• Overview
• Installation Instructions
• How to configure database and schema for the masking policy ?
• How to apply masking policy ?
• How to remove masking policy ?
• How to validate masking policy ?
• Process flow
  • Create masking policy
  • Apply masking policy
• Known Errors and Solutions
• Credits
• References
• Contributions
• How to do an integration test ?

Overview

This dbt package contains macros that can be (re)used across dbt projects with snowflake. dbt_snow_mask will help to apply Dynamic Data Masking using dbt meta.

Installation Instructions

• Add the package into your project.

  Example : packages.yml

     - git: "https://github.com/entechlog/dbt-snow-mask.git"
       revision: 0.1.7

     - package: entechlog/dbt_snow_mask
       version: 0.1.7

✅ Packages can be added to your project using either of above options
✅ Please refer to the release version of this repo/dbt hub for the latest revision

• This package uses dbt_utils package. When using dbt_snow_mask in your project, please install dbt_utils as well. You will get an error if you attempt to use this package without installing dbt_snow_mask

     - package: dbt-labs/dbt_utils
       version: 0.8.2

✅ Please refer to the release version in dbt hub for the latest revision

How to configure database and schema for the masking policy ?

By default this process creates the masking policies in same directory as the database objects. There are 2 methods for changing the default behavior by using the following parameters in your dbt_project.yml

Method 1 : Use a common database

To change the database that your masking polices are created in set the following parameters:

• use_common_masking_policy_db (optional): Flag to enable the usage of a common db/schema for all masking policies. Valid values are “True” OR "False"
• common_masking_policy_db (optional): The database name for creating masking policies
• common_masking_policy_schema (optional): The schema name for creating masking policies
• create_masking_policy_schema (optional): Valid values are “True” OR "False". The default value is “True”. When set to "False", helps to avoid creating schema if the dbt role does not have access to create schema

Example : var block in dbt_project.yml to enable using a common masking policy database

vars:
  use_common_masking_policy_db: "True"
  common_masking_policy_db: "DEMO_DB"
  common_masking_policy_schema: "COMPLIANCE"

Method 2 : Use a common schema (in the current database)

To change only the schema (so that a common masking policy schema is used in the same database as your model) set the following parameters:

• use_common_masking_policy_schema_only (optional): Flag to enable the usage of a common schema in the current database for all masking policies. Valid values are “True” OR "False"
• common_masking_policy_schema (optional): The schema name for creating masking policies
• create_masking_policy_schema (optional): Valid values are “True” OR "False". The default value is “True”. When set to "False", helps to avoid creating schema if the dbt role does not have access to create schema

Example : var block in dbt_project.yml to enable using a common masking policy schema (in the current database)

vars:
  use_common_masking_policy_schema_only: "True"
  common_masking_policy_schema: "COMPLIANCE"

✅ If both use_common_masking_policy_db and use_common_masking_policy_schema_only are set to True, then use_common_masking_policy_db will supercede use_common_masking_policy_schema_only.

Allow Custom Materializations

To enable dbt_snow_mask to apply masking policies to models generated from custom materializations in dbt, configure the following parameter:

• custom_materializations_map (optional): A dictionary containing key-value pairs mapping custom materializations in dbt to the objects they generate in Snowflake. For each pair, the key must be the name of the custom_materialization and the value must be either table or view.

Example : var block in dbt_project.yml to enable application of masking policies to a model generated using a custom materialiazition that ends up as a table in Snowflake.

vars:
  custom_materializations_map: '{ "custom_incremental": "table" }'

How to apply masking policy ?

• Masking is controlled by meta in dbt resource properties for sources and models.

• Decide you masking policy name and add the key masking_policy in the column which has to be masked.

  Example : source.yml

  sources:
    - name: raw_sakila
      tables:
        - name: customer
          columns:
            - name: first_name
              meta:
                  masking_policy: mp_encrypt_pii

  Example : model.yml

  models:
    - name: stg_customer
      columns:
        - name: email
          meta:
            masking_policy: mp_encrypt_pii

• Create a new .sql file with the name create_masking_policy_<masking-policy-name-from-meta>.sql and the sql for masking policy definition. Its important for macro to follow this naming standard.

  Example : create_masking_policy_mp_encrypt_pii.sql

  {% macro create_masking_policy_mp_encrypt_pii(node_database,node_schema) %}
  
  CREATE MASKING POLICY IF NOT EXISTS {{node_database}}.{{node_schema}}.mp_encrypt_pii AS (val string) 
    RETURNS string ->
        CASE WHEN CURRENT_ROLE() IN ('ANALYST') THEN val 
             WHEN CURRENT_ROLE() IN ('DEVELOPER') THEN SHA2(val)
        ELSE '**********'
        END
  
  {% endmacro %}

Its good to keep the masking policy ddl organized in a directory say \macros\snow-mask-ddl

• Create the masking policies by running below command

Resource Type	Command
sources	dbt run-operation create_masking_policy --args '{"resource_type": "sources"}'
models	dbt run-operation create_masking_policy --args '{"resource_type": "models"}'

• Alternatively, you can also create the masking policies by specifying pre-hook OR on-run-start in your dbt_project.yml

  on-run-start:
    - "{{ dbt_snow_mask.create_masking_policy('models')}}"
    - "{{ dbt_snow_mask.create_masking_policy('sources')}}"

• Apply the masking policy by running below commands

Resource Type	Command
sources	dbt run-operation apply_masking_policy --args '{"resource_type": "sources"}'
models	dbt run -- model <model-name>
snapshots	dbt snapshot --select <snapshot-name> --target <target-name>

• Alternatively, you can also apply the masking policies by specifying below post-hook OR on-run-end to dbt_project.yml

  Example : dbt_project.yml

(For models)

models:
  post-hook: 
    - "{{ dbt_snow_mask.apply_masking_policy('models') }}"

(For snapshots)

snapshots:
  post-hook: 
    - "{{ dbt_snow_mask.apply_masking_policy('snapshots') }}"

How to remove masking policy ?

• Remove the masking policy applied by this package by running below commands

Resource Type	Command
sources	dbt run-operation unapply_masking_policy --args '{"resource_type": "sources"}'
models	dbt run-operation unapply_masking_policy --args '{"resource_type": "models"}'
snapshots	dbt run-operation unapply_masking_policy --args '{"resource_type": "snapshots "}'

• Alternatively, you can