH1LdcJK7CRxe+DAgaZHjx5lnoVi4p933nllGufRRx81p59+epnGoDMEIAABCFQ8gbfffttuXK23kTAIQAACEIAABCBQXgQQssuLLONCoIoSUFiEpKYQDArFoE0NDz30UPOvf/3LfPTRR5WyGVzSOVdmu4suusi0bNmy1FPQq7tJYkqX+gQJOrZv3z6xkC7v/TPOOMMo9vFWW21lzjnnHBti5YcffkhwprI1kZdwWezuu+82elug0E0hSK666qqcLXPIkCHmn//8Z6nG0wMEROxSoaMTBCAAgbwg8Mknn9i3c/JiMkwCAhCAAAQgAIGCJICQXZCXlUVBoPQEjjnmmFJ1fvbZZ83ZZ59t6BflxgAAQABJREFUdthhB6O4x926dTN33HGHjX2ci3ADpZpUnnWqUaOGkTd7aUzxg0srEJbmfFF9FCZFsZaztZkzZxqJnIqdXbduXSMP9QEDBhhtblgRwna281V7idllsSTxxJOMr3Ay5WGvvfZamT2ow+Z1ySWXmH//+99hVRnL4mKZZ+xMAwhAAAIQqHQCd911V+SmvpU+OSYAAQhAAAIQgECVJ4CQXeUvIQuAQG4JKAbyuHHjyjSoxKgnnnjCbtam8BK1a9e24udnn31WpnELobM8sq+99tqsl6LN9GrVqpV1v/LooBAS2sSzLPb+++/bDQwPPvhgK2zL01si/8qVK8sybGjfPfbYwz4EePLJJ81jjz1mtHliElN4krKYNjL9+eef0+J/K354nImBHy/8p59+sj87fpnSWlOcvfLKK2njqI82s3S2atUq07t3b5eNPGrzLj2k0uaOeuCgTTHlWZ/JzjrrrExNqIcABCAAgQIloAfXGAQgAAEIQAACECgPAtXLY1DGhAAEqjYBbdA4dOhQc+aZZ+ZkIRK2hw8fbj/y1JYnbuvWrXMydlUc5PzzzzdPPfWUFQWTzP/cc881EnrzxeRZPmrUKLPzzjsbhYPIhb355ptGn4svvtgoBIs2FFXImrKavNglXK+++t/PbfXWQffu3c1+++0Xu6Gg1qa3Cfy+2c4nuIZMDyPUPiwGerBMG7PG2XrrrRc6jusjUV9e8lGm88lbPiiYt23b1uijUEIdO3aM6m5eeuklez3btWsX2SZJRbNmzcxuu+1m2rRpYzbffHMjYf/rr7+2Dz+S9KcNBCAAAQhUPAE9ANX/oQothkEAAhCAAAQgAIFcEvj7L/tcjspYEIBAlSeg2Ma52JwwCGLkyJFWlNKmcPIKLUarXr266dChQ+KlS/zPN1N4EHnut2jRIqdTk+ev4iQrprbirZfF+vbta0XxMCFabwpok8NMlq9hTzLNO1P94MGDY5uMHTu2hIjtd5BHvh5IxdmIESPiqjPWKQa/4q0qxIuupeLxH3HEEUbe3htssEHG/jSAAAQgAIHKI/Dyyy9X3sk5MwQgAAEIQAACBUsAIbtgLy0Lg0DZCVx++eXm888/N9lsAJn0rApzcPjhh5vffvstaZeCaacQKzfddFPi9SgmdT6K/k5svueee8xGG22UeD1JGkrQVrz1SZMmJWke2ubUU08NLXeFRx99tEtGHgtxw8fvv//eKLRLlOmNjCQPWuQ5H2cKh1Oan295g7/xxhumR48eccNTBwEIQAAClUigQYMGsWd//fXXY+uphAAEIAABCEAAAqUhgJBdGmr0gUAREdBrofKiVtiH4447LqcrV+gCeWYXk0mQPvnkk7NaskTHG264Ias+aqwN97ThYGk/9evXz3hOeZdrPbNmzbJzVAzwXJo8cL/44oush5SneKa51KtXz2gTzTgrRCE7k5dc0gdXCl8i0TvKFFJID8KyNQnku+yyS7bdqnT7xYsXW29zfd/jPvpZu+qqq2zYl99//71Kr5nJQwACVZtApoeNEyZMqNoLZPYQgAAEIAABCOQlAYTsvLwsTAoC+Udg9913t5vxLV++3LzwwgtGoUdy4YWrWNzPP/98/i24nGZ022232YcC2Q6v2NESprOxefPmZdO8RNsFCxaUKIsqWGeddYxifysciOJiap177713VPPE5RJDjz322MTtXUPFVk5ijRo1im3266+/xtZXxcpMIVtOOukkI5E6yWf8+PGxCD799NPY+rDKbB/0hI1R1cokSn/zzTcZP7p2o0ePNnpbRg8c5syZU9WWWlTzfeedd8wpp5xiwyXpXoZBoJAIKNxTnGlPg3x8myxuztRBAAIQgAAEIJD/BNjsMf+vETOEQF4RWHPNNe0medooTyK0vGVfffVVu7mbNvcpzR/rCjNywAEH5NU6y2MyCilyzjnnlHroE044wbz99ttGXtD5bNqUT3Gu9fn555/NlClT7HdEMbXjQlpErendd9/NeuPAjTfeOGq4tPKGDRum5Yshk+QBR2l+jsPYzZgxI6w4sqxnz552I8c///wzsk2hV+ghzL777ltimRKEFHLnlVdeMb/88osVveW9rljimTb/LDEYBRVCYOnSpWbq1Kn2XLoXBjdtrZBJcBIIlBOBTKFFdNply5YZvf2EQQACEIAABCAAgVwRyG81JFerZBwIQKDcCCj0iD7yolQ83MmTJxsJ2o8//rgVXZKceOLEiVYQL+Td7eVxWVZPUxdiJFNs4iTMK6pNrVq1TKdOnexHIRHkQSpB++mnnzaZvHn9OWrDv3bt2vlFsekkf2BrgJo1a8aOU4iV2Xjal3X98sjLxpo3b55N84Jsu8022xh5xUeZrl/Xrl2tmD19+nQzbdo0s+OOO0Y1pxwCEIBAuRDQQ/U6deqYJUuWRI6PkB2JhgoIQAACEIAABEpJgNAipQRHNwhAoCQBeQXuueee5sYbb7QxkwcPHlyyUUSJvJUL2UobUiTIRCFGPv7442BxlckrlEfv3r2tmC0BLqk4ne2ai1GgTvolyFZcTjpuWLtsPaszhXoJO0exlSmk00EHHZRadqYY8nqI9scff6TaJ02oT2nicJf2fG5eK1euLNV59V1T6KtsrTQbkuoc6lcartnOj/YQyGcCcSK25q2fZwwCEIAABCAAAQjkkgAe2bmkyVgQqMIEFB6kW7dukSuoXbu2uf/++41iZSexGjVqmAsuuMDGcVUcxZkzZ8Z20yvzhWoS6c8+++ycLe/EE080b731VoWHEzj44IONwnxE2SGHHGLuueeeqOoS5dtvv7157bXXzE033WT69+9fot4vKM2mgX5/0n8TqMjXvHUfyMaShoTJZsxCbLvbbruZJ554wi5txYoVJZaoMBYPP/ywee+998wHH3xg3zzYaaedTNu2bW0YJ3lRhtnChQvNY489Zh+WqZ9MwnmbNm3sZr9bb711WDfz1Vdf2fnIQ9w9dGrVqpXZdtttzTHHHGPCrqvuiRKCdT/TAwy9xaOY0i6uuu4Pxx9/fIlY+y+++KKNE77hhhuayy67zL7Zof+/9DaQQq5ovnpApn0c1l9//dD5fvvtt+aRRx6xMf11b9lggw1sH8enWrVqof20T4HeONJDOHdPatKkidlrr73sOt2+EQ899JBl74fx0Zs0Ci2iN4/69esXOj6FECg0AtprAYMABCAAAQhAAAK5JICQnUuajAWBKkxAISDiQg6o7vXXX08sZDsUm222mbnjjjtKiBGu3h39P/hdWSEcswkpMnv2bCsWvfnmm7FLdyFG5J0dZ6uvXraXboLxXDVe3HdEsXpvv/12k414qTH1wEPikL5fUaaYzfK2XGuttaKaUJ6QgBPbopofd9xxpkuXLlHVWZUrln42hid9Mlrz589PNWzdunUqrYTEZImm/kaQEngl9uqjsD66J0u89U33lQEDBpgffvjBL7Y/89qQV59zzz23xOarY8aMMYMGDUrro4w2ptTnmWeesZtT7rPPPmlt3njjDZvfYYcdzJVXXpk2X1VIENcDLom+PXr0SPWdO3euFa31Pf6///s/869//StVp4TuUVqj1jpq1Ci7aanfQKGNBg4c6BfZNesepI9i+ms+QTF75MiRJuwtI23SKeFan/vuu8+0bNnShsqSsO6bE/gVNxuDQCEQ+PHHHzMuI+phUsaONIAABCAAAQhAAAIRBBCyI8BQDIFiIyDvtkymP/BLY/rDPpNJSC9ESxpSRAKwRH/Fgm7RokVGFJdccomRB7S8FqNs7733NtmGdogaS+VJ4k5/8sknJiisxY3p6iRmxQnZapeNQO7G5ViSQJh3rN9KnrRHHHGEX0Q6jwgsWrTIelu7KSmmtjPFo+3bt6/1TFZZr169jH62fv31VyNPZonRX375pS1/9NFHUw+Gvv/+e9OnTx83jDn00EONPLj14EiCs/YxkBiujXkVx1yeyzK9UeGL2Mcee6zZeeedbWgQCblPPvmk7XfhhRfatzU0l6Dp3idTLH3ds3TOSZMm2fBDKr/11lvN4YcfXkKQlmAtEVsPP7TmLbbYwgrITz31lN0IU4L8iBEj0taljRediC0hX3zUT2OprR4CiJHCZF1++eU6vbUJEyakidiKYb7ddtvZjexefvlly0EN5QU+evRouxZteiuvdidoa7PeddZZh43v/ouUfwuAgHt7Im4phfq7XdyaqYMABCAAAQhAoHwJIGSXL19Gh0CVIZBEyNYf6LNmzTJbbrllVutyf8jHdUoiksb1z8c6vXqeJKSIXoN3IpJEKXkD+iJK1NoqOsRIkmskj8ShQ4dGTTmyXN6Tcda4cWNTVg/zuPGLqS5TeCCFTcAqj4C8rYP3TIXgkPej4mHLy1iiskxCrDZcczZ8+PBUnTyE/YdiHTt2tN7C8iqWF/FLL71kDjzwQNtVb1M4U7iOww47zGWN+imUiby1Zc8995wVshUjWmGBnMnL2wncKtN+Cep3/vnn2yYSwR944IHQn+PTTjstbYPLDh06WI9xhUeRSTCTQB40idES5F24nF133dWuyb0J8Pbbb6furatWrTLXX3+9HUKhTMTH9xZVCKxLL73UivbyzBZbtVO/YcOG2X4SzbVOn6seKGpchXrRddG1UwxzrUH93bU86qijEj0MDK6RPATylYB+9uJMIYkwCEAAAhCAAAQgkGsCZXvvPNezYTwIQKDSCOgP9CQb70n4yLS5j78ICTB6/TuTySuukEwhRXr27JloSfLC9l9j1+v08nrMZC7ESKZ2uaqXMJPJ5IF+5513ZmqWVi+vxUziqe91mtaZTCiBuJ9RiYtxpp9Xee0mMX0H69evH/rReSQCYtkRkPiqcBr+Rw/E5Eks8dWJ2LpPnHLKKanBVS6RW6ZQHL7Y6hpJTHXl8paWyYtbDyll8sb3RWxb+Nc/8pRu3769FWZdeCHF6XfhS+SJ7YvYrp9iRx9wwAE2K29nxZgOmkKEKBZ20Dp37pwqkhd6mMkD2onYrl7itkR0mWJhO1O8cPe9VjgjX8RWG92DnViv/NixY3WwoUbcOhV2x/Gzlf/7R6K3YmVLuHZt/XrSEChEAuPHj49dlh6CYRCAAAQgAAEIQCDXBP5248n1yIwHAQhUOQL6Iz1TfGZt2igxW159e+yxR+waFQtUgoq82+JMsZjDvO3i+uR7nV6Xz8RSa7j66qtNUKTVq/USt50YE7dWhRjRJoxJwrfEjZOkTqKUrpXiVceZXvOXkCqRLWpTOddfAprCBmSyJG0yjVFM9YpNLPExzHQN5UUa93MpEdUJeWFjqEziYu/evSPjpu+yyy5p3sJR41BeOgIK+aHruPbaa9sBvv7669RAeoDoPIFThf9LOOFX3xFtCulvtBsmYqub3oYYMmRI2lDa4NGZQpFEmcLUKFyHTH2C9yp9TxTKI2gShZ0pNEqYRYUxUpgmveWhuPrOnIitvDbIjOIjIVxhSXT/1j3M5yqv7TCrW7euUUgTDAIQ+JtApt8R/25JCgIQgAAEIAABCCQngJCdnBUtIVDwBCQ4nHrqqRnXKU88eecqhurJJ59sQ40o7q4EFXkFKqSGRDBtjpVJ9NTJFDvUfz0+4wTyvIFe/5cQmMnk2SfPwDATX4mEErQzmTy/dU3CxKBMfbOp1zVSCAD3en5cX202p88555xjNwiVt6IEIgliCxcutDFlJWInEft1niiBLW4OxVyn0DS1a9e2XrJuI1fF9FWMXpk8T+OEbIWPkCetYhBvtdVWaSgVd13xliXy+eJgWqO/Mpk2Iw22J/9fAnpQKG/roEl8FW+F6NA9VkKs3n5w4Yu0WawzheRwYTlcWdhRDyN8D2KF8ElqvpAd18+vU0iToDVs2DBYlDivtwGSmsJiOVPM7kzmvMB9r+5M8eUzjUk9BIqFgMLV6S0ODAIQgAAEIAABCOSaAEJ2rokyHgSqMAG94q3QEHpdO4m9++67Rp+ymgTPQjGFFNFGYEns/vvvj93A8LrrrrMbkGV6GKDwDvKQl3d2eZvEyUceeSTNizPunLfccovRpywmsd/3zizLWIXSVxvJxZm+M8Hv4XnnnWduvPFG201xsuWxrTjJUfbCCy+Yrbfe2sgTX28NSHBUWAlt8JcpFIz6KF4xlj0BPTByDxz83iqT56/u0c4zWF7ATsgOhnFRuKhMJo9s//6it0GSmry+ncU9RFtzzTVdszQPaVdYltj32fRVTG9nSdi4NSk2uTNX5vIcIQCBcAJ6GMcGzeFsKIUABCAAAQhAoGwEELLLxo/eECg4AvLIljgSJ3DlctHaGLCQvNy02drrr7+eEdG5556bMZyKPJjvuusu071794zjaZMyhRkIvrafsWOWDdZbbz0bpzcqbEWWw2VsrocrWhuWTkBvQ/gb9KXXhudcbGVXqwcp8tL2hUxX5x9feeUVo082pg0DsfIhIDFbYYcUOkPXVCGc5H2vtx6cBTdedOVhR/V3prclokx1CrkhMVd7Gvj37blz5xrf89ofw/f49ufot6mItMKNOJs0aVJikc1fl2PtxvGPCkGiUCa6Ftl4ivtjkIZAIRDQz5pC1WEQgAAEIAABCECgPAisXh6DMiYEIFB1CcjDTZuAVURsQ3naJvX+rgpEFVLkzDPPzDhVCSNXXnllxnZqcMwxxxh/07O4Tgox4nsdxrUtS502cBoxYkRZhkjUVyK24gBLPMfSCbRp0ya9oBQ5iYqPP/54KXrGd5HHcEU96IifSeHW+nH1ncewLxKHbaroaOghpb8pqy/URsWNVjgZhUv6xz/+YU488USj/KabbuqGtKGNUplAwh/Tn2OgWblnfSH7008/jTyfNtQUHxd6Z5NNNkm1feedd1JpPyGR/8gjj7R89HAWg0AxE9BD1iRvPRQzI9YOAQhAAAIQgEDpCSBkl54dPSFQsATkUabNufSHeXmZYvgmibVcXufP9bjZhhQJCx0QNadhw4ZFVaWVK8RIRTE9+uijjUJPaOPA8rDmzZvbEBbNmjUrj+Gr/Jg77LCD2Xfffcu8Dj0kmThxYs6uo95IOP3008s8LwaIJ+B7/C5btsw21hscO+64o03fd999djPO4CgKDaNX/h944IFUeBiF7XGhe/QQMyyO9ZQpU2xcbo2n791qq61m90hwYtWtt95qvbWD5/v++++NvMNlml95vzESPL+fb9u2bUpc0z01GIpFbeXlrrWIz+LFi213f0NJvcUQtvGk9oNwprA9YeaHYgmrpwwChUBAP++5eNBaCCxYAwQgAAEIQAAC5UMAIbt8uDIqBKo8AQkUo0aNsps26jXyXJlCIkydOtVcccUVVgzJ1biVPY7+eEsSUkTejJ06dcpquoqHfNNNNyXqo5AOmeIXJxooQaP99tvPbj6nDSBzaVdddZX56KOPSmwymMtzVPWxFN7h6aefzsmbE/o+ytO0LF7UeqAhT9a+fftWdbRVYv7+Wwrz589Pzdm9EaKQI8cee6wNESVBVl7bCg/jx9F3G6hWq1bNnHXWWakxFBJAgq76KFSGPKr9B2SHH364bVunTh274acyOp/eHlH8dIWqUd8JEybYMjew5uaEb1dWkUcx0wa6Mv0fpPSHH35o5z5v3jwzZswYc80116SmpPubTB7ZWptMm2xqk1PdY7X5ptapUFwSuGUS6/0N7vz16uf1gw8+MP7mkbYT/0CgAAjo4bze8OnWrVsBrIYlQAACEIAABCCQzwSIkZ3PV4e5QSAPCBx00EFWeB0/frx5+OGHbdiR0kzr+OOPN7169bLCm7z5KsL8GK7lcb4NN9zQDqvX7AcNGpTxFBL73GZ7GRsHGui1/gcffDCRSC2PwnvuuScwQvlk69WrZ+TdeM4555jHHnvMejJ++eWXWZ9MHtgSxCW+Oa5ZD+J18D1WveKskwpvErRM82vQoEGwSyqfq3lpwFq1atk3J5577jkrIMibtrSmTR1ffPFF+9HmnBozicnD9vzzzzdHHXWUyWajwKixFf8Zy0zAf6NDb2K4h2OKeS6PeP1MKp61vK/DrEuXLsYJtapXuCCVSWyVKK2NQcNMP6Pbb799qkrX/bPPPjPjxo2z51Ps/zCTuKX/SyrbNF+J0C+//LL5+OOP7f9JYXPS/dz//0P/d33yySe2z/Tp00tspOrG0Aa9/kMGP/yKxG59WrRoYR/6uD4cIVDVCeihkP4f0O8DGAQgAAEIQAACEChvAqv95cnzp0QlCTH6yFw67Kh693qkjrn01NTYGAQgkN8EfvrpJzN79mz7+rk2t9Jn1qxZqdfR9YfM+uuvb/+gkeCh17m33XZbs+aaa+b3wphdTgjo/w15HOrz1Vdf2e+HhG19Z7RRmkQeeXLqOyKRR98PvYbsi0Y5mUgRDqL46EuWLLEfsVa4G3lu62dPzBs2bGiqV0/2/FpipuKTz5gxwygchWIAr1y50oag0HVTrGMd/VjNmZC73zGC7fxyl/aPSvt5/e7hytzRlflHxazX/UgPSfLdJDo7YVkhnS666KLYKev6OvFaDRX32hdQJW4PGTLESHT1TR7D8pqXN7Y8sYPm4mcHw4so9IjE7Q4dOgS72LwedEqkDT7EUmggnU+bUwZNP/syeWqfcMIJwWqj/2v22msvWy4eLtSVwngMHjzYlr/99tuh61Ccaj34k0e0vMR903dGXtR6g8DfiFJtJDJLrN911139LjatnyeFbHniiSdKhFHZZZddzNlnn23CQiHpAZN/LoTsEmgpqKIE9Caa7q/6XU9/S2qPFR39tF/m6rRcl9bR5f1jMG0b/e8f18cvIw0BCEAAAhCAQPEQQMgunmvNSiEAAQhAAAKVRsCJ0cEJ+OUu7R+V9vNOrHblOroy/1iVhOwgk1zl9XBDDxv1YEIPMuTxLmEpkymkiB4+ia02g/RF8ri+rp/OoZBINWrUiGte6XXionVK1BcfPWBLYnqQILFfb0VI5M/F2whJzksbCOQTgZkzZ9pY/HqAI3HZF61d2h3DhGtXpjU5cdod/bLgmv02wTryEIAABCAAAQgUPoFkrlmFz4EVQgACEIAABCAAgYIiII/8pk2bZr0mCbPZeNu7E5S2n+tf0Ud5bOuNoWxNGyLrg0EAAhCAAAQgAAEIQAACFUsgs1tOxc6Hs0EAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAE0gggZKfhIAMBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAL5RgAhO9+uCPOBAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBNAII2Wk4yEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgEC+EUDIzrcrwnwgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgjQBCdhoOMhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIJBvBBCy8+2KMB8IQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhBII4CQnYaDDAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCOQbAYTsfLsizAcCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAATSCCBkp+EgAwEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAvlGACE7364I84EABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIE0AgjZaTjIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQL4RQMjOtyvCfCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQCCNAEJ2Gg4yEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkG8EELLz7YowHwhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEEgjgJCdhoMMBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEI5BsBhOx8uyLMBwIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABNIIIGSn4SADAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAAC+UYAITvfrgjzgQAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgTQCCNlpOMhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAvhFAyM63K8J8IAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAII0AQnYaDjIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCCQbwQQsvPtijAfCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQSCOAkJ2GgwwEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQjkGwGE7Hy7IswHAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAE0gggZKfhIAMBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAL5RgAhO9+uCPOBAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBNALV03JkIAABCEAAAhCAAAQqncCSJUvM3Llzzc8//2w22mgjU79+fbPWWmtV+ryYAAQgAAEIQAACEIAABCAAgcoigJBdWeQ5LwQgAAEIQAACEPAI/PLLL2bs2LHmgQceMAsWLPBq/pvcZZddTJ8+fUyrVq1K1F1zzTVm6tSpZrvttjODBg0qUZ/PBaeeeqqZP3++Ofzww02PHj3yearMDQIQgAAEIAABCEAAAhCoRAII2ZUIn1NDAAIQgAAEIAABEfjhhx9Mz549zZw5cyKBvP3220afU045xfTu3Tut3cKFC80333xjNtxww7Ty8s5ceumlRufeb7/9zJFHHlmq033yySdGIv7SpUtL1Z9OEIAABCAAAQhAAAIQgEBxEEDILo7rzCohAAEIQAACEMhTAqtWrTJnn312SsTecccdTffu3c2WW25pqlWrZubNm2c9tceMGWNXcOedd5qtttrKdOjQodJX9PHHH9t5b7rpppU+FyYAAQhAAAIQgAAEIAABCBQ2AYTswr6+rA4CEIAABCAAgTwn8Nlnn5np06fbWUqcvuGGG6yA7aa98cYbmzZt2piddtrJXHbZZbb4/vvvzwsh282RIwQgAAEIQAACEIAABCAAgfImsHp5n4DxIQABCEAAAhCAAASiCUybNi1VecQRR6SJ2KmKvxKdO3c2ipMtkyf0ypUrbTrun99++y1Ru7gxclkn7/M//vij1ENqPfliv//+e16xzRcuzAMCEIAABCAAAQhAAALlRQCP7PIiy7gQgAAEIAABCEAgAQHFmHa2fPlylww97rPPPua7776zdYsWLTLy1g7ajz/+aB588EEzfvz41KaRW2yxhTnggAPMCSeckCaUf/XVV+bmm2+2Q5x55pmmWbNmweGMYlgrnMnqq69uBg4caCRGX3311badi+n9/PPP2xAoKjzjjDNM8+bNU+ModvfIkSONBHvnea7zaHPHLl26pNpFJSZPnmwmTpxo5/Hll1+amjVrmh122MF+FIJl7bXXTnVV2xEjRtj8cccdZ3beeedUnRI6/x133GHL5P3etWvXtHoJ5RdccIEV2zt16mQOPfRQ21792rdvb+f8yCOPmPfee8/GK1fnKLZpA5OBAAQgAAEIQAACEIAABMpMACG7zAgZAAIQgAAEIAABCJSewLbbbpvqfO+995qtt97aNG7cOFXmJ+SxrU+ULVmyxBxzzDEpAdu1kwB8++23mw8//NDceuutrtj8/PPPRuKv7MQTT7TH4D/Lli1LtdH4a6yxRirv2mqzRjeOzu+E7Ndee81oQ0jV+/b555/bECqTJk0qUefayeP8tttuM48++qgrskd3Lp1v7Nix5vrrr08J8JtssklqHg0bNiwhZE+ZMiVVrw02g0K2RPs33njDnkcituzTTz+1fWrXrm3F61dffdWWu3+i2Lp6jhCAAAQgAAEIQAACEIBAbgggZOeGI6NAAAIQgAAEIACBUhFo3bq19TKWQCuBV57KElHlAdyqVStTt27dxONKVJXJ41neyhtttJF55513zKhRo6xgLPH33XfftfG2Ew8aaKgx+/XrZxRaY9iwYbZW4ru8xWUSk2Vay7nnnmvT+ufII4+0wrKEcAnGEu0/+OCDVH0wobGdiC0v7F69elmRX57ozz77rF2HvL1PPvlkK2ivt9569txau8798ssvm4suuihtWHlSO5NALe919XMmVs523XVXl7THcePG2WN5sk07IRkIQAACEIAABCAAAQhAII0AQnYaDjIQgAAEIAABCECgYglssMEGNnTHKaeckvJOHjNmjNFHJuG4Xbt2ZrfddrNC8DrrrBM7QQnggwcPNjVq1LDtJMgqFIcTlSUea+PI0tpaa61levToYbs/88wzRuFFWrRoYXr27Jk25F133ZXKDxo0yBx44IGpvMJ67L333qZ3796pNacq/0p8++23RiE8ZFr/fffdZxo0aGDz+kdhUuRZ/vDDD9v+CqWi0Ciyfffd1wrZ8riWsK/QHzJ5eEvE9+2jjz4ye+yxR6rIeWNrfmGcy5ttaiIkIAABCEAAAhCAAAQgAIESBNjssQQSCiAAAQhAAAIQgEDFEthmm22sV/FZZ51lGjVqlHbyBQsWmKefftr079/fisF33313qPjrOkmwdiK2K5MILq9m2bx581xxuR0V91se0TJ5nPsitjvpVlttZb2sXd4/ar3OFLPaF7FVrnjdp512mhW5lZeQrdjdsj333NMe9Y/vgT1jxgxbLg4S0YP1S5cuTcXw7tixo60P/pMPbINzIg8BCEAAAhCAAAQgAIFiIYCQXSxXmnVCAAIQgAAEIJDXBBTi4vjjjzejR4+2oTPkxdytW7eUR7Emr/Aj2njxvPPOsx7GwQXJu7tJkybBYhvX2pX/+uuvJepzXeA2gdS4hxxySOTwBx98cGjdF198YcslOu+1116hbSTW+/HCv//+e9tuyy23TD0McHG7VeHCmOy+++7GhQ1RzGxnU6dOdUkb1iWV+V8iX9gG50UeAhCAAAQgAAEIQAACxUIAIbtYrjTrhAAEIAABCECgyhDQRoXyYpYX9siRI61HtmJEO1OIjAceeMBlU0cXnzpVUEkJX8iO2rhSU5M4HGZOyFY86tVWWy2siS1z4rwy3333XaqdQo/IFCpkxYoVNu2E6rZt21ovcRUq9IhCkMjefvtte9xxxx1NnTp1bNr/J1/Y+nMiDQEIQAACEIAABCAAgWIigJBdTFebtUIAAhCAAAQgkFcEtNmgNi7URxsURplE1L59+9q40K6NE15dXsfq1XO//ckff/zhnyJR2oX5UGOFAYkzF/LEb+P6Z+qreN3Oli9f7pJp4UUUB/u3334zzvta8cI322yzlIj+4Ycfmj///NO88sortn+nTp1S4/iJ8mDrj08aAhCAAAQgAAEIQAACEIgnEP+XRXxfaiEAAQhAAAIQgAAEykCgWrVq5sorr7SfRx99NONIinXtvJgl0P7+++8Z+5S1gfNYzmYcP873okWLIrtKfFa4lKBtuummtujrr78OVqXlfS9s32NaMccdJwn+n376qe0n0VybP8rL24UXkaf27NmzU57Z/uaPaScjAwEIQAACEIAABCAAAQhUKgGE7ErFz8khAAEIQAACEChmArVq1UrFtH7zzTdD4177fOQ57DyPJRZLCC+L+V7G2uwwzD777LOw4tgyX8h+8cUXI9sq9EeYSWyWSUSP81R/9dVXU939c0qo7ty5s617/fXXjbyuZe3atUt5iCvEiEye2m5TyBYtWpTYWNI24h8IQAACEIAABCAAAQhAoNIJIGRX+iVgAhCAAAQgAAEIFDMBJ6hKtL366qttmIsoHi+99FLKg1mbFpbVnNeyxpkwYUKJ4ebOnWsef/zxEuXBgqBnuGJ8t27d2jabOHGi+fjjj4NdzE8//WTuvffeEuUq2GeffVLlN998c6jnuQRyF/d6zz33NMEQJW6TSMXBfvrpp+14O+20U2pcN79vvvnGjBo1ypZHhRVJdSIBAQhAAAIQgAAEIAABCFQaAYTsSkPPiSEAAQhAAAIQgIAxffr0SYXBGDdunDn++OONRNqFCxcaxadWfGdtfnj77bebAQMGpJC5DQ1TBaVI1K1bN3XuSZMmmYcfftgsWLDAKHb3a6+9Zk444YTYUdddd11bL4/myZMnm2nTpqW8yk899dRU3549e5rRo0fbsRVKRO179+4d6W298847m/bt29v+2thSjD755BM79rx588x9991nLrzwwtT4/fr1S6VdomXLlilxW2K1TPGxnSkUiRPyJXbLJIhjEIAABCAAAQhAAAIQgEB+Esj9jkD5uU5mBQEIQAACEIAABPKSQL169cy//vUvK2Brgorn7Iu0YZOWl3KrVq3CqrIq02aKvXr1MoMHD7b9hgwZYvTx7cgjjzRPPvmkX5RKN2vWzM53zpw5xonJt956q5G3eJs2bczpp59uhg0bZttfddVVqX4uIS/qsBjZqpdof/7559vxFQ88SlS//PLLjYup7cbVUWFXDjzwwJS3tc61+eab+02sWD5mzBhb1qRJk9Bx0jqQgQAEIAABCEAAAhCAAAQqjQAe2ZWGnhNDAAIQgAAEIACB/xLQ5oQKG9K3b9+UF3EYmy5duhhtCtmhQ4e06jXWWMPma9SokVaeJNO1a1fTv3//Ek0Vc/riiy82Rx99dIk6V6D5Bufi6nSUJ7aE7a233tovtmmF+VDYkmBIENewQYMG5v777zcnn3yy2WijjVxx6rjLLruYkSNHmkMOOSRVFky48CIq1zwVO9s3F9ZFZVEe7mVh65+LNAQgAAEIQAACEIAABCBQNgKrzZ8//0/9Uq/Ng/SRuXTYUfV6zdUd3WY8toB/IAABCEAAAhCAQAgB9ztGsMovd2n/qLSf1+8grswdXZl/VCgOeTo3b948eMq8zyuUyF+/nxnFp1Z4kXXWWcfUr1/fNG7c2GhzyPKyVatWma+++sqGFdlss81SYTdydb4VK1aYWbNmmTXXXNN6PvsbTSY5h8KdaH61a9e2LORNjkEAApVDYObMmWbRokVGb2Xob0n9POrop/0yV6fZurSOLu8fg2nb6H//uD5+GWkIQAACEIAABIqHAKFFiudas1IIQAACEIAABKoAAXkAS7TWpyJNwnLTpk3L7ZQSsFu0aFHq8ddbbz2juNcYBCAAAQhAAAIQgAAEIFCcBHBlKc7rzqohAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCFQZAgjZVeZSMVEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAsVJACG7OK87q4YABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgUGUIIGRXmUvFRCEAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIFCcBhOzivO6sGgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAlSGAkF1lLhUThQAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQnAQQsovzurNqCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAJVhgBCdpW5VEwUAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgEBxEkDILs7rzqohAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCFQZAgjZVeZSMVEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAsVJACG7OK87q4YABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgUGUIIGRXmUvFRCEAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIFCcBhOzivO6sGgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAlSGAkF1lLhUThQAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQnAQQsovzurNqCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAJVhkD1KjNTJgoBCOQVgW+//da89dZbZv78+Wbu3Ln2WKNGDdOgQQNTv35907hxY9O+fXuz/vrr59W8mQwEIAABCEAAAhCAAAQgAAEIQAACEIBA1SOAkF31rhkzhkClEVi8eLG55557zMiRI83777+faB4HHXSQ6datm+nevbtZY401EvWhUfkT6NWrl3n22WdLnGjTTTc1kydPNtWr899DCTgUQAACEIAABCAAAQhAAAIQgAAEIFBpBFAqKg09J4ZA1SHw22+/mbvuustcdNFF5j//+U9WE3/uueeMPtdcc40ZOnSo2W+//bLqT+PyIbB06VKzYMGCEoOrbMWKFQjZJchQAAEIQAACEIAABCAAAQhAAAIQgEBlEiBGdmXS59wQqAIEFDZk1113NWeccUbWIra/vJkzZ5r999/f9OnTx6xatcqvIg0BCEAAAhCAAAQgAAEIQAACEIAABCAAgVgCeGTH4qESAsVN4IsvvjAdO3Y03333Xc5A3H333dYT+NFHHzU1a9bM2bgMBAEIQAACEIAABCCQvwT+/PPP/J0cM4MABIqCwGqrrVYU62SREChkAnhkF/LVZW0QKAOBRYsWmXbt2uVUxHbTGT16tDn22GMNf9A4IhwhAAEIQAACEIBAYRDQ73dhn8JYHauAAASqMoGwexN/k1blK8rci5EAHtnFeNVZMwQyENB/5toMMCyGcljXNm3amEaNGpmVK1ea2bNnG4URyWQSsxV3+5RTTsnUlPpyINCqVSvzyy+/hI5crVq10HIKIQABCEAAAhCAgCPgBCHlfSEIj0dHiCMEIFBVCPj3MH/O3M98GqQhkB8EELLz4zowCwjkFYH777/fSGiOs3XXXdfceOON5qijjjJ16tRJa6qQJMOHDzc333xzWnkw07dvX7PPPvuYpk2bBqvIlzOByy67rJzPwPAQgAAEIAABCBQaASf2uGOhrY/1QAACEPAJ+Pc6RG2fDGkIVB4BQotUHnvODIG8JKCNGC+//PLYuW200Ubm9ddftxs3BkVsdZQwfdNNN5l77703dhxV3nDDDRnb0AACEIAABCAAAQhAoHIISMhxn8qZAWeFAAQgUPkE3H3QF7crf1bMAALFRwCP7OK75qwYArEEnnzyydi42FtssYWZMGGC2XLLLWPHUeVJJ51k6tataw4//PDItgovcsUVV5iGDRvaNvLmVnzuMGvbtq2pXj3+tvXRRx+ZX3/9tUT3NdZYw+y4444lyv2CadOmmXHjxpkPPvjAzJ0718yfP99ssMEGZpNNNjGbb765OeSQQ8zuu+9uVl898zPAzz77zCxZssQf3qYl8terVy9VrnM9/vjjZvr06WbWrFmmQYMG5oILLjC1a9dOtfETuWKgDTzDNvFcc801TevWrf1TRqZ//PFHM2nSJPv55ptvLLPly5dbXo0bNzY77bSTOeKII8yGG24YOcZvv/1mpk6dGlovTnHe+mK3YsWKEn31tsC2225botwVfP7552bx4sUum3bceuutI9mnNSQDAQhAAAIQKGACCDUFfHFZGgQgUGYC/j0ST+0y42QACGRFYLW/hJo/9YPnni6pt0uHHVX/xx9/6GCPErUwCECgcAi0b9/evPnmm5ELmjhxounUqVNkfVjFhRdeaAYPHhxWZcuuvfZaM2DAAJuuX79+ZGzuN954w25AGTXQf/7zH7PeeuuFVktUfeedd0LrJDoff/zx5t133w2t9wsl0D744INm77339otLpLfaaqvQWOEK6TFo0CArIiu0ynPPPVeir7zcw0RwNcwVg+7du5sRI0aUOLcKFDt77bXXDq1Tobz2hwwZYgX3yEZehR5oDB061NSsWdMr/W/yiSeeMN26dStRrgLFXo8SuTXHWrVqhfbTGwPz5s0zUb9USuTWg4Mw04OQli1bhlVRVkYC/i/8/lB+uUv7R6X9vH4HcWXu6Mr8ox6K6WFI8+bN/dORhgAEIACBDATcPTeumfZDkeNBs2bN7P+3esiv/3f1cWl3dOU6amw/r3Mo7x+DaVv5v39cW7+MNAQgAIEkBMrz/lGeYydZG20gUEwEMrsVFhMN1gqBIiewbNmyWBFbgpBiWmdrffr0ie3ywgsvpOqjRE01ePbZZ1PtwhLyDo6yo48+ukSVRK9hw4YZeeEmEbE1gLyYxSBT2BSJvWGmDTE/+eQT6x0eJmKrz1577RXW1ZblioE8oaNMXKLsyy+/tPOT13hSu++++ywzebgHrUOHDsGiVP7999+P9M6Pu17apDRqw9Hvv/8+UsTWQ4rtt98+dX4SEIAABCAAgWIjkETETsLEPWgMHpP0pQ0EIACB8iAQvB+5fC7OpbEwCECgYgggZFcMZ84CgSpBYMqUKbHzPPfcc1NeM7ENA5UKQ6KwHFH2yiuvWC9g1ccJ2fLejbMxY8ZEVivEhW/y3j7ggAPMGWec4RcnTvfq1ct6kf/++++J+6ihHhbIm1tia5R17NgxqsrkkkHkSSIqFHZG1zLOYz+iq3nrrbeMwqL8+9//TmsiD/w99tgjrczP6LsRZorRHmfyXA+zl19+OazYlulhB94UkXiogAAEIACBAidQFiHGCULuWOCoWB4EIFBABNx9yx1LuzT1xyAAgfIngJBd/ow5AwSqDIFMQrbCUZTWFF4izhTvWKYY1AoNEWbyBo4KCSEPYwmtYaawIopx7ZvicitMSlns+uuvN5dccklWQ9xxxx2xIrYG22677SqEQTYTlyd6165ds+lSoq3GkMezvKJ9i3t48eKLL/pNU+k4QVqNXnrppVRbPxHntX/YYYf5TUlDAAIQgAAECp6AE26yFWD8ftn2FdRgf/J/b6gJC1jwHcjtdyDbG3mQfzb9/b7Z9KMtBCCQnED8rmnJx6ElBCBQAATmzJkTuQqJy1HxpyM7eRWZ4ulrc0VZtWrVbLzqm266yev9d1LhOFq0aPF3wf9SkydPNvKyDrN//OMfacUKWXHzzTenlfkZxWZWyAttNKhYy0899VSkgC4x+/zzz0/bwNEfqzRpxZRUzO7yZJDtvPr16xfZRZsryrtd3GrUqGFDpyicSJTddttt5p///Geq+qCDDjJnnnlmKu8nxo4da4YPH+4XGW0oGSVUu4YSrPWLpO9hrZAp2swzzLSG3XbbLayKsipOIPjgpIovh+lDAAIQyAkB/R+ZrWXTx4k5Uefw/3+OakM5BCAAgVwQyHTvynQ/8vtnauvP1/XLpo/fnzQEIBBOACE7nAulEChKAnHhLjIJ0ZmANWrUKLbJ4sWLU/VHHXVUpIgrUTksPnNc7OguXbqkxlbs6t69e6fywcSdd95pgjG9Bw4caLRJo0TrMJPQqvrSmATUXXfd1Wy44YY2Vrc2TpLX8lprrVVuDLKdp0K2PP3006HdNHd5wm+88cZp9WeffbY58MADbUzxtIq/Mtrcs3///qZ27dq2St7y2mBx2rRpwaa2vzbj1OaZzvQgIpPpu6x+in/uTGFNor7jxxxzjKlenf8SHSuOEIAABCBQuAScuJLNCpP0cW10zCTcuLbZzIG2EIAABEpDIJv7UZK2mdoE55jknhjsQx4CEIgmwF/t0WyogUDREVi4cGHkmps0aRJZl6Rigw02iG0mAdfZzjvvbLTxnkJRBE2xluVhGRROH3/88WBTm2/Xrp3x5z5ixAgTJYTefvvtJURsDbLGGmuYa665xrz66qs21nPwRDfccINR/PBatWoFq2LzCm8iAVwe2EErTwbBc8Xl9YvX6aefHtpEXvoK/VGzZs0S9RLj77rrLitml6j8q+Cee+6xnuyuTvGpw4Rs1SuMiC9kR8W/dmO5o+Jo+0J2XDgSwoo4aoV3DN4rCm+FrAgCEIBAcgLZCshR7d2myq5eR1/cUd7Vhc3ObxtWTxkEIACBXBGIuxfpHP79KNjWr3PzcW3C6lyb4FF9smkf7E8eAhD4m0BJ9eTvOlIQgECREZB3cJT9+uuvUVWJyvUfd9z48pR2prY9evRw2RLH559/Pq1MAmiY6K1GwbjeURtCSpQ9+eST08b1Mwp5cumll/pFqbRCmkQJ6alGgcTDDz9sLr/88lARW03Lk0FgKrFZeTFHsb366qtDRWw3YOfOnW24EZf3jxL/3S+BKj/00EP96rT0hAkT0vJRG0CmNforE2z3wgsvBJuk8nEbbKYakYAABCAAAQhUYQL+/7uZlqG2Ye1debDOLw/WuXMF25DPbRxgeMKT70Dm74C7H/nHILeoOr9cadcvWB6VV3sMAhAoOwE8ssvOkBEgUDAEwjyD3eKi4k+7+kzHn376KTKGtfoGPba1saAfR9kf/5lnnjH+5pGKmx1lfliR33//3QRFcL9f1MaCro3WEGXOMymq3i/X5pPBuN1+vUuXBwM3dtKjvNCjTDzGjx8fVW3L11577dB6hfhYtmxZKryINrhU+Bpt6Bk0hTXRZp7yjNcx0zldf4Wb0S+MeiigBzFR/bTZZJhXuRuHIwQgAAEIQKCqE8hGQIlqGyxX3pXp/1rf/DpXHmzjyt0YLs8RAhCAQFkJZHO/Cbb170l+ncr9vJtjVLmr94/ZtPX7kYYABP4mgJD9NwtSECh6AvJKjrIvvvgiqipRedxGkhqgXr16aeO0bt06UtiUQClh3Xl4jxo1Kq2vy+yxxx5pIUiWLFkSKaZLWFVM59La/PnzE3dVfOgkVh4MkpzXbxMmLLt6hVMpiymcjIuTrXEUXkTxs8Ps3XffNbvvvrv58MMPw6ptv4suuiitTt+RGTNm2M1Bp0yZklbnZ/yHHX45aQhAAAIQgEAxEfDFG3/dwfJgXm39MqWd2OOX+2OShgAEIFDZBKLuU65c83P3MFcWzLs1RJW7eo4QgEDuCCBk544lI0GgyhOIE7IVXmLlypWmRo0apVrn119/HdtPmx0G7YQTTrDhN4Llyst7+vDDD7dhL6JiXge9nv0NJcPGLEtZNkK2BNmklmsGSc/r2sXFTXdtSnuUkN20adNUd4UXiRKydb3FLSw+dvPmzc3xxx9vgkK2Blb7Fi1a2O9L6kSBxP777x8oIQsBCEAAAhAoHAJOYIlbUVQbv9ylV6xYYfR7j/Yskbijj97qc0JPWJnOHaz388G5qc6dz69zffwy0hCAQPESKO09IaxfsEx57YFUt25ds+aaa1rIro3uTy7t048qz7aN3540BCCQTgAhO50HOQgUNYG2bdvGrn/06NHmqKOOim0TVTly5MioKlveqlWrEvVHHnlkpJCtuUjIHjduXIl+riC4gV9caBDXp7THTB7n/rhxDwz8dkrnmkFw/Ex5hf8oL/M3+NQ5FHJFbOQdHzTFt9bGmGEbNu63336mUaNGRoJ2MMSL2vfp08eMHTs2OKTNS8SuU6dOaB2FEIAABCAAgWIgECYYB8tcXiL2N998Y5YvX260f0j16tVLCNlO1HYh6yT2uI94unRQBPLzftq/BlHlfhvSEIAABHJF4JdffjE///yzadKkiRWzfaHa3ReD9yW/Ta7mwTgQgMDfBBCy/2ZBCgJFT6BDhw6xDG6++eZSCdnz5s0z9957b+TYLVu2NGEe2dtuu631pp0+fXqJvk8++aS5++67jeJlh9nee+9tGjRokFa1/vrrp+VzmdEak5iEWv3Rl9RyzSDpeV27YOxyV56LY1DI1h/Eild92223lRj+zTffNGof3MBRDffaay/b/qCDDiohZCt++ty5c402BA0zPSjAIAABCEAAAsVKwAkx/vr9smBa/xdLtNHvM7vttpspz9+t/DmRhgAEIFDRBCRi641eCdm692288cb2/ufui07AVt6l3RzDylwdRwhAoGwEkqspZTsPvSEAgSpAQP85h3m1uqm/9dZb5u233za77LKLK0p0vOeee2LbHXDAAZH1PXr0MAMGDChRr/jHEimjNvA79thjS/TRa2FRtu+++5o77rgjqjpjuUTYJLbOOuskaZbWJpcM0gZOkInzHpeX8zbbbJNglPAmwbjoaiUv+zAhW3W33npraIzzdu3aqdrss88+5pZbbrFp94++J0OHDnXZEkeJ3xgEIAABCECgUKbrY7cAAEAASURBVAk4wSVsfWF1fllYWsKOfudp1qxZaq+SsLEpgwAEIFDVCbjN4LVpvO59Mt0XnWgdlXbr9utdmTvG1bk2HCEAgXACCNnhXCiFQNESOOOMM0y/fv0i13/aaadZ8ThO4PQ7y5N28ODBflGJtOJAR5k8ZsOEbLVXXOQoU7zloMlrSBtEStwMmkKDbLHFFsHivMjnkkG2C9pyyy0ju/z22285Z6YNOqOu0VVXXVViLnrw4jzvnaAdbBQVd3vXXXdN2ww02I88BCAAAQhAoCoTkFCSjfntw9Iq++OPP6yQ7TbczmZ82kIAAhCoagScmK17n+6BErHdUWuJSidZp983SXvaQAAC/yWAkM03AQIQSCNw4oknmksuuSRU7FVDbayoV0knTZpkNt9887S+wcyzzz5rwgRlv53iWGszvijTZoBt2rSx5w22CROk1UZxj8NClShW4yGHHGIeffTR4FBG4UtmzZpl4oRbdVJs7qlTp5bov+eee1qP4BIVOSjIJYNsp6N1RZk8suVBHWeKsa2QNPpFLWgDBw4sEWZFm4lKuH/ggQeCzUPzBx54YKq8du3aRuK03hxIYl27dk3SjDYQgAAEIACBgiMQ/H/Zz7u0O2rxLu2OBQeEBUEAAhCIIeDufTo6MVvNXTrMS1v1rr3SGAQgkBsCCNm54cgoECgYAvKw6d+/v91YL2pRX375pRUM77zzTiMhUeKjb4olppjYF154oV8cmr7oootCy/1CeV5LQE9qxxxzTGRTCa9hQrY6nHXWWZGbAqr+008/jRRuFZO7PC2XDLKZ51ZbbRUZbkbXuHfv3pGhZuS5IG/6sJAt8rweNGhQ6FR0jZIK2UGhvXPnzomF7IMPPjj0/BRCAAIQgAAEqjoBJ7qErSNY5+dd2h3VX2k/HzYmZRCAAAQKnYB/HwwK16oLljkefp0rc8e4OteGIwQgkE5g9fQsOQhAAALGCtk77bRTLIoFCxaYLl26GMU5liCo+MSK5dyxY0dblkTEvvjiiyNFUP/kOk82FucFLm/fqBAUirktL92vv/467XSrVq0yI0aMMDvvvHNaucvIC9htOOjKcn3MJYNs5qZfyIYNGxbZRbHFJTpLtPZNDzu6d+8eKmKr3aWXXuo3T0t36tQpLR+XCV5Lff+SmEKSSKTHIAABCEAAAhD4LwEn0rijSpV2eT8NMwhAAALFRMC///lpMfDvkcXEhLVCoLII4JFdWeQ5LwTymIA8rB977DGjkBaZzG26mKldsF7i7xVXXBEsDs1vuummVnxWvO1Mps37Nthgg8hmCi9y++23m1atWoW2efLJJ40+LVu2tELn8uXL7QaXEu6jLE6UjeqTbXkuGWR7bgnL3bp1MyNHjizRVde/Z8+e1vt+u+22s/Gq9SAg7lopVIwE8CirVauWDS+i6xBnukbBEDKZHsC48SSyYxCAAAQgAIFiI+AEF7dul3dHV66jylx58Oi3Iw0BCECg0An490A5+ri888J261e5q/frXLlrxxECECg9ATyyS8+OnhAoaAKKFT1lypRy2ZFeIrbiZ6+xxhqJGR577LGJ2saFFXEDSAC94IILXDb0OG3aNPPEE0/YecaJ2AoponAWFWG5ZJDtfBXnOs7E6KWXXrJhW+JEbI1xww03pF69ixoziQd6mBi+1lprGT3MyGSKlY5BAAIQgAAECpGAE1gyrS2snSvT0U9rLL8s09jUQwACECgkAv79z783+ungel1dsDyYT9ou2I88BIqVAEJ2sV551g2BBAQkOL/77rumcePGCVonayIBURtFKiRJNpZpU0E3VhIRU2210WBSYdiNHTxKxB4zZoyRl3dFWK4ZZDPnRo0amfHjx5f5wYY2y0wSTzzJw4GocC6ZQpNstNFGdgPRbNZPWwhAAAIQgEBVIBAniETVuXL/6Ke1buVdWVXgwBwhAAEI5JqAfx9098OosrBzuz7Z1oW1pwwCxUygYtSXYibM2iFQxQkojvD06dOt8FuWpUg8fPjhh80zzzxjFDoiW9t4440zCqCHHXaYqVOnTqKh11lnHfPII4+Yp556qlTirARzeZWXZi2JJhjSKNcMQk4RW3TAAQcYxb4u7QOAsWPHmrj45f7JFR4mzOPab7P77rv72VQ6U5zsf/zjHxk9wlODkYAABCAAAQgUAIGggOLyUUct2a9z6QJAwRIgAAEIlJqA7oXufuiOGsylo47uhK7e5TlCAALZE0DIzp4ZPSBQdATWXXddc+WVV5pvvvnGxkLeYostEjPQZnxDhgwxs2fPNhIQy+K9nElATRJWJDhxhbCQOHvyyScHq0LzmoNCrkiUrVmzZmibuMK6devGVWesKw8GGU/qNZAnvXsA0KJFC68mPClv/qFDh5qlS5cmCvnhj6KNOaNMcbajYqFvv/32sQ8nkorpUeemHAIQgAAEIJCPBJIKJJna+fVKu7yfzsf1MycIQAAC5UXAv//5aZ3P3SOjzp2p3vVL2s615wiBYiWw2vz58/90wejdD46OUR+B+uOPPywvHbMRtIoVMuuGQCESmDFjhnnrrbfMvHnz7EcxkhXzukGDBqZ+/fpGoSgU+kH5qmIrV64077zzjvniiy+M1rNkyRLr4a2NFjfZZBPTrFmzEpsLVpW1ldc858yZY4X9v/4vMYsWLTK///67DUUjXk2aNLEbZlavzr7C5cW/Ko3rfscIztkvd2n/qLSf1+8erswdXZl/1M+xHrw0b948eEryEIAABAqSgLtXhi3Or3PpuKNfp7T7fP755/ZtNO6tYZQpgwAECpHAzJkzzc8//2z/FpR25n+0Xpd36bijX6d00DQWBgEIxBNAXYjnQy0EIBBBYJtttjH6FJLVqFHDtG/f3n4KaV3luRY9sOjatWt5noKxIQABCEAAAhAoAwEnSicZwgnWauvS/jHJGLSBAAQgUIgEwu6lEp5deVIRWu2Tti1EjqwJAmUlQGiRshKkPwQgAAEIQAACEIAABCAAgSpAwAkuYUdXpmUo7efd0sLKXB1HCEAAAoVKIOzeF7xP+nnXPngsVD6sCwIVSQCP7IqkzbkgAAEIQAACEIAABCAAAQjkKQEnurjpOWHGP7o6jhCAAASKhYC7B/rr9b2qVe/n/XakIQCB3BLAIzu3PBkNAhCAAAQgAAEIQAACEIBAlSEgAcY3J9i4cndUGz/t9yENAQhAoJAJ+Pc+l9bRffy1u3q/jDQEIJA7AgjZuWPJSBCAAAQgAAEIQAACEIAABCqcQJRwElbuytxRk/XT/uRduY4u7deThgAEIFAsBPz7YNT90C93aXf0OYWVqT6q3O9LGgLFToDQIsX+DWD9EIAABCAAAQhAAAIQgEDBE8gkkKje/wiIn8/Uv+ABskAIQKCoCQTvgQolElYWBUltCT8SRYdyCCQngEd2cla0hAAEIAABCEAAAhCAAAQgUDAEgiKMv7C4Or8daQhAAALFSCDuHhlXV4ysWDMEckkAITuXNBkLAhCAAAQgAAEIQAACEIBABRIoq2CSqb/q/U8FLo1TQQACEMgLAv49MMk9syyTzjR+WcamLwQKgQChRQrhKrIGCEAAAhCAAAQgAAEIQAACHgFfDHHp4NE1V3nUx7XR0fX3y0hDAAIQKHQCwXtfMO+v3w8fonYuBIl/VHtX5/clDQEIZCaAkJ2ZES0gAAEIQAACEIAABCAAAQgUJQGJLe5TlABYNAQgAIG/COg+6MwXq10ZRwhAoGIIEFqkYjhzFghAAAIQgAAEIAABCEAAAnlDwBdloiYVbBPMR/WjHAIQgEAhEQje+4L5sLUmaRPWjzIIQCCeAEJ2PB9qIQABCEAAAhCAAAQgAAEIFCSBKKFF5cG6YL4ggbAoCEAAAhEEgvfAsPuk6xps68o5QgACZSdAaJGyM2QECEAAAhCAAAQgUC4EfvnlFzNr1iw7dqNGjUydOnVsrMVyORmDQgACRU3AiTJBAcaVFzUcFl+pBN555x17/rZt25rVV8cXr1IvRszJv/jiC7No0SKz+eabm/r168e0rLpV7v7ohxZxZVqVX151V8nMIZDfBBCy8/v6MDsIQAACEIAABIqMwMyZM83jjz9uPv74Y/Pll1+mrb5mzZqma9eu5thjjzX16tVLq1PmmmuuMVOnTjXbbbedGTRoUIl6CqIJPPjgg2b06NGmbt265u67745uWMA1MKh6F1cCir6va6+9tjnuuOMSLcAXXdRB+WCZG8gvj2vn2ufb8fTTTzdz586NndZmm21mmjRpYvbbbz/TokWL2La5qPz888/NhRdeaIe66qqrzLbbbpuLYSt9jPnz55u33nrL6P+wefPmmYYNG6a41q5du9Tze/HFFy0vXaMnnnjCPProo2bUqFGVfq+ePHmyufHGG+26br/9dtOgQYNSr7Gqdgwy+Oqrr8yAAQNMq1atzD333FNQoq67/zmhWnmX9q+fu2f6dVFt/X7BdGn6BMcgD4FCJYCQXahXlnVBAAIQgAAEIFDlCEhIlbARZfLQfuihh+znuuuuM506dUprunDhQvPNN9+YDTfcMK2cTGYCCxYssOx++umnzI0LtAUMquaFveWWW8wff/xh9PN/zjnnlMsinDhTLoOX46DfffedmTNnTuwZdM+UPfzww/YhoRj6IlRs54hKeRDfe++9pnr16kb36nXXXTfVcuXKlfZeo4IVK1akyqtyYty4cWbgwIGhSxg8eLDp37+/6datW2h9XOGPP/5orr/+ettE16VatWr2euqaVfa9evny5anruGrVqrhlFGxdkMHee+9tmjVrZj766CMzYcIEs//++xfc2hGYC+6SsqAqSAAhuwpeNKYMAQhAAAIQgEDhEfjnP/9pnnrqqdTCunTpYlq2bGm22WYb+8e7PJ1GjBhhPa7VSF5Pw4cPNzvttFOqDwkIQKD4CEjElt155532mCsxO0y8DiuzJ83zf/Q2y4knnpg2S4mP8iL+4IMPUoKkvH233nprc+CBB6a1zTazdOnS1L36559/ThOysx0r39vLC9sXsTt06GDDYL3++uvmhx9++H/2zgPMsqJ4++dvQFAEURRQwpKjkiQJSF5yzuASl7zAyhIkCUiWDCsiIqASBIlLFiSKpEUXBMkgIIKSBBUJ8s3Xv5b3WLenz40zs3dmqp7n3u7Tud/Tp0N1dXUsPszsL3/5y8Vyyy3XUnVo06Sx6KKLFssvv3xLcT3wwCOA2hdOQYwdO7Y46aSTihVWWKGYcsopB74g/ZBjru9zpnY/AO1JOgJNIOCM7CZA8iCOgCPgCDgCjoAj4Aj0JwJI71kmNseUl1xyyZos0Tm50korRWns008/PfqNGzeuuO222yKjuyawPzgCjsCwRCDHzBYDRmYzwNiw1t5M3G4MAzNthx12yBaNjQAY2Keeemr0x+yUkZ3NaAg6fvjhhwVMaojNAjZXpSoFXGFmM05BSKi3wshGGhs1W9DWW28dTf522WWXqEbnk5/8ZOnmlu5BYNllly2404OTEEhlr7feet1TuD4qCX2iTm1Ye6PkFVZmo/Du7wg4AnkE/KaEPC7u6gg4Ao6AI+AIOAKOwIAgwGJfjGkyRHVIysS2Bdlmm22KNdZYIzqhauR3v/ud9c7aP/jgg4Lj7K0Q5Wo1jtJnkcaR41aJcrZLncRtN8+qeJ2UpRnMwRaMWyEYTrxTp6GPAMxs1I20S1Vtq8q93Xy6JR5SpOgX/+pXvxqLhATwW2+9NeDFU7/ZKs6E76TPoW9opt/JAfLiiy+W0uwwmMXEJiy4IpErFVjc+0BezdI111wTg8Ig/8Y3vlFGm2aaaaL+7dw9EWUgYwGbVjE10QfE2un7a4Qr77dRmFxF2ykXDN511lknJoe6nm7HPlfvKrequlS5V6Vj3TuJa9NxuyMwnBBwiezh9La9ro6AI+AIOAKOgCPQdQjcfvvtxeOPPx7LhX7JZi4b22ijjYobb7wxxkEiO6deBGk2Lu+74YYbCnQfQ3PMMUdkgm+77bZZKe5HH300SsBNnDixjEM8Lm5ac801C/KFOSHiEi70eqOT+9BDD4153XHHHQUXQMFk/9KXvlQgnTVmzJhi2mmnVbQak7zAgEsquQSNOEsvvXSUwEMP6pVXXlnAuDjqqKNq4vEAE+XCCy+M+jiJ+/nPfz7m9/Wvfz3WE32qfUXkc99998XkuBxun332qUkaqfprr702lgVJNLCmHkggphsT6JPl/RGGI9jgfvPNN0fckBxlMwNVMieffHLMg7rzDGOHfEgf5s5iiy0Wj3GjkzRHqDSAkQDGqE8gDm1F+Ew33XS5aO42BBCQZDbtqxMaTkwWGNkwWyG+seuuuy5eXsgz3zvffY6uuuqq4tZbb419IxftPvzww/GyQ4U98MADo2qRueaaq9hrr73kXJr0lxdffHFxzz33RLdmvu1//OMfMQ7lRR8x/S39AOPH2muvHfuGMoOPLGeddVbxxz/+MfZJG2ywQew76RvUrzUaH9L0eLYXEldJW3OBrgi91lVjgcLIvPTSS6OVsWeKKaaQcyG8uUDSXmp8yCGHFIx7qDaB8c34x7tgbABT+r3FF1886uq20tyHH354VF/yqU99Kuozrxo3kDxH5zrSxrqssyxUxkJfTf8LkR/3X1AOUSvjF4xo9IyzGYnqjtlmmy2ON7QZxlw2w6kz3zthUKNDOZFopxyaY9DGR40aVTDXyBFxwfc3v/lNHDdoV6h1YQxbZZVV4piVi5e6rbbaalHVEe2DsYexaqgRfaOksoda3bw+jkC3I+CM7G5/Q14+R8ARcAQcAUfAERjSCMCEELHAbIZYFMJ8qFpIvfnmm8UWW2xRw4wmXRaVqC2ZNGlSjRQ4fvUumqSM/GAIwJQRvfzyy5H5CvP55z//eXHaaafJK5ow0GFEs9C+7LLLIkPaBoBRoWPpcifOhAkTiltuuaVYccUVY/owqFPKXS6GJCXMXn4s8I844ogswz5Nq9EzmJ177rkx2KyzzlrAMBEhscZxepjPlsCaHyoL0ovOcId5RXlh4u+7775lVG1kwIQmDEQYy7DBDQYDzAZ+P/7xjyOzAXcRDCveFQw5EXF4F/x4LzC2ctgqvJuDGwExs/fee+9eFRlODOpela9wgDks+sxnPhMZ19pM4rvcdddd5V1jnnfeefE7g5HMppu+WwUScxy92SnRb/ANW2r0bZMejFRtUCou/TM/+vKddtqpGD16dE3/BzOTssEAZvygH7BUb3yw4ax9lllmKXbbbbfoNNNMM1mvaKd/FIMeJmqzTGx7SSebA5aoI/VI+y4YtvSpr7zyShzfwFGE/c4774w/+lMukFR8GO1sQkJsqKYbj7iDtRjrnIpqRKhUsbrqzz777BomdqvjFziqnaCq48QTT4wM4rQcCrPIIovE8c/2/4Sl7TAesaGS1gPsDjvssPJ9KW0Y0fzoT2jrOrkg/5zJpg9Me3C/++67hyQjO1fvnFvVPC0X1t0cAUegOQSckd0cTh7KEXAEHAFHwBFwBByBfkHg+eefL9MVE7N0qGOpkhojCgwJCMbKlltuGaWcWeTDTGZhCRPggQceKCW5CY+0GMTinmPBLFY5ug1D9Ac/+EGMd/nll0dpMJg1lljkw8Rm4QqzB8m+p59+Our9RqqaBTIXVe68885lNJgtYmITb/vtt48XW7766qtRWhlGC4v9HMFs0OVilBeGDXlSDvKhzEg8IwXHwrxdQjoNfbkwoyEwoZ62/ueff37JxOb9sYEAYx9MzznnnFh36gljDElJS2Cjeih9JNhTEhMbxgPScTDckBaVJOX48eOj/lnFQy0C70GMHPCBsfHvf/+7QIoebCgf7tRtqFzGpfq7+T8EYD4hoUq7SSnHzM65EU/uMtO0BvszfRTfhoiLCWeeeebYH+LH5hr9lz2RQtgnnnii3CzaeOON47fPfQYw/sTQ5gTM1FNPHftTpS9TjMdmv236R/pKEe8WVVP0SZzsYFMNYnOL/i+nF1z9arPjg/LKmaTBL0eUlY0A+jlo3XXXzQXLuiFJLcoxyOWXMzX+cWknTF+YqpxoYfMOJjjvBsllJLaRqCUMdogTTDlGNiefRI30p7MJy2XMEGMb72LeeedV9MgsV7/fzvh1xhlnlG0OqWsk/WecccYyfSxsvkKodUH6mj6ecundI8GNVL7GMr5rNj4ZWyHqqHioL9NGLm2PMZY8GxGbvto82XPPPRsF73p/9X2YOUnsnHvOresr6gV0BAYBAs7IHgQvyYvoCDgCjoAj4Ag4AkMXgSeffDJWjgVpPeZ0qwhwzBsGqo5ko+YCZqZUYrCYl0oSjpeLWADbRSrMWyT4Dj744BiEhWluoc+CHKao9JaSH4vhkSNHxngwXcXIRlenpEWJx0Kfo9Ii4sGAlvoUuWP+5z//idJ02MEMiUYr5bf66qtHiWlUdSCZDbOWcK0STOzjjjuuvISTY9tI8U011VRlUn/5y1/KenCUGhUgeoccY6csMKiQimMzgCPylhEmRjNxYSKIqVBmYCxI9Nnj2WDEJgWMGaTl33vvvYKj8RDMLKUNPnaDhAtDv/a1r8W2AYMJlQik5TQ0EeC7st9zvVqKUVMvzFDzY9MHBjDMQX0zMIeleoKNKfpENslgrtKHWoI5KKKv4xsmPn2OGNmbbrppL0aj4mC28m1zikK0++67R6a2mGr0uTAuOdlDXSj3+uuvX1jVHorbyvigOM2aSIODl5UGPuigg6JqqmbT4NSQaIYZZpC1aXOZZZaJfZz6a8YsNmiRZEdCnM1OJIXBgW+EsZDNXcYMJJYVTxmycQjRl9b7nginzVM2NBnnkFoX9cX4Ba4wyBlvaGtVRPuwGxmEZbyVuhM7ljNeiomdniCiXXE6ShLcqMFBlVgjYiOIPBijOI3APGKokzOuh/ob9vp1CwIf65aCeDkcAUfAEXAEHAFHwBEYbgjA0GXBD4kB3FcYwLAWE1tpsrhnAQxx/FoEcxVGLQzN3CLdMorF7FFcmejBTuvAopnLviD0gYpgIKje6PK0TGzCwAzO6ZLFD6a7JO7222+/Gia24koajmcdGcfeLPFe0Jt6xRVXxChIPJ500km9mBvoEhWx+BcTW27gJl2q1NduGCgMGwXHHntsXSY278UysRUXiTrRa6+9Fq28HyTvIRgPlokdHcMfjDW5I2XvNDQR4LtC5c9nP/vZtio4lBjbSFWzuZT+0PtLXwOzTWRV/dhTFDfddJOCRJPNLjE4JRVdE6CJh1a+bZjunGSBkIKm7xQTW1nxzrVZiRuM2Ry1Mj7k4tdzY5PUMrEJS59vx4B68fFDbZWoHUY2/W7KjGbsU39M2uiPFiFNL6KsllBzAuMb4p6IKqLfFRObE0JIeVsmNvH6avxik7oeExsmek5VGZupIo0ZPIu5jRT7JptsoiClyXihkwC0QauGpwyUWOwGMtL5Q5GGUh85FN+P12noIuAS2UP33XrNHAFHwBFwBBwBR6DLEYDxyeIa5qNduHdabBjIHOtNCSlDHfdFzYSIhWu6eOXSLNSePPbYYwXqMxpRTnUBcTjWjS7Wd999t0wCtSMiJAhzxEJcUnLWX0xs3JBCltSjDYMdDGBewZTYZZddUu/KZ8qJdDSSyiKkCSWhKTdM1YN3CE45oowimBipNLuVmFO41JTkfOpumSTC16qqgdFWhY82HZDmRh83qk+chg4CYmJzEWszzJZ6Yer5DR3Eiqh+hW8ftSIimKhsxtGHwbRG77E2CJHk1oYc6inaoVa+bcsIhvFqT3fYvGGO63Jc218qTKvjg+I1ayKFjE5nxjTUecAEBj/0M6OWgvwbkZishBXejeLIH0yRBs4R7mzoIpWNWhgRTGGNxajfsOOSHQvY+MgRuqO1yYA/YwbfXkr2fbQ7fsFsRkq6Hi211FLZMcsylzUHYJwQo55Nr3vvvTebtN004V2y+V2PbF7c2zGUiD7R4mHrVs/PhnO7I+AItI+AM7Lbx85jOgKOgCPgCDgCjoAj0DECSNbBTIQhgiRwKtVblQF6KzmmjDqJhRdeuCaYZXDWeNR5YFGNxCGMT9KGCdwKtSI1Z6X1xFDN5WUZSvJ/5plnZK2RrisdE4sYIolz5SObCpZxQUB0XeckxDk2DREn5x89zd/rr79unv5rhSnRiFL9p/XCP/fcc6U3UnaStCsdMxYwckZ2BphB6sTmESplcoy0Tqo02Bnakpa1GNDfsmkGg5M+LMec2nDDDSMjlu8cJp8kYaVWhPhIerdDrXzb0jVNPrmNSuUP4xcmIv0suqFTamd8SNOo97z44ouX3qg2QSUTJz8YU375y182tbGovjI9rVMmXMeCjvJ6BHYwsikP7xQGNphxUgUpai6FhPE63XTTxWTQmw2hmqTqdINlYhMW3eAwt9PxvC/GL07xNKJW9Irb01moV+HXiJoZV23bzl102iiPbvR3JnU3vhUv03BEwBnZw/Gte50dAUfAEXAEHAFHoGsQYKEOIxtCwtdeClVVyH/+85+lvmkkr9C/bOkTn2htioeuZ46pW+Y1knBzzjln/KHb0upmtXnJXiUdKH9rShLMuuXsSPWlZN1gQDSinCR1ozj4w5iGCQwmMAXREYpuaUtsJIiaKUvK1CBuM9KJuXjKNzVtmfBrplxIZDsNDQRgYqNOpN4Gka3pYGdO27rUs/OdtXLZoE0LCV7i0xfA1ISRzaajGJyom2il/7Npt/Jt23fVKD9994wVKbU6PqTxW3mmnEixS4URlw43c0JGZWx2rLBlUlzrZu0Wc06yCCvahy595HJH3isbg1I700jqnvgw4NkMRsKZ8YOLPi31xfjVzKZxo/ZRVSbchYcNk9p1Aih1r3q2bbcqzFBzd6b3UHujXp9uQqC1VU43ldzL4gg4Ao6AI+AIOAKOwBBAwOqk5th1TmowraZVY1F1ND2NU+8ZndJiYqPqgmPrdrGMJGAjRna99FM/K03Iwr9KcjQnTQijToREZKvHzhW3nokEIUfI0XM6duzYGJTLrdCpOuWUU5ZRYfSDG2pVuLCyVYJhYJkqrcbPhbfY8s7alRTNpe1u3Y2AmNjNqhPp7tp0T+n4RjfbbLPYB3IpHmojYG6qz0SVx0CQ7ZP/+te/VmaJqggxX+34UhmhAw8udkQnNsx9pJBzRJ/JyRNOsDSrQguJYk4pWSn0XNo5N3viJ+dv9TVL6ppwfD9Ik3PpIbrFYWT/+te/jkkgdZ9e9GnT3nrrrYu99967QFIZNV1IenOB6PLLLx/HEYXti/Fr6qmnVnJ9YloVILvttlux44479km6VtLb3rPRJ4l7Io6AIzCsEfDLHof16/fKOwKOgCPgCDgCjsDkRgApLklAsXhutAhHygdVF6LcJYDya8ZEGlf6MUeOHFnsvvvuNUxs0rAL/2bSbBTGHm1Hd2qOYGKrXNbfMgKk2sP6y44U9fjx4ysvO1O41ETyUnpQl1tuuXgBJmF4Lz/84Q9rgsPIhtC1CuMiR1yKRTn4TZo0KRekT90sI/uRRx6pTBv1KZQJfbZOgxsBTnXAsEQSu2pTaHDXcPKXHrUSIlRPwNCGOBGTU4GksH1p2n7zrrvuqkza9jO2v6yM0IGHmOv0NUip5wjGuhjSzTLWdVKFfrWZiwVtvowp3PGQIyS8dZkjar1SVTK69BEd0OgkR182hNqRelLO8ofhbS8L5dJgi4t9H/0xfuXq3MgNCXaNG7btpPEY5zSWSTd8GsY+27mM3TCwYdzuCDgCjkA7CDgjux3UPI4j4Ag4Ao6AI+AIOAJ9hAA6N0ePHl2mtv3225fSdKXjRxaY2DCrkBiDFlhggWLBBRf8yLc9w0r2aTFrU4IJoePWuPPcKdlLos4999woxWbTfP/994vTTz/dOpV2JIzF+EelSqpKg4AwMojPJZXStVom0KJl3LhxZX4XXnhhqQaGZFZaaaWYGswWi5HNAkltysGvHiPExunEDgNIOmpz2JI2TIj9998/lunhhx/uJDuP2wUITJgwIV4050zs/nsZ6PuVbuwrrrgiXvxIbuiAbkR90WeSB0xS3YfAaZScLmP6TisZvfLKKzcqXkf+nFqBkE6nHeYItSLa6GtGvzNp2LHISvbm0s+50ffl6OKLLy7LwsZtSlzsqfHl1FNPLRnwrUjdszmNOhqIzVjGbNFAj1/Kt5G55pprxiDoDs9d9ggz/sgjj4xjBmPZNNNM0yjJApVlIqsvW25uOgKOgCPQLgLOyG4XOY/nCDgCjoAj4Ag4Ao5AHyGANJcW7jAEttxyy3hRFAxrdJwiXYakFExVy+BlYdmpagouORNddNFFxcSJEyOzGkltdHfvscceUeenwvz5z3+ukTCTeysm0lnSkwpTdeedd46SbxyH5yg3OlWReswRC2iOs0Pggx1sYJTA8ICZcvTRR5dRc8yK0rMJC0eikaoTffe73y2kHxSGsZjyP/nJT+JCnzrATMKEuQ2mEMe3F1poISXTr+aee+4Z0weTrbbaKl5eCUOfdnT77bcXBx98cJl/M4y4MrBbuhIBLnzttB9IKzYcddqmGKTPXPoI0S/ybcHwFHM7DStmKO5XXnllVL+BhG8nhPTwPvvsUyaBGgjUHXFihj6JfhCdzJL0haHazGWyZYJtWOg/VFf6Xfo8ygPzHkYm6jVQ1QQRbo011mgqF6syy262NhU5BEI/NeMjUsT0x+i65kTNmWeeGZOgLJtvvnmv5PiWUA0C6bQQfbwkz3tFyDjwng488MDSBylmXfI40ONXWYgGFlSj6D2OGTOmYNOWsZ5LoLn8+ZhjjinbFVLrVsVWVdJq72x2DGXVIt5XVrUAd3cE+g8B15Hdf9h6yo6AI+AIOAKOgCPgCDSFwFRTTRUvFDzqqKMKJO2g9AJHmxALTpirqBTolNAxDcMDtSYwZ3bddddeSaIDGj2oEIx0GDknnXRSr3CtOIwaNao8us2xcxjElpAs5oJFpB/Ty7tg/CNJzIVcHAG3Eu02je9973t9cuwfqcZVV101vhuOS8MMEUMJyWbszz77bJSKvfrqq20Rop33dcoppwyIRDYZwjBnA4I2xMYIZcwRjLlOGf25dN3NERiKCMDQpF+Sbmz6zSqGnu2bzzvvvLgxyQkaVB51QpzAYUNT/e8JJ5xQ8EuJPlsbWqlfXz5/4QtfiH039yxAMK755YjxzapHyYWRm71Y10r2yr8Zk764qj8+7rjjSsZtmhbv1b6nDTbYIA3S8Bl1M2BCPhB3X8DkZ8NpoMevhoUNARijvv/978exgnkA4xW/lFDHgi7wZkjqZJZeeulmgnsYR8ARcASaRsAlspuGygM6Ao6AI+AIOAKOgCPQfwhwgdOxxx5bHHDAAXWl6JCAu+qqq4rckfFPfvKTsYCtXoBInlxmlhKLW6SluTRwm222Sb1rLlpMdY32Cpw4wACC0cwliuiZFcEoQmoPPeBiEuFmCXcW3Ui92YuqFAaGEVJwrRwHV1w2FXIEMxg8IKSskfSDkGiH6bHFFltEJld0NH8wivHXEXzjVddqmffWXjeS8URFzdlnnx3VzxjnaAVPLqwT8yn1r8IgDefPjkC3I4CELdQXbRom5HrrrVdW2erNLh0/ssCwreqf7Pds7WkaVc+c2EFdBczqlOgPueeAPjvtN9sdH9I80mc2+S699NJSnUbqTx+IepEq6fU0PM/0tQqfU3VBmKp3Sl+MehWdciKsCJUfSBvrJI3crTn77LOX/Sbl4K6EHNl3J2xtOC6L1DtCSh4MoE7Hr1xeNl/szYRJ48Bw5j0K99SfMYU7FTQO4l+FASeSYIhD9bCOAfzPEXAEHIEWEfi/cFSnh4UHRyJ0LEL2nEn60vOF2eqkvMXyeXBHwBFwBBwBR8ARGAIIaI6RVsW6y25N7PaZuYfcZMrNmk8//XQx/fTTF/PMM0+a5aB55jj0n8KFhxyJRo82jJGZZpqpZuHY15Vh4Yn0G+pMyA9pO0scFeYIOwt9u4C1Ydq18/7+/ve/1zBfUBuCJDiMEkm25dKn3OAEowmMJucxZqQ1wYl3RlmqmC25evSX2wcffFA8//zzkbFAmXivA6Gvu7/q4+n+DwH1j/9z+a/NustuTez6EUP9p9zss+yYQ6FvTbFq5RlpaFROIJmKvuXJTegupr/hQsQRI0bEfmdylom+hjGEfhCd7ehGbnesuP/++yNTnvpwuWajCwNhmJMvjGxduEhZUF+FSg+k5JtRwcPYy5jDuIJqJp2+6S9cu2n8Uh351l9++eWIXTvvkdNAnERgYwXVOoN9vHnyySfjXR5cVkpd4J/JTO16Bkvs9ic3a6Z2nkXEdXIEHIHeCLhqkd6YuIsj4Ag4Ao6AI+AIOAKTHQGkqmHEDyQzHkkrFmpV1Oyx8Kr4ckeHKnqwIVSMrL766nFRaCUIWThKnYk9pq80rEm5O7300qbXiZ062Hp0klZfxUU6r9577at8PB1HYCgjgK5m6U2WvuzJXV8YsyMCA7tbiL6G/rpRn91MedGTjdAcaptQI4WEc6uEig9+rRD3CMBchlAz0t/UTeOX6gqTFiZ07sSTwlSZMMGl0oWNgMHOxK6qp7s7Ao7A5EPAVYtMPuw9Z0fAEXAEHAFHwBFwBIYlAkh4IUHIcevTTjutVNMhMGBcjB07Vo9FOzpKy8hucQQcAUegTQTop5DQhbFpLy1sR21Rm0UYttGQRtX9B+iXRtq7vwhJbk4jIIV84oknxmxgpCN579QaAkjPgycM+rXXXru1yB7aEXAEHIEmEHCJ7CZA8iCOgCPgCDgCjoAj4Ag4An2LwC677BIvCePY99Zbbx31giPx/cwzz0QJPOWGehHUYTg5Ao6AIzDQCNx11129LqLdbrvtCu40cOp/BFZbbbXikksuiRcMT5gwodh44437JVNUYUiKWBlwP4RTawiw6cPmNMQFzv6dtIafh3YEHIHmEHCJ7OZw8lCOgCPgCDgCjoAj4Ag4An2IABKNJ5xwQnkhF9LZSHIhjQ0hzYVebBjeTo6AI+AIdAMCMFa33XbbbijKsCgDUtlctAtx0SB3NFRRu7q4c+mhC10XNeb83S2PwLXXXhv1anNhJHrGnRwBR8AR6A8E/LLH/kDV03QEHAFHwBFwBByBGgQ4spsj6y67NbHbZ106JndMuVlzuF9IlsO6m92eeuqpeKSbyx65pHPmmWeOUtjoW3VyBByBagTUP6YhrLvs1sSuH3HVf8rNPsuOOdz61rfffrt4+OGHo3oRToy4qom0pQ3M81tvvVW899578aLaqgsbeVcwurlgl8t2WyEuhWQzFWY491JwSaVT6wiAP++ByzWnnHLK1hPo0hh+2WOXvhgv1rBFwFWLDNtX7xV3BBwBR8ARcAQcAUegOxCAOeQMou54F14KR8AR+B8CMOSWW265/zm4bbIgMO200zbMl3fFrx1q51LIdvIZ6nFgXg8lBvZQf19eP0dgsCLgqkUG65vzcjsCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AIzBMEHBG9jB50V5NR8ARcAQcAUfAEXAEHAFHwBFwBBwBR8ARcAQcAUfAEXAEBisCzsgerG/Oy+0IOAKOgCPgCAxDBLj4qRE1E6ZRGu7vCDgCjoAj4Ag4Ao6AI+AIOAKOgCPQXQi4juzueh9eGkegaxDgsp9bb721uPvuu4tnn322eP755+MFK3PMMUfUY7rpppsWn/vc52rK+/LLLxeTJk2qcWvlgctbRo4cGaPccccdxTvvvBPtuOH3xBNPxLIoTW6Ob3RD+euvv17cf//9MQqXhq2yyipFq0yugw8+uKA8o0aNKnbZZRdlH81XX321+OUvf1lwUdkzzzxT/Otf/ypmn332ApxWWGGFYtlll60J7w+DE4G//e1vxYMPPhgLv8wyy/Rq+2mt+upb4PKhhx56KCa/9NJLF9NNN12a1bB81jd81113xX6C/mrFFVds+dseluB5pR0BR8ARcAQcAUfAEXAEWkbgt7/9bbx0lPn4Ekss0XJ8j9A8An/605+Kxx57LEb45je/WXzmM59pPrKHnGwIwA/hclTWaquuumpDXk27BXVGdrvIeTxHYAgjcMMNNxTf+c534i3tVdUcN25csf/++xcHHHBAAYMYYnDfZJNNqqI05Q5DCtp5551jJ4j9pZdeKriE5R//+Eex1lpr4RTphBNOKPbdd189Zs2ddtqpuPLKK6Pf8ssvX6y00kqRKZ4NnHGEgX3MMcdEn3POOacMwe3phxxySDF+/PjSLWdZeeWVi+9///vF4osvnvMuXnjhheL//b//Fy9GGYw3pL///vsFzFaIjY10cyNb6UHoCBNbbe+CCy4ott5667q16KtvgY2kzTbbLOY1YcKEYt11162b72DyVNvhm2+37ey1117F008/Hav9xz/+sZhhhhkK9SGDCQsvqyPgCDgCjoAj4Ag4Ao5AdyMwduzYKNy14IILFghTOPUfAj/96U+Lww8/PGbw+OOPF/POO2//ZeYp9xkCV199dQGfCJo4cWIND+Ttt98u3njjjegH36OTi2FdtUiE0f8cAUdACNx4442RYffwww/LqZh55pmLxRZbrPjSl75UusFUPvTQQxsykssIfWD5+te/Xg5oJLfffvuVTKxc8r/4xS9KJjb+559/fktM7H//+9/FDjvsEJPeddddi/nmmy/a33vvvWKjjTbqxcReYIEFinnmmSeG0R9S7TDPxWyTu8yFFlooSnBvs802chpUJlLySKDz++EPfzioyu6FnbwI0HY4uTDnnHMWZ5111uQtjOfuCDgCjoAj4Ag4Ao6AI+AIOAKOgCPQLwhceOGFJd9AJ53bzcglsttFzuM5AkMQgRdffLFYc801y5ptt912BWo15pprrtINFSNIGJ955pnR7fTTTy+WW265AlUjHO2/5557yrDWQjowdaGjjjoqqviw/tg/+9nPpk69ng888MDiiiuuKKXFd9999+Kmm27qpVLglVdeiVLdSuDss8+OTDM9N2PCmEWtCgTTXkQZVBfKDIN8nXXWKaaYYooY5D//+U9koCPVTnyY/uuvv37x+9//vgyjtNwcmggMxLcwNJHzWjkCjoAj4Ag4Ao6AI+AIOAKOgCPgCAw2BD796U+Xwo86td8fdXBGdn+g6mk6AoMUAdRoiGC8/uQnPyk+9rHagxuzzTZb8YMf/KCYaqqpipNOOikG//nPfx4Z2V/4wheiHm2lYc3pp5++fETXL792CGYx+S288MIx+s033xyfU4lmGNwwkKHVV1+9GD16dLQ3+wcz+pRTTonBUe2AahMROrFFt912W82RGdzR2w1jH3UiiyyySCwHag+Qckeq3GnoIzAQ38LQR9Fr6Ag4Ao6AI+AIOAKOgCPgCDgCjoAjMBgQ4BQ7v/6mWg5Vf+fm6TsCjkBXI4A+XhGM2JSJLT/MI444ony8/fbbo57n0qGfLV/72teKY489tsxlzJgxxV//+tfy2aoUQWIa3da6HK4M1MBy/fXXF3/+859jKMskR2pd7qhcqdJ9TUTUJlgd3rp0skHWTXnDaOcCwv6if/7znzH9btY3LN3cOQzQv9wuPlzYyWWNH3zwQS7prnCjbNSfy0bbpXr4sQmEHvhW6cMPP4zfIici3n333Vaje3hHwBFwBBwBR8ARcAQcAUdgUCHAnJn1IeonWyHdF/Paa68VrO3aoUZrQtJutVzNlIM1ImuJd955p5ngfRqGdUa767RO1oiqRNUaijUkd3u1gwl4sv7k7qxWaXK+C5W1ChP597XpEtl9jain5wgMYgToPEV///vfZc2a3Bw8atSo4r777osSyAzg3OA8UASDGBUjDzzwQJR43meffQr0LqUqRVCBAsO5VUIVCQQjfLXVViujMxkQUWcG0XrHZpAGp1yQJMSRfEftiHW79957i2WWWSa6bbzxxpEBjhqXLbbYIrpxsSX+SKNzGSc/bnC+9tpr42WAMNjnnnvu4mc/+1kMn/6ho5v3BXFJ54YbbpgGKdBVBV6UBQlyEfrRv/3tbxebb755WddTTz21uOSSSwoubRDhxoWE0NFHH11w0eUtt9xSqmVBJQ0XbubooIMOKpBun3baaQv0tItQ2fL666/HyxXZsPj1r39dXHbZZbHeTBgto53Jw/HHH18gpU8dIDYTuDEZlTkbbLCBku1lcsPyiSeeGC8stfrhOZmAWpxuIeqFap7rrruuLBK667faaqvont7o3Qp+3A7OxaZsaOn98+5p/1ziWnWagO+AdokqHsVT4dAZv+2228b2rO+EdnLppZfWtJ3TTjutuOaaa+L7pH6oZmmX2LTiO+XCWPJEpY+TI+AIOAKOQN8i0M5CvW9L4Kk5Ao6AIzD5EOAupfHjxxdcSmiZeAg5MZ9mnZaj5557rvjxj38cVVOmQjfMf5m/av2n+M2uCRWetSYnqDGVB/N57m1CQOsrX/mKgrZksu5lHs96jIvttbZlLcI6i/urpJKUNeJaa61VIOTCehohMU4t5whhr7333jt6sfbSOtmG5UT0eeedV/zmN78p81122WUjzqxtuTi+itpZIza7huJ9gjVrIWFNOajzlltuWeyxxx4FQng5Yh177rnnFtRNeBKPdSvvCjWvVRcitvIulDdr8SuvvDI+st5m3Z0SjHTeG+s71tBHHnlkGaQZTC6//PK4pibSBRdcEO9CWm+99aLwlYQB8eMess9//vNY47ew4447ttZWghRjTwC8BzMwgOIvMLN6wsfYE3YTekJmPYFB0vPCCy/0hA8o/sLL6uEXFv4BeydHwBEYKgiEzq0n9CXxFxiAPY8++mifVS2o5yjTDszNhukGBlgZnr4oR4899lgZhnKHAbInMGhLN+ztUJAkrUwj7OKWfuR52GGH9YSBpKVswiBck4Ywlxk68pjeQw89VIYLUuY9gVlZPhN27bXXjuF4VzyHQbKyHHfeeWcZN1ys1ytcYNyX/ipHaobJQk+YCMS4gTlZN3wYzGO4wLAswwUmd6985RCY3jFcGLzlFE2VITCxeyi3nmUqMFjZNiN/a37ve99T8BqTdkO+NmxqD5sLpX8YlGvit/rQyrdg8bPx0vLxTP0DY6GmOArXCL8wgWqIQdBFX5M2D2GToSHulGHdddft4dsJk6OeRm0nLAjiN8V3RZwgRRJ/fJdh0RDrSDsMpwZ6wmS5fC+BiR7LE5jYPWEzonTvVWh3cAQcAUdgCCFAv5r7BeZBj35BYq+HH/2q7VvVr9K3ql8NjImewIDoCQINPW+++WbPG2+80UO/Gk4AxfVi2OzsCZf1xvDE8Z9j4G3A28BQbwP0efR9QcVmnF+Gi8p7Fl100XKuqfm2NYOKzh76WOaxzGfpe4NASt04in/cccfFfl1DVbNrQvL47ne/WzePIODVE4RXlHTTJutx1oIqY5UZBM3KNIMq0TJ8YH6X7qllr732KsMFYa3offjhh5dugbld2nP5sgaCL5CjdteIyqfeGmrSpEkN10+kE5jvvYrGmNqoXqz1GZ9TauddkEZQvVriyBouR7Qh1Z21pyW518MkqJ4t40+cODFGDxsdpZvSsCa85VbbSn5LJKTq5Ag4AsMPgVVWWaWsNJcULrjgglHHUehE427nNNNMU/p3g2W++eaLeqyRFobYPRSxm4mEaDtkJThT1SFIeCLNrN1MVKxg33777YuRI0cW888/f0M1JmGwLXbbbbdYNFtGuUky25b9jDPOiJKycmPn+6tf/aoeOzKR4mb3X4QUOdLUSNgj+Xv11VdHLyR1d9pppyhhjsQAlzkg+Sqd4Ug/ExfSbnx86IM/JP+RehDxfvVuUK/BhaOSCqAM7PzSXm28MLGLl20ecMABSqYIA2xNu0ECGUkA6vLII4/EuvEtsLs8uQkpZgjpA9ogerg5lYAkM/Tkk0/GHW21o+j40Z/FASeLH1IVqBIS8Y6/8Y1vFGHSHaUn9P7BFTVCK6ywgoJGqQ7yhfT+ab+0DcLqnVFGvqslllgixs+1Hb4fKG07SFiHWVD0q/fXqvqgemm5nyPgCDgCjoAj4Ag4Ao6AI5BDgJOcIu5l4u6mwIyLUrmByRi9kCrmlC33SkGsU+wpX+bESN1y4jEwvONJV524JC6njXWaMSbw0V+9NSGnGoPgTgzJXB8pZ9bzSIxzQvh3v/tdVIHCuom1gb0DyuaR2gNzM56qZU0EsQ7lpC7rpsDkjyct5bfRRhsVgXkcpZDBRqdkL7roori+TNNGNQqS1koXKeCUtBYBM9Z4I0aMKAITuZSCZi2y5JJLFkiu2xPinawRVYZ6ayhOxGr9yaljJKjBBsljJK05OQ6BCSffpbaVdQ1ud911V/SHN4BE8qyzzhrXc5wSJl3aA+FYR3384x+PYdt9FzFyH/3VwySXBXwSJPQ59Qw/AYKXAN8EKf0vfvGLRattBV2WLpFttxnc7ggMcwQCU7NyxwyJX3ZMkaxFUqcVstKkfSWRTf5IGIWBo1eZA+OxleLVhLWS6UF1R40fD0gnhYG7V56hT467suyuhosie/7whz/U7Kb3Sig4hElGTCdMbHp529130uYX1INEqSgbuBOJbCQF2JlX+mHgtElHe1A5UvoTjlM8Iiv5Go7Rybk0rURxJxLZKl+YwPQEBnOZPpbAhC/Lxy5wSuAonEkHCTNROLpVxv3Wt74VJSbkh0nYwMAtwxBf0uY2XCv2Vr4Fix95h4ltbPM2P/vNpu1IuMlM8UNKBCkG+YcJlU062qmv/JHEECGxJ3f6hjDhkldpBpU4ZZjTTz+9RmrQtu+giiZKDuakBiWVLclBpM6R/EklspHEQLoAyUG+PZWtLIxbHAFHwBEYggjkpLFxkzQ2Zq5vpf9Xv+oS2S5RO9Qlar1+3sY7aQOpRDZzzMB86wkqMeKamDkx8+CgjqEnqO0o56BBqKOUyA6qHEr3IDRS00fTZ9NPc4JR81fWXyI7Z5Z/uiYMaiTLuMzt0apgifm0lchFcrtZCvdN1aSNtoaUrHRxYMJHb+bqdg3GO0gJSW3VyZbJSmTjz3oPaWFLaJGwa/LDwklpS52sEVUmmekairzlRxl4f5bA264heYeiwNQv47IuTHFBWttKKAe1mYra0+67IAH7/juRyFa9U0zIIyeRjTsUVJiW9U6l1FttKx8LhXByBBwBR6BEAD3K7JQhlZoSu2iBGRV3QtFDxe7aU089lQYb0Gd2J9FDZondYXYv2yXtKBMfKdOU2OlFnzN6q9l1tcTuKbvGSIkjMY106fnnn9/2hRQ2bfSOIT09/fTTW+eO7BdffHF5eSVSvuPGjeuVHnhKvzaeSPBODgqDZWybSBaIkH6QPnMkhpFeSAm9ZOj+FqHbGwoTiqhrHDvvMRwB7CX5QDsHo24gduuRstCOvMpkdX8jiVBFOfyQ8pZEdTjGGCXb0/iBwR+lBHCnbwgqh2IQpNlF6Nubeuqp9ViaYRJW2pHeb0QuVd0IIfd3BBwBR8ARcAQcAUfAEZjcCCD9zP1Elpijo/tXJOlsnu+55x4514SRI9K6Sy21lB7jHUHlQ2LJrQmPPfbYMhQSzukdUUh3ByZjwXoCCiobm1qfBv5jwV1GoqDusphllln0WJqsI0RXXXVVtHJ3D/wCEXqyU9LJXtztetOGo8ycYk51bM8000xRkl1hOSnNWhzqZI2o9GTm1lCB+SzvqBs7MLLLZyzgzSngsDkRf0jdi9DpDSE1z3vgpKol1vro3BahUx3q5F0orb4yc5h0knarbcVVi3SCtsd1BIYoAqgVYABi8EU9wK233hpNy+Cl6jBo+cHoSy+lGEhoTj755JrsODbF5RZWBUJNgAYP4aRKGSJ3CQKeqK3gwkmObHFBBYxtGLzgZQnMGMBhpOLPgNUuMWnpa+KCR9Guu+4qay+TSyx06WFu8tIrQj84MDlJj9gFydsyJxiuVcTGhiZHTMBCLy4qAABAAElEQVR22WWXqDpE4XmeYoop9FhjsnHBxkSQsq9xH+iHrbfeulf9KQNtiuNZtD17YWtavhx+Vo0ORwSrCOxg9EOoM2Ezge9Lk7L0vRCOCSSXirRDzaoTSdNuN16ajj87Ao6AI+AIdI7AO2sv0nkinoIj4Ag4AgOEwKevm9R0Tqi4yBEqAEXhBLOs8QJD1nLMVT/1qU+V7lhgUKKuAXUUzVBuTSg1FjCwWcvniIsDWS+hbpGLCblgsNF6OdyjV15iiIBK0A2eS7pA5SfrXlQTWsYsKjMQhIO4/I8L5EWEReUJxFomVS+ocGPHji3VcshNJnFQkSiGOAI6qJ/sZI2otGXm1lDkC4Od/FAlguDUoYceGlWNStAN1TH8LAVJ6FKILEhj16hCseFIX+s7BI/gudCedKFkO+/Cpt+pPYdJp2m20lackd0p2h7fERjCCHCjMcwzfhAMXhi2MLI0WODOjbwMmujbGmhi8JO+aps3gzSSo+3o9dYAQXqN4sPAY8LC75BDDok720j6otMK6Wkx/5lcwCjM7UTbclfZ0VOO/qi+JitRj+R1FcEsnXfeeau8B8QdieuUwgV/pRPMVvRrNaJw9C4GsfrtpG+7Km4j/6p4femeSn3YtKVzzbql9hx+dpLHBKyKJN2Av26cJk9NxGnnTMBhjKNbnA0S+x1VpevujoAj4Ag4Ao6AI+AIOAKOwGBCAN3SmgOn5bZzchjUIqSJ+QU1IlG/M2tDTjszb0bfs51rK07OzK0J0ZtMWhDz9HrrV5sPurMbkT3tmbvHycafffbZ7WO0s75Aepf6cmoZRi73/EAIeak8MDGrCD3i9Qj92OJNsCZh3dbJGjHNK7eGIgxrf06lQjC0JTQFg5u7x9D3zR1A9tQqOsVFCAnBpK4iYYM/+r7t+2rnXVTl0457FSbtpKU4rbSVjymSm46AI+AINEJghhlmiJLXdLgwqqzaDXYJB5rozO3Fdlwsp+NSDOI5NRPNlNEOGlVSulXpwNhmsA06uoqgszfuvitsuIU5SqnquRUz3JLdSvCmw1pGtiYVTUcewIC0NTsxVNZI/Vri3VX9FE6MWJm424tBFM6aHF2b3GQnQa2WpQo/2qioCjf7PRDWnliAcc0ELdzeXnDhCep2aOdiYndyAkHlatV09SStIubhHQFHwBFwBBwBR8ARcASaRaDRuqEqHYTBUD3JWpE1LOoyuPAvnWtXxcc9tyZMT2Q2O6fXfL1efn/6059K7xlnnLG0t2KxgkZgILJMXFRcVpEknKv87RpWjPdO1og2n6o1FGFgXKNqkYseLcHU5t1y2SebHpxsFql8em72XaGisS/ehfLtxKyHSSfpErfZtuIS2Z0i7fEdgSGCAEeLNICECx1LNRJV1UN6l2NC66yzTgyCpPZAEjvc4QKHcuAPl/bFjm+RRRYpJcPZ5aRO7Fy3QjDsReHigeLzn/+8HuNxKN0wDBO43o43THD0lf3qV7+Kt0STCINdbre6zKDC0uyt0hXRi3CpU9YLHdCicNlTzVEwuQ+EWVU+5c3t1Dni1ICIyUQ9qXKFQwcXZDG1es4Uzprh0kf7OOjsVfjRFsXQ54bsVP92rqKSzKf9cxxRk28mNejW58ghjG0kyMOlN730B+bSbMVN6kNShrV9lp1vl2OLrW5ItVIeD+sIOAKOwHBDAOk/J0fAEXAEHIHmEYCBa9X4oRpijTXWKOaff/6oUoN582WXXZbVn21zsesXuVtGL0Ik3KnTDK288soNg1mhFNbF7RCqP6Qr+6c//WkRLrsswuXthQThUG+p9Vku/TfeeCPLwFdYWy7dJdXJGlHpYlatoRQG6e8777yzgNGMhHm4xDCqZZVEOOukMWPGxDUW9bTCUUiqIwjUDLFmsxsWts7NxG82DOumRtQIk0bx6/k321ackV0PRfdzBIYRAuywalcWiUrpQ64HgT3SwjEejkrlpGbrpdGuHwMf6jsgBlguQYB5hYoPGPHSxcWFG6gY0aDWTH52txlGnGVkozNbOMGUbmYCgH4r9HZD4ZbnZorQK0x6uUWvAA0c0l1pBUefmcqGqg2kBHLEcTVdNMFRKXvBYC58q246DlcVL6eDmbBM/kQwUdn5bpasHjYmG2yGVJEmI1X+3e5ehR/vWxszqBCybb9RnTgBISY2UiWnnXZaLx3eHB/shPim7bFMPctM007dmfii4mfbbbftVbY0rj87Ao6AI+AINEYAJrbV+9o4hodwBBwBR8ARQA2FiHWs1FDgxvwVSi8MjI7JX25NiO5rBEpYj8MoRad0XxHCKaLHH39c1qyJAJfUX3BKk3JBMKn33HPP4owzzogXx7MuRRWnaLvttpM1a5JvlW5uIth1GjhAnawRYwIf/VWtoWwY7PAa2KjQZgV8AnSRw1eBqDuMbJ0ex43NjFbeVV+8C/KtR6nEeC5ss5jk4jZya7atOCO7EZLu7wgMEwTY5YMhDGPq7rvvjnq26unMBRZ0eolg6A4UE5sO1t4IzXEdu+vKLdLseiNpCtN5jz32qLnRWGWuMi0zD0lcsBGxc6qLOJD45gIHTT4UJjXFKMbd3kadhmv3WVLVMIPZnc2poBDTP81D0rW4czty1eV8YCrdY80w75WPLQvl4+bmlFBPIYZo6tfoGUa8iEtHqxjZTOy08cIlI7QZG/fUU0+NF3fmJofsTMO0HYq00EILldW6/PLL47dSOhgL7x5pAogbz9FBb29fZ3Kem9TYyyRNcv1qTb9HGPUc+UvdKQTH/nj30LXXXlsjPc6FLTryiCol25Zh3HMJLnT44YfHewLiQ/J34403xnaFM6dFLrnkkhgC3f6SluHy0arJObr1XnzxxaiffsKECUnq/33kQh82DDiNwDeQI/w4dcBGn/ovvgPpSAcjK82jNMBk3Lhx8ZF+lE1CEccm9T2jxokLU1NS/0KfAdYQ44a+U/paMJpqqqnSqMWHH35YcJGSdNrT3+oehmZwYQGh+x24kKaZC4nZNEGyBqw4popkTa5sLDRJm3fD8WJwUvtiEScJIyRW0AephRyVtO+eZ/xtX3TvvffGjRf8IC4Trrp0mA0awkNsJCHZBQl38AK3lOy7Q8ehNn7TcNRPCzLCoTJr//33j/rw+R6QHMvhw8Wzag9ql+3Go0ykRZqQdEvSPhZYYIHoxh/fh+pdOn5k4f1fdNFF8Ykjq1zSDFn3KpxtPmx2qr+ICYQ/vombbropPiKF1exdFiqr/Tbaxchu9qlcmHLnMil96+DIt46f/bHQPuCAA2J0Trux2EY4QWnIjolEWD3JOVuGnL2Vy9Ry8d3NEXAEHIG+QGAgL6N9++23C6lzhNFadUE9c5d2ifkL6x3GeJjECy+8cDYp5my6YJE1vxXsyUVgLiNiPYCKQXt6WX6s8w466KD4yPhs5z44ogMbZi7E/FrrYxi7jdbHzFO4kytHrH3POuus0kv1sXOrVteIZWJ1LOR59NFHx1OfpI+ebkuoj2E+KKxgtiOFzkaDeC6sC4477rjsiWg2jb/5zW/GdwqTnPlzp+/CStcj6JeqRKH8t9xyi63GZLE301ackT1ZXo1n6gh0HwIswmFKaLG32mqrxZuM7c6fLTUMXi16cEdP7kAQiyiOI4kos93Rxp1OmsW7LiFgsETFSDOMDOJbBj6dvFVXYTt8sOIYGAyvKpUMTBS0ACdtGOE5YmBrl9CVpskATBExb5QeTGzccwSTAuYExM45zK10IIZxICY24SwjW8wb3HNHkezxNxhoTHBsHOrdri5z8kSimPLAVIQRy09MMvxF5CFJer0DJhi8T5h4bHrwHo855pia8tHeKLPiKr2hYvJN8B2zkXDggQfGi0nsxI964gcTWxggPQBZdSwwe1KC2WGlDNL2YdtB6pemxTPhxVTJ+Vs3mzbu9FeWESMGjt1AoX4w5ZSHPbIHQ8/ewA5DS4zs448/Pl52O8sss9gixIn+kUceWbrBlJVuOyupDk5VuhYlmQM+ilsm+JFF2KOepyoMdYdQH6QwnDYRsTmY9kFIs9vyp7r5JHFDGlxAo3SVpjVJW/4wQNlAYUL+yiuvRIY+fbrdCOUd0L+Kic1mIhN/pdEMLqQtAm/FlVuVSR/IsVfisNmQlo14XDDMxUwQ44OkV2AWiomNH/2OLQdubKgtuOCC8aQQz0gonXnmmeVGUBqe75PNhHSjCCa7mNhsZoJRWsd33323lxt5omqHjRXqABP2ggsuKDcJ8BexSaO2KvxhqquMbH7mxn7bN8A0pVztxqMstm3aOnLBEicuIPov3pfdcMKdzTTNa3hm40dp2O+f01J2gUdYSN8XduqluDxDOk1E30GfYev+3xD1/+230S5G6rPSnNQPwkARUU/6AeKoT6V/ZOwTIW1Nv5Smq/Dg1gkjW/m46Qg4Ao7AcEGA8dgS87J07XjHHXcUZ599dhmsVRVOzNW1XkP4gE12CTspURjlp5xySnxkfJb0svxzJgxpJKY1v9l3332L8847L15cacOjolCUO7kLY501GJc+nnzyyeW6wt53pfipyXwHJjhzJkuM0fvtt1/phFoKrT07WSOWCdaxsCEt9YwIa1A3jbuKZuckM888c7mWYOOadSdrD4SBWIOn7QGhK83zWHeQdqfvwq5VmMNZvgZlZo7QzKl81a9V0+JTT61oM23FGdmtou/hHYEhjABSp3SY7ObSsbKjycDFwn5E2I1l4YI7C2gW3uq8GQib1e/UKXwM8DfffHNMhkWn3YG1abO4Rmpb0odIGLGrqcHNhk3tqAIRsQi2jHIYEOAk6VQkuhgIGNTpdEmfhSm74ezOSqKT9Aib3nANc4BFITvi+BOfgZGyNkvoKYaxAjEZ4PgVEwgW1UhZwWirIvKyqljYEUcqm4ENfJls2A0LBl4rHWjVrtAmiIPecMoEk58fbtSRdoW+cqQIOe7FRYMcuQKrToidbDHfaatIksE0ZLBmwsZETox8yoIKEhE76cKadGDa876RDgBHNiKEreIMJRMGKu0OhhvviPeCRCnMHrBiE4Z2zHcPsTkkSQcw11E+Ng+Ix4T4pZdeiv0ITCXSFCHxSHhJUdq2wwRQbYe2R7uxJAaKdcvZc+GYRMLkgymT/mwZmGBSfjFvrP57+j/SkR/pwQBEagGm0OjRo6OkKpjAkIVBiOS6mFowO9lg0gTOqjqiDyC9HOmEAIzHqjCa+NK3VIURkxhmm8KwkSNVR/QR9GF8M0jaUH76OZWfssGsZcGg928ZWddff31k5uMGBuBliU0A5Ys7bWOjjTaKQTg9A1OcfoF4bBogpa6NAgLBUFW+PDeDixiwhAdvmz9uVfTtb387ShpTd5UNKSA2dSkbUreSZCINpEZIm36fOojohyQhLTeZtA358Q6uueaaUvLdXqZKeO6fYNOBMvB98i1SBo1thIHRnW5A4W7fN8+WWEBp048NC9JHbRRS8mwykK9OXfBe2fSi72cxJeYx9eAbZ+ObeQALdTZV7WIW6XnwaTceZbabSPY90m+xUcu7ZtOZhTtu9DFgRh3OOeecstosgDVW4Gi/cTaE7dimSJaRrb5EftQdhi/EhmozDAHFlWm/jXYxUr+kNGXiTp9jN1tYLIOR/dYZu3PfuhVkSPOwF2spPzcdAUfAEXAE8ggwRvJjDGc9xBqV00GMQ6jZYCyTtLJSQO8yG/+zzjqrnOqarGcQ8GJOwboSRi5zfNan9PHMWWFAixgLND+UW5XJvE2MbDa/EWBg7kseCDqgfpL1MMR8Xqey0vQ4FYWubK0r8K+StE7jsl5ljsEalzkh60jKojUe4SWcpbidrBGVRpVp5xNgA8bwGzR2MpeyAiGM8SIEfVhvM49gYwEJeuaNzOVoD6wxGJtFVoivk3eh08mkyztjQwUeDu+MdRpCAXbtpvz7yrRzB3gAvEOY85wcowyWGrUVZ2RbtNzuCAxzBHREGkauBhg6Zg1cOXgYlLko0u7w5cL1hRs6nO2uLcyveoxpFmwwMakLnTIDLhMFMZOqygRDC0YmDFY69ZRYLCMpqCPGTEjsDbtpeJ6R6qXDTgnGsRi5MGsgGCNirkaHBn/UC2kq1RM1IPwswaiyDGnrR74cd5MOL5jVOUIS1w7IhOG4lCZm5C81BExmYEaySCeOJHPJQ/koD9JlkmaZ/vJrxmQH/Ec/+lE5aWJzo2qDg0mclX6FacpArgkCTOsc41p1bKY8gy0MbZc2KMyYxOQIJo1l4DFJVd/AhgcMq5SYmMAMp23AmGRCDrMLxmzadmCkQjDJUkZ2mq6+YZnWH7fUPX1W+NQ9fU7DWX++MaQJpGO8Si0PRz2RPKlaLJCmTVd5pmajMK2mw8IBRi2EJLFlwirvtdZaK6qRgFHIJifPbEYgHQxzmAkpfvzYyIBgYlpmo9Ky5WfhQzi9c9KW1InCy6R/YmOlimy6Nox1bxYb4sO0hUnMd6F6V5WNBRPvF2K8kaQyCyw2O20ZYqCP/ljkIEFEHIj+C0aoPf2DO+MqzHMWbjp1g7slFoRIIFXlVeXOySP6ZhjaEBtW/HLENympLjZApOeSsGwuWwkyG59FG5uXlKHdeDY97LY+vCsY1SxuwQn8q8YvGPH08za+TRv3nF/qZp81dpMO45j1s2k3siteX2Fk8yNtFqka1/jWdeGWDce7uu+++wpOYmCyGczCOj0JkDK0bRpudwQcAUfAEahGQCesCAEDll9KrHOlio21G2tsGNrNEnHpx2FkI3DGmjJHzM+tJHMujHVjPsI6jXgQjFZ+OaJeVcx3BI7sGMSGulRv5NKSG2sQ1tusO/jliLUnAmeWOlkj2nRyduYgYKAT4EjDSyI+DQ9fQet8/NgYR7UeJ8a1RrICHDY+giWoBhR18i6YZyLQJeY/J9hTFXTM8eCXgHdfE/N/EW2UH4QgRcrIbtRWPqaE3HQEHAFHAASQ+OLoLAMhDN0qwg/GDVJQ2nmsCpu6w8RqRJK4s+Gk1xI3Ov5UhYYNix1pSzHneIaBik7PZkgS5nSwYk7YeNo9baSuBAYDEuxI/uaIneLcLmQubJUbAylMDg2kNhzMCqQbLZMqlQrXBgYDZU6ijIEFpj1H3tJ3hzQoC2Q7wNr8sfPeYAylAxTP1J33og0JJAjbIXbAWXRbtSc2Hd4nDDi7ey5/NgKQPEyPV+FPOwcXO2kS00HxOzFTPNO0UiZC6p8+t4Mf7YHvncmXVatj02Yjhk0du5MO4wZJ3FwccIM5h+43+92SpvCj7cBIrWo7CidT5bHPkkZWuvJL+w/c9culg5u+C6Vh343iWhNduLRrjuDlGLdMNKk7ag3Q4W/jKg9b7tSfZ1umnL9Np15a+EE2DfRyM3nNSfIilQujHp2EnMqxBEOedMCYdiNGrsLYPOSGad2xI1FD38g3Sx+WEvqd2YhEj2Qat1VceJdpGvWeqROLE8qYKxtqOegTOL1BOjAH7SYPDGokTOrlweLSLri+853vlOGFBcx0+p9c++K9Ib1F++Nd2LwUH9O6p3Y2M8DYSujYuDAzwQFpLhsXxjHS2Lb8Nh7lZcHOuEEfprjtxiO+SGnJZFGE9BnzAds/KbxOUdGe2VhVPEz7jRPe+lm70krfKWOiiPZq4zSyKx6mDdsJRjYd7PpWaa8w/HPfOgwEpLt4V6hqsaT4abp6tmHd7gg4Ao7AcEBA849m62rD07+ziY9wTEowGBGMQJ2EXcvYeW4aJ/fMfPP2IECCJHZuTUfebD7D9K0SsMilixtrWoTK2KDOEetQ5kPMHaoIBq6958oytavi4A5jlTVzupbED7xYA1bpHe9kjUj69YgT4JySs6d9bXjKy0k/NiO01pU/QhqsTZlL5urFOos5GAJ0KXXyLhBaoEwpsXZDzQnzAeY7UDvryjRd+8w8hFMBMPYtpfMx/Bq1lf8LRxh7mJCww65ddtlzJolK1yJm7gMhjJMj4AgMfgQ4UouaAI4+w9xGLymdHIMkHVCrg+tgQoSj7rpAEkZCbhBRfdA/ybF7fhwzhoEOTjD4rQoBhe9Pk114BkUW7PTPkqJrJU+k1znWhMoEmHGoPmCc6JRoP0h+c+SbI9yoNWl1EtVMGWi3lJ/3Qdk5Mp5jRuXSoozgxzvleLpVPZELPxTdkJhGxQp6U3n/SFXUY6gzVwBrjhZCSKOm7Y4+BIlJmE65yRrxNAexdrlpPiI/PTdrMl/JhU3Ts8/YIeKJrD11Q7UE9USnIYw8JmCDgagT/TzvG+J7sSoXcKM/pG/jm+2PeqkM9F/0DbS7/ugbqEs7hLoPxkDqzriQtu920qyKw6aaFmMs2lisQHw/vAcWF4y/fb24oN9Eeou2wEKXBRfjSCPieDE/VFlRJsY8+t1G1G68RunShth8pv0wBuYWR43SaMYfvNgAQGofSaIqqfRm0qoK0yxGuX4pTZMw/GhD+tbp2+mPcddakPcPfrQxfeuKS5rY6e/ZNLCXBaf56Tl3mdpAXvbIfEbq4WAiWQaRytiKCTOCEzYQUofCqJU0PKwj4Ah0BwKt9E+Mj8xzmeMyvtBnykzteqaW2O0PN+aJrFPonxijmFulYzqMWeau9LOdjGOsueizmaPS5yOo0BfzK8rGvAhMWGMx721mzkD9ESriJCdzDcacVPiEMFXE2Is6CuZlzDUYq1qN3+4asapMcud+Cc2nwZj6Maeut4ZSXEzGZ056MQcfEVTtNbsGbfdd0CZY87L2Zd4tvoct0+S212srzsie3G/H83cEHIGuRQDpJHas2SV/8MEHu7acXjBHYDAhACMkR9Zd9pyJm3XXs8wqprX8U5OyyE32nGndsKdEGk6OQKcIwMjWaSOOFYuR3Wm6Hr9vEUD9hvR6Mk+oOlnSt7nmU0v7HpgmkHW3dpuKdceePius3DFhXgwWRjYbDVJ7hSqdddZZR1Vqy5wwYUKpgxVVZblTAG0l7JEcAUdgwBGYXIxs9dEyqbi1WyCq3G2YwWTn7impUeO0Z9WJ5cFUJy9r/yDQqK18on+y9VQdAUfAERj8CKC/lQUqajs4NsTRYSdHwBHofwSYuItxksutnn9fT/ptXtaeliuXb706pPH92RHIIZBrV7lw7jawCOiyTfT5czx4cr2nen1SiogNa+02XJW7DYOdcE6OgCPgCDgCjkCzCCD5q7tRiIPKDydHIIdAM23FGdk55NzNEXAEHIGAALp/uUEYPdvoL4WZ7eQIOAKdIVDFKMm5y00mOVu7SoJbO2TTsvZ6adm8GjGqbdh6abqfIyAE7JFf7PZZYdycvAhwQuvmm2+OhUAfeivHmge65OqDbF8lN1sW3DjNkpLi2TjY7XMax58dAUfAEXAEHAEhgM5s5jKMnahogbh/BbUbTo6ARaCVtuKMbIuc2x0BR8ARSBDgEiQu8eLSRy6aqLrgIonmj46AI9APCMA8yTFW5FaVZStMF+UhkzSt3eahdBvlb+O43RGoh4DalMKkz3J3c/IhcMwxx8TMubBTR6QnX2nyOVf1WYS2bUrhMK17mqr6uEbh0niD6RlGPlJg7eqjRe9ts7pQLS7txiON999/P95XM5TvrLFYud0RcAQGHwLcXcE6WsQ9UlwY7eQIpAi00lackZ2i58+OgCPgCBgEvvjFLxaXXnpp3EW2N0+bIG51BByBAUZAzBdlW48BQxiYMI3CKC1r2nxsfDF1FNb6yc1NR6AdBLiMaf/9949RuUzQJbLbQbH/4nAJMhcGcsHj9ttv3xXvJ+2PcrVXH2XDpv2bwlj3NK12+9I0nW55fuSRR4pLLrkkXjzG5WGiRRZZpFhrrbWKjTfeuO47vuKKK4rbb789qqD717/+VaBqhrgbbLBBvDBa6aUml7eium7SpEnxEmwu9UJ93RJLLFGsueaavS5T56JKGO077LBDvIj1F7/4RXH//ffHS89Im4uUt91229guldeZZ54ZL/LiGT20XKSbEmly4pBLvxZffPHYptMw/uwIOAKOQCcIcDcBm3xcaLnooosW48aNa/oiw07y9biDD4FW2opf9jj43q+X2BFwBBwBR8ARGNQIWGaKrUjqruecad2w60d6sqdm6qfneqb1w26J9J0cAUfAEZicCFT1Q7iLOa0wMlVe+4xdz/Xszz33XLzkcP7551cylWYrl6lVJtKBR73LHq+66qriiCOOqJv6JptsUhx88MFlGHvZ45JLLhmZyaVnYiFtjkmnxOm+Qw45JHUun2FkczGllbKG+QONGTOmoNw6nl9G+sgyduzYyNDm8fLLLy+OOuqo6FN10SWM/FGjRsUw1JP6OjkCwwWBVvonvrnXXnutmGuuueLmFn0rG82YqV3P4Ch/mXKzZmrnWUQ8J0fAEeiNgEtk98bEXRwBR8ARcAQcAUdgMiDAhF2MlFz21j+1Kzzx+2Lin0s/LVtVPmk4lc1NR8ARcAT6A4FcX5T2Q7ZPk591a6ZcNl4z4bs1zDPPPFMysZGGhuGMVDOn8B599NFi/PjxBRLWl112WWQe56SZkYiGvvWtb0UVM2DD5eCoo4MOO+ywYvrpp4+XgUaH8Ddx4sSSiU2+XHY2xxxzFH/729+Kiy++OOZ9ww03ROnFHJOdckGrrbZalL6ecsopi1tuuaW49tpro/upp55abLjhhsU000xTrLrqqiUj+8YbbyyQdEvp1ltvLZ0I7+QIOAKOgCPgCAwGBJyRPRjekpfREXAEHAFHwBEYhgiIySJTENjn1E6YZpgtildlko78sEM8i5SHnq1pw1l3tzsCjoAj0NcI1OuLyCvtx3L5EwY1Ewqr5zSslUBM/QbT8wMPPFAWlwu9UQkigqH9uc99rjjwwAOj0+OPP14stdRS8q4xYSwvu+yypRtqZ1AJhOQ0hD/P4In+7WOPPTa6oyP2ggsuqFH3scYaaxQHHXRQ8atf/apA8nunnXYqCJfSHnvsUYwePbp0XmGFFYrpppsuqirBkfIiLQ7zfeTIkTE99NO+9dZbNfnRbq6//vqYDuWmzk6OgCPgCDgCjsBgQOBjg6GQXkZHwBFwBBwBR8ARGDoIsKivonp+xJE/Zs6uMPJvx7TMGuz62bTkVmXasG7/77tyHBwHbwN93waq+iC5W8zlhil3a5dblWn7V+yDlVDbAQOaC7wtE1v1sRLY6I/OEXqwLRNbYXDDD3rssceKhx9+ONphnj/77LPRjh58mweOlAlGtuiaa66RtTRnmGGGUnVI6Rgs6PMWvfrqq7LWSGHfcccdpTuWJ554opBe8Jy0dk1gf3AEHAFHwBFwBLoIAZfI7qKX4UVxBBwBR8ARcAQcgVoEYKggOSaz1rdW2pAwkA0vNxsvTUvPMglr7YqLm6gZKUiFddMRcAQcgf5CoJm+SGFkqizq59S34Z+68Yy0NoRdP6UxGM1NN9204Gfp7bffLp5//vmo3uP888+3Xll7Tv+1AsLIRpc1RJoLL7xwycTG7b333it++9vfYu1FqBx54403CqSod9tttxp/JMO5NC0lK7nNhaQipME/85nPRDUpN910U43O7ttuuy0Gwz/HkFcabjoCjoAj4Ag4At2GgDOyu+2NeHkcAUfAEXAEHIFhgICYJbmqVvnJPWeSjpgwNs16bkrHhrdu2KGU+YOb/LCLcuHk56Yj4Ag4Av2NgO2Xqvoj9XH48+NZP1s+JLWVhtLNhbNxBpMdZjK6o2EYP/jgg5F53Er5LfM4jTfLLLOUTi+88EK0P/3006XbfvvtV9qrLFwsl9KXv/zl1Knu8yc+8Yl4geNPf/rTyDh/8803oxoSIkmtyLrrrltMMcUUddNxT0fAEXAEHAFHoJsQcEZ2N70NL4sj4Ag4Ao6AIzCMEIApIkZJvWrnwsnNmqQhxozMeulaP6WDm7XrWWHrlZd4To6AI+AIDCQC9fokW460X7N+2PGvCqO+TWYad7A9v/TSS8U222xTw7xGEnquueYq5pxzzsjsPfPMM+tWCyZxFVm/d999NwZDR7YIKehGlJO8ZnOhVULtCIxsCPUiSIs/9dRTxZ///OfoZtWSRAf/cwQcAUfAEXAEuhyB6hG4ywvuxXMEHAFHwBFwBByBoYtAylDRs0xqLrs1m0FE4euFJQyUMonknvOLEfzPEXAEHIEuQUD9VdqPUTz1gzm/tPhKB1O/NMxgej7ggANKJvaOO+4YpZZnnHHGsgpIUTdiZKNfmksWc/S3v/2tdJbk9ogRI0q3W2+9dcCkoOeZZ56oBxzmNepFYGTffvvtsSyUbaGFFirL5RZHwBFwBBwBR2AwIOCM7MHwlryMjoAj4Ag4Ao6AI1AyXsSAARLZWzEtlIpn06ryt+4Kn7r5syPgCDgCA4lAFSO6yp2y2X4vV1b8pRfbhsddz7l4g8HtX//6V9SDTVlXX331YsyYMb2KbRnRvTw/ckDH9HzzzZf1vuuuu0p3qQOxjGwugURvdo6Qnn7rrbcKwtfTw52LW+W20UYbFccff3xx7733Fq+//npx3XXXxaDrr79+bAtV8dzdEXAEHAFHwBHoRgSckd2Nb8XL5Ag4Ao6AI+AIDBME6jFUmvVTuJzZKoxKw8bDDarHGLLh3e4IOAKOQDciUNWX4Q7jmj5OYWRSj9Run7uxnvXK9Morr5Tes846a2mXBRzsZY+Woa8wmBdeeGEBI1iMavnBKL7gggviIypEFltssWj/+te/Xl68OH78+OKHP/xhYVWQEAhJ6VNPPTWG32uvvaLZF3+rrbZaZGST1jnnnBMvoMS+xhprYDg5Ao6AI+AIOAKDCoHWFW0Nqup5YR0BR8ARcAQcAUdgMCOQMkzsc86Om/1Rd/vciR39pLlfJ2l63Nr35Xg4Ht4GOm8DuX4Ktxy2qbvGi1xYuSnMYDTtRYwXXXRR8cADD0QmPpLakyZNKnbbbbd4AaTqhi7pDz/8UI+lSfjNNtus+PWvfx2lnP/5z38W99xzT7HddtuVakt22mmnYuqpp45xpp122mLnnXeO9okTJxY77LBD8fvf/74gHZjrV199dXHkkUeW6Y8cObK0d2r5whe+UKywwgoxmV/84hfRXGSRRQqpPek0fY/vCDgCjoAj4AgMJAIukT2QaHtejoAj4Ag4Ao6AI9ALAZgj9aSdU3/73MiOP2QlDa29V2HacLBlaCO6R3EEHAFHoM8QUJ/XbILqD9N4cpdJetihNGx0HCR/U0wxRVTZMWHChMhEFnPZFh8p6t/97nfRCQlpGNynnHKKDVJwOeQbb7xR7LvvvjXuelh55ZWLzTffXI/RhPH90EMPFejI/sMf/hCZ2TUBPno46qijiq985Ss5r7bd1l133XjZoxJAmtzJEXAEHAFHwBEYjAg4I3swvjUvsyPgCDgCjoAjMMQQaJUZbMOndqBJmS9ivFj3NJwgtenJrZHZTpxGabq/I+AIOAKtIKB+rp04Nq76STGulZ7CyJT7YDA/+clPlsU88MADi09/+tOFpJPlgSqQUaNGFaNHjy7OOOOMAn3VVfSjH/2ouOSSS4rLLrusJghSzjCsv/Wtb/Vi+E855ZTFiSeeWFx++eUxbaS9LS244ILFHnvsUSyzzDLWubSnqkhKjyYsyy+/fKnahOAw2p0cAUfAEXAEHIHBiMD/hRuXe5iMMFHRZEX2nEklpSsMc4455hiM9fYyOwKOQAYBJtRIiEAcQWSSD/3973+PxyWxL7744sWXvvQlrMVrr70Wj2RiZ/Kd0zWIn1M1An/5y1+idA4hll566WK66aarDtyFPjfeeGMcO2afffbKS4+6sNjDpkgcW37wwQcL2hlHi7faaqs+aWP0E/QXzB+4LKuvmBqah1S9oJx/6pY+//vf/47Sb1zMRZnDvKfgiDfSbvRna6+9djH99NPXZJmmUeM5DB6ee+65eBnYI488Eo+8/+c//4nzvTnnnLNYcsklK5ksnUBDW+WCNaQlV1pppU6S8rgDiAD9C3MBvinGsG6ll19+uXj44YfL4qEzGJUa9Yh+jr4T5qPUMhD+pZdeKvg2IJiDmitxQR+X6UFI9H7xi1+M9v7+q+qvrLvs1sSuH3046zo9Y2q9Z+24PfPMM7HPHDFiRMOqvbP2Ir3CfPq6Sb3cJpcDaj14x6gFYQ7LOGnpxRdfLN59992COU4VExl/+sz33nsvhuNbaJbIn7gf//jHo67tVuI2m4eHcwQcgTwCrfRPzB8Z6+aaa644dtBnWrVM1i4/csVuf3KzZmrnWUTcbqM//elPBRfWQt/85jfjBlm3lXEol4cx+Mknn4ztatVVV60cm/oLg7vvvrt4++234xyHux8mF7lE9uRC3vN1BLoQgUsvvbQYN25cLBn6+2DyQE899VSx1lprRTtHK8eOHRvtLArl/pOf/KTyiGQMPEz/3n///bhIovqf+9zn4s9CwWCA5A7EMVeOfg4kvfDCC3GxykJ9xhlnbDnrNddcM8ah3JTfqSgavfOBwAjGw6677lqcffbZNdkttdRSRTOTDiYoHJmGaBe0D0tnnXVWceaZZ0YnLrbiiPVAEBN66mYpdbPPN998czza/Y9//MNG6WU/4ogjiv33379kyHfjwqFXofvB4Z133onH5M8999xeqaMHVrTssssWhx9+eGTiya1Tk7EH/bIw/2AeOQ0OBI4++ujihhtuiIWFoWfp1VdfLWhT0GyzzWa9Btx+wgknxMv1lDGbsCuuuKIes+Zhhx2WrRvStAcccECM89vf/ra8zO/pp58uNthgg+hOfnvuuWc23W51TPs99aWYslN2PXdrPVopFxLYc889d2UUq0+7KhDj4/zzz1/lXded/BdaaKG6YdzTEXAEHAGLQKM5ug3bH3ZOqjAHhB5//PFi3nnnjXb/GxgEuE8hx68ZmNyL4tvf/nYUZOT00eScr9cXRRgoNDwfR8ARcASGKAJPPPFElNBBmocb6ruNWEBRtm222abbijZoy9MN7/y6667rxcRuBdALL7ywbLdIXA4UwSBpRDkmSuqG1CAMNjbaUiY27T0lGFYbb7xxPH2itFox0/QG4zNMOKROUyb2Zz/72V6MHjbgkGiFoefkCFQhwKY3C1x+ku6tCtuf7ki9puPv+eef359ZTva0W+m/FJZCy25NVUZuenbTEXAEHAFHYOARmFxz9IGvqefoCFQj4BLZ1di4jyPgCHyEABIjUieiI7QOjiMAAmoXSJs7dQ8Cd955Z1mY4447rty5Lx2HgAWmSk46m6qxMYPuUhG6SvlxyoS2itQ8J0qQMj7kkENisOuvvz76c8FXIxU/Vfkqv8FmwsS2UoEwr7ngDFURqJDjyCyMyFtuuaXgErL77rsvVnHrrbeOfQBHSzsl3qfI2uXmZnciwLeCFD0qYeq9N/zq+fdn7XKnhdCNfNJJJ/VSK1RVDlv21K7nqaeeulQnwlxJ7lVpDqR7M2UhjPo27DZO6jeQZfe8HAFHwBFwBBwBR+C/CDC/0Prb3v0w3PBxRvZwe+NeX0egDQQWWGCBqFe2jageZYgjgL5hp+5DQGpBKBlM3Srdnt1X8v9KBIqZ0qh8lrmisLfffnsNExvG63e+8x15R0YNTDdUrPCDWbvhhhtGyW1038LcQpq7Xhksg6dMeBBbkEgXccz+2muvjRL5csNEhyv60NFfvckmmxSoZoBQySLGdnTo8A9shxq+HULS1dGblWyenO8V1Wci1AipvXNJ32677SavXqZth9ZuA9p6MVeiD+lGaqY/s3VMw8tPZjfW0cvkCDgCjoAj4AgMdQRQHclvuJOrFhnuLcDr7wj0EwJvvvlmvDynk+RhxnF5To6kh5iLN7iIrB1CdyeXM3UjffDBB1G3NjpGWyWwZzHN5UXdQrxLLtuiXv1BvEvaQjvEsXMuceFS03aPv9drq+2UKReHi/C4uLAZspeYcaJioIj3AJbo72uVUAGi77EVZglhFZ73Z5nWxx57bHHggQeW/pRJ4WWiTgNJY9H3v//9qPNN/vXMDz/8MF6GmEu3Xjz5oV+cvkzPrZrEp923Gs+GR3UMDD0ISWyk+ZHCtmGs/VOf+lRx0UUXxfD8cUkjl5XZMO3YywSDxcbvFGP6QdqjTbMVO/nTD+fi0Ne+8sorcQzK+ddzoy+sSrdePPwY8+hPKVujsP3hXw+TND+919R9oJ654+M3v/lNLAanMnbYYQcVqUDXf71ylAGDJQ0nv9S92Wf6Kvp0NoOZ5zQbz4Zj7KIdwHS27o3slJ12y3hC2BylaSgMedHvODkCjoAjMFwR0LyilfprLsOcrd21Riv55cIyF2Le0p/E2NLuWs+uA/q6jKzTJif2fVE3LiZuh6h3FT+lXnqM98wxtDarF3ag/Vg7OSN7oFH3/ByBQYjAH//4x2KZZZaJvyuuuKKyBjA0Nt9884LLcbj8DabIggsuGCWedLtxGhnpKNLebrvtoheXRhx00EHxiD+3xz/00ENlFJglMKlmmGGGAmbKV77ylXiMl2M1SAlyVDgljhSr7BrAuYRp5MiR8ZZl1ArIX5c3pWnomYvzFPZXv/qVnLMmx/IJu8UWW5T+csP91ltvLd2t5d577y3WWWedeEyb+nF0iPpysQKL1hzB1EBXLRiw+AR7LmAAf+Lutdde5YWTxL/jjjvKekh/MPmqbieeeGIum6wbOBLv0EMP7eXPJVi0B8rEu/zyl78c60X7+N73vhcHx16R6jhQT1QYkB/thoF59913LxZeeOH4LjneTtqoO9DlY1XJUV/CTTPNNAXHwYnHEXmkTilzTsK0UVuFYUrZWn3nVWVkokubW2+99eJ75F1ynIz6jh49uvjDH/5QExWmBG2AMthvgRutcaNejYi8CHvMMceUQWH84MYvN4lionPBBRcUSy65ZHwPYDnttNNGvbjopcW/irj5fOedd479BO8CtR+o/+A7b1U3N+2MC1AeeOCBmB3tf4899iiztoyZ0jFYcCdPXdKG3/HHHx/dFYfvb7nllivWX3/9yEREXQsM8KmmmqqYddZZY/vGj/o2WqDAKN5yyy1j/zXTTDPF9selqeSZk+ZE/Ql583v22WcL+mOkSOeZZ56C+HxX9BVc/FLVR9j6pnbatYi+Yvrpp9djpQm2vDcR/RkXNaqcfAv16JxzzinDciFnSnzrnWD8/PPPR2mVr33ta7E/pE60T8aWXLsivMqO/m8WnD/72c+KrbbaKvbBO+20U1lE6ok74w7fJO+f73L2oHsd6X8m/VXE++GCJPJig4n3xnvkfdJ26xFMz/322y/GJT8uT6T9ER+scotT+nLVq2ohQntde+21YzhJKlOOZjFhDCUPXfwLk5NvA7ebbrqprBJ9N25g15dtpcygwsJ7FJE3l9fqkmrmJffff7+8OzZJT3hfeeWVvdLjHXBJLu2SCwIZp+kv+Z6Q5uY9sjizxGaH0mT+xYYr7Zj+mDGLdsDYxykJ3lkVwVg4+eSTy/FkzjnnjPFot3vvvXfsW9TfYVqiD2fzin4Lfef0lUsssYQN4nZHwBFwBIY0AszPmKctv/zycbxnw585N3Mo1r85Yi7xy1/+slhllVXieE1/z7yNU4H0oT/+8Y+bFlAh/Xbm6MwhR40aVdDnMzdnjUg5WBM0mnfk6pRzo46Mq8zjVT/GLcYqxqx6VG8dMHHixHpRG/pRd9Z61Jd1KGMl6wzWBqxnfv7zn5frGzt3Q6BF6556c6c11lgjhsutgSlcO3WDB0De48ePj/WjDswRqQNzRog1v8r3zDPPRLf0j7X+ZpttFuep1Js5B2t2BHxyaw3FZ7xn7Uk5aC+sMcCM9sMcRRd4K3yzJnMZlfmMM86ojIZgjcKx5rHEuzjllFPiPAQ+EJIAPWFy3IMZdlDiL7zInvBye0Ile4JkVU+4jbLnhRde6AkTpPgLzKQefgG4UFcnR8ARGCoIhCP1cJziLwweZbXCQq90Dx1I6R4619I9XPxV2pVGagamchlXlnDBWowXFuM9gbnYExZ0NekEhmIMGphTNe5p2noOkwwlHc0wEJTxAlO8JywWy2fiHHnkkTXPoZOsiW8fKKPyCYt169XLvu2225ZhFceaYfCMcS699NIyXBhwSrsNKzv5hwGkJq8wSeoJi/O68YgfJlyxTyfyeeedVzf8jjvuWJNHvQeVbd11160JFm60rpuHysS40ywFRm2ZZmAE9AQmQPmsclgzTC57wCelwGysG09p3HbbbTVRG7XVwAyqm67eeU2iFQ/gEhhDddOjnEGisCcwomIqQdqgbnjaTyMKGyd102Dsh8IGQhmuUfurak9h4tvrexf2MgMjLNaPOjbzGzNmTFmusFkS3z9toNEvME57wsZLGZe2hZt+3/jGN0q/MBEs7SqnNcNCo4f+QXFlvvvuuz1hsls3Lvkyt1IczLApUcYJF/zUxYx3HDanauLbtFJ7YJqVaVMH5n1pmKrnIN0R+yP6pMAk6wmT1Jq0aI9VcW1fyhyUcH2BMekE3eh1MaKeYaOrpmxhEVqWPTDsegLDrnwmfFigxfDnNeg7Cau+Nq07edh6Ezb9BSZ3TbmUxl133dXT6Ntk7AwbwTXxw+KnzEM4K02ZtEuVY9NNNy3jN4sJ2Cg+aVIGPedM2ninbUVlb2TSNjWnwKSuxOE7Utl22WWXss5pemnd5B82w8v4zI/kzhxG6TKfkjsm+Dd6/8QNi8eynMRj/aU0g8qjmu9E7jKp46RJk+L3yDfJ980vLKZ7wsKwTEfhUxNcmAMFxkP88Q0/+eSTlWNR2JjpafR7dcW5e9Jfozju3xhXx8gx8jbQeRtI+yaeq3ANm891+9Crrroqzr+CtHaZRhAEqRuHPjhsDPYwn6qa48ZJ90d/jeYBmqMTnDSDgFbD/JknUOdWiLmKxo8gxFHa5WZNxr2wyZtNvtl1QDZyHUfm/IyXthypnfHS8i4YJ0V2jVO13meMVZqs31Nqt25Kk/UMazw9yySfKn4NfpTru9/9bq94io/JPMzWl3gQ4z/zQBs2tS+22GJxnqt0/huz8T/rC6UVBG8qIwSBkDLcI488UoZjPkLeSgPTdWQHFJwcAUegcwQkVRc6xyi1g8RRGFCLMLAXXJ4GsZPMDmHuYjB2bJEokoQw4UOHFXcDcVt55ZVxisQuNs/otw0L0yh9et1110U/pKr32WefrE5gpHeRZhSFwTXu6iFxeu6550ZnJLg5fpwS0q9hQRedkepiR7serbjiilFKD6lhdqohdu/RMQvNNddc0bR/gakdH5dddtmos5fdYySwrrnmmuhO/ugjZWdWxM6kjvmHQbkIDOUiMITizi3S7Eifgx+7mkjpgg31VhpIkIrkxk5oJ8RR6cDIL5NA2p56I0X46KOPxkvkwqI+lonycPt2q8RFfSKkJdFzTD3ZuRZehwW9v0hYH3zwwQpaIImteuKIJCJ4Iw2HSgyk5dRGkGbkPaZU1VaRPkA6s5V3nqbNc2BexF1zW8exY8dGqWGkHfmm0AMNoSONOiKhze606gYG1AcKjOQo/YF0fyPafvvtoxoG8kYyFQKD+eefP35T7OqnpPbHd4GkSphExXaq7x79tEj8ffWrXy2j8p7CZKl85h3SbpFG5NJFSYnQbqgrEp5QmNGUcXIWvTv8eLdIFjaKQ1jCLbXUUlEyknYEdki402blHy3hT6cxkEoEG8Ig1YmUMUQfQl+mPjE6hj+k3MPGWXzkW0X6mXaHVAgYItFDvtSV0wxIQaSEZAkEVuRPH4HkJzqtIfqIsInUtO48K4HC+0HCuFmi3fETIR1K+znvvPOiE21Q5VUYzDAxLftSJDxzfWm7GCMZbk8e8F3Qn9GuOKXBu4GQHiZsbixCCgb8RXw3YEO/Rv1E9HFIt6hfO/3006OqCPrafffdN0r6KCySKORF24KIR1+N9BJt5wc/+EF0R1obSS30joueeOKJ+F3pmbIwljKGBAZ3HF9Ilx8SUbSjvlYnVIWJymRN6iTdjbRL9UOBYRy/M9pJX7YVm3dqR4+7MCd/3RVA3yD60Y9+FKWM+Cb7k7YL46DmEMwFaAOMW7Qf5kVqA2AWmNFxfpOWR2MZ8yz6ddJBbQpSfRB15VTAxRdfXEalP2a+JMkm2jP906KLLlrQtpDsYq4G8b3S9jlJp36Tdo4EPYREFt8sODIWOTkCjoAjMFwQCMzeWFXWiMwX6VtRS8ecFWJOxjyDeTDEulRrS545aci6NTBZYz972mmn4Rzn9Kzt7Mmv6JH5a2WOzjzESr4inYtkOPM2xhykkSHWgUi6trMWI77m66zNmZuMGDEijmGkz1qPcY8TcZwYYuwXtbsOUPx6JvMxjZeE48Qk0vOac1FXxst0nl4vzVb8+qJunAyWVDZ5M0fh9GgjYg7AqWeIOKy/GNNZa1Bv1mbMy1izkodda9C2tYYmPvMM1htIYTPfhE+htR3+A0msn5Q3c5944tYlsktGv1scgWGPQNUOXzMS2aEz6wmDWJS0skCyI2x3pAPT0Hr3SMqV+PzYbQ4LuSjJpIBhoIl++Ifj7HIuTXZekQhWGqGjK/2sRLb8kaZCulcUGHZl3MA4k3ONaXefKU+zFBiCZdqBkdUrmpXIpnxholNTdyKEo9FlGuweWwJP1QtJuJSshFi40C71LqXV0nR7BaxwUN5WIptdaLkHRnWvmJz44T0TJgyyWanpXpGCg5XIVlx7ckBxAmOizJ9wdjfd7lIHdRiKUppIolWVrZm2SkKN3nmZWYUlTHzL8rNrHjZRakLS3sPxrjIMGKYnCcKEuPRP/WoSq3gIDP0yfmCU9AplpRXAOExke4Wx3304ylb60ydYyUSkTVNCep10+aV9BmGrJFf07ogXNhQqw4Fh7hcYS2W+SDYqjP3OSJt3JD+Z9CO8C5WbfkJ+YSJfulN3TrjJDxNJ0bAJUYZBclv+SBgrTUwkbJCylD+mPQERVMnU+Nlwqf22cOpAaW+00UZNx0vT0TPvUukhuS53a4YNpjJMYFiXYTrFmP7BtquwUCvTVv62LyU/uVvpY5U/TOjjaUWFsX11UDVTxpV/WBjU9B1IxcjPfo9hg6x0lz/527ZDnyW/wFws8QoMyCg5JT9Mvm/b7pEKk79tU0hBy92afI+qM5I48msGE8JaqWXFlUl5lbbFA/9O2orSb2Qi3az8GStseN6v/HLfM2Gr6sY7VFzmR0rXjrdBjUfpzrii8Jwm4p0pjsxwlLkMExbhpT+nYhUXk+/btg/i2/6FMJI8B/NwRLiMz/fx9NNPR0k9wvDNILVucUIKjPJR5rA5V8ZFapB+i9NCjAnMN6okF617KxKPNp7bO5c2dQwdQ28D9dtAK/0TfSsnOuGdMZ4yx0RK1K45mENKItuOv2HDMM7b6JP5cdomMDvL/pWxsmpem86PeW40R0cC2o4b5J8SJx5tGMavZsmuiUmDtTn1ssRaz0rQHhbmfqK+WAcordQMakRr5lPwAVIKQlW9TvVaaXa7xrFrSJsO9RV+ViK707opTZnwVqxkMmWo4tcwvise4z3zB0usHWzdWBOLwoZ1GZf5KGualGhHSh+TNWqz1KlEtp3fc8IN+lgohJMj4Ag4An2CAHqNUv2qSJch8cTuGYSUJ7t6VYQ0GdJSVtLPSsexO5gSF9sh2SQKg46svUx2GtmlRleUiN1GJCMhdHqya2kp9JVRXypuSEKxq9sfFDrpuItq604+7PKL2NEWsUMKnhCYobsyJaTaReyMDwRxCYoIScSU0J+GPjEkEtHfLIm5NFyjZ3R45Xan0d2LlL3ISp3fdtttcq6R3JQj+sAWWmih+Ei5kPivolxbrQrbrDttDakNEXVUeeRGe+fkgXTSUk7CTS5CigQpjJS22Wab0ilMYEo7O/qSTETfGlIBKSEVoG+dNo4kv6VUhyt+gSkTpT8ULifpKz/i25/c0RcrkpSinmUi2YmUYkr0QVZ6wuoZp54iJNTpRyyhb5kTAPQBEH1mmCTbINGOP/oY0z4CaRNRUEUga0PT6tab99QCkAAAQABJREFUbbbZGoZvFMD2pUhV5/pSSQGBARLtOWoHY06+qF2hAzDXrpA4Vd+Qa1cqC2MEku12PGumX0NfNHoFkXpSv0Y7ksQsUrjoW0+JE0ySyMWPbwQKi5JSSiosLOI4ZMcuwqDjn/qKGt0PoHCtmjlMWk3Dhu+rtmLTtHYkjnRSge8GCWRLnCAR9Xf/afWyo6uUd5YSEn6i3LgpP04Noa/SEvMr+y1prGc8oU2KuMsAPZspSXoLd51uo38Mi9wYlPJyugud7E6OgCPgCAxHBBgDGatTQtJZ811OfXJXAmTnDJzUTInTd8xHmDNI93Eapt1nO/9kvRAEFXolxXwEXdAinRjUc7Mm4yvrLJ14UjzWekEQQ49x7qp5UV+sA8qEEwv3YigfTn7au3IUlDU/c7z+oL6sG1LuzFWRqG6G7FyQ05G5tUZggpdrDS681lrDtgXWLMzRUqIdhU2M1HlAnjkNLQobSNH6MTm46Qg4Ao5AJwgwWKBWIUcMbkwARHZRJzdMGHj2iIv8uCwChiI/jidZYqHGxAHmUCNiQGDCkCPUjog4amuJoyw6lguTNGUi2bCd2GGywNBKCQaGFqlWFQBHkoUL6iZSClJV5fGi1K8/n7n8QgTTCsxhrsB4FwWpr3jMH9UpMI9bpSCBmJ2YKR1UcYjsxY0c9wKzsGPea9LFYA4zrOoiTqWHWdVWbZh27EHarWTGsgkhZnUuLTEZ8IOpPrnIMoRsGewkyE7ibVmtGggbFzsMH1HuktmUEQ2D31KQVLSPde1Ky7bRKqaN1LfkEmRBQ9uE2DShf4J0YQ2TSotL9PzoDwYlfQAEI0rH+T/yjgZYt9JH2Lg5OxuNIvqLviCLT/rebF/KBkhVX2rTSMtUhbFtV4SpItuuchfyEc+OV0pHaqF4hiHIRhyqK2ybYcHEMVvGEPVrqFIRsUFTReHETOmlxZ+97BhVNPFymzLU/yyki1odfu0uRv+XWt6WwyQfsnlX+57bbStVufGORKiYSQl1G4ytEHMI+57SsJ0+o1aGdsLPjk1Kl80OGMWNiCPrqPfIkeYI+GnBZ8cTGOWLLLJIr6j0ffPNN19sO3xDHJPHjYWiNqLYTE+Z570ScgdHwBFwBIYwAqjuqiI7l5WqDavCis15VCmyHkF9oIhNbsJzEW9fkl33wMiuItZiIi4ib4cY09L5t9JBBZpVIyhhAztfs9gpnkw7X0vnCAqTmnbexJq9ihBKkxBbVZh23Puybgiu5Ob8VeXSZfeN1hqai7LWkLCg4pI2KsSqiLY8OWiLLbYos4Wfg/DPJ0oXtzgCjoAj0AECViI6l4yVDLZSgDZsbscYfxjh/GBMMUCgUxQdvuitRpekdl5tWjm77QRTfxhEGtDRVbbnnnuWQaTjGgd1/qVnH1rmnnvuytSqJglibCCFzmIchhnSqwzkmjBUJtpPHjPOOGPB5EFSbkh4ScqLdgIDAUlsFvdVjKxGRWMQs0y4NLydnKAHVKQJAQwFJnpgBvOH9iTdWwpbz6xqq/XiNOOnDRPCpps2aXy7Q9+fTJg03/RZpy1Sd5ghonBkUtb43eohJ90iP/tdS8+u/FKTvGAEUxZhyKZPKo2Qxkufn3rqqdKJCbitgzzQUZxzx5/vkVMCkoqFkYRecdoXRD3qMYRsnWEipfnQR6RuMeHwZ/uIqjAKK9O+u3DxS2XaCt+MSV+q/hOJF9mJazcJ6UurytkqxmyA2m8gx7BT2S3GnBSgDLYcLD61GaE4mEgX2X4Nhp90Y6pfQxI77des3naktnLSQTYf7EhiUya1ZdzQrWnLiZuIfg1mZEo2PHb7rLDWzYax7lWYkIYNZ+05v9S/L9qK6mFN+ht7EodNIat3XGHZrFJ7QIorZSbb8lq74mPiLj+Z8tcz45zGOt4pYw9zF9osG/uSoLbxFFcmftxVYJ8VHtN+/zwTzp7OQFd8Li6bbbiPGDGiADee+dm+kE0Bu1lOOOKk5SZfp//f3nnATXdUZXzFhoKgWLAnUbFGICqCSExQRBNAI0GxJ4pABBU0QSkWxIgQJTTFFopoABsqgqKCAUURLICKWLH3Quzd9fwneS5nZ2fu3m3vu+/3Pef32517p9/nzp05c+bMGSNgBIzAqYgAi9f0jXVfy7Nm7WstAMIPwMswV4XYsaddeyj8IEhFK3qMDy4J1/xDKUfzP3i8bJe6zooxkPkUQkzGQhYwx3Yz1um5hzcZI+Yymkcz/sEjCxPSjT2/xmfirZoHEAcKs1c3XMT/GC/IGBYm5soccEiwg4tdPltWoFhVNd57nmtgD7xHGVfaKwpewpf581ibYY7P3Erxe2Xs2p9dumiZU3d+D3vYwyzI3jXIzs8InK4IrDokjEPJRD1B9tjWKgQgaGZrcFZe67itLbVKT6fNYUwIsRFosjWMSSMTNh1eFnakZ2cl0wNKuyu3td14Vd5sQWbrsITGdXwEMscx2cQ0Ahpij44tSPmdITjmx7Y3tqOxrWkTUy0tzf387AgN9Oy5fDQh2D7Ftqk8kOe0U67H2uqU9L04CD5FMAtjhDYhP55DzMtY/H2Frdtute2S+kx9Bxy0N4WYNEj4Rz+zjiAbJjALHVs7TMivJQzKdcvmKMI+3YL2DfGmPnPru10X61yv1jXCK1H+TuQ35nJYkDQzwn78LE6IL9G37Us3wZj+YFftaszECv0V24HRksl41f0aQlT1aywQZJry/jVByGlXjbG5jF1fj2GyTVnbtpVe2RwQKwyJ09O8z+kZQ9Fmr0235DjbXLMIz06e3uFS6svHypAG+VicHJZNkbUWZ3Lc+pq+K1MW1GR/XxsBI2AETgcEwt74pMcU7wa/xmG8LJBysGMe+9nNxQ9taYTZ8Ay7ml/mHZBT5irs8pE2Lv3+uoLsVWNLnv9rTNoVv9Z6IdksYC67FXcKPq10Y367ejYWIVqLJr2y845t4uT21kuDP+01z7FWvU/SwBNmHgu/fRMLHvDdCLC1484a2ftG3fkbgdMEAdkr6j1u7lB7nWTPHyF2HIQxZI32GyYXEDSjNYmWIva5Oc15jFYJBtnqjiAbwsZVHExRhK5iSmRbtUQ4gD+0itGUEwPCJBeBEppXDIAIihEKoUmoZzjKarM1iR/ahZjrgKHDBrnqwoCEdjZa5C1b12N1VR5T4uR2xda+fIo3GhYInGhDtCVwQ+tyle20nOdYHdYNkzkC0q0y9YB5FH1XvOuTQjDrYoDYGiZNxbH6t+y/t+LTJ2hbJ6fFI3ScSrJLTHw0Emp7f/ir3lz3KA6aGYJgonNb4RtFCDqF+Db2TfQNIp6NLYY90yeKJ5dtqBLm5nZLOKYc1JeiiYMZHIS9+m7H+upNMKbM3K6YOG7arjIm5FtT3a9hv7Du19DEol+mX8uLbmyTrW011/lzf7Ob3ax4Z1z3JUiMw39aVVjwW4XJQuQ1b7ZpK72i1PZ64S1/+lLO0MjboFvxNvFDu5mFXfXXjDPYtUdbDCEC4w/9/a778Sz4hl9YRSzSoXEI5YUT2iy8hbS1EZSoja7KsxX+b/dYNnHSimc/I2AEjMChIIDQmbNY2GVHXymlBl3rnn5c1+zSQ9kIRSx24cA3MRfS+Q08G+eJoCjFXGhsx95UHDLfMHZmlPLLCjQ827rE/H9ssTvzLlL0yPzarucBWcgKP57xqJ9tCj51Gt33eKddPVtWNFGZY24918hnX4ylY66R33uew/TSjZ3j0Usz1b+HK+mR42CyFMUDzluzIHsqqo5nBIzAKAJ5W3crYjbvgMCwRS3BEfFgAERs/802s+SfbY7Jr3ZXCTYQAMOAIJy55pprivAFATnEhLB1oF1dxlHes5ovITbCfQR4eSBTXWC8jpN43/wQEPOe2I7PgWfSnGVldV1BNlu3mFSLWayfL2uTycwIK84SYvM+0drLJm+UB5q5q6jXVlelWxWev41V31Te2YAA96QQWtM68BWb0KsWmNZ5LkwV6GBFmB2ExjCVmSSoyX7svMiHpLRs6io+2/Vb2tqEk3feVkg8TOAguKK9IxBs2chV3kft8v0guNO2Tw6BmSLI5jllPoU6Y04jU92XcrirzIpM6UvXxZiyd9Wupn7brX6NhTL1a9dee23p1/K3yRiCQHAqZXvICEMxydQiNMUe8YhHlCAWL1tmNFrp8JOGVC8c/6mYjOXRC9u2rdT5MjGVtg5hTKI5T6JHT3ziE2eXX355CWbc34cgm4M8JcTGLviTnvSkJbuX20yoe89GvyPK263ll10Wf9Do4ttGMz2PRWw9v+yyywbTI7RFJr5juCrv1eJzxbRrBIyAETh+BHr9muaAMvGGtiw8lFyu9aufgvknJjjoSxlvGJfgEWTSEr6Bc1XyWRl1HlPvqT98AEoB7DJkTiOzinUe9Pf53KpNFq0ZW8YW6PNOR41Ju+LX6ufhHjNrKBhAyB7GzDRmfr0kWOOvxzvt6tl676xXxWxecZO5htoMu9JRlJLp0ro8+E0psdRhu7hH+W0VYRKHnQw3WRXR4UbACBiBKQiwOjamlc2BFqKp2pXEZ2VQHSYDYEuITTwJdLnelGBAOFALggFg1RxGA8LsSI+5KRGO4U8HyFE0ApSWEBuBkCbQR1VF7MBixgUbzrUWGAIRmMGnPOUpQ3U2eXcwfb0t2mSMEFMkQXY+gIN21BJiI9BEc/S4CEZCxPONmQxBOCKCcTopdPbZZw9VlXBz8EgXCFfRCuSXBVMpytIlOPCtih7ykIcUDRrd42qiIRc/BEtitnkHCG16hLCrRzDPEmTSX8mOuxZq6MvyQTR1PkxwEOzzm8LM1ek3uWfniQgTDFMOO+X7yt9J/S2BrWxjb9KXboJxthm/ql0J46ntCnwuueSSsoBB++31a2wfFqlfy7arn/e85yl4yaXdqF6a3GZBNuaaesQOEtnfzNpVWSOXsxNa9JKXvKTlfWR+27aVuqIZYxZPV43b+WBQ+lx9v3W+29zng1sf9ahHNYUKeXzapqyc9sxkOohF+bx9OMdjMk8/gOkcTAYxIaYtypQR/QI2NNVn4pqMgBEwAqcTAuy86hFnCDBew/dxWDNKO8w98Gvt5mVshs/Mi85jvGGv3J5/Fiw//elP70Uru5k1R0QhapO+Pc/n6oIQ2DOuiLRAus95QOYFn/a0p6noJReeH4WmFm3DO+3z2Vp1zX5T5xrIDDS/0lwjt5nnPve5OduFa8lFFjwn3ORdXD1+B966xZOy2IJcgV8+/8SC7AnAO4oRMALTEEBwwSpeTQgLJBxB2HrPe96zjtK9Z/KUCUFjTUy8so3oKRq1dR66zwdCot2prfAIMTahzBSMbZfZJO+sac1BmDVR3oMe9KDBe6z8WjAzJNrgAkZFmgDZXEPOKm+fy4KeHGfVNVrdOlQlx0X4K61c/GXHN+PVakfEJV0WZEzR9Cddpm3eOYL+bHqC93f99dfn7Ms1A31m0BDY7JLyM7S+6W3K4hsTk4gWaUtTEMYaYR7fHz8Y7KmU8cNUAFs2e4tstAO2i15xxRVD9mhms9rfoyuvvHLQ9shx3vSmNw2anfhLy5PrfMAfz9V6pyxMoR2qPocJ0VEQk60s/EfrNy8E1XVAE1tCasJohxLY57i5L0XzXs/FQtcq2gTj3K7YxdNrV9R9k3bFhHSTfo3FFZmJQcDeE7LTXlQvHZ7EQURqB/RrmYEXhox3ub/jEClRXhhrCe1Z6GTb874o9yNj4882baWue8ZoyuHM2MikjxC1cFLYpm62rdoaq9GEZjwTjWGlOFNcBNKZd6Gvq8c03hELeSLMbaFhyE+7R9hGjA18jZv5vSqdXSNgBIzAqYwAO9YYM6HcByKshYekn+SH1jW8PGbFOFD6Oc95zqCQVeOTzV5IyFvHad3n8ls8eh5PEJa3+CHO4ECgKcL28CaEUoN2u+b0jHU5T3Y7ydRa5td2PQ9gzNMcg0V+5gE1oSSX+fI6PJ+p1eKHaQcsSrdon8/WKi/7SQkCP55vnbmGxnvSwivknfT4Qdj/ZoflJpTbOjKhWqOd3QGYQ9FcIZfBzkb4b34obfDNQRZkZ5R8bQSMwFYIMFhjG5SJIBo+2P1icM9a1GxZHRMS1RVA8C1NYwSMCFzY9sIKIvmjQX3++ecvJEOwLWZjIWDCDTZtNfGjw4Q4YECrnBOyWIiSD81A4HP11VcXsyVszd2W8uopgkw00cAIfDDBggDlRS960VAMjMyrX/3qolklT20jQ5MUASCa89hw24YktCEPbOFywNWrXvWqGeY+GBg5PPPe9773UIQORRs8Jl6wmg4G4MpzwUyB713ucpdBCx2GQidiyyV7NAQQWFIf8sEsy4UXXrjEmKCBkQ9OmVK1bd951q7nvfAeYaT4png3MKVZ8IImXWa6ptRxVZx8QAr2jdH+RqtDmhur0o+Fc8CbhM3kB4OCII5nY5UeYS79iJgZTu1eh8HHnAftXwSGlIEAEy0DTLbwXfBcCMjZUi/iVGxsIENMFPRTuNxzzz23bL9nKyjvhTaNn7Rw6bPQwlF6bHUjIIKoD22RNHyrmFnhHeZvgjbAVlSlV7m6b7mKg9sKH/PjUFYJTElPH4gNXyZu1A9tXjQ6eSbs8qsdcFYBWkWtvLGF2OpLEdK24lNupnUx5rvL7QoB/eMf//hSf2xTIqxDSJ/blbYIUx9Rq2740SZF4MDki36HcQJNe+wyZ7Mh9GvKKwuamcyxQIVpKHBlooWfbLszAbvoootKWrZ25vbJxIQxD81hyiQP2pbGKtoz/a/KzWZi6Ns5B4I2y6IJ/SZ9i96lnk1pcUXZr75WHNw6TGM3YTwzC85oq9Xx1m0rdXrd81x5ZwULAQobc/PiCrgwASd+pjq9wqb4563NnPfBJA4hAn0B3xiLuWqX5Eu7YsKovFUWrvxaruLlMH0ThKFJRdt6/vOfP4MHYcykTcC7QbQ9+kAR70xa2SwQUPcXvOAFM8xaSTlBce0aASNgBE5lBFiQhD9EA5ldNlpcZpepbAbDY2gnFaYPRPAP8NHwn4zX8CQs2GdhKDzPVFrFo8N/wMNB4rPhJRhb0G5FGAgfKt6BsXIbsybwJcz34GPEL8IPZW3svPtvn/MAeEEEsSLeD/coAPHOxK/3tLFJh8kzEbwT5gYZ8+DxeY9oXde8k+Lv89lURs/FzF+ea8DjcV4Q75w5FvOe/J6Za7BoDcE7av4OP8KCDLsM4RP4MTe74x3vuMCr9OrR81ebJJw5N+2QORQKMtQLnr1F7KxT3eDx4HvL7rvYZjaPys5xYzti+YVmwDy03OaxijSPBj4P4cM8hELzkJyXX5wGOucXjEwIz01GwAicKgjEhIpTfsovJoTDY8XAN/hHRzb4v/SlLx38QwgyXCuP2o0V4nlojw3puYiBbki3EJBuKLPOq74Pu5MLcYIhKDlEJzn4x6Qx5dq/DMHNkIZyyGNTCu2neUzmF/IjzxBMlixDY3kIiwlit5jowEu8mGgOcULAOg+NuyF9jQn3wajMQ9C/ECcEGUMesciwEEaamMgO4asuVGYMnAtRg2FZyldxsxsCnHlony2k7d2ERvWQZwvTnC/XYMb4JgptsnkMokMedXzuwTe0+BbihCCgZDGlrRJx1TtXfcZcvr8p31QsYMyDuV7KKoQTwzPEIWJL4as8QogypM84MfZDIeAYwsO2a/Gr//jWlTa27y8Ex06LeQhAh3DFq10woJ1vQmC46vvI5QWz1y0mmPyhrqveC2UG07iUF/xUzieXna/BKgRpQ/pt+oghkwkXobU+D0ZyeM5cp9Z1CLELzziW9Tp9acZmU4w3bVexpXd47hA6dx9pm34tTIMMZbTwlF8s+i2UT78Vk7CVaem79H3mDFb1ebHAM/Q1+TudikksbAx1y+VyHYtfQ5iej++jReu0lVZ6/DIfEEKCXrQl/9DOWqhnnONQ4vSebV1eKYQeC/kLi+yCfT2uhaZdmYspXmjtL9UdD9pIKAkMZcTEsPjRj/CLxYMhTHm13DDnVMaT0HaagwljRyzmzsMedjN9szL2NAJGwAicggi0+szsd+aZZxZ5GTx57HIt/WcIsJt9Z07HNfNc+vHWrwXlKh6dNMj1QhFkZfnwXsj41qFQfhjyXcWv8Xya8+YyNuXXch6966l5wzfpXdT806a8E3WaWn5rjqP68O561ONBiL/pXIO0yH4zL666ZDdj1uPnyKtFsRAw4J3z1DV5h5LIECcWfoZskEXXPNINIvhIbTICRsAI9BDoGfzP/mj9oLHHYYk1seqLiQm0ZTc5NIrtLqSNDqzOutg5xpY1WlRarSPSqoMdlzJKHtGJl4My5HXf+95Xl2u71AP7kuTZonUPc8ja7KzIs8Ks1decfwwGZVswq6j1NiCtvhIfTcGYQA/bsHIe21yHwKdoEde2c5Un7eSqq64qmmDrYkAeaOmizZo1k5V3MAYzNEzRps4nMaOlhqZu3nqlNLhomrLSi7YF+IkyXvIbc1e987G0CmMHANrJaMT12j02pLGb27IBm79N5bmOi4YgWgv19ywTEuvmn9st9SA9Gn48A/1DizAPgfZI1jxpxev5gSE2B9E4zO+zjq+2hDbJKuJdoEVJnjVRBrtP0LRptXtMGKABQl9JG62JvNFYRfs+t7l1v48a67qc3j1aJJi9QENizJQLdcceJIe2YmNvjDbpS4Mx3hjjfberbfo1ds3QHvM4lbHDlBX9T9beJZx+i346Fo6b7Yo49GloycZEmtsFYhdC3masQHDGrAia6piggDZtO8qzdtF0Zmtxqw+r427SVnIeaFFnsyDaWZHj9K717Sp8zD6k4rTcXr/I98T30urreA/042iqY9M/E+9+3e+f9KoH6SE0qdHgRwOqRYyjaLMzBoqUFg0s+Aj4BGlnK45dI2AEjMDpggBzg97uQEyDsRs478iEX0ZrFLNMvTGQHcXwwXXfvwrTVTw66eHPGHfQpK15ecLh5eBH4Ut7B5gTbxWxwxEepcVnw+/A97TMfO2TX1Pe7CRtjbv48b6yeRGNeXrebXgnlb/POY7qWbubzjXIB9Mv8Jrs/IU3qYn5Ehr3aGtvQuzIZA7VmgOxI4GwnLd4Gcpi5zG8SJ7DvwWa2Ly4EHeXHxF13XIJj9UinOK2KlIC/WcEjMBpi0CsahbTHkyK2X7TErRtAg52I8kb21YwCBwaqQm48mPApI/isAcJ3RQ21Q0N0xlbnSEmb0wwD53YBoS9KfpzBiLZIVO9Q7OqCEbBTOZEFLZvl8PHsAHKNizaAszVJqYwYoV7ELQgMJT5CEx/MEnH9iftLTOSvWejLrQl7GYjKD3rrLMWFj+wO4sQlboyzmXBYi/PffqzbZEtgAjJeYd5cN9nuUeVN+8WMy/YmaZtwFRvIsDp1Zf8WfigLdJebnGLW5SJBcysvvVeWvwxVwODxWREB6ZhVx7BI98WJirWnQiQjm+WfEjL4WrH3c4yBnwDmCNiKybEMzKJm/J9KZ9t+9JtMd5nu9qmX0PoSv/D+6c/PuOMM2b5IBzh13IZB+nv6Lt4F6SdskAsLOkn+caY7BwSbdtWDulZenVhXsU7pw+C+J7yeRH4YRYNM1xsCaafmkLk26McxjX8EWZNGFNoc7QfeDXCWj/iy59rxnIEAPAYeYtyr3z7GwEjYAROBQQYdxmn4NdYOIaHQ9jHeApPzvyr92PMp+/kxzV9O32o+E/S9WgsrJem5Y9pFOoND4Fge+r40sqr5cdzYRILHhm+hjKm8CbKa5/8Gs+OCQvqg9k5ySUwEYcQHmJcZDysaRe80z6fra5vfb/NXAM+AcE1c2HmAOu8z7oe9T28DvNa+A/eyTrzWvhf7M9bkF2j6nsjYAROewQ4tAJ7XxBavdnO2WkPzjECACMgjcEsyD7GKrno0wSBliD7NHn0rR7TfelW8J1Wid1WNn/dCJp7lMN0LcE0aXQ95kqYLZczSlhEaWn59ephfyNgBIzASUYAQTYHh7MAiXAZxYPscj3249kVrmvhgX+PxsJ6aew/DYEpguxpOTnWcSBg0yLHgbrLNAJG4GARYLVch28wScsHfB1spV0xI2AEjMCBIeC+9MBeyAFXx23lgF9OqpoEKrgIvtFUMxkBI2AETnUE6Ovo83IfeKo/s5/PCBw6AhZkH/obcv2MgBHYOwJo+nLK9EUXXVTMNugkYgTa29ja3nvFXYARMAJG4IAQcF96QC/jwKvitrK7FyThyjo51mm4r/2UX/bnGpMkcRBl2WZvYbZQsmsEjMCpiAB9HCZF6PPo++r+sPXMxMnxiFPft9LVfpukqfPwvRE4VRF4q1P1wfxcRsAIGIF1EHjjG9844yeK04rLwW26t2sEjIARMAKrEXBfuhojx7gBAbeVw2sJWXCCBqJI/vhxMCy2LSGEPApTXLtGwAjsHgEOOrvkkktKxo997GNnF1988e4LcY5LCNDnIcTGLq8OwKPPq/s9+dX+SxnawwgYgZ0gYEH2TmB0JkbACJxkBDi8AJvLHPTAwRuYE3ngAx+4xKSc5Gc8FerOe7ryyivLo9zpTnc6FR7Jz3BCEHjAAx4wu+CCC478oNQTAs9QTfelAxS+WIGA28oKgI4wGMFLFlqraAlkchh+HMrEYaHYi+WAXg75Ik79Ix+lVVjtp7JqV+lqf98bgdMZgUsvvbQ8PofpMWcxLSKgPmvR94Y7hWU3XxOL+/rHzlwOB6TP06GOOX/Fz366Vv66t3tYCNztbneb3fzmNy+VuuUtb3lYlXNtViLgwx5XQuQIRsAIGAEjYASMgBEwAkbACBiBw0SgJ/jN/rpuufiN/XTQY47T8svh+RrUdK9rIYm/KF/Lz64RMAJGYB0EsgC5dZ2Fz7pe5epwxxyv5ZfDdU3duW652a9ESH9Kk7x8aQSMwI0IWCPbTcEIGAEjYASMgBEwAkbACBgBI2AEmghkgYqEzS2/nLgOz/eKR14tf4X3XNWhF25/I2AETj0EpvYVdTzdt1z85F8jprAc3vKr0/neCBiB/SNgQfb+MXYJRsAIGAEjYASMgBEwAkbACBiBI0UAoYuEvrquXVUI/x4pD8JzPPlnP+VBWMtf4S2X+MqzFS6/dfNVOrtGwAic2gi0+gb5tdzsx3X+CamWH2HZv75WWsVrudkvx/e1ETACqxGwIHs1Ro5hBIyAETACRsAIGAEjYASMgBE4SAQQokwRAPcqvyo94ZlUVu2f40y5XlXulDwcxwgYASMgBOo+Kd/rOrv1Nff1L+edw+TfcpVvK2yK37bpp5ThOEbgJCNgQfZJfnuuuxEwAkbACBgBI2AEjIARMAJGYEMEEJhIMF1n0Qvbp5BFeffqVNfR90bACBgB9Rs1Etlf19mtr7nv/eq8uVf6dcNa8e1nBIzAdAQsyJ6OlWMaASNgBIyAETACRsAIGAEjYAROJAIIXcYExLVQhri13y4ePNcjX+e8Ve5YfXN8XxsBI3D6IaB+ovXkOax1jZ/8db2uS7l1mlZd5KfydG/XCBiBzRCwIHsz3JzKCBgBI2AEjIARMAJGwAgYASNwEAggIGkJfVv+8pPLA+Tr/EDyx4WycFvlKSyny9c5D6Wpw7kfC8vxfW0EjIAR6CHQ6o/kN+YSln/KX37c19eKk13iiHQtV/64Lb8x/5zW10bgdEfAguzTvQX4+Y2AETACRsAIGAEjYASMgBE4bRFAoJKFyFnAgn8Or68BTXEygDle9td1Kxw/KNdF8e0aASNgBMYQUP9Rx8n+us5ufV3fKz/5c69rXP0UL4dnP18bASOwOwQsyN4dls7JCBgBI2AEjIARMAJGwAgYASNwYhFAKJMFyRLYbPpAyq92yU955/KyP9d1GH4mI2AEjAAIqA9poVGH6X7MJSyH677n5nKVLvv52ggYgf0gYEH2fnB1rkbACBgBI2AEjIARMAJGwAgYgYNCAGELwuGWS0UlOJZQRvd6CPnrvuUq7zpM/nIVrjzrsghXmOLaNQJGwAiMIdDqM+Qnl/S6xh27Vrji5LIVJr98r/i1q7h2jYAR2BwBC7I3x84pjYARMAJGwAgYASNgBIyAETACB40AgpSWkLhVaQldiK/rHK/nn+PoWuXKlT+u8s71kp/i5TD52TUCRsAIZATqfmMsTHHH3BzGtX7kq+vsZv9c9tg16U1GwAhsjoAF2Ztj55RGwAgYASNgBIyAETACRsAIGIETiQDCFAmms8vDKEwPlgUviquw7NbpFCZ/udmf65bQOpep+HaNgBEwAqsQaPUd8pNLHrrGzdcKq/3zveqgdErTchXXrhEwArtBwILs3eDoXIyAETACRsAIGAEjYASMgBEwAseGAAKVlkC4rtCqeDlcQppaeJ3vc3yVJT+58sfNecpffrqf8hyKa9cIGIHTG4G6/8ho1GG6H3NbYfhlf11TVr7OZet6Vfi68RTfrhE4XRGwIPt0ffN+biOwBwT+6I/+aPaGN7yh5PxxH/dxs5vd7GZ7KOX0yXIXeF533XWz//iP/5i913u91+y2t73tiQDvV3/1V2d/8zd/M3ubt3mb2Sd8wiesXefrr79+9spXvrKk+8iP/MjZu73bu62dx6me4C//8i9nr33tazd+zLd8y7ec3f3ud5/9xm/8xuzP/uzPCgP/SZ/0SSsZ+brAX/7lX5793d/93eyWt7zl7M53vnMdvPP7X//1X5/9+Z//+eymN73p7K53vetO8t/Fd7qTiqyZyYtf/OIi8DrrrLNmH/zBHzyk7mHEe+Z9Q+edd97s7d/+7Yc0+7rolZm/cfo1+jeTETAC4wggSMnCYd33XHLLYdxn4TX3UynnU9dBeWR//Eiza/rP//zP2Ste8YqS7fu93/vN6P9M4wj84z/+4+xXfuVXSqTb3e52s3d5l3cZT+DQLgI/+7M/W76h933f953d5ja36cY7pIC/+qu/mr3+9a8vVYKnfsd3fMe1qvea17xm9g//8A+zW9ziFrM73OEOzbTwFq973etmlPVO7/ROs4svvnjtcuqMe/2H/OWSTtfZzdeKk/3ytcrGjznXy1/+8tlLX/rSwh/zTO/+7u9e3jfv/FM+5VNmt7rVrZRkyRVfTMC55547u/nNb74Up+dB2cz7IHC8053u1Itq/9MMgd/+7d+e/eEf/uHsrd/6rWcf//EfP7vJTW5y4hF4i7/+67+e89HBPIiB0HXL5Yn/7//+rzw4LkyAyQgYASMAAl//9V8/e/SjH13AoMP8oA/6oHLtv80Q2AWeYrTuda97zV7wghdsVpEjTnWXu9xl9gu/8AtFAB1j1NqlwwR+9Ed/dEn3xCc+cfbQhz507Tx2neC//uu/Zn/xF39RsmUSsO5EYNf1+eEf/uHZfe5zn62yhUd48IMfPHva055W8vn7v//7Uea8Vdg973nP2Yte9KISJB6kFW9Xfvsobxff6a6eb518en1DD6Orr756dvnll5ciEGowod039co8xG9831g4/zcj8E//9E9FMIIPAgIWpo6a/uRP/qTMhyibOhwKqV5v+7Zv261X7mtb1/LDzdc84zp+ii9slFfvHn8WNv/t3/6tlIOwb11irEVwBLFAyi8TYWeffXbxetCDHjR7zGMek4N93UAAQeQnfuInlpArr7xydtlllzVi2QsEWHxFPkK/0FKi0CIAC//XXnvtiQDtx37sx2b3u9/9Sl2pM3Vfhz7rsz5r9jM/8zMlCd93JvoE+IpnP/vZ2Xv2kpe8ZHb7299+9s///M+zN73pTSXs1re+9Yx+bYzE17Ti1GH5Xtctdx0/Fsk+8zM/syjjtOqA3zu8wzuUZ/6yL/uypbkAZSHo/vEf//GSnLnQOkoezDO0sI+M7g/+4A961bD/aYbAIx7xiNnjHve48tQo4JxxxhknHoGTL4o/8a/AD2AEjIARMAKnOgK/8zu/UzS/0P769m//9lP9cf18RsAIGIG9IYAwhb6UHzt4joMQhlL+53/+5x9H8d0yVa9LLrmkGycHSEjT8iNM4dmVf3bR7mrdZ/98TVzua7+v/MqvnJ1zzjmzj/iIjyhVUpyp7hvf+MaSlvTPetazhjJyej1rrkMO9/UN7yXjYMyWMcn46BpFDNoeiyTyy+5JxXGbevOdiTIWXCOwroXYxNW3idIFePJjt1idvr4nXf1TnOyPn+51Lbf21312VUe5COS/+Zu/eYamKztKM33gB37gwqIGwnmUvlgQ+Jd/+ZchKvmbjIARmI6ATYtMx8oxjYARMAJG4AQggEkbacIchfmDEwDJUhXPP//8wfxKHfioRz1qxvZXCO2rlnkXNEp2QWx95F1hRsZ0tAjoGznu3QFH+9QuzQgYAQQmWTta93IzQhKuEF/h8iNe7a84dR4qT2l1Tzz5ta5zWM6zd53jc53vd5F/r9xT2R+e6l3f9V3LI8JT1Zieys++6bO12h55CUd2CpxEHHvPNYYTPAbPjUmD+pllBpD0X/d1Xzf7ki/5kiGruqz6fohYXdRl5OA6LN/rWi7pdI2r65b/Qx7ykNl3fMd3DEV97ud+7uwLv/ALy6IcJlUgdpiiyPIN3/AN5Z6dZWir/8iP/Mjsrd7KIrkCiv+MwBoI+KtZAyxHNQJGwAgYgcNH4EM/9EMLw3j4NT2+Gr7zO7/zjF+LtPWVMOzr7dPG3vd+7/e2qmC/I0BgE7M9R1AtF2EEjMAxIoCwJgunqYoEOPLHL19zL+r5K1yuytF9y5UmZSuMclqkuips3Xuls/tmBDhD4fd+7/fe7OGrSQjUbY9EJxHH/Bxc5/spQHzXd31XN5rMhhABoS7C7jGiT9iUWvXOfq1r+dUudcCP32/+5m8uCLG/8Ru/cfZVX/VVpZpKxw2mUTBFxxlSMtWDaT3MrlxwwQUlvv+MgBGYjsDmvcH0MhzTCBiBE44A26T+/d//faunwC7hf//3f6+Vx//+7/8WW4fYVJNt/nUyYPsWh9RsQ7JrvE0eddp//dd/LXb0OLBsk+civ03wrOtR32Nbst4SV8fZ9J7nBMv/+Z//2TSLkpZDCnsT2E0z3qadsC0QzHZdp23b/qZY7CodNk6xFYkt210QBwXx7tftQ7YpmwkWB0PmrZ/r5reP73TdOhxi/F30ges8Fwe88S5OBwJb2i3f4LpEP8Z3tum4RHl8q+Bd0yH0abvgZernWud+0zF20/4vC1HqetZh+V7XcunH4Ve4l1925T/m1tv2idvyU77Ud1V+EnRnt06fw1SesFAd8IfAWQt8dbqxe/IR7zQW7yjDeGf0efDum5YLFpukpQ+i/E3SbpOGg+54ZvqfbfKp0zKP4P3Sh9Vh9b3aFm4ddmj38OPgBY8zVrfeNwUetBG+m7H0Y2EcHC5ip18dN5dNGPerfuRHvRjPFLeVtuWn+Hw3zA10T55cy83+X/3VX138+fvar/3aphBb6XDZ5SitbO5/8Ad/cMib+0MiMGTutgk/wXPsYsz927/92yZPIZyYF2w6v5zC8/B9UAfirkPb8rnCfpN5FN/kprIT+BR4yG3lJ+tgtWlcC7I3Rc7pjMApjACTWFbQOXCCFWR+bCfktPIv+qIvmnG69BRicL7wwgvLSdXv8R7vUcwHYD/ukY98ZJkUtfKAMfr+7//+smLNVivSsSUNZofDxajXmFCdAwwe8IAHzD7swz6slMuWNtI9/OEPH05dr8vlcLOP+ZiPmX3rt35rCeKk6S/+4i+evc/7vE85NOOiiy4q4cTJ2gN1PhyIQhx+z3ve8xaCf+mXfmn2OZ/zOaVOnEBN3phV4Lnue9/7zl71qlctxG/dbIJnK5/sx0AL40WdOUSFd/3+7//+swc+8IGzH/3RH81R176GCWSr4F3vetfynBxAgrYFbQBtBQ4HXEUw2o997GNLGtK+53u+Zzm8iXf2bd/2bU2By2/91m9134PK26SdKC02WTn4hjYG4w1mMMS0s+/7vu9bELY+6UlPKnXh8BeR/MBcJjwI27btK//jcmG6eH4O2mQrMm2c7bMc+sp2yhYTSF8ADne/+92Xqv2Lv/iL5dtgwoD2OO8eEyTkywFdCNx2SbQ17DHSXimTU+Xf+73fe3jHHMwzZWFrl98pbRx8+P30T/9083HppxWHQ3Zr4rl4JuLQ14jAHL+v+Zqvkdde3V30getU8Pd///eLnVK+Sw7eYixhiy9jEt8guGTiUCXhqANxcjjXtDvFqft4xf2Kr/iKIU59sJXiZJcJkvJ86lOfmoMWrn/oh35oiIcd4EycRH/FFVeUvojxhXbLN8jz0pdjW7RHfJdPf/rTZ5/8yZ9cvle+M8ZN2gpbpREO1YRWGXW+9NJLSxDtjm8ZrPlWX/e61xX/XfdpauuMCSK2bwu/+vvcFS+jsl7+8pcPZTG+QbRrlf8t3/Itijq4m46x6/R/Y/XioLBWvaigBDOqbL6/7rrryvul/2aXDuMch4fBx7zwhS8saYmvNLiM6fQ1/Gg7CpcrwRG8EsIcfn/8x39c+EH6o7vd7W7DoXDUCa1F4tDOlEfP5dBh4n7BF3yBHqccRKxyfu7nfm7IQxHIi3EEcwZ8Mzwfz8s12qF/+qd/OqSpyyUPdhTd+973LnwidnBJR12f8YxnFMFLnaZ3Tx1UT3jsXjz8v+mbvmmISx+nuHxrHOh9j3vco3z3HJSJJjX9HjwdtscRWiq+3E//9E8v+cFb40db+vIv//LZh3zIhxQs8OOMD9WPQ+iUNrukg/e+7W1vW/CgfPIAj5/4iZ9opqG9KN/v/M7vbMahjLq95HI53BRBIs/Ioas8M22VfgxzD69//eu7+eZ86utXv/rVpe70oRyKxvulb+OZHv/4xxdBqdIwdug5tPCN2Qj5PeUpTxnqwHwCf8y2KT3vXHE5oFz+2eU5+UYUjz4/h0+9pt+Cr8DmNN81eNFueU7aAnxGK6/8zXDYM3HBg++F7wb8OUyO+VmdnvGCevPshDGm0E7xY1wT0b/jR5th/OH6CU94goLLeI4fv7otE2md75G+iHaJTWt+vDcEd/AG1ANsnhU29qH6eeSHSzshH5FMo5AmU32fz1aA72zxxzn9UV4jGMbet3gC5m7wE3xX8BP0Oz3adMzFVrrGUQ6oRM5AXw6/jxk8eDjGFbAS8X7g55gXaH4JD5LblOJeddVVJX/NNegr6buZo4jnoX2KV6KNit9jnkcdaDO0Ddp/jzbhc+u6oaVP+6duPNeqeZTqguyC8RnM+DaRncDLPfjBD145d6Ht0/fwPSMLoE8gLe02HwCvsg7GjRWreayWzHGjUyi/GFDnwQzOQxo/D42qeQzk8+hA58FslF90nnN+0dDiuzMZASNwKiFAPxBbnFh2HP3FJGUeA9bCo8fhFUOaT/3UTx2uW3kFUzh/wxvesJA+GPH5/e9//9F05PVpn/Zp8xhoF9JyEwKkeQw4o+l/6qd+aimd6hcMyJzn0r3cYKoGvziUZCm9PPIzx/ZBec9DiDekV54tNyaOQxoutsWTPFTOve51L24XKIQNc96D4rTcGMgX0ky9CWHvPJjb0byDMZj//M///FKWH/uxHzuki8NQhutW/cA8NMUW8gjGckgTA/NCGDebthPSxmRvyLtVH/yofwgviD6PA7dG4wfjXeJt2/ZLJjv6+4zP+IyhzsFcjuYaBxoNcT/7sz97uG5hE8L/pbxiMjOkyYHf8z3fM/i38sKP9kV/tQ71ygP/VfVXmfBGmXbxneb88nUISwccLrvsshxUruHNMj4xQV2KE4tkQ5yHPvShQ7jS1X1DD6OYUA75BCM/5DPlYtM+sFfmqm/8Oc95zlBXPWft8p2CnwheV3FoWy3KfVpM5JeihCbgkEeYOFoKb3nQnlTu5Zdf3opS/ELwMcSLrcxDvNe+9rUrxz3yf8UrXjGk0UUI0ed53FI9skt7COGEkhT34osvLnVh/IiJ21L5tLl99GmMGblu9TVzE9E2vIzyqN1nPvOZo+XXfdymY+y6/d+UesGvtX68p/zjXYfQc/Q5wT0EGvNY2J/HhH/4xQLLkC6EiPPQ4lv4MS7yiwXuIR59SQgPhvv6nXIfk/l5CJpGfzGBH83jmmuuKenhzVRGCGrmsfAz3MtfLmH0NXXZzIdjct9NR3ryjoWspbR1XtyHEKE8o8oNIU4zXWjZDfUNIUVJR/rQ2JvncVv51O5ZZ5015/lzHRSH9/nkJz956ZmIG0LqwT+EuAvpqVMs3g3hyq92Q1hb5A257PwuYqF4Id8cL5QthvxDQDzEC/vKAx51efkePibnt+p6Cp8HlrR38mrNG3L58IEqU/4hgBv8QlA/PB/hIZAawkgHjxsm3oY44K381nGR6dz+9rcf8lFdajcWchfyh09VnBD+Ddfyy+4HfMAHzBlXcr34FhQHf+qh+5ZLHrTvVpj8YoFiKGPq9xgLJ6X/UT/E/ED58Z3HIsVwjz84qH9jbOcX2qrDj3lo5lF4L7FAvtCfqm9t9b3kR/71fBaeTPWKRZJ6GBq9z/xEj48Zy4D0eQ6metTu85///KVsthlzf+AHfmB4Zr6nsbk8mIQCxhC/rhv3sTi/UD/NVch3jB8NAe4cPmLV3JMxq6axfHMd67l+rlvGIafRdc1jUAfaWJizGcWD546F4SFOKHMN1acPj4WtIUxl1e7VV189pDmUC9vIjrdkMgJG4AYE0FBjtVIrkviG4KNoWaE5gYbuy172shI5hCpFyxZNghahQQHd4Q53KCuYZ5555iwm3GXFnK1Gv/u7v1s0N9HGQTMZYoX0u7/7u8s1f2h4kT466VlMwstKOf4cjBETt1kIvbktxEokGgIiwtBEYosMq+WqD6dE8wznnXeeog4uWtHSysYzOv7y7J/3eZ83rMw/97nPnXFfE6uZKgObwsGIlSiszqLdLQqhwCyYhBl2nDG9gBYRGsQQWlPnn39+ua7/lPc6eNZ55Hu0ANGMllYZuLDSjFZGxgFtbVa7Ze8t59G7RnOEVXERK9mc4M5KLyv5vDs0CmkH5557brEvh3Zzi2LhoXjH4kVZjWdnAPVTOwEXVtV5/1Nom3bCyepoHInADE0O2i8r6HpHaOfQ/q699tryPqkzmplo6kLBXJbTyrlWO9mm7ZPPIVAID0s1QiBc3itaHWhM/Nqv/VrxR+sTDakP//APH60uW0Jj4jfEQTsHrMER7So0Zmg7tCG0X8F5W0ITQfXnu4+JROk/0GxAuxTtFL4VykQTl3JbpDawq++U5xbFxKFotusel7aWCQ1/vrVM+dsIoWUOOpLrXfWBUyuLxg5tUER/fJ/73Kdo6+ldEgZ2jBEhTCnaPmigEJf68p7pq/R9Ep/+Gn/Ri1/84jI25a3RaOGJsva7/Pbh8qzqx+lP+V7oc6kvmqGqE/0kmp9oFUExESl9Zywmlns0DtlpgiYl4zPjEfnSt5EWTcz8rCTC3ATYqnz80PRDg2gffRoaWmyzhUdR22fMREuSHVxoIEG75GVKhjf+gZHG85i0DkHyQ6NMtOkYu0n/t069VD+5aFzRFkQPe9jDFvgg+CrGOd49Ws3suoHQoIXvCaF7uSePWuuwdZ/LIiFxaC/i5+DXQphS8pR2sjTDimfnD7uzjBHwqvSVUAgbi5Y312iMUlauE98whNYbbYv4tCu+GyiEbjN2Z6DpKaL+fHNqf7e5zW3KeEX/QZ/B+EQ68iYe2oH1d6O85NJ2+W6xrQvxrTFW1oSWPnlDfKs6IA4N2xCAFH92ZKClSF9GndBsZHwjXQhoSn3YXVQTWoa8UxH5nHPOOUuYEZ4x5HDo/C3EIlfhe3hm+hZ4ZigWEsq3C/8nyvngV9+34hFH8XhnwgO+mgP26ANoP/Br7J6D0K6n71bfp3xbLrxF5vPIk50CtK1QvinfBt82WLLTk+ehDaj9ijclb/nd8Y53HOqcy9RzkD88RQiKSjDtnnGIdwDhzz1EHwNfrrTFc+IfmuTMwyDaOs9J3fmO6ef13fBc7IZAW7smxaEezBnYuQbfI61kvgF4Mj17nZ56o/Gp8Py9w/cx3+AdohHLuIL9aR0IyfhGndTXk1fve4R3Y2yPxZmSD98j7QD+gLZZ48f3xvsVgQt5KJ5cheuesVJEHyR/+eG2/PBnl2kvjPCjJnh2MBafAx8BH8OYzq4M+hiFwRPAT7EDA9rlmIt8AcJuOHNmeHLGHWyJQ3zrImQU7ALF9Anfovpl+sdLo0+tv3nalMZr2iA8ILsI2OUFz8SPbwOiXL4F2gK7vYhD/wDFYuzwvXC/Cz6XusWCJNmVsYN3MWUexY4P+mERfD7a68znY4GmfI/kLfwUTy5mbjRPY36KBjc8BfwdfJzmrvRRzEmQXxwMWSM7ukCTETACBYFg3pnNlB+rkmiFZGLVjxVqxYlOvmiEKE7WTCROMElLK83s9sgrf2jmiNCIVt7BGMl7cFnFVHjWhmNVOzrdIayl5Zs1ClhtzqQ85YYQap413lhhz5pgaNnUFMz6UD7aHKKsSRIDsbwHF00L5Q2eYCzaFk/y0TPVWpe8G4WhUVATmmTUR3HQvJpKIegf0sWgN0cLIhPaQ7w/5Y3GXybej8JwgznJweUaTZxcv6w53NPW3KadoDXBN6F6hZBnqU5ooSscNxieIU7WOAtmaPDXxaZtX+l36WbNroxrqwxpEui5W99tbP0fcIlt0QvZ8O6VVgFozMsvGCd5Dy59SO+bGSJ1LlrlETW3uTCTsJQ6mNShTuwIybSL7zTnV1/nOqOFlCkY8qFeYMY3QX+VKZjhEoewrPkjjOu+IZeX88maR+toZG/TB/bK7H3jfKdZazomIQvPzPOgBYi2tJ4/f8u5vBDq5MefZ+14pQ3mfyFObKEe8kVTegplDap1NbL5FlQXxtX63aM9Rh+sOPTroqy1zjevXSQKR6suhGFD2pgEKWgujWzly/cY5iYWyt9nnxYLwEO9Wprm2/Iyw4OOXGj8QcupRZuOsdv2f716tTQCsx+8B/2L3ikudaFN6Uf/EYKnhTjgTztjfEXLS+nZ/cH3mH9oe/PLfSbjpvxxQ0Ay5EGbzGFTrtHYVR3YUVanCUHMEE68MFNQdvbkeKFcsBAnhABDPllbnu8A/ianDUHIPAQrQ/oQEC6E57j5Gn5b9UZrNofpOgQvQ5zXvOY1Q5wQKg7+fOOKLzcWIIbwED4uhKtMuaGEMK/fCe9Y4bGoO6Snj5M/Ln2kypQbQvmFONRFYfldoMEv/9pttRe0JlU2eIVAeyE9fGbWQGTMqPNt3ed+ES3xOg7lSluYb61uo/r+aFd1Wu5VZ8bZHI5WPtgrHA15wrM2PHmH4HQhXc5j1XUI5Ib82YFUx89arrEgM4SHYHpIR/3CjNUS3mjAqu71s+ddvnWZmT9EJlWH510CsVC/FL7N98gzqs5ymePyLujP+GUNbK7pA/WjXzzvvPOGPPgm6UfzL/exrevW2HFcGtnsWhEOzKnzjjXVM+/gyvz5tmNurYnMzo9MYB5C86F+1JO+PlM9x8uWI+q5Cm0pU96RR97wkfVcn/yEDzxPpm343Lpu68yj6OfU51C3UMbL1SrXjOt5/ko8+jFRlp/keavCM1/b2vWpeMfh2kZ2vE2TETAC0auFzJOVRxH28s4++2zdFpeVTTRzdboyK3zEaxGreWhpSGNEcbDXhw1sEbbTyAeSZgXXaLDWhOYVq6xoS6JBI2KVWKviaM+gaVwTWhWkhVixRbOzRWhSEp41hFm91woxadCWqSnb5EIjRRTCd12Wle3h5sYLNJGEMzjEpK+OUu43wbOZUXjGADa8N1ZXWWWtiVV2tMVF+Z3Jr+Wyap+1l9DIRWMjUwy6RaMaF0IThFXjFoE7q+o1oW2EFpKIlfJVtE07QauIlXoI7fAQOC0Vh9ZC1tbPmrBLkSuPTdt+lc2x3qLdgIZOTdkWoDTt6jj5PmOB5lNN9CHYdaYfQJNJ/Ucdb+o9mhzS4ojJZdk5UKfl3Yqkkd2f0gkAACrCSURBVKH77O7yO1W+aLyKcn+Cn3YsoD0FgUXeUYOmlTRu0fSo++OSaM9/uc4tLeWpfeCUaqJVL40h+nI0HOtnRsua3QEixiD1u7n9SltT8dBGhbI2EDuFMmE7GEITUppKOXzX1yFEGbKkXcbEerjnAo0vxmy+FX56TsKwmQvRD8dW3qJxWDxu/MNGaO7Ls6Zhjsd1TOCL5lTWPM3f8TrjeZ33uve75mXWLZ/424yxGbej6P/0fGgGYn9ZRPtA6y5rDHJNXwOfJdLYS1iOS7j85K97pa3j1OFKl+Pv+hptNvqgTGjkoV0pyu+BnYIQ3w07+NDUzYRtUml045+vc7z6mn5JGv1ozWInNhPfNruBIHa8SVuW8Usaq/DmjEE1haB38MrPMnjeeEG+9NdTNe6w7SqCJ2rt+GGMVhshbm5jSruJm/s+nqnV91EnxnR+IeSaVEz+/lr9Fna4sQVNnmg9bst/qFJoIqN1Kr4Y7Xi0nzP/y+4HtIQ3JTQsRRwGVxM8nPB6u7d7uzq43KOdikZ47usJYHwRsSvzqKj+HrHlrH4El3EslGGG6nCt8MHzxgt2+2Ifnmev47TuSZa/0zwvJYw0J4UYN4UldaavabW13PfrHKVdj7loIos/EX7wcdJWxo/39FEf9VEKLi7fUOYxw9TJQrhu4Pn4djPBs7HzSBRKDcXOtO5x0VZm7gnBb/Hcol3xuevOo9h5oj6I3VNoU9dEf66dU3UY96v6Bebh4iF7/UIr36Pwu8lRFOIyjIAROHwE6PAloEFoI2F1q+YwMSImsC1iu0+9pUfxYNjpcEUSQmdGCKEzW73YrpMZVLYnstWFrZKiXIc8iClcbhYyanucwuQywDH5rylvVddkQnFgfHUABc+VBbcIMxEewETXApVYYS5bdvKBf8qzdjfBs85D92w1FSHg7xGTWFH9zPKv3Zw3AhSY/hYxccwnfbNFrUW1mYQch3cdq+LFCwwzU5Hj6XqbdqItquSVFzWUt1yE6xx8xi8LxRTeczdt+738jsM/fyO5fLbuiVoTQ4XJ5YAZEYI0Dhr5yZ/8yYVT00Pbs/QDfMe1EEJpp7oIIvhG+Ykxz2kRBnPoyxTa5Xeq8phYisBBxFZHCW2z6R8JXImXr1mAOQ7aVR84pe7aHknc2O3THYOYjLCIBzEJQPAIMTZJAM2kNjSwij9/sTuhXDM26p3kxSpMGsiMBwfuHMUklvpKcMVCG3VHGKKxnAozYWPM5McWXIi6amGOyaHMe5XA9Ef+LCBDLASGtly5zn8sgHNYUk3H1aftmpepn2vKfR4H1x1j99X/TWmPeUE5CxJyWq7zZJmFMvxyHDCSn/zzvfxyvB6udbop9zmvVnyFsyiVTY7kuGr3xGUMIIzDvrUYi8IC301Oo2u+GwnC4Q0ZWxQ25mJaQYS5hhwXYbUEFiwOKwzBHfXjxxZw+cvFFE8tPFYYbiZ4e4RBObyOQ3yFq7/Dj8Nm5V+72spPPBb/cjh+UParr2+IccO/wsAYoSrEO2HhEj4VHkNxeIfgz49w+Y+5GhfIl4VR+GAOQKTvUzr4UvKkT5TZG4WRTiS/7CoMN/tzfVYsoGTzLowjGpsQymMypk4TuyCKWQDGvtYPPkFpsiAQhR/M4GB+Q+Hw08KLtij/XGcOLm+1EcwYqM3TBystbqbsvypMcZVe93Jb36PiyiVu/h5ROsrfo+IhFGVcJ75I5bT8FAcsRPo+uc9pFF67U+LUafZ1n8dN+CPMCrWIBTT4TuY4L3vZy0qUnHYX8oM8V891yPNJ8TI5nGvNCWv/fJ/lD9k/8zG1kFzxUKRp0a743HXnUXnujKmgHsEH9hYo+aZF9JOYlUMpTQSm4iEx53RIZEH2Ib0N18UIHCMCEohQhd4AoeplbWXsl7WoNwgobi5DZWOfW0IE4qEpg4YKgmUYODrXrG2ovPKkkfQwVK1fnphoEq885GYmVn642HfWSixakFmrRVqRxKsHYOqOPTiE8Uz4sLXLQIDmCwxQZixJ36NN8OzlJZvchFPfFlb4ZaYBu3dTCKZYlLWA5Jfd/K7zoJnjSFs9++ka/MBRhP3XMdqmneTnytq5dXlo09BW+NWaWnXcfL9p2895HPc12gotysx6bK1sRVnwo91lhgyNfb5/Juz0B9iCQ/shtm8upNvmhm+UH8IAymNBi2+T98hENQ7am5T9Lr9TFYi9SGmKUDcJE7GXKkIgI8FhFq5mm3jKQ2mOyt1VHzilvrkfyf1LK23+jnP/lvtkCfboW7TgGluJB7u7CJu00KpJHWWts4jVqts6fnlBkDrSp9/61rcubReBC4s9WcuQvDNOaKf3xgD883PlcU91zAue8sM9rj5N/AR1yHwG9zVN4WXqNFPutxljj6P/45lYWFcbpy+vFzfox9WXo5Wlvg7hTUu7M+OktHI3DVP6Va7y78VTOLbVe3FqjVPiCR/SPyt2m9E39355EZGFo1452f+iiy5S1YpQNoflRVaE6Dnspje9abHzj9CanSTsREEIynkU9AVZkJ3TcZ2Jb7YO173i6Z5+T3wRAlgUOBRWu/BCub0ggFQc5Ysrv5areDkMzWgRdYG3RouU50YRhv4Zze2cZtU1318++4fFYzTNeT76fhZIebfwMq28VB/cTcJ5t5n/IR+wC/MqzfxY1Gf87/2wf6t6gI80vvluwY9xEsxYHKFN10JopaUeEIsH8qvdrLyUw25IecN/9te1wnWfXYXJzWFTvkc0svm1vkflicu4n/PmOpPC5Kf7zPcyr5S/4p0Ul/OqRNoZovva5XuHN5bG9q7H3Dz3zGXnPpl32qLcBlvh+NEntijnnxXSctxaIU1hu+Jzc3tS3ri5PeZ5FAsKorE5N+npI1qE4mDuFzgngwULcMKuPDwiC2KHSBZkH+JbcZ2MwDEgAPMi6g0iCqfDU6fXEiwTb9WqKNsvRRpAOdgEwQGMovJXHJhJOtfb3e52MzSW/ii0EET5gA6Ys95P8XE5UKkmBpCxQTBsuQ1JsnkRmRWhzkwEMsHss60STNFWQMsJZjFrDub4vetN8OzlJQ0Phffwwl/UE/wrXG4e7FbVmUPFRJkRkh9bvfLgLf/sZmYmbJzloKXrbdqJJmxkmtvuUiEbemza9jcsbi/JdDDRLjJHKwltKGmbKk92aPA9IZRFuyBv51OcTVwEdGGTskx40ABn0oh2myZKq9qyylwVL7cd9XtKO+Zm8yISYGtixlZ/BBlhl7JkQd+EUApC8A2hcXFcWwJ31QeWB1nxlzHN2jWtZGeeeebgnbdCZyG0tLCFOQkQKkjzjHvt9FBc2gCHex0VIbjmoDa242ai7WLeC8EIWGRTTBkn0kwZA4jX2lFRb6cmHnRcfdqueZkbnma9/23H2H31f2PjaX63vNNeXPmjySxCI1b+8sPFr/7l8HyteC0/hU11V+WhcHi2Xp6Kg6s4NY8x9buZKshGeCLtOBbe4TsoG8GF+EwWLOljVCdc3h1a8nznCMMRXqJZK76lHpdyWj0nwikEOTksXyue8OCZRGovOX59nQU0ai/EEdXx873i4GZ/djvAE9TmBHluviF27Z0Z/Tymk3K6VdeY1WM3mDS+VT4HjXNgInw+c5GwX72Ur+L2ylA4bi9OrVDDIj6Cslb8LNTKees6C9wRWmNWsdb6hP9Bu5zdhuDFIgC7SHN5ym/smyG+KKed4k+6Oo3ue3lu+j1mrX3lLaGs7nFVfq6//BUPga6oHlfl33LJE76O9PwyD9KKv2+/PKdeJQOo63IIY25dp6O+3xWfu+48KvMaeX7Rev4er0a/AL9Y7x5jZx+7XFjYIy1jDLsZDone6pAq47oYASNwfAjk7floJY4RDI6EnLWgSenQ0DnjjDN0u+RmDbEsjEQrEiESNnAR9qINhiZzFhyjAY3QBnMPaEueFQy4BK1obedV1aWCb/TIzIfiwMCNEUyHNCXo3BFsY59QZjfQdqD+mbA//dSnPnXwYhLCFh8YZLa7wdyT55j9KhJviudQcLrIgxlCkKyZmKItXMJIT6G8io120Bhl7b5cJ6XRO9V9y81lrBrEt2kntDMRGrHraFsr3Sp3k7a/Ks+THI4mAD+0ZTEdw5Zkvn2ZTYDxQqCNEC9r5q/7zHzDbCnVNmkmagj/0Erh+6SPY1GFLYUqu1fGLr/TXAb9hszsIDCl/5PmtTSta+Eq34MWiHpas7mMfV3vqg+cUj+0I7X4wLvgvkd5MTMLetDm472DXRxsV8Yj2cLWogGMP+2EcZAFBbZjylwVml1TxqBevXr+2cxJHYf2Tz2YoNMuqC/fjDSDqSeae9QLYUXeHkvda8FGnb/u6UNrytjVYcfRp+2al6mfacp9Hs82HWP31f8hQGmZ4cq4SUgpAU4dH//8/YiHU3wwytcZM/y10KZ4OW59ne9zPr3rHJ/rfN9K0wvP/sonfzcsaPGOphDfTc5vLA2aseIp0ShG+QEBqsYe2lPOi/ELjWHGQYh+if6eHYSUC6/J+IWgTnnk9KrLmcH/tvwJz/5c88s8kQT1yqvl5vZCv5zzVPyWH2Fj7YW+jwVt+j76PM674F6KC/R9CGbRpBT/rvLGXBYU+GEDmfzIFxMjwhBhOQJt3k2Ph+49D+US1grnObIpFuIiMGeHKnaBa2L3WBxKWXsP9/RFuRzaMPMNhPuME/yYZ+XFWsJ4pygTtCjn1wrHrxen5680dXi+5zrfb/M91vVGeJvzrsN7YXlBLw7FXBIG1vnoOZlHsNgkWld4rHS7cuk3RHl+Lr8xN48du5AfjJV1qGFHyedmDJCzaK7MfDi/ixyPa43rtT/3tD8W7zj3DJkLP/V7is8CH/3T1DOzlG6frgXZ+0TXeRuBE4QAQlVRz1yIwvPhFmzNbBHbXXo2toivCTbXWVODe4gJNxNsfmhiw4xi+1PCHIQMdLLYfUXwQKcLsZ1yU4YAjYcxYqstjC2TDLbsw5jDxIpqYQDhEmLDJMAsthjezKQrr9rdFs+cX35nTIAQ2u2KsgZL3vLUyj9vb+8tiKClkDW3cz5MrrO5kF48pdmmnbDNSlr0tH/yahE7FHQoGsLGvFW4Fb/lt07bb6U/1fzom/gxCUXrAeEiEzoJaekXthFksxVbQmwm/wgPWsI5mfQYw3eX32kuB0EEdUP7DFt1PL/6UAmws3CViW82DVBreOW893m9yz5wSj35TnVwJ4KGMUG28CPfPP5xT1+OORnaBQtuCDAgLRogFOEQM+xoIzhmIUQCjtaBZyXxln/Z/EkvKwSKaCHqrAiEW9i9lW11xiME2bm/pV1h231T6m21zfkdZZ+W3+UueJn8HFOvdznG7qP/QyhTC6dZnKWfYVLMtwFfIp5IQhylwc3nRqAJTBzFE071vfwzDym/k+Bm/oZdF2MCxE2fB0UHxh/6E8Y2BNkyKwIfmW2oUwaLuxJiUycW1DYZv/Sup9Y7txeExrm91HnQXsQ/EZYFkHXc1v2U9kLfxyKiTEPRPh8dSjE6tJeDOdcRZKseCCr5oZUI/0Ffir1qaUIivGzx9Uq/jgtO7AzTWMJCCQeNQ7QDzCPW86pVZiB65bNDi4VZfhDazU9+8pPLj3t2pGFDu9WWCD8EWvd77PVHPEs9jo3F1bMTRzwBfnyL2CxGW79HyhceTQR/lm1ty/8o3SyQXzV3w1SRdt9iLvMQxtyjxKou66j53Fx+5nmZU4+ZU8vz5ZxHvqZfYIFOu8vpFziTTOeSsXMDPvJQ+gWbFslvz9dG4DRGgAmMCCFtz2QIcfIW5Z5AD+2BHrHay4q/iEEQBpGBVLbaFCYXBh4thXyoGSe7Q9mOcl7hVlq5MGbYfOLHBGETQltGhEBJ2z0RxtcDiLacE7+nlcW2P4RTq2hdPMfyY+ATiUnWfXYRFAqvfLhTjlNf57xpJ2gLtYj3DdMsamnIEyahsOJlF4GVhJngv4oR3Kad5Pqxat0jhF9MmPhp0t+LK/9t2r7yOJVcvjH6AezX1u2HyQamH/L3ICH0phhICEB6tCpaDBoLKiymraJcrzpuq9+r44zd64AahEwwkyIJ8REWivlEuKoJPNrc2Do+DtplHzil/tnmce5f6rRso5XWI2F5Esd9Ni+C9omE3lo0II5MuSDYYHEFYpzKcYrnir+82yXjlZPxHch0SfZnHOVbof6y553D0RrFlJWI5yAvBEnUFeL56u9M8RFOIShhHADbk9Cn7ZqXERbruHkcXHeMPar+TwKV/FxZSIZdzJqUBj5L/SELIfKf2pa1m4T8SZt/uczsv871qjwUPpan4uAqHgJ7fTfwkyxuKiy7jOmYu0AblgXGnEeO17pGoMzuPggBMT9pxqKogQA5p8sCYhY4+VZzONcII/S+6rqUgm78q9Pl+1a8bJP1mc985lK5So9wXeUjbMeEH2F5Gz38vOJnF4xb7QXNwbNC4xzejDE8p+Gavu8Zz3jGUG1w7L2vnBbsyZf3Vsfn3TA25LGlLnsoMC5yvroeC6e+zCsg6g+mmDIRsfWfvlp5reMytvBc/DC7UqdFEYQdrbkPwAyJ4qkOum+5ioObw3v+iqNw3WdXYbjZn+t1v0fiM2ftjWM5/1xu65q4EO0kKzE98pGP7JpfUBrMM7BLQKTFBN0fh3tm7MgQ0bchnG0RsgGekTkOOyAwa3cIY26rrkfll/m2bef669Y587xoTPcI3g9luppY8IOH5Icpuprwf8ITnrCwWDdFIF7ns697C7L3hazzNQInDAEERGxRE6H5fP311+t2cJlM586yp+GAcFbayEPiuOCANjSsRQhnYC4oH6YfbSAEhVlbV3Fx87YZrcajJa3JBYeXtFaTYaLZWo2mAz8mX5sQDIcEXTCdEmqirSEmRfnCBIt6duwe97jHDcJY4jIBatG6eLbykB+MnLQImJD2hP8I9YQXmvFTCOZbtlp5lxxEVh/KBxOJnWMJh2AEVZ+6DATD0rDMYRwWRP1EV1xxhS677jbtRBqOZI4GQktoRJuFARTlZ8ptozYRsE3bpywmUgj8+eXyVY+T5rKwJa3ALLDNz5G3NWehUY4z9Tp/p3VbJQ/el3aC6L6X9y6/07qMLFz90i/90hKMJk82ZyThKppB+q6P06xIxnbbPrDGo3WPEFBjAW1HC405Lod/MRaI0KqsBf0sDqifF9bEp38TZYE1GnoQu1tWLagpvdw8pjExrO1s0l8+5jGPGbT0lA4XIQ7fCgt6TEJaE/QsLGLCKUEYGn4QfXyrnyaMxUjaNHEYA3I/RniPtu3TevnKP9cDU2eZds3L5Lxb161FgG3G2F31f6161fUHx4xl1sxHaaDFS9E+1d7JL4+9uS2zY44FQJWhchjTaU89UjzC67Gylyb7b5s+51Vfk7eel2dgt0NrzIBHljmQdb4blZcFY+LDCMv+ipv72FZdwDD3d5tgqrJqN7eXhz/84c32wqKhMCN9vq7bS6vv67WX3PexoDe176ufob5nUZA+FcF3j5+awn9M+f5y2Xxr7JYRsQBJX4bAU2cuYDYrf3uKO8WFT+K5+NGvt8xH0L6zib7WbtkpZe0yTv6e675+0+9RCyk57yl1Jr5+OT6mMEUsbDNPzKYTcxrm1SyWyAQaGPfm0crzKFwE0pdeeulQFN9paz7KYodIO06PesxV+Yfi5j74KPjc/NyXXHLJwPNiMiibYVU8TI70lNHYPaZ+gcWJKf1CVvxg4U3zz2yeSGXv3Y0Vl3kMxnPcMNZefnE6+zy2DMzjMIZ5PNw8VnLnwYzMY4Apv9hOM+cXW31i3DAZASNwqiAQwt55TN7n0fGUX0x6589+9rPnsQI7j21Q8xBAD2HEiUMZFx790Y9+9EI4cWJgnMe2yHls8Z0HUziPbdcLcfAXxUnrQxj1CO3GUjZ9UGidzGMyP4STdzDISjq/+uqrF8Ji61OpM+kIi8nEEB7CnyEdF3re2n8hUrqJCd6QRmlDkJBi3HAZW8EX4oXwdh7M6jy0HAomF1xwwUI4eYXwZR4MUMlgWzzJRPULrcwbKnXjfwhihzDiBAM9D63Ceay0zkMLZB4CmSE8BEPzsDe7kH7sJgSrQ1ryDoHuPMw1zENwPX/hC184py6qF24sjixkFycrL4QTJxZZ5qGVM49te/PQFJvHQX9DHNpKMBJDHvnZYjvU4M/FNu0kBF5DmdTpqquumr/yla8sbRvM8rcTQqKFchlP9czEixXueQz+82BmS7xt2n5MdIe8wWVbiq25Q371u6nzDgHvEDfsr9XB5T60Ooc45J0pTDIMYfIPM0GDH5jxvYUwrfAhfD+xgLSAdeyuUNKVbqu8YP6G8mjroUFZ+JvQVJgTFmYYhnDqQ5wQUgxtbhff6cqK3xght3u1wZyW71ftTC48XosUXvcNLYxIT5tVGr7xKbRtH9grc+wbj+3QQz2pb+zkKX0HYw3vNr9P3qX62/p5QrtxIR/660whNCptQZjg0s9tQnlc5B3HInAZ++iTc5jK0rgZk46FOsbC8Dx2VM0Zj/jFJGNh7Lv//e8/VI/xnudXnvTTjD+M9zxH/raJE7ZUh7R5fBg8q4tt+rQqq6Vb6ql6M17EBGx+zTXXzGPCVuJuy8ssFdjwyO2IPiA0RAvPoai5jVLXqWPstv3fqnqpfj23bm+hEVr639j5Uniy3GbAnu8gJu/lx3UsuA3vhrYMHxfatvM4eHYhTO+P9kY6/WLCPaSPSfo8FmjmoZE8hCtez4VfVN6MtSF4Ke+GsYM0OZyxs5dPHJg45JPrGDZgF76bMAUyj10N5RnhdelvVD5u2K7vltErG/8wV7GQD/w4Y2mdJgSeQzzeDViFWaU574uw3B6oD3HgW2JBr+SlusZunqW8VRbjr+LBQ8kfN79v4tBeyJ/2z7uv20sIx7rp12kvfOuqE26cYTMPE1Bzxhx+9GGZ7w9lk4Vy8zPka+Y6OV94uRDQlPkGPCz8Z+b1QpllId+MN3Ok0H6eX3fddUMc5R2HSg9+IfReeN+02VwnylU63FigXQjPcceuaavKh/ZFWyFv5lKhrTkPje8hnPamvGjfSgeu8q9d5c87z2EXXnjhkD77c817Ud6hoLKQjvBcNv0NYyO8cwiES9xtvkfyUtn0u3Xd1K9Ncev5KW0kFnoKz8GcD3z5HnLboexQ1FnqivMcietYJFr501wnzzVCSL6U95gHsj7hgcucmHk7fSfjP/2xwnnHyAVF2465eUyHb2kR8yyVD5/TolikGeJkbDM/05ur5Oejf2wRPJbqQLuAtuVzp9RtbB4Vi31DnagbfRb4MF9mvhTKYgvhxEGOK4L30zPRL8An885pD4xfoWU+hNMvZMp5wzMfNbF1wILso0bd5RmBA0YAAQWDnzq1nhsryIURzo+SBTpT8oABzBSr7fNYyV5ZNnVCWJEptmqViWKvvvKnXnFYQU46lDdVkM3goPxwQwN5IT/dMMjVk8KcjmuYgcw84ofQFtoWT/JQebWwijAYbIWPuQjt1iXe7VieCoPpqCkLsle1IwZVBI6ZsgBBzJ3Ct2knCPNbiw96Frmh7T+nLWdi8lYzsMTXN7BN2z/VBNngxgRQeI65MJWhYZahHr1uCWnpD2hHY+XArIV9yoU4TE6hXXynJaMJf1m4Qn0RGGRiIpYFBzCoPdLz1n1DCyPy6AmVe/njv20f2Ctz7BunPdSLrnrW7PI9IrToUS3QYOGqprzoQ969yU+drr5H6JTrVl/zTmO30RBHgmzyCe37wb9Ol+8RsDDJzcREr9Uv5XRcIyjONEWQvU2flstqXYe2ZPOZ8+RsG16mVWbtlyd3wut+97vfQrRNx9ht+r8p9VqoZHWDUhO8kJ6p5zJOIwCrhTz522ylpS0jmFFYFhLTf7EgoTC5WahWC5vqe77/VptGKYO42wqyyQOhV6sM1VcugrK6flPv+eaUDy7jTCstC5WbjF8oBpCfythUkI3iG2mVT8+lvfB91s8Af9lLg/9YewnzWaNplS99H++9Lrt3H5r2k/JFeA5PmfOp+XnqEAfDD3FUpyzIRvAkf3CiDec8uYaXVRww4dur46y6J82Udks5jH/KLwuTj1qQjRBYz51dlClVv02/x1qQXfdl696zkMW7yfXsXROPPqlFWZDdS1/7swgEbSPIJn0WKNdl5HvaQU3bjLm53JMmyN6Wz91WkD11XpvbZuaVEFhP7Rf41jIdtyDbpkXiqzQZASPwZgTYUo29p+hYh63Vbw6dFTtJbLfDxhpblHsU2jczzGZEx7kUJYQr5UAM7L1lYks22+FJF51qDhquOeyE7eLZvhiBbK9nazV1i451iJ8vsOsVk6yFrXM5fOo1+ecygkltJmU7WTAqC9s6c8QQGBXzGrFKv4AT295q2gTPOo/6nu1sHEzC+2gR21hDW2PJ9ncrbu3Hu+WwtWDIFp5N8dh6R9m0sx7F5KyYFQktwqUotCtskWFXcZ2DdrZpJxyeFxrlxTZcCNibdeJwnJgALJkXwH4xB8PFJGUpHR7btP2cIdsDd0mrzCRksxZTyuUgkSkUgpxitqf3bmNiOgvBYrEduu4hVXX5bKXFZBJttSbaGdunMa+Qt48S76i+01ynbF4Ef9nHVhzqlJ8DUxfHSbvsA/NzjLU72gNtA/MqbOuvibHlktiOSd+WzYPU8e585zsv9F2tuBz4KMJM1tiYqHgtF5MlmFBq9SuYaiIsP0t+fuyih7bULBZNW1mXZ8B2bmjWFDNeORLPCA70pa2xGhNc4Njblprzqq931afV+XLPNvnQzlo4tBL/3F/tipch3xbBp3CwXAs3xd90jN2m/5tSL9Wv5WJjGZvvoXm7hC/xaaMhVC2HbbcOWKYt0x57bZmwXlsmf9oi29p7PCBxxoixFj6yN9ZuMl7k742y+W5iMWkGn9N6/3w3nFEwxt+MPQNhISRdiMLBfy1i/OIw2hCMLgVTN3hltnxjPihTa/zK4fm6fv4cRnuBP13VXjCb1GsvIRzpthfCeu0FPpJ+rR4XVT+en/E7tGGX+j7FabmYjIF3H+M/sF3NQY91e+IgPMaCVrtolYWNWsYrEbbpacM10QerTYf2a3deUafL99i7pS2M9eeY0QuBZLHxrrT1M8q/507l80g/1rYIp6/HjCM8X6bc16/7PWZTH8oTv22JdsichHFhrP+KBc9ZaPGWvq5V5iZ8vM4nyLi08l7lR9vlcFXmpy2KRc4ZNpJb39w2Y+66baxVtzG/Ve1sLO2qsG353HXrVn9fpEf+Qd+RZROqN37MS/N3n9s7/QJznGyCSmnlYpqT8xg4+6FH27a9Xr5j/m+BRjYPE9L1wb6UrlsumcXKQ8kTt8WojBXoMCNgBE4WAtj5wn4SjBU26dbtcGPFvNiai76mHDAFM4I9rVWEbS5ORebHNTZMsaXNyeRTKFYoi51tbCnTScNA73ugHKsXjGesgJbDY5h4cOBKZlY5VAshO5MC+tXeJGNTPMfqRhj5Uj9sFHIQ2BlnnDETY7Qq7apwxhLypS0hDB57vl5e2BtE4BLbCGfYRm9NiJSWw/908GZosZSJjMJqd5t2kt8pbQzcMnNQlzX1ftu2P7WckxIvNARnYfKsHBaFoJBvBLz3Qdg9pa3yHulv+GWi/bHQR1/I++7Rvr7TXnknwT9/L9v0ges+K30r9ij51nmfY+9t3bz3ET+0Y8qYy2QltKzWGnOxvxkaWTPGPcYQJtP05VPHPsZbsGK8PTMOf7rVrW61k0c8hD5tW15mWyA2HWOPsv+rn5GxG5vyCDZCS7QIk2p78nWafL9NW875HPr1vr6bdZ97V+PXuuXm+MfVXrbt+/Iz5Ovj/P5yPXZ9jV1fxorYkTZjjGRuBV+Vz1TYdZlHld9xfY81/8/3GDtOZqEJXw5E5PwDxtUpc+CjwmqsHOR81J02wnyQees6i/XHPeaOPdu+wo6Lz83PQx/MYgPtDB5ynXd20voFC7Lzm/e1ETACRsAInHgE0E5CawBaJcg+8Q/rBzACRsAIGAEjsGcEEGqbjIARMAJG4M0I1MLrN4f4yggYgX0jsFotct81cP5GwAgYASNgBHaEAJolbOkVTdXgV3y7RsAIGAEjYASMwCICWWBjofYiNr4zAkbg9EEg94Wnz1P7SY3A4SFgQfbhvRPXyAgYASNgBDZAANugcSDaQsqejcOFSL4xAkbACBgBI2AEJiGQBTkWak+CzJGMgBE4wQjkPu8EP4arbgROKQQsyD6lXqcfxggYASNw+iKANnYmDjfCPpjJCBgBI2AEjIAR2D0CPQGPBdy7x9o5GgEjsF8Eev3Zfkt17kbACGyCgAXZm6DmNEbACBgBI3BwCFx44YUzTvvmMCoOezznnHMOro6ukBEwAkbACBiBUx2BnkDIAu5T/c37+YzA4SPQ658Ov+auoREwAkLAhz0KCbtGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI3CQCNzkIGvlShkBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBG4EQELst0UjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbgoBGwIPugX48rZwSMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACFmS7DRgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMwEEjYEH2Qb8eV84IGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBCzIdhswAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGIGDRsCC7IN+Pa6cETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAhYkO02YASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACB42ABdkH/XpcOSNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARsCDbbcAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBA4aAQuyD/r1uHJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2BBttuAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgcNAIWZB/063HljIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbAgmy3ASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIAROGgELMg+6NfjyhkBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgAXZbgNGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI3DQCFiQfdCvx5UzAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAELst0GjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbgoBGwIPugX48rZwSMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACFmS7DRgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMwEEjYEH2Qb8eV84IGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBCzIdhswAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGIGDRsCC7IN+Pa6cETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAhYkO02YASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACB42ABdkH/XpcOSNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARsCDbbcAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBA4aAQuyD/r1uHJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2BBttuAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgcNAIWZB/063HljIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbAgmy3ASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIAROGgELMg+6NfjyhkBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgAXZbgNGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI3DQCFiQfdCvx5UzAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAELst0GjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbgoBGwIPugX48rZwSMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACFmS7DRgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMwEEjYEH2Qb8eV84IGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBCzIdhswAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGIGDRsCC7IN+Pa6cETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAhYkO02YASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACB42ABdkH/XpcOSNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIAR+H/MMmMv7Wt3PAAAAABJRU5ErkJggg==" + } + }, + "cell_type": "markdown", + "id": "130377a3", + "metadata": {}, + "source": [ + "----------------------------------------------------------------------------------------------------------------------\n", + "\n", "## Setup\n", "\n", "### Prerequisites\n", @@ -157,15 +173,9 @@ "\n", "This will cause every notebook cell to run in the virtual environment.\n", "\n", - "![Screen%20Shot%202022-08-26%20at%202.42.41%20PM.png](attachment:Screen%20Shot%202022-08-26%20at%202.42.41%20PM.png)" - ] - }, - { - "cell_type": "markdown", - "id": "f8d1892a", - "metadata": {}, - "source": [ - "### 6. Install the required stix-shifter libraries\n", + "![set_virtual_env.png](attachment:set_virtual_env.png)\n", + "\n", + "### 6. Install the required libraries used in this lab\n", "\n", "This installs the core stix-shifter and utils library along with the STIX-bundle and QRadar connectors." ] @@ -184,17 +194,8 @@ "stix-shifter-modules-stix_bundle \\\n", "stix-shifter-modules-qradar \\\n", "stix-shifter-modules-mysql \\\n", - "stix-shifter-modules-reaqta" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4b91ed03", - "metadata": {}, - "outputs": [], - "source": [ - "%pip list" + "ipython-sql \\\n", + "mysqlclient" ] }, { @@ -202,7 +203,11 @@ "id": "174f0aa9", "metadata": {}, "source": [ - "# Lab Exercise 1: Using CLI tools with the STIX-Bundle connector" + "----------------------------------------------------------------------------------------------------------------------\n", + "\n", + "# Lab Exercise 1: Using CLI tools with the STIX-Bundle connector\n", + "\n", + "The STIX Bundle connector is different from other connectors in that it doesn't actually translate any STIX patterns or JSON results. It will simply pass the pattern on the [stix2-matcher](https://pypi.org/project/stix2-matcher/) library which will then use it to query against a bundle of STIX data. Since this library returns a bundle of STIX data, stix-shifter does not need to translation the results back into STIX." ] }, { @@ -215,7 +220,7 @@ "\n", "https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json\n", "\n", - "The stix_bundle connector will query the sample STIX bundle and return a subset of data based on the query pattern.\n", + "The `stix_bundle` connector will query the sample STIX bundle and return a subset of data based on the query pattern.\n", "\n", "Note the bundle of observed-data objects that are returned. Each of these objects contains a numbered set of cyber observable objects (`url`, `network-traffic`, `ipv4-addr`…) which contain the data from the target data source. Given the above CLI example, the `ipv4-addr` object should contain a value property with **12.111.222.0**" ] @@ -253,7 +258,7 @@ }, { "cell_type": "markdown", - "id": "495c68af", + "id": "d8876e52", "metadata": {}, "source": [ "### STIX Identity Object\n", @@ -280,7 +285,7 @@ }, { "cell_type": "markdown", - "id": "33cae353", + "id": "11d38a9a", "metadata": {}, "source": [ "### Authentication object\n", @@ -383,13 +388,7 @@ "metadata": {}, "source": [ "## Step 6: Run the execute command\n", - "The execute command runs through the entire stix-shifter flow:\n", - "\n", - "* Translates a STIX pattern into a native data source query\n", - "* Sends the query to the data source via the data source APIs\n", - "* Checks the status of the query via the data source APIs\n", - "* Fetches the query results via the APIs and, if needed, converts them to JSON\n", - "* Translates the JSON results into STIX objects" + "Notice how the identity object, bundle URL and authentication, and STIX pattern are passed in. The result is a subset of observed-data objects from the original STIX bundle matching the pattern." ] }, { @@ -406,9 +405,11 @@ }, { "cell_type": "markdown", - "id": "04c029bb", + "id": "56507fe5", "metadata": {}, "source": [ + "----------------------------------------------------------------------------------------------------------------------\n", + "\n", "# Lab Exercise 2: Using CLI tools with the MySQL connector\n", "\n", "This connector relies on running a local or remote MySQL database. The transmission calls interface with the datasource using the source APIs, in this case [mysql.connector](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_transmission/api_client.py#L1). This is differenct from the STIX bundle connector that searches against a static JSON of data." @@ -416,31 +417,61 @@ }, { "cell_type": "markdown", - "id": "f0a0f72c", + "id": "da7fb10e", "metadata": {}, "source": [ - "## Step 1: Set environment variables to be used in the CLI and load MySQL\n", + "## Step 1: Set environment variables to be used in CLI and load MySQL\n", "\n", - "### Load the variables\n", + "### Database variables\n", "This will set variables for the database user, password, host, and name." ] }, { "cell_type": "code", "execution_count": null, - "id": "4511cc31", + "id": "3d572932", "metadata": {}, "outputs": [], "source": [ "%env DB_USER root\n", "%env DB_PASSWORD giveamanafish\n", "%env DB_HOST localhost\n", - "%env DB_NAME demo_db" + "%env DB_NAME demo_db\n", + "%env DB_TABLE demo_table\n", + "%env MYSQL_CONNECTION_OBJECT {\"host\":\"localhost\", \"database\":\"demo_db\", \"options\":{\"table\":\"demo_table\"}}\n", + "%env MYSQL_AUTH_OBJECT {\"auth\": {\"username\": \"root\", \"password\": \"giveamanafish\"}}" ] }, { "cell_type": "markdown", - "id": "d156958d", + "id": "c3fd5d0a", + "metadata": {}, + "source": [ + "### STIX Identity Object\n", + "The identity object represents the data source the STIX results are taken from." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8dbde031", + "metadata": {}, + "outputs": [], + "source": [ + "%env MYSQL_IDENTITY_OBJECT \\\n", + "{ \\\n", + " \"type\":\"identity\", \\\n", + " \"id\":\"identity--20a77a37-911e-468f-a165-28da7d02985b\", \\\n", + " \"name\":\"MySQL Database\", \\\n", + " \"identity_class\":\"system\", \\\n", + " \"created\": \"2022-04-07T20:35:41.042Z\", \\\n", + " \"modified\": \"2022-04-07T20:35:41.042Z\" \\\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "3a287299", "metadata": {}, "source": [ "### Load the Jupyter notebook MySQL extension" @@ -449,17 +480,17 @@ { "cell_type": "code", "execution_count": null, - "id": "6a2d97d9", + "id": "466a109b", "metadata": {}, "outputs": [], "source": [ "%load_ext sql\n", - "%sql mysql+mysqldb://$DB_USER:$DB_PASSWORD@$DB_HOST/$DB_NAME" + "%sql mysql://$DB_USER:$DB_PASSWORD@$DB_HOST/$DB_NAME" ] }, { "cell_type": "markdown", - "id": "bc87c97e", + "id": "eab57f00", "metadata": {}, "source": [ "## Step 2: Examine the demo table contents\n", @@ -470,8 +501,10 @@ { "cell_type": "code", "execution_count": null, - "id": "3c949717", - "metadata": {}, + "id": "20d3977c", + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "%%sql\n", @@ -479,10 +512,371 @@ "SELECT * FROM demo_table;" ] }, + { + "cell_type": "markdown", + "id": "43e69765", + "metadata": {}, + "source": [ + "## Step 3: Transmit the ping command\n", + "The `ping` command will check that the connector can talk to the MySQL instance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "79f0cfe7", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "stix-shifter transmit mysql \"$MYSQL_CONNECTION_OBJECT\" \"$MYSQL_AUTH_OBJECT\" ping\n" + ] + }, + { + "cell_type": "markdown", + "id": "667963a0", + "metadata": {}, + "source": [ + "## Step 4: Translate a STIX pattern into a native SQL query\n", + "\n", + "Translation from a STIX pattern to a native query is controlled by a `from_stix.json` mapping file. A snippet of the [MySQL from-STIX mapping file](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_translation/json/from_stix_map.json) shows:\n", + "\n", + "```json\n", + " \"url\": {\n", + " \"fields\": {\n", + " \"value\": [\"url\"]\n", + " }\n", + " },\n", + " \"file\": {\n", + " \"fields\": {\n", + " \"name\": [\"filename\"],\n", + " \"hashes.'SHA-256'\": [\"sha256hash\"],\n", + " \"hashes.MD5\": [\"md5hash\"],\n", + " \"parent_directory_ref.path\": [\"file_path\"],\n", + " \"created\": [\"file_created_time\"],\n", + " \"modified\": [\"file_modified_time\"],\n", + " \"accessed\": [\"file_accessed_time\"]\n", + " }\n", + " }\n", + "```\n", + "The outer key is the STIX object and the `fields` attribute contains a dictionary of STIX properties for that object. Each property is associated to a list of native data source fields. Using the following STIX pattern as an example:\n", + "\n", + "`[file:name = 'myfile.exe']`\n", + "\n", + "The connector would translate this into SQL query against the `filename` column in the table.\n", + "\n", + "The CLI input format for pattern translation is `translate query `. The MySQL connector requires that the table name be passed in the options. The translate query command returns a list of native query strings; in this case a list of SQL statements.\n", + "\n", + "Below you will see that several STIX patterns are stored in an environment variable. Try running each one at a time followed by the translate query command and see how each pattern is translated into a SQL query." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a22e96dc", + "metadata": {}, + "outputs": [], + "source": [ + "%env STIX_PATTERN=[url:value = 'www.example.org']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73e3930f", + "metadata": {}, + "outputs": [], + "source": [ + "%env STIX_PATTERN=[ipv4-addr:value = '10.0.0.9'] START t'2019-01-28T12:24:01.009Z' STOP t'2019-01-28T12:54:01.009Z'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d1754d9d", + "metadata": {}, + "outputs": [], + "source": [ + "%env STIX_PATTERN=[file:hashes.MD5 = 'edbe588a5881726e9bc41332ee330c72']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f1800cd8", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "stix-shifter translate mysql query \"$MYSQL_IDENTITY_OBJECT\" \"$STIX_PATTERN\" '{\"table\":\"'\"$DB_TABLE\"'\"}'" + ] + }, + { + "cell_type": "markdown", + "id": "2d1fad86", + "metadata": {}, + "source": [ + "Examine the [from_stix_map.json](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_translation/json/from_stix_map.json) file to see other supported mappings and experiment translating new patterns." + ] + }, + { + "cell_type": "markdown", + "id": "16e603af", + "metadata": {}, + "source": [ + "## Step 5: Transmit the query command\n", + "The `query` command sends the native query to the data source." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5aa7ece9", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "stix-shifter transmit mysql \"$MYSQL_CONNECTION_OBJECT\" \"$MYSQL_AUTH_OBJECT\" query \"SELECT * FROM demo_table WHERE url = 'www.example.org' limit 10000\"\n" + ] + }, + { + "cell_type": "markdown", + "id": "278f6a1e", + "metadata": {}, + "source": [ + "Note how the search_id that is returned is just the query string that was submitted. This is because the MySQL connector is synchronous. If this was an asynchronous connector, a search ID from the query API would have been returned instead." + ] + }, + { + "cell_type": "markdown", + "id": "fa444815", + "metadata": {}, + "source": [ + "## Step 6: Transmit the status command\n", + "\n", + "The `status` command passes in the search ID, in this case the query string, and returns the status of the search." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e82766b", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "stix-shifter transmit mysql \"$MYSQL_CONNECTION_OBJECT\" \"$MYSQL_AUTH_OBJECT\" status \"SELECT * FROM demo_table WHERE url = 'www.example.org' limit 10000\"\n" + ] + }, + { + "cell_type": "markdown", + "id": "2fd0c37e", + "metadata": {}, + "source": [ + "## Step 7: Transmit the results command\n", + "\n", + "The `results` command returns the raw query results in JSON format. In addition to the query ID (for MySQL this would be the query string) an offset and length is passed into the CLI command. The example below passes in 1 and 2, this would mean that the results start at the first row, returning two rows in total." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8244d828", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "stix-shifter transmit mysql \"$MYSQL_CONNECTION_OBJECT\" \"$MYSQL_AUTH_OBJECT\" results \"SELECT * FROM demo_table WHERE url = 'www.example.org' limit 10000\" 1 2\n" + ] + }, + { + "cell_type": "markdown", + "id": "e66e9fe6", + "metadata": {}, + "source": [ + "Notice that a list of JSON objects are returned. This is required by STIX-shifter before it can translate the results into STIX. If the data source API does not return JSON results, the results transmission logic will need to conver the results into JSON." + ] + }, + { + "cell_type": "markdown", + "id": "28cd409a", + "metadata": {}, + "source": [ + "## Step 8: Translate the query results into STIX\n", + "\n", + "Similar to translating STIX patterns to native queries, translating JSON results to STIX is largely driven by the connector's `to_stix_map.json` file. A snippet of the [MySQL to-STIX mapping file](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_translation/json/to_stix_map.json) is shown below:\n", + "\n", + "```\n", + "{\n", + " \"username\": [\n", + " {\n", + " \"key\": \"user-account.user_id\",\n", + " \"object\": \"useraccount\"\n", + " }\n", + " ],\n", + " \"displayname\": [\n", + " {\n", + " \"key\": \"user-account.display_name\",\n", + " \"object\": \"useraccount\"\n", + " }\n", + " ],\n", + " \"filename\": [\n", + " {\n", + " \"key\": \"file.name\",\n", + " \"object\": \"fl\"\n", + " },\n", + " {\n", + " \"key\": \"process.binary_ref\",\n", + " \"object\": \"process\",\n", + " \"references\": \"fl\"\n", + " }\n", + " ]\n", + "}\n", + "```\n", + "The mapping is the reverse of what we saw with the from-STIX map. The outer keys are the field names returned in the query results and the values contain a list of properties: \n", + "1. The `\"key\"` property contains the STIX object and property that the data source field maps to. In the example above, data from the `username` field would be written to the STIX `user-account:user_id` property.\n", + "2. The `\"object\"` property allows multiple properties to be grouped under the same STIX object. In the example above, data from the `username` and `displayname` fields would be written to the same `useraccount` STIX object under the `user_id` and `display_name` properties respecitvely. \n", + "3. The `filename` field is mapping to multiple STIX objects. The data in the file name is written to the STIX `file:name` property. When a `filename` is encountered in the results, it also creates a reference between to the STIX `file` object (note the `\"object\": \"fl\"`) from an existing process object under `process:binary_ref`.\n", + "\n", + "### Load the sample results we wish to translate" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2876a76b", + "metadata": {}, + "outputs": [], + "source": [ + "%env MYSQL_RESULTS \\\n", + "[ \\\n", + " { \\\n", + " \"source_ipaddr\": \"10.0.0.9\", \\\n", + " \"dest_ipaddr\": \"10.0.0.9\", \\\n", + " \"url\": \"www.example.org\", \\\n", + " \"filename\": \"spreadsheet.doc\", \\\n", + " \"sha256hash\": \"b0795d1f264efa26bf464612a95bba710c10d3de594d888b6282c48f15690459\", \\\n", + " \"md5hash\": \"0a556fbb7d3c184fad0a625afccd2b62\", \\\n", + " \"file_path\": \"C:/PHOTOS\", \\\n", + " \"username\": \"root\",\\\n", + " \"source_port\": 143, \\\n", + " \"dest_port\": 8080, \\\n", + " \"protocol\": \"udp\", \\\n", + " \"entry_time\": 1617123877.0, \\\n", + " \"system_name\": \"demo_system\", \\\n", + " \"severity\": 2, \\\n", + " \"magnitude\": 1 \\\n", + " } \\\n", + "]" + ] + }, + { + "cell_type": "markdown", + "id": "f2d7d9b9", + "metadata": {}, + "source": [ + "### Translate the results into STIX" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85a0a007", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "stix-shifter translate mysql results \"$MYSQL_IDENTITY_OBJECT\" \"$MYSQL_RESULTS\" '{\"table\":\"'\"$DB_TABLE\"'\"}'\n" + ] + }, + { + "cell_type": "markdown", + "id": "cc1ed395", + "metadata": {}, + "source": [ + "Since only one row was in the sample results, only one observed data object is returned in the bundle. As mentioned before, the identity object is inserted at the top of the bundle and represents the data source the results are coming from; note how the observed-data object has a `created_by_ref` property that references the identity object by its ID.\n", + "\n", + "The observed-data object has an `objects` property that contains a numbered dictionary of cyber observable (cybox) objects. The properties of these cybox objects hold the data returned from the query based on the to-STIX mapping. The sample data had the value `spreadsheet.doc` stored in the `filename` field. You can see how that was written to the `name` property of the `file` STIX object.\n", + "\n", + "The translated STIX shows how referencing works. The `network-traffic` object has a `src_ref` and `dst_ref` property, each pointing to the numbered key for a `ipv4-addr` object in the same `observed-data` object.\n", + "\n", + "Experiment with editing the field names and data in the below sample data and try translating it again to see the results. If you rename a field, like changing `filename` to `file-name`, you will see that it's data no longer appears in the STIX results. This is because the new field name is not represented in the [to_stix_map.json](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_translation/json/to_stix_map.json) mapping." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4f58f237", + "metadata": {}, + "outputs": [], + "source": [ + "%env MYSQL_RESULTS \\\n", + "[ \\\n", + " { \\\n", + " \"source_ipaddr\": \"10.0.0.9\", \\\n", + " \"dest_ipaddr\": \"10.0.0.9\", \\\n", + " \"url\": \"www.example.org\", \\\n", + " \"sha256hash\": \"b0795d1f264efa26bf464612a95bba710c10d3de594d888b6282c48f15690459\", \\\n", + " \"md5hash\": \"0a556fbb7d3c184fad0a625afccd2b62\", \\\n", + " \"file_path\": \"C:/PHOTOS\", \\\n", + " \"username\": \"root\", \\\n", + " \"filename\": \"blah.jpg\", \\\n", + " \"source_port\": 143, \\\n", + " \"dest_port\": 8080, \\\n", + " \"protocol\": \"udp\", \\\n", + " \"entry_time\": 1617123877.0, \\\n", + " \"system_name\": \"demo_system\", \\\n", + " \"severity\": 2, \\\n", + " \"magnitude\": 1 \\\n", + " } \\\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "757dd4db", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "stix-shifter translate mysql results \"$MYSQL_IDENTITY_OBJECT\" \"$MYSQL_RESULTS\" '{\"table\":\"'\"$DB_TABLE\"'\"}'\n" + ] + }, + { + "cell_type": "markdown", + "id": "693c0773", + "metadata": {}, + "source": [ + "## Step 9: Run the execute command against the MySQL connector\n", + "\n", + "We did this before for the bundle connector. The execute command will run through each of the translation and transmission steps covered above and return a bundle of STIX results. The STIX results are based on the pattern that is passed in. The format for calling the execute command is:\n", + "```\n", + "stix-shifter execute \n", + "```\n", + "The connector name is repeated twice to allow for the possiblity of using different modules for translation and transmission." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "28b6240d", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "\n", + "stix-shifter execute mysql mysql \"$MYSQL_IDENTITY_OBJECT\" \"$MYSQL_CONNECTION_OBJECT\" \"$MYSQL_AUTH_OBJECT\" \"$STIX_PATTERN\"\n" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "b4956816", + "id": "0208af54", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/set_virtual_env.png b/notebooks/set_virtual_env.png new file mode 100644 index 0000000000000000000000000000000000000000..2ca7cdef15b4be74a3ffc9909a614cc182dc0fc2 GIT binary patch literal 146242 zcmb@tWmsInvM!7h+=2%W?h*)2LU0Qb7=jKkxI4juJA~j)&=A~haQEQu!CeO!2JYmX 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zjp~?`A+Rbc%m`rJiNGhGzX`Q;dVNVC$X=27Ta8^^fyO=yq2gL6Di)Ha{}vW$yUYIlV{EDWf9);A z6VBKEw^MK(0P4pE43u{y5C-G_92!E$yZ*nO!vA%=e?LI}ujBo5KmYT>{C^$q-wvk# d&sV&|pk6VU@P?x|n27LESJ6@~Q#615{{VB~8zcY# literal 0 HcmV?d00001 From 268bea2d7e205af99e33f3e12bca9a4d95142a07 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Wed, 7 Sep 2022 13:23:20 -0300 Subject: [PATCH 13/19] add coding lab and table population script to CLI lab --- notebooks/STIX-shifter CLI Quick Lab.ipynb | 206 +++++++++++++++++---- notebooks/connector_coding_lab.md | 141 ++++++++++++++ notebooks/data.csv | 14 ++ 3 files changed, 325 insertions(+), 36 deletions(-) create mode 100644 notebooks/connector_coding_lab.md create mode 100644 notebooks/data.csv diff --git a/notebooks/STIX-shifter CLI Quick Lab.ipynb b/notebooks/STIX-shifter CLI Quick Lab.ipynb index bad9d4951..defa0ab03 100644 --- a/notebooks/STIX-shifter CLI Quick Lab.ipynb +++ b/notebooks/STIX-shifter CLI Quick Lab.ipynb @@ -149,33 +149,53 @@ "* venv\n", "* Ability to run bash commands\n", "\n", - "### 1. Open a terminal and install a Python virtual environment\n", + "### 1. Open a terminal and create a working folder\n", + "\n", + "Call the folder **connector_lab**\n", + "\n", + "`mkdir connector_lab`\n", + "\n", + "`cd connector_lab` \n", + "\n", + "### 2. Clone the stix-shifter project\n", + "\n", + "`git clone https://github.com/opencybersecurityalliance/stix-shifter.git`\n", + "\n", + "### 3. Install a Python virtual environment\n", "\n", "`python3 -m venv labenv`\n", "\n", "`source labenv/bin/activate`\n", "\n", - "### 2. Install jupyter notebook\n", + "### 4. Upgrade pip\n", + "\n", + "`python3 -m pip install --upgrade pip`\n", + "\n", + "### 5. Install jupyter notebook\n", "\n", - "`pip install notebook`\n", + "`python3 -m pip install notebook`\n", "\n", - "### 3. Install ipython kernal to use virtual environment\n", + "### 6. Install ipython kernal to use virtual environment\n", "\n", "`ipython kernel install --user --name=labenv`\n", "\n", - "### 4. Run jupyter notebook\n", + "### 7. CD into the STIX-shifter notebooks directory\n", + "\n", + "`cd stix-shifter/notebooks`\n", + "\n", + "### 8. Run jupyter notebook\n", "\n", "`jupyter notebook`\n", "\n", "### All remaining steps take place in the jupyter notebook\n", "\n", - "### 5. Change the Kernel to use the virtual environment\n", + "### 9. Change the Kernel to use the virtual environment\n", "\n", "This will cause every notebook cell to run in the virtual environment.\n", "\n", "![set_virtual_env.png](attachment:set_virtual_env.png)\n", "\n", - "### 6. Install the required libraries used in this lab\n", + "### 10. Install the shared STIX-shifter libraries used in this lab\n", "\n", "This installs the core stix-shifter and utils library along with the STIX-bundle and QRadar connectors." ] @@ -188,14 +208,7 @@ "outputs": [], "source": [ "%%bash\n", - "pip install \\\n", - "stix-shifter \\\n", - "stix-shifter-utils \\\n", - "stix-shifter-modules-stix_bundle \\\n", - "stix-shifter-modules-qradar \\\n", - "stix-shifter-modules-mysql \\\n", - "ipython-sql \\\n", - "mysqlclient" + "python3 -m pip install stix-shifter stix-shifter-utils" ] }, { @@ -234,12 +247,31 @@ "The transmission commands use the data source APIs to send a query, check the status, fetch the results, and ping the connection." ] }, + { + "cell_type": "markdown", + "id": "1204ef99", + "metadata": {}, + "source": [ + "## Step 1: Install the STIX Bundle connector library" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8ceff7d8", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "python3 -m pip install stix-shifter-modules-stix_bundle" + ] + }, { "cell_type": "markdown", "id": "0257bd78", "metadata": {}, "source": [ - "## Step 1: Set environment variables to be used in the CLI\n", + "## Step 2: Set environment variables to be used in the CLI\n", "\n", "### STIX Bundle URL\n", "This points to a publicly aviablable, static JSON file of STIX data. " @@ -307,7 +339,7 @@ "id": "e407e416", "metadata": {}, "source": [ - "## Step 2: Run the ping command\n", + "## Step 3: Run the ping command\n", "The `ping` command checks that the data source can be reached by the stix-shifter connector." ] }, @@ -327,7 +359,7 @@ "id": "533c714d", "metadata": {}, "source": [ - "## Step 3: Run the query command\n", + "## Step 4: Run the query command\n", "This command sends the native query to the data source." ] }, @@ -347,7 +379,7 @@ "id": "a5496cbf", "metadata": {}, "source": [ - "## Step 4: Run the status command\n", + "## Step 5: Run the status command\n", "This command checks the status of the query." ] }, @@ -367,7 +399,7 @@ "id": "a94dde00", "metadata": {}, "source": [ - "## Step 5: Run the results command\n", + "## Step 6: Run the results command\n", "This command fetches the query results" ] }, @@ -387,7 +419,7 @@ "id": "49f1244e", "metadata": {}, "source": [ - "## Step 6: Run the execute command\n", + "## Step 7: Run the execute command\n", "Notice how the identity object, bundle URL and authentication, and STIX pattern are passed in. The result is a subset of observed-data objects from the original STIX bundle matching the pattern." ] }, @@ -415,12 +447,35 @@ "This connector relies on running a local or remote MySQL database. The transmission calls interface with the datasource using the source APIs, in this case [mysql.connector](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_transmission/api_client.py#L1). This is differenct from the STIX bundle connector that searches against a static JSON of data." ] }, + { + "cell_type": "markdown", + "id": "6e8194e1", + "metadata": {}, + "source": [ + "## Step 1: Install the required MySQL Connector libraries" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "718c2997", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "pip install \\\n", + "stix-shifter-modules-mysql \\\n", + "ipython-sql \\\n", + "mysqlclient \\\n", + "mysql-connector-python \\" + ] + }, { "cell_type": "markdown", "id": "da7fb10e", "metadata": {}, "source": [ - "## Step 1: Set environment variables to be used in CLI and load MySQL\n", + "## Step 2: Set environment variables to be used in CLI and load MySQL\n", "\n", "### Database variables\n", "This will set variables for the database user, password, host, and name." @@ -434,12 +489,12 @@ "outputs": [], "source": [ "%env DB_USER root\n", - "%env DB_PASSWORD giveamanafish\n", + "%env DB_PASSWORD Giveamanafish!1\n", "%env DB_HOST localhost\n", "%env DB_NAME demo_db\n", "%env DB_TABLE demo_table\n", "%env MYSQL_CONNECTION_OBJECT {\"host\":\"localhost\", \"database\":\"demo_db\", \"options\":{\"table\":\"demo_table\"}}\n", - "%env MYSQL_AUTH_OBJECT {\"auth\": {\"username\": \"root\", \"password\": \"giveamanafish\"}}" + "%env MYSQL_AUTH_OBJECT {\"auth\": {\"username\": \"root\", \"password\": \"Giveamanafish!1\"}}" ] }, { @@ -484,16 +539,84 @@ "metadata": {}, "outputs": [], "source": [ - "%load_ext sql\n", + "%reload_ext sql\n", "%sql mysql://$DB_USER:$DB_PASSWORD@$DB_HOST/$DB_NAME" ] }, + { + "cell_type": "markdown", + "id": "08dc6541", + "metadata": {}, + "source": [ + "### Create and populate MySQL table" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fbce8f2e", + "metadata": {}, + "outputs": [], + "source": [ + "import mysql.connector\n", + "import json\n", + "import csv\n", + "\n", + "# Drop table is exists\n", + "\n", + "cnx = mysql.connector.connect(user=\"root\", password=\"Giveamanafish!1\", \n", + " host=\"localhost\", database=\"demo_db\", \n", + " port=3306, auth_plugin='mysql_native_password')\n", + "cursor = cnx.cursor()\n", + "data_file = open(\"data.csv\")\n", + "\n", + "csv_reader = csv.reader(data_file, delimiter=',')\n", + "csv_rows = []\n", + "fields_list = []\n", + "data_types_list = []\n", + "table = \"demo_table\"\n", + "\n", + "sql = \"DROP TABLE IF EXISTS {}\".format(table)\n", + "cursor.execute(sql)\n", + "\n", + "# Create table\n", + "\n", + "for row in csv_reader:\n", + " csv_rows.append(row)\n", + "fields_list = csv_rows[0]\n", + "data_types_list = csv_rows[1]\n", + "\n", + "fields_and_type = \"(\"\n", + "for index, field in enumerate(fields_list):\n", + " fields_and_type += \"{} {}, \".format(field, data_types_list[index])\n", + "fields_and_type = fields_and_type[:-2]\n", + "fields_and_type += \")\"\n", + "print(\"Creating table with the following fields: {}\".format(fields_list))\n", + "sql = \"CREATE TABLE {} {};\".format(table, fields_and_type)\n", + "cursor.execute(sql)\n", + "\n", + "# Populate table from CSV file\n", + "\n", + "print(\"Populating table with data\")\n", + "sql_insert_parameters = (\"%s,\" * len(fields_list))[:-1]\n", + "for index, row in enumerate(csv_rows):\n", + " if index < 2:\n", + " continue\n", + " sql = \"INSERT INTO {} ({}) VALUES ({})\".format(table, \", \".join(fields_list), sql_insert_parameters)\n", + " value_tuple = tuple(row)\n", + " cursor.execute(sql, value_tuple)\n", + " cnx.commit()\n", + " \n", + "cnx.close()\n", + " \n" + ] + }, { "cell_type": "markdown", "id": "eab57f00", "metadata": {}, "source": [ - "## Step 2: Examine the demo table contents\n", + "## Step 3: Examine the demo table contents\n", "\n", "This will be the data the MySQL connector will query against." ] @@ -517,7 +640,7 @@ "id": "43e69765", "metadata": {}, "source": [ - "## Step 3: Transmit the ping command\n", + "## Step 4: Transmit the ping command\n", "The `ping` command will check that the connector can talk to the MySQL instance." ] }, @@ -538,7 +661,7 @@ "id": "667963a0", "metadata": {}, "source": [ - "## Step 4: Translate a STIX pattern into a native SQL query\n", + "## Step 5: Translate a STIX pattern into a native SQL query\n", "\n", "Translation from a STIX pattern to a native query is controlled by a `from_stix.json` mapping file. A snippet of the [MySQL from-STIX mapping file](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_translation/json/from_stix_map.json) shows:\n", "\n", @@ -625,7 +748,7 @@ "id": "16e603af", "metadata": {}, "source": [ - "## Step 5: Transmit the query command\n", + "## Step 6: Transmit the query command\n", "The `query` command sends the native query to the data source." ] }, @@ -654,7 +777,7 @@ "id": "fa444815", "metadata": {}, "source": [ - "## Step 6: Transmit the status command\n", + "## Step 7: Transmit the status command\n", "\n", "The `status` command passes in the search ID, in this case the query string, and returns the status of the search." ] @@ -676,7 +799,7 @@ "id": "2fd0c37e", "metadata": {}, "source": [ - "## Step 7: Transmit the results command\n", + "## Step 8: Transmit the results command\n", "\n", "The `results` command returns the raw query results in JSON format. In addition to the query ID (for MySQL this would be the query string) an offset and length is passed into the CLI command. The example below passes in 1 and 2, this would mean that the results start at the first row, returning two rows in total." ] @@ -706,7 +829,7 @@ "id": "28cd409a", "metadata": {}, "source": [ - "## Step 8: Translate the query results into STIX\n", + "## Step 9: Translate the query results into STIX\n", "\n", "Similar to translating STIX patterns to native queries, translating JSON results to STIX is largely driven by the connector's `to_stix_map.json` file. A snippet of the [MySQL to-STIX mapping file](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/mysql/stix_translation/json/to_stix_map.json) is shown below:\n", "\n", @@ -852,15 +975,26 @@ "id": "693c0773", "metadata": {}, "source": [ - "## Step 9: Run the execute command against the MySQL connector\n", + "## Step 10: Run the execute command against the MySQL connector\n", "\n", "We did this before for the bundle connector. The execute command will run through each of the translation and transmission steps covered above and return a bundle of STIX results. The STIX results are based on the pattern that is passed in. The format for calling the execute command is:\n", "```\n", - "stix-shifter execute \n", + "stix-shifter execute \n", + " \n", "```\n", "The connector name is repeated twice to allow for the possiblity of using different modules for translation and transmission." ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "12c0bc97", + "metadata": {}, + "outputs": [], + "source": [ + "%env STIX_PATTERN=[url:value = 'www.example.org']" + ] + }, { "cell_type": "code", "execution_count": null, @@ -876,7 +1010,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0208af54", + "id": "3a1c8f2f", "metadata": {}, "outputs": [], "source": [] @@ -898,7 +1032,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.10.6" } }, "nbformat": 4, diff --git a/notebooks/connector_coding_lab.md b/notebooks/connector_coding_lab.md new file mode 100644 index 000000000..81ce53d05 --- /dev/null +++ b/notebooks/connector_coding_lab.md @@ -0,0 +1,141 @@ +# Connector Coding Lab + +This is a hands on lab to start implementing a connector module in STIX-shifter from scratch. The main purpose of this lab is to give developers experience developing a functional connector. You will basically recreate an already existing connector. We will mostly copy and paste required code blocks and functions. We chose the MySQL connector since its coding complexity is simpler than most of the existing connectors.  + + +## Prerequisites + +Github account +Basic knowledge of Git such as forking, committing, branching, pulling, and merging +Working knowledge of the Python programming language. This lab will use Python 3.9 +An IDE to write Python code, such as VS Code. + +## Steps + +1. Make a copy of `stix_shifter_modules/synchronous_template` module +2. Change the name to `lab_connector` + You should have connector module skeleton for the new connector name lab_connector +3. Implement `EntryPoint()` class in `stix_shifter_modules/lab_connector/entry_point.py`.  + + ``` + from stix_shifter_utils.utils.base_entry_point import BaseEntryPoint + + class EntryPoint(BaseEntryPoint): +     def __init__(self, connection={}, configuration={}, options={}): +         super().__init__(connection, configuration, options) +         self.set_async(False) +         if connection: +             self.setup_transmission_basic(connection, configuration) +         self.setup_translation_simple(dialect_default='default') + ``` + +4. Implement input configuration of the connector in `stix_shifter_modules/lab_connector/configuration` + + * Implement connection and configuration of the connector in config.json file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/config.json for this lab + + * You can also implement the language definition of the input configuration for the UI label and description in lang_en.json(for English) file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/lang_en.json for this lab. + +5. Implement stix to query translation + + * Go to `stix_shifter_modules/lab_connector/stix_translation` + + * Update `stix_shifter_modules/lab_connector/stix_translation/json/from_stix_map.json` file with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/json/from_stix_map.json + + * If data source API offers one schema type the dialect prefix can be removed + + * Update `stix_shifter_modules/lab_connector/stix_translation/json/operators.json` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/json/operators.json + + ### correct? + * QueryTranslator() class can be left as it `stix_shifter_modules/mysql/stix_translation/query_translator.py` + * Update `stix_shifter_modules/lab_connector/stix_translation/query_constructor.py` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/query_constructor.py + + * You can now run the basic query translation CLI command from your workspace to tests + +6. Implement stix transmission module. + + * You need to implement four functionalities of the transmission module which are `ping`, `query`, `status` and `results`.  + * First step, create a class called `APIClient()` in `stix_shifter_modules/lab_connector/stix_transmission/api_client.py` where you initialize the connection and configurations needed for data source API requests. This class also includes the utility functions needed for the major functionalities of the connector. + + ### Ping + + * Define and implement a function named `ping_connection(self)` inside `stix_shifter_modules/lab_connector/stix_transmission/connector.py`  + + ``` + def ping_connection(self): +         response = self.api_client.ping_data_source() +         response_code = response.get('code') +         response_txt = response.get('message') +         return_obj = dict() +         return_obj['success'] = False + +         if len(response) > 0 and response_code == 200: +             return_obj['success'] = True +         else: +             ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) +         return return_obj + ``` + +* Define and implement `ping_data_source()` function inside `APIClient()`: + + ``` + def ping_data_source(self): + # Pings the data source +         response = {"code": 200, "message": "All Good!"} +         try: +             cnx = lab_connector.connector.connect(user=self.user, password=self.password,  +                                           host=self.host, database=self.database,  +                                           port=self.port, auth_plugin=self.auth_plugin)   + + +         except lab_connector.connector.Error as err: +             response["code"] = err.errno + + +             if err.errno == errorcode.ER_ACCESS_DENIED_ERROR: +                 response["message"] = "Something is wrong with your user name or password" +             elif err.errno == errorcode.ER_BAD_DB_ERROR: +                 response["message"] = "Database does not exist" +             else: +                 response["message"] = err +         else: +             cnx.close() +         return response + ``` + + ### Query + + * As a synchronous connector, it doesn't require any API request to start or create the query. Therefore no need to define and implement the functions of the query function. `self.setup_transmission_basic(connection, configuration)` statement inside entry point class `EntryPoint()` takes care of that automatically. + + ### Status + + * Same as query, synchronous connector doesn't return any status from the data source hence no action needed. + + ### Results + + * Define and implement a function named `create_results_connection(self, query, offset, length)` inside `stix_shifter_modules/lab_connector/stix_transmission/connector.py` + + ``` + def create_results_connection(self, query, offset, length): +         return_obj = dict() +         response = self.api_client.run_search(query, start=offset, rows=length) +         response_code = response.get('code') +         response_txt = response.get('message') +         if response_code == 200: +             return_obj['success'] = True +             return_obj['data'] = response.get('result') +         else: +             ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) +         return return_obj + ``` + + * Define and implement a function named `run_search(self, query, offset, length)`  in `APIClient()` class. + + * Copy the code block https://github.com/opencybersecurityalliance/stix-shifter/blob/8ae2cf2a0196531b8e0daf8f5ff141b4251ec201/stix_shifter_modules/mysql/stix_transmission/api_client.py#L40 + + * You can now run all the transmission CLI command from your workspace to tests + +7. Implement `ErrorMapper()` class in `stix_shifter_modules/lab_connector/stix_transmission/error_mapper.py` for mapping any API specific error code message for the return object. This same content can be used: https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_transmission/error_mapper.py + +8. Add any data source specific dependency to the stix_shifter_modules/lab_connector/requirements.txt.  In this case add `mysql-connector-python==8.0.25` + +9. You also need to create a `README.md` for the connector which includes the details of the API or SDK used in the connector and also some sample commands and the results `stix_shifter_modules/lab_connector/README.md` \ No newline at end of file diff --git a/notebooks/data.csv b/notebooks/data.csv new file mode 100644 index 000000000..2e03d39ee --- /dev/null +++ b/notebooks/data.csv @@ -0,0 +1,14 @@ +source_ipaddr,dest_ipaddr,url,filename,sha256hash,md5hash,file_path,username,source_port,dest_port,protocol,entry_time,system_name,severity,magnitude +varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),varchar(100),int,int,varchar(100),double,varchar(100),int,int +192.168.16.4,213.213.142.5,www.example.org,photos.exe,2bc21ad4860422599ef29e6d23d354625a67a53d1ff8e09f7ce392ce7e779dc4,276134d96a0648c24505b455150cb41a,C:/PHOTOS,97bd1036example.org,143,8080,udp,1617123877,demo_system,8,5 +10.0.0.9,192.168.16.4,www.example.com,calendar.doc,a2c0dd1eeed012132907c1cc8dcca1f77a12c537d7d875f3627c440502f295c2,60f7ec355f60c768bc684ccf718d48d7,user/preferences/lib,root,143,8080,udp,1617123877,demo_system,2,1 +172.16.25.9,10.0.0.9,www.example.net,photos.exe,b0795d1f264efa26bf464612a95bba710c10d3de594d888b6282c48f15690459,276134d96a0648c24505b455150cb41a,usr/bin,root,143,8080,udp,1617123877,demo_system,7,4 +10.0.0.9,10.0.0.9,www.example.com,calendar.doc,d502e7541b1a79ba77a010634beb6eedd178f1110535bc73f96a50c891eed1ef,60f7ec355f60c768bc684ccf718d48d7,user/preferences/lib,1eeb5a46example.org,143,8080,udp,1617123877,demo_system,2,1 +192.168.16.4,10.0.0.9,www.example.com,appointment.xml,fe095939f684e9c3d3c5d9aa15436e1b1de9c22cee23afa8332e226560ea2b2f,9affc3c0175130f9ac80b086d7949291,C:/PHOTOS,root,143,8080,udp,1617123877,demo_system,6,5 +172.16.25.9,172.16.25.9,www.example.org,photos.exe,3be262c0c7a91818a3795a814cda5efaae0a759f77b8050921b5aea099093357,276134d96a0648c24505b455150cb41a,user/preferences/lib,15e6d6f7example.org,143,8080,udp,1617123877,demo_system,3,2 +10.0.0.9,213.213.142.5,www.example.net,calendar.doc,a8db77b872512df0fd15943a79efb4e16c745cd8122efaf948b3c56d463e4b70,60f7ec355f60c768bc684ccf718d48d7,user/preferences/lib,user,143,8080,udp,1617123877,demo_system,2,1 +192.168.16.4,10.0.0.9,www.example.com,calendar.doc,63fcbaa237eb8d9a3f32ecf850831fd283512b30ece26ee8bc43ec013edf2210,60f7ec355f60c768bc684ccf718d48d7,C:/PHOTOS,admin,143,8080,udp,1617123877,demo_system,6,5 +172.16.25.9,192.168.16.4,www.example.net,appointment.xml,e2df00798b677eaba24393c340913de955d16b0920af6e5a5f1d3a1b4f8669e5,9affc3c0175130f9ac80b086d7949291,C:/PHOTOS,user,143,8080,tcp,1617123877,demo_system,1,1 +10.0.0.9,192.168.16.4,www.example.net,photos.exe,efe833b6172b3eb4be1e73dfe56f589f7b1ad86493b8a1b3ec5f018fb037d7c6,276134d96a0648c24505b455150cb41a,C:/PHOTOS,root,143,8080,udp,1617123877,demo_system,4,3 +172.16.25.9,10.0.0.9,www.example.com,photos.exe,3be262c0c7a91818a3795a814cda5efaae0a759f77b8050921b5aea099093357,276134d96a0648c24505b455150cb41a,user/preferences/lib,admin,143,8080,tcp,1617123877,demo_system,6,4 +10.0.0.9,10.0.0.9,www.example.org,spreadsheet.doc,b0795d1f264efa26bf464612a95bba710c10d3de594d888b6282c48f15690459,0a556fbb7d3c184fad0a625afccd2b62,C:/PHOTOS,root,143,8080,udp,1617123877,demo_system,2,1 \ No newline at end of file From 1356bfd3522bd458be6dd29ad8b11eb55c83003a Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Wed, 7 Sep 2022 13:38:34 -0300 Subject: [PATCH 14/19] add deployment readme and add link to notebooks from main readme --- README.md | 4 +++- deployment/README.md | 3 +++ 2 files changed, 6 insertions(+), 1 deletion(-) create mode 100644 deployment/README.md diff --git a/README.md b/README.md index 5ff8b7c8b..148bc62d5 100644 --- a/README.md +++ b/README.md @@ -98,10 +98,12 @@ We are thrilled you are considering contributing! We welcome all contributors. Please read our [guidelines for contributing](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/CONTRIBUTING.md). -## Guide for creating new connectors +## Developer Guides If you want to create a new connector for STIX-shifter, see the [developer guide](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/adapter-guide/develop-stix-adapter.md) +There are also a few [Jupyter Notebook labs](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/notebooks) that cover the CLI commands and dev process. + ## Licensing Licensed under the Apache License, Version 2.0 (the "License"); diff --git a/deployment/README.md b/deployment/README.md new file mode 100644 index 000000000..ff5cd3eb7 --- /dev/null +++ b/deployment/README.md @@ -0,0 +1,3 @@ +# Connector Deployment Scripts + +This folder contains scripts that deploy connectors into specific security products that use STIX-shifter. \ No newline at end of file From 9b50dcd584e2286bd14c38f30873751af2a84356 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Wed, 7 Sep 2022 13:43:12 -0300 Subject: [PATCH 15/19] remove old quicklab and test comment --- adapter-guide/cli-quick-lab.md | 290 ------------------ .../test_mysql_stix_to_query.py | 2 - 2 files changed, 292 deletions(-) delete mode 100644 adapter-guide/cli-quick-lab.md diff --git a/adapter-guide/cli-quick-lab.md b/adapter-guide/cli-quick-lab.md deleted file mode 100644 index 67f01b057..000000000 --- a/adapter-guide/cli-quick-lab.md +++ /dev/null @@ -1,290 +0,0 @@ -# STIX-Shifter CLI Quick Lab - -## Overview - -STIX (Structured Threat Information eXpression) is a JSON structure used to share cybersecurity threat intelligence. STIX-shifter is an open-source python library that is part of the Open Cybersecurity Alliance. It allows data repositories to be queried using STIX patterning and return the results as STIX cyber observable objects. This lab will allow users to test out the various stix-shifter CLI commands. - -### STIX Patterning - -A [STIX pattern](http://docs.oasis-open.org/cti/stix/v2.0/cs01/part5-stix-patterning/stix-v2.0-cs01-part5-stix-patterning.html) is used to query [cyber observable objects](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html). STIX patterns take the format of: - -`[: = 'some value' AND : IN (value_1, value_2)] OR [: = 'some value']` - -The `[ ]` represents one observation. A pattern can have multiple observations joined by the AND or OR observation operators. An observation can be thought of as one instance or row of data. Within the observation is one or more comparison expressions that looks for a value associated to a cyber observable STIX object and its property. This is a sample pattern with one observation containing an comparison operation for an IP lookup: `[ipv4-addr:value = '1.2.3.4']`. The STIX object in this case is `ipv4-addr` and the property on that object is `value`. - -### STIX Observed Data - -STIX-shifter returns a `bundle` of STIX `observed-data` objects. The bundle is a container object to hold the results. Below is a sample bundle containing one identity object (representing the data source) and one observed-data object: - -```json -{ - "type": "bundle", - "id": "bundle--57d455df-105d-4722-8277-e569110e82ed", - "objects": [ - { - "type": "identity", - "id": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff", - "name": "QRadar", - "identity_class": "system" - }, - { - "id": "observed-data--4db61897-4725-483b-9e68-2874e48650c5", - "type": "observed-data", - "created_by_ref": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff", - "created": "2022-04-28T14:16:41.544Z", - "modified": "2022-04-28T14:16:41.544Z", - "objects": { - "0": { - "type": "x-oca-event", - "action": "Logon Failure - Unknown user name or bad password", - "outcome": "Host Login Failed", - "category": [ - "Authentication" - ], - "provider": "Microsoft Windows Security Event Log", - "agent": "WindowsAuthServer @ microsoft.windows.test.com", - "created": "2021-06-28T19:35:58.000Z", - "network_ref": "2", - "user_ref": "4", - "url_ref": "7", - "file_ref": "8" - }, - "1": { - "type": "ipv4-addr", - "value": "109.0.216.203" - }, - "2": { - "type": "network-traffic", - "src_ref": "1", - "src_port": 3000, - "dst_ref": "3", - "dst_port": 1000, - "protocols": [ - "TCP" - ] - }, - "3": { - "type": "ipv4-addr", - "value": "192.168.1.11" - }, - "4": { - "type": "user-account", - "user_id": "bill_holland" - }, - "5": { - "type": "ipv4-addr", - "value": "0.0.0.0" - }, - "6": { - "type": "artifact", - "payload_bin": "PDEzPk1hciAyMSAwMTo0Mjo1MCBtaWNyb3NvZnQud2luZG93cy50ZXN0LmNvbQ==", - "mime_type": "text/plain" - }, - "7": { - "type": "url", - "value": "www.example.com" - }, - "8": { - "type": "file", - "name": "myfile.exe", - "hashes": { - "SHA-256": "86c5ceb27e1bf441130299c0209e5f35b88089f62c06b2b09d65772274f12057" - }, - "parent_directory_ref": "9" - }, - "9": { - "type": "directory", - "path": "C://filepath" - } - }, - "first_observed": "2021-06-28T19:35:58.652Z", - "last_observed": "2021-06-28T19:36:58.652Z", - "number_observed": 31 - } - ], - "spec_version": "2.0" -} -``` - -Each observed-data object contains a numbered set of cyber-observable objects. The properties on the cyber-observable object store the data returned from the data source. See the [STIX 2.0 standard](https://docs.oasis-open.org/cti/stix/v2.0/stix-v2.0-part4-cyber-observable-objects.html) for more on cyber observable objects. - -## Setup - -### Prerequisites - -* Python 3 -* pip -* venv -* Ability to run bash commands - -### 1. Open a terminal and install a Python Virtual Environment - -``` -python3 -m venv labenv -source labenv/bin/activate -``` - -### 2. Install the required stix-shifter libraries - -This installs the core stix-shifter and utils library along with the STIX-bundle and QRadar connectors. - -``` -pip install stix-shifter stix-shifter-utils stix-shifter-modules-stix_bundle stix-shifter-modules-qradar -``` - -### 3. Store the STIX bundle URL in a bash variable - -This is a bundle of sample STIX data that will be used to demonstrate the `stix_bundle` connector. - -``` -BUNDLE_URL=https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json -``` - -### 4. Store the sample result JSON in a bash variable - -This is a list of JSON objects containing sample data that will be used to demonstrate STIX translation. - -``` -JSON_RESULTS=$(cat <Mar 21 01:42:50 microsoft.windows.test.com", - "url": "www.example.com", - "magnitude": 8, - "filename": "myfile.exe", - "sha256hash":"86c5ceb27e1bf441130299c0209e5f35b88089f62c06b2b09d65772274f12057", - "filepath": "C://filepath/", - "eventseverity": 7, - "credibility": 10, - "relevance": 8, - "sourcegeographic": "Europe.France", - "destinationgeographic": "Canada", - "domainname": "Default Domain", - "EventID": "529" - } -] -EOF -) -``` - -## Lab Steps - -### 1. Examine the STIX Bundle - -This is a bundle of STIX observed-data objects containing sanitized data from a CrowdStrike instance. - -https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/data/cybox/crowdstrike/crowdstrike_detections_20210723.json - -The stix_bundle connector will query the sample STIX bundle and return a subset of data based on the query pattern. - -### 2. Run the execute command - -The execute command runs through the entire stix-shifter flow: - -- Translates a STIX pattern into a native data source query -- Sends the query to the data source via the data source APIs -- Checks the status of the query via the data source APIs -- Fetches the query results via the APIs and, if needed, converts them to JSON -- Translates the JSON results into STIX objects - -``` -stix-shifter execute stix_bundle stix_bundle '{"type": "identity","id": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff","name": "stix-bundle","identity_class": "system"}' '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' "[ipv4-addr:value = '12.111.222.0']" -``` - -Note the bundle of observed-data objects that are returned. Each of these objects contains a numbered set of cyber observable objects (url, network-traffic, ipv4-addr…) which contain the data from the target data source. Given the above CLI example, the ipv4-addr object should contain a value property with 12.111.222.0 - - -## STIX Transmission CLI commands - -The transmission commands use the data source APIs to send a query, check the status, fetch the results, and ping the connection. - -### 3. Run the ping command - -This command checks that the data source can be reached by the stix-shifter connector. - -``` -stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' ping -``` - -### 4. Run the query command - -This command sends the native query to the data source. - -``` -stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' query "[ipv4-addr:value = '192.168.0.8']" -``` - -### 5. Run the status command - -This command checks the status of the query. - - -``` -stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' status "[ipv4-addr:value = '192.168.0.8']" -``` - -### 6. Run the results command - -This command fetches the query results - - -``` -stix-shifter transmit stix_bundle '{"url": "'"$BUNDLE_URL"'"}' '{"auth": {}}' results "[ipv4-addr:value = '192.168.0.8']" 0 2 -``` - -## Translation mapping for QRadar - - -### 7. Examine the STIX pattern to AQL mapping file for the QRadar connector - -This file determines how STIX objects and their properties are mapped to the target data source fields. - -https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/qradar/stix_translation/json/events_from_stix_map.json - - -### 8. Run the STIX query translation CLI command for the QRadar connector - -This command passing in a STIX pattern and returns a list of native data source queries that can later be passed to a query transmission call. - -``` -stix-shifter translate qradar:events query '{}' "[ipv4-addr:value = '109.0.216.203' AND file:name = 'photos.exe'] OR [url:value = 'blah.com' OR url:value = 'path.com' OR url:value = 'crhs.ca']" -``` - - -### 9. Examine the JSON to STIX mapping file for the QRadar connector - -This file determines how fields returned in the data source results are mapped to SIX objects and their properties. - -https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/stix_shifter_modules/qradar/stix_translation/json/to_stix_map.json - - -### 10. Run the JSON results translation CLI command for the QRadar connector - -This command passes in a STIX identity object and a list of JSON results (each element in the list represents a row of data). A bundle of STIX objects is returned. The bundle contains the identity object, which represents the data source the data comes from, and an observed-data object for each of the rows that were translated. -``` -stix-shifter translate qradar results '{"type": "identity","id": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff","name": "QRadar","identity_class": "system"}' "$JSON_RESULTS" -``` - - diff --git a/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py b/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py index f698b4d16..1249ac041 100644 --- a/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py +++ b/stix_shifter_modules/mysql/tests/stix_translation/test_mysql_stix_to_query.py @@ -99,5 +99,3 @@ def test_start_stop_qualifiers_with_one_observation(self): assert len(query['queries']) == 1 assert query['queries'] == [where_statement] - - # AND (entry_time >= 1548678241009 OR entry_time <= 1548680041009) limit 10000 From eaf3ce4fb475cdb15c8a86abde3eda5d9ff3c792 Mon Sep 17 00:00:00 2001 From: Md Azam Date: Thu, 8 Sep 2022 13:20:00 -0300 Subject: [PATCH 16/19] updating codig lab --- README.md | 2 +- .../STIX-Shifter Connector Tutorial.ipynb | 0 .../STIX-shifter CLI Quick Lab.ipynb | 4 +- {notebooks => lab}/connector_coding_lab.md | 50 ++++++++++++------ {notebooks => lab}/data.csv | 0 {notebooks => lab}/set_virtual_env.png | Bin 6 files changed, 38 insertions(+), 18 deletions(-) rename {notebooks => lab}/STIX-Shifter Connector Tutorial.ipynb (100%) rename {notebooks => lab}/STIX-shifter CLI Quick Lab.ipynb (99%) rename {notebooks => lab}/connector_coding_lab.md (76%) rename {notebooks => lab}/data.csv (100%) rename {notebooks => lab}/set_virtual_env.png (100%) diff --git a/README.md b/README.md index 148bc62d5..2b5c6f4e8 100644 --- a/README.md +++ b/README.md @@ -102,7 +102,7 @@ Please read our [guidelines for contributing](https://github.com/opencybersecuri If you want to create a new connector for STIX-shifter, see the [developer guide](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/adapter-guide/develop-stix-adapter.md) -There are also a few [Jupyter Notebook labs](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/notebooks) that cover the CLI commands and dev process. +There are also a few [Jupyter Notebook labs](https://github.com/opencybersecurityalliance/stix-shifter/blob/develop/lab) that cover the CLI commands and dev process. ## Licensing diff --git a/notebooks/STIX-Shifter Connector Tutorial.ipynb b/lab/STIX-Shifter Connector Tutorial.ipynb similarity index 100% rename from notebooks/STIX-Shifter Connector Tutorial.ipynb rename to lab/STIX-Shifter Connector Tutorial.ipynb diff --git a/notebooks/STIX-shifter CLI Quick Lab.ipynb b/lab/STIX-shifter CLI Quick Lab.ipynb similarity index 99% rename from notebooks/STIX-shifter CLI Quick Lab.ipynb rename to lab/STIX-shifter CLI Quick Lab.ipynb index defa0ab03..0d887add4 100644 --- a/notebooks/STIX-shifter CLI Quick Lab.ipynb +++ b/lab/STIX-shifter CLI Quick Lab.ipynb @@ -179,9 +179,9 @@ "\n", "`ipython kernel install --user --name=labenv`\n", "\n", - "### 7. CD into the STIX-shifter notebooks directory\n", + "### 7. CD into the STIX-shifter lab directory\n", "\n", - "`cd stix-shifter/notebooks`\n", + "`cd stix-shifter/lab`\n", "\n", "### 8. Run jupyter notebook\n", "\n", diff --git a/notebooks/connector_coding_lab.md b/lab/connector_coding_lab.md similarity index 76% rename from notebooks/connector_coding_lab.md rename to lab/connector_coding_lab.md index 81ce53d05..82834f9fd 100644 --- a/notebooks/connector_coding_lab.md +++ b/lab/connector_coding_lab.md @@ -5,17 +5,25 @@ This is a hands on lab to start implementing a connector module in STIX-shifter ## Prerequisites -Github account -Basic knowledge of Git such as forking, committing, branching, pulling, and merging -Working knowledge of the Python programming language. This lab will use Python 3.9 -An IDE to write Python code, such as VS Code. +1. Github account +2. Basic knowledge of Git such as forking, committing, branching, pulling, and merging +3. Working knowledge of the Python programming language. This lab will use Python 3.6 +4. An IDE to write Python code, such as VS Code. ## Steps -1. Make a copy of `stix_shifter_modules/synchronous_template` module -2. Change the name to `lab_connector` +1. Open stix-shifter folder in VS Code IDE +2. Open a terminal in VS code +3. Make sure you are in `stix-shifter/` parent directory +4. Create a python virtual environment +``` +virtualenv -p python3 virtualenv && source virtualenv/bin/activate +INSTALL_REQUIREMENTS_ONLY=1 python3 setup.py install +``` +5. Make a copy of `stix_shifter_modules/synchronous_template` module +6. Change the name to `lab_connector` You should have connector module skeleton for the new connector name lab_connector -3. Implement `EntryPoint()` class in `stix_shifter_modules/lab_connector/entry_point.py`.  +7. Implement `EntryPoint()` class in `stix_shifter_modules/lab_connector/entry_point.py`.  ``` from stix_shifter_utils.utils.base_entry_point import BaseEntryPoint @@ -29,13 +37,13 @@ An IDE to write Python code, such as VS Code.         self.setup_translation_simple(dialect_default='default') ``` -4. Implement input configuration of the connector in `stix_shifter_modules/lab_connector/configuration` +8. Implement input configuration of the connector in `stix_shifter_modules/lab_connector/configuration` * Implement connection and configuration of the connector in config.json file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/config.json for this lab * You can also implement the language definition of the input configuration for the UI label and description in lang_en.json(for English) file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/lang_en.json for this lab. -5. Implement stix to query translation +9. Implement stix to query translation * Go to `stix_shifter_modules/lab_connector/stix_translation` @@ -45,13 +53,12 @@ An IDE to write Python code, such as VS Code. * Update `stix_shifter_modules/lab_connector/stix_translation/json/operators.json` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/json/operators.json - ### correct? * QueryTranslator() class can be left as it `stix_shifter_modules/mysql/stix_translation/query_translator.py` * Update `stix_shifter_modules/lab_connector/stix_translation/query_constructor.py` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/query_constructor.py * You can now run the basic query translation CLI command from your workspace to tests -6. Implement stix transmission module. +10. Implement stix transmission module. * You need to implement four functionalities of the transmission module which are `ping`, `query`, `status` and `results`.  * First step, create a class called `APIClient()` in `stix_shifter_modules/lab_connector/stix_transmission/api_client.py` where you initialize the connection and configurations needed for data source API requests. This class also includes the utility functions needed for the major functionalities of the connector. @@ -75,7 +82,7 @@ An IDE to write Python code, such as VS Code.         return return_obj ``` -* Define and implement `ping_data_source()` function inside `APIClient()`: + * Define and implement `ping_data_source()` function inside `APIClient()`: ``` def ping_data_source(self): @@ -134,8 +141,21 @@ An IDE to write Python code, such as VS Code. * You can now run all the transmission CLI command from your workspace to tests -7. Implement `ErrorMapper()` class in `stix_shifter_modules/lab_connector/stix_transmission/error_mapper.py` for mapping any API specific error code message for the return object. This same content can be used: https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_transmission/error_mapper.py +11. Implement Datasource results to STIX translation + + * Make sure datasource returns the results in JSON format + * Implement ResultsTranslator(JSONToStix) class + ``` + from stix_shifter_utils.stix_translation.src.json_to_stix.json_to_stix import JSONToStix + + class ResultsTranslator(JSONToStix): + pass + ``` + * There's no pre-processing needed fo the results + * The parent utility class JSONToStix automatically translates the results into STIX. + +12. Implement `ErrorMapper()` class in `stix_shifter_modules/lab_connector/stix_transmission/error_mapper.py` for mapping any API specific error code message for the return object. This same content can be used: https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_transmission/error_mapper.py -8. Add any data source specific dependency to the stix_shifter_modules/lab_connector/requirements.txt.  In this case add `mysql-connector-python==8.0.25` +13. Add any data source specific dependency to the stix_shifter_modules/lab_connector/requirements.txt.  In this case add `mysql-connector-python==8.0.25` -9. You also need to create a `README.md` for the connector which includes the details of the API or SDK used in the connector and also some sample commands and the results `stix_shifter_modules/lab_connector/README.md` \ No newline at end of file +14. You also need to create a `README.md` for the connector which includes the details of the API or SDK used in the connector and also some sample commands and the results `stix_shifter_modules/lab_connector/README.md` \ No newline at end of file diff --git a/notebooks/data.csv b/lab/data.csv similarity index 100% rename from notebooks/data.csv rename to lab/data.csv diff --git a/notebooks/set_virtual_env.png b/lab/set_virtual_env.png similarity index 100% rename from notebooks/set_virtual_env.png rename to lab/set_virtual_env.png From 94283cfc9272e1c780921802902874479edd7a30 Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 8 Sep 2022 13:50:28 -0300 Subject: [PATCH 17/19] fix tabs in code blocks --- lab/STIX-shifter CLI Quick Lab.ipynb | 33 +++++++- lab/connector_coding_lab.md | 121 ++++++++++++++++----------- 2 files changed, 100 insertions(+), 54 deletions(-) diff --git a/lab/STIX-shifter CLI Quick Lab.ipynb b/lab/STIX-shifter CLI Quick Lab.ipynb index 0d887add4..a4540ac58 100644 --- a/lab/STIX-shifter CLI Quick Lab.ipynb +++ b/lab/STIX-shifter CLI Quick Lab.ipynb @@ -704,6 +704,17 @@ "%env STIX_PATTERN=[url:value = 'www.example.org']" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "f1800cd8", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "stix-shifter translate mysql query \"$MYSQL_IDENTITY_OBJECT\" \"$STIX_PATTERN\" '{\"table\":\"'\"$DB_TABLE\"'\"}'" + ] + }, { "cell_type": "code", "execution_count": null, @@ -714,6 +725,17 @@ "%env STIX_PATTERN=[ipv4-addr:value = '10.0.0.9'] START t'2019-01-28T12:24:01.009Z' STOP t'2019-01-28T12:54:01.009Z'" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "f1800cd8", + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "stix-shifter translate mysql query \"$MYSQL_IDENTITY_OBJECT\" \"$STIX_PATTERN\" '{\"table\":\"'\"$DB_TABLE\"'\"}'" + ] + }, { "cell_type": "code", "execution_count": null, @@ -1018,9 +1040,9 @@ ], "metadata": { "kernelspec": { - "display_name": "labenv", + "display_name": "Python 3.9.7 ('labenv')", "language": "python", - "name": "labenv" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1032,7 +1054,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.9.7" + }, + "vscode": { + "interpreter": { + "hash": "f3502a7b96999c043d33f48856eab8d61ec3fa3cf2d4f6b6e0ae39bc34297855" + } } }, "nbformat": 4, diff --git a/lab/connector_coding_lab.md b/lab/connector_coding_lab.md index 82834f9fd..44b020f89 100644 --- a/lab/connector_coding_lab.md +++ b/lab/connector_coding_lab.md @@ -29,12 +29,13 @@ INSTALL_REQUIREMENTS_ONLY=1 python3 setup.py install from stix_shifter_utils.utils.base_entry_point import BaseEntryPoint class EntryPoint(BaseEntryPoint): -     def __init__(self, connection={}, configuration={}, options={}): -         super().__init__(connection, configuration, options) -         self.set_async(False) -         if connection: -             self.setup_transmission_basic(connection, configuration) -         self.setup_translation_simple(dialect_default='default') + + def __init__(self, connection={}, configuration={}, options={}): + super().__init__(connection, configuration, options) + self.set_async(False) + if connection: + self.setup_transmission_basic(connection, configuration) + self.setup_translation_simple(dialect_default='default') ``` 8. Implement input configuration of the connector in `stix_shifter_modules/lab_connector/configuration` @@ -61,7 +62,26 @@ INSTALL_REQUIREMENTS_ONLY=1 python3 setup.py install 10. Implement stix transmission module. * You need to implement four functionalities of the transmission module which are `ping`, `query`, `status` and `results`.  - * First step, create a class called `APIClient()` in `stix_shifter_modules/lab_connector/stix_transmission/api_client.py` where you initialize the connection and configurations needed for data source API requests. This class also includes the utility functions needed for the major functionalities of the connector. + * First create a class called `APIClient()` in `stix_shifter_modules/lab_connector/stix_transmission/api_client.py`. This is where you initialize the connection and configurations needed for the data source API requests. This class also includes the utility functions needed for the major functionalities of the connector. + * Create a file called `connector.py` if it doesn't yet exist and add the following code to the top of the file: + + ``` + import datetime + import json + from stix_shifter_utils.modules.base.stix_transmission.base_sync_connector import BaseSyncConnector + from .api_client import APIClient + from stix_shifter_utils.utils.error_response import ErrorResponder + from stix_shifter_utils.utils import logger + + + class Connector(BaseSyncConnector): + + def __init__(self, connection, configuration): + self.api_client = APIClient(connection, configuration) + self.logger = logger.set_logger(__name__) + self.connector = __name__.split('.')[1] + ``` + * Now we can add the required transmission functions ### Ping @@ -69,44 +89,42 @@ INSTALL_REQUIREMENTS_ONLY=1 python3 setup.py install ``` def ping_connection(self): -         response = self.api_client.ping_data_source() -         response_code = response.get('code') -         response_txt = response.get('message') -         return_obj = dict() -         return_obj['success'] = False - -         if len(response) > 0 and response_code == 200: -             return_obj['success'] = True -         else: -             ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) -         return return_obj + response = self.api_client.ping_data_source() + response_code = response.get('code') + response_txt = response.get('message') + return_obj = dict() + return_obj['success'] = False + + if len(response) > 0 and response_code == 200: + return_obj['success'] = True + else: + ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) + return return_obj ``` * Define and implement `ping_data_source()` function inside `APIClient()`: ``` def ping_data_source(self): - # Pings the data source -         response = {"code": 200, "message": "All Good!"} -         try: -             cnx = lab_connector.connector.connect(user=self.user, password=self.password,  -                                           host=self.host, database=self.database,  -                                           port=self.port, auth_plugin=self.auth_plugin)   - - -         except lab_connector.connector.Error as err: -             response["code"] = err.errno - - -             if err.errno == errorcode.ER_ACCESS_DENIED_ERROR: -                 response["message"] = "Something is wrong with your user name or password" -             elif err.errno == errorcode.ER_BAD_DB_ERROR: -                 response["message"] = "Database does not exist" -             else: -                 response["message"] = err -         else: -             cnx.close() -         return response + # Pings the data source + response = {"code": 200, "message": "All Good!"} + try: + cnx = mysql.connector.connect(user=self.user, password=self.password, + host=self.host, database=self.database, + port=self.port, auth_plugin=self.auth_plugin) + + except mysql.connector.Error as err: + response["code"] = err.errno + + if err.errno == errorcode.ER_ACCESS_DENIED_ERROR: + response["message"] = "Something is wrong with your user name or password" + elif err.errno == errorcode.ER_BAD_DB_ERROR: + response["message"] = "Database does not exist" + else: + response["message"] = err + else: + cnx.close() + return response ``` ### Query @@ -123,16 +141,16 @@ INSTALL_REQUIREMENTS_ONLY=1 python3 setup.py install ``` def create_results_connection(self, query, offset, length): -         return_obj = dict() -         response = self.api_client.run_search(query, start=offset, rows=length) -         response_code = response.get('code') -         response_txt = response.get('message') -         if response_code == 200: -             return_obj['success'] = True -             return_obj['data'] = response.get('result') -         else: -             ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) -         return return_obj + return_obj = dict() + response = self.api_client.run_search(query, start=offset, rows=length) + response_code = response.get('code') + response_txt = response.get('message') + if response_code == 200: + return_obj['success'] = True + return_obj['data'] = response.get('result') + else: + ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) + return return_obj ``` * Define and implement a function named `run_search(self, query, offset, length)`  in `APIClient()` class. @@ -141,10 +159,11 @@ INSTALL_REQUIREMENTS_ONLY=1 python3 setup.py install * You can now run all the transmission CLI command from your workspace to tests -11. Implement Datasource results to STIX translation +11. Implement data source results to STIX translation - * Make sure datasource returns the results in JSON format + * Make sure the data source returns the results in JSON format * Implement ResultsTranslator(JSONToStix) class + ``` from stix_shifter_utils.stix_translation.src.json_to_stix.json_to_stix import JSONToStix From a14d81da905c6fbd0de3befd0aa8450aa47c70aa Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Thu, 8 Sep 2022 16:22:52 -0300 Subject: [PATCH 18/19] add CLI samples to coding lab --- lab/connector_coding_lab.md | 310 +++++++++++++++++++++--------------- 1 file changed, 184 insertions(+), 126 deletions(-) diff --git a/lab/connector_coding_lab.md b/lab/connector_coding_lab.md index 44b020f89..2175c9a00 100644 --- a/lab/connector_coding_lab.md +++ b/lab/connector_coding_lab.md @@ -5,176 +5,234 @@ This is a hands on lab to start implementing a connector module in STIX-shifter ## Prerequisites -1. Github account -2. Basic knowledge of Git such as forking, committing, branching, pulling, and merging -3. Working knowledge of the Python programming language. This lab will use Python 3.6 -4. An IDE to write Python code, such as VS Code. +* Github account +* Basic knowledge of Git such as forking, committing, branching, pulling, and merging +* Working knowledge of the Python programming language. This lab will use Python 3.6 +* An IDE to write Python code, such as VS Code. ## Steps -1. Open stix-shifter folder in VS Code IDE -2. Open a terminal in VS code -3. Make sure you are in `stix-shifter/` parent directory -4. Create a python virtual environment +### 1. Open stix-shifter folder in VS Code IDE +### 2. Open a terminal in VS code +### 3. Make sure you are in `stix-shifter/` parent directory +### 4. Create a python virtual environment + ``` virtualenv -p python3 virtualenv && source virtualenv/bin/activate +python3 -m pip install --upgrade pip INSTALL_REQUIREMENTS_ONLY=1 python3 setup.py install ``` -5. Make a copy of `stix_shifter_modules/synchronous_template` module -6. Change the name to `lab_connector` - You should have connector module skeleton for the new connector name lab_connector -7. Implement `EntryPoint()` class in `stix_shifter_modules/lab_connector/entry_point.py`.  - ``` - from stix_shifter_utils.utils.base_entry_point import BaseEntryPoint +### 5. Make a copy of the `stix_shifter_modules/synchronous_template` module +### 6. Change the name to `lab_connector` + +* You should have a connector module skeleton for the new connector named lab_connector +### 7. Implement `EntryPoint()` class in `stix_shifter_modules/lab_connector/entry_point.py`.  + +``` +from stix_shifter_utils.utils.base_entry_point import BaseEntryPoint - class EntryPoint(BaseEntryPoint): +class EntryPoint(BaseEntryPoint): - def __init__(self, connection={}, configuration={}, options={}): - super().__init__(connection, configuration, options) - self.set_async(False) - if connection: - self.setup_transmission_basic(connection, configuration) - self.setup_translation_simple(dialect_default='default') - ``` +def __init__(self, connection={}, configuration={}, options={}): + super().__init__(connection, configuration, options) + self.set_async(False) + if connection: + self.setup_transmission_basic(connection, configuration) + self.setup_translation_simple(dialect_default='default') +``` -8. Implement input configuration of the connector in `stix_shifter_modules/lab_connector/configuration` +### 8. Implement input configuration of the connector in `stix_shifter_modules/lab_connector/configuration` - * Implement connection and configuration of the connector in config.json file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/config.json for this lab - - * You can also implement the language definition of the input configuration for the UI label and description in lang_en.json(for English) file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/lang_en.json for this lab. +* Implement connection and configuration of the connector in config.json file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/config.json for this lab -9. Implement stix to query translation +* You can also implement the language definition of the input configuration for the UI label and description in lang_en.json(for English) file. you can copy the content from https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/configuration/lang_en.json for this lab. - * Go to `stix_shifter_modules/lab_connector/stix_translation` +### 9. Implement stix to query translation - * Update `stix_shifter_modules/lab_connector/stix_translation/json/from_stix_map.json` file with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/json/from_stix_map.json +* Go to `stix_shifter_modules/lab_connector/stix_translation` - * If data source API offers one schema type the dialect prefix can be removed +* Update `stix_shifter_modules/lab_connector/stix_translation/json/from_stix_map.json` file with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/json/from_stix_map.json - * Update `stix_shifter_modules/lab_connector/stix_translation/json/operators.json` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/json/operators.json +* If data source API offers one schema type the dialect prefix can be removed - * QueryTranslator() class can be left as it `stix_shifter_modules/mysql/stix_translation/query_translator.py` - * Update `stix_shifter_modules/lab_connector/stix_translation/query_constructor.py` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/query_constructor.py +* Update `stix_shifter_modules/lab_connector/stix_translation/json/operators.json` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/json/operators.json - * You can now run the basic query translation CLI command from your workspace to tests +* QueryTranslator() class can be left as it `stix_shifter_modules/mysql/stix_translation/query_translator.py` +* Update `stix_shifter_modules/lab_connector/stix_translation/query_constructor.py` with the content of https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_translation/query_constructor.py -10. Implement stix transmission module. +* You can now run the basic query translation CLI command from your workspace to tests - * You need to implement four functionalities of the transmission module which are `ping`, `query`, `status` and `results`.  - * First create a class called `APIClient()` in `stix_shifter_modules/lab_connector/stix_transmission/api_client.py`. This is where you initialize the connection and configurations needed for the data source API requests. This class also includes the utility functions needed for the major functionalities of the connector. - * Create a file called `connector.py` if it doesn't yet exist and add the following code to the top of the file: +### 10. Implement stix transmission module. - ``` - import datetime - import json - from stix_shifter_utils.modules.base.stix_transmission.base_sync_connector import BaseSyncConnector - from .api_client import APIClient - from stix_shifter_utils.utils.error_response import ErrorResponder - from stix_shifter_utils.utils import logger +* You need to implement four functionalities of the transmission module which are `ping`, `query`, `status` and `results`.  +* First create a class called `APIClient()` in `stix_shifter_modules/lab_connector/stix_transmission/api_client.py`. This is where you initialize the connection and configurations needed for the data source API requests. This class also includes the utility functions needed for the major functionalities of the connector. Add the following code to the top of the API client: +``` +import mysql.connector +from mysql.connector import errorcode + + +class APIClient(): + + def __init__(self, connection, configuration): + auth = configuration.get('auth') + self.user = auth.get('username') + self.password = auth.get('password') + self.timeout = connection['options'].get('timeout') + self.result_limit = connection['options'].get('result_limit') + self.host = connection.get("host") + self.database = connection.get("database") + self.table = connection['options'].get("table") + self.port = connection.get("port") + self.auth_plugin = 'mysql_native_password' +``` + +* Create a file called `connector.py` if it doesn't yet exist and add the following code to the top of the file: - class Connector(BaseSyncConnector): +``` +import datetime +import json +from stix_shifter_utils.modules.base.stix_transmission.base_sync_connector import BaseSyncConnector +from .api_client import APIClient +from stix_shifter_utils.utils.error_response import ErrorResponder +from stix_shifter_utils.utils import logger - def __init__(self, connection, configuration): - self.api_client = APIClient(connection, configuration) - self.logger = logger.set_logger(__name__) - self.connector = __name__.split('.')[1] - ``` - * Now we can add the required transmission functions - ### Ping +class Connector(BaseSyncConnector): - * Define and implement a function named `ping_connection(self)` inside `stix_shifter_modules/lab_connector/stix_transmission/connector.py`  + def __init__(self, connection, configuration): + self.api_client = APIClient(connection, configuration) + self.logger = logger.set_logger(__name__) + self.connector = __name__.split('.')[1] +``` +* Now we can add the required transmission functions - ``` - def ping_connection(self): - response = self.api_client.ping_data_source() - response_code = response.get('code') - response_txt = response.get('message') - return_obj = dict() - return_obj['success'] = False +### Ping - if len(response) > 0 and response_code == 200: - return_obj['success'] = True - else: - ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) - return return_obj - ``` - - * Define and implement `ping_data_source()` function inside `APIClient()`: - - ``` - def ping_data_source(self): - # Pings the data source - response = {"code": 200, "message": "All Good!"} - try: - cnx = mysql.connector.connect(user=self.user, password=self.password, - host=self.host, database=self.database, - port=self.port, auth_plugin=self.auth_plugin) - - except mysql.connector.Error as err: - response["code"] = err.errno - - if err.errno == errorcode.ER_ACCESS_DENIED_ERROR: - response["message"] = "Something is wrong with your user name or password" - elif err.errno == errorcode.ER_BAD_DB_ERROR: - response["message"] = "Database does not exist" - else: - response["message"] = err +* Define and implement a function named `ping_connection(self)` inside `stix_shifter_modules/lab_connector/stix_transmission/connector.py`  + +``` +def ping_connection(self): + response = self.api_client.ping_data_source() + response_code = response.get('code') + response_txt = response.get('message') + return_obj = dict() + return_obj['success'] = False + + if len(response) > 0 and response_code == 200: + return_obj['success'] = True + else: + ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) + return return_obj +``` + +* Define and implement the `ping_data_source()` function inside `APIClient()`: + +``` +def ping_data_source(self): + # Pings the data source + response = {"code": 200, "message": "All Good!"} + try: + cnx = mysql.connector.connect(user=self.user, password=self.password, + host=self.host, database=self.database, + port=self.port, auth_plugin=self.auth_plugin) + + except mysql.connector.Error as err: + response["code"] = err.errno + + if err.errno == errorcode.ER_ACCESS_DENIED_ERROR: + response["message"] = "Something is wrong with your user name or password" + elif err.errno == errorcode.ER_BAD_DB_ERROR: + response["message"] = "Database does not exist" else: - cnx.close() - return response - ``` + response["message"] = err + else: + cnx.close() + return response +``` - ### Query +### Query - * As a synchronous connector, it doesn't require any API request to start or create the query. Therefore no need to define and implement the functions of the query function. `self.setup_transmission_basic(connection, configuration)` statement inside entry point class `EntryPoint()` takes care of that automatically. +* As a synchronous connector, it doesn't require any API request to start or create the query. Therefore no need to define and implement the functions of the query function. `self.setup_transmission_basic(connection, configuration)` statement inside entry point class `EntryPoint()` takes care of that automatically. - ### Status +### Status - * Same as query, synchronous connector doesn't return any status from the data source hence no action needed. +* Same as query, a synchronous connector doesn't return any status from the data source hence no action is needed. - ### Results +### Results - * Define and implement a function named `create_results_connection(self, query, offset, length)` inside `stix_shifter_modules/lab_connector/stix_transmission/connector.py` +* Define and implement a function named `create_results_connection(self, query, offset, length)` inside `stix_shifter_modules/lab_connector/stix_transmission/connector.py` - ``` - def create_results_connection(self, query, offset, length): - return_obj = dict() - response = self.api_client.run_search(query, start=offset, rows=length) - response_code = response.get('code') - response_txt = response.get('message') - if response_code == 200: - return_obj['success'] = True - return_obj['data'] = response.get('result') - else: - ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) - return return_obj - ``` +``` +def create_results_connection(self, query, offset, length): + return_obj = dict() + response = self.api_client.run_search(query, start=offset, rows=length) + response_code = response.get('code') + response_txt = response.get('message') + if response_code == 200: + return_obj['success'] = True + return_obj['data'] = response.get('result') + else: + ErrorResponder.fill_error(return_obj, response, ['message'], error=response_txt, connector=self.connector) + return return_obj +``` + +* Define and implement a function named `run_search(self, query, offset, length)`  in `APIClient()` class. - * Define and implement a function named `run_search(self, query, offset, length)`  in `APIClient()` class. +* Copy the code block https://github.com/opencybersecurityalliance/stix-shifter/blob/8ae2cf2a0196531b8e0daf8f5ff141b4251ec201/stix_shifter_modules/mysql/stix_transmission/api_client.py#L40 - * Copy the code block https://github.com/opencybersecurityalliance/stix-shifter/blob/8ae2cf2a0196531b8e0daf8f5ff141b4251ec201/stix_shifter_modules/mysql/stix_transmission/api_client.py#L40 +* You can now run all the transmission CLI commands from your terminal: - * You can now run all the transmission CLI command from your workspace to tests +#### Ping CLI Command -11. Implement data source results to STIX translation +``` +python main.py transmit mysql '{"host": "localhost", "database":"demo_db", "options": {"table":"demo_table"}}' '{"auth": {"username":"root", "password":"Giv3@m@n@fish"}}' ping +``` + +#### Query CLI Command + +``` +python main.py transmit mysql '{"host": "localhost", "database":"demo_db", "options": {"table":"demo_table"}}' '{"auth": {"username":"root", "password":"Giv3@m@n@fish"}}' query "SELECT * FROM demo_table WHERE source_ipaddr = '10.0.0.9'" +``` + +#### Status CLI Command + +``` +python main.py transmit mysql '{"host": "localhost", "database":"demo_db", "options": {"table":"demo_table"}}' '{"auth": {"username":"root", "password":"Giv3@m@n@fish"}}' status "SELECT * FROM demo_table WHERE source_ipaddr = '10.0.0.9'" +``` + +#### Results CLI Command + +``` +python main.py transmit mysql '{"host": "localhost", "database":"demo_db", "options": {"table":"demo_table"}}' '{"auth": {"username":"root", "password":"Giv3@m@n@fish"}}' results "SELECT * FROM demo_table WHERE source_ipaddr = '10.0.0.9'" 0 100 +``` + +## Results Translation + +### 11. Implement data source results to STIX translation - * Make sure the data source returns the results in JSON format - * Implement ResultsTranslator(JSONToStix) class +* Make sure the data source returns the results in JSON format +* Implement the `ResultsTranslator(JSONToStix)` class in `results_translator.py` - ``` - from stix_shifter_utils.stix_translation.src.json_to_stix.json_to_stix import JSONToStix +``` +from stix_shifter_utils.stix_translation.src.json_to_stix.json_to_stix import JSONToStix - class ResultsTranslator(JSONToStix): - pass - ``` - * There's no pre-processing needed fo the results - * The parent utility class JSONToStix automatically translates the results into STIX. +class ResultsTranslator(JSONToStix): + pass +``` + +* The parent utility class JSONToStix automatically translates the results into STIX. + +### 12. Implement the `ErrorMapper()` class in `stix_shifter_modules/lab_connector/stix_transmission/error_mapper.py` + +* This is where you map any API specific error code messages for the return object. You can use the same error mapper content that is used in the MySQL connector: https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_transmission/error_mapper.py -12. Implement `ErrorMapper()` class in `stix_shifter_modules/lab_connector/stix_transmission/error_mapper.py` for mapping any API specific error code message for the return object. This same content can be used: https://raw.githubusercontent.com/opencybersecurityalliance/stix-shifter/develop/stix_shifter_modules/mysql/stix_transmission/error_mapper.py +### 13. Add any data source specific dependency to the `stix_shifter_modules/lab_connector/requirements.txt`.  +* In this case add `mysql-connector-python==8.0.25` -13. Add any data source specific dependency to the stix_shifter_modules/lab_connector/requirements.txt.  In this case add `mysql-connector-python==8.0.25` +### 14. The entire end-to-end query flow can now be tested with the CLI `execute` command: -14. You also need to create a `README.md` for the connector which includes the details of the API or SDK used in the connector and also some sample commands and the results `stix_shifter_modules/lab_connector/README.md` \ No newline at end of file +``` +python main.py execute mysql mysql '{"type": "identity","id": "identity--f431f809-377b-45e0-aa1c-6a4751cae5ff","name": "mysql","identity_class": "system"}' '{"host": "localhost", "database":"demo_db", "options": {"table":"demo_table", "stix_2.1": true}}' '{"auth": {"username":"root", "password":"Giv3@m@n@fish"}}' "[ipv4-addr:value = '10.0.0.9']" +``` From 54dee7d0a44fe0bbca6e60c31e455d83bb37999b Mon Sep 17 00:00:00 2001 From: Danny Elliott Date: Fri, 9 Sep 2022 09:34:10 -0300 Subject: [PATCH 19/19] duplicate notebook cell fix --- lab/STIX-shifter CLI Quick Lab.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/lab/STIX-shifter CLI Quick Lab.ipynb b/lab/STIX-shifter CLI Quick Lab.ipynb index a4540ac58..30d30950b 100644 --- a/lab/STIX-shifter CLI Quick Lab.ipynb +++ b/lab/STIX-shifter CLI Quick Lab.ipynb @@ -728,7 +728,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f1800cd8", + "id": "5520cf09", "metadata": {}, "outputs": [], "source": [ @@ -749,7 +749,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f1800cd8", + "id": "f799598e", "metadata": {}, "outputs": [], "source": [ @@ -1040,9 +1040,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3.9.7 ('labenv')", + "display_name": "labenv", "language": "python", - "name": "python3" + "name": "labenv" }, "language_info": { "codemirror_mode": { @@ -1054,7 +1054,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.6.11" }, "vscode": { "interpreter": {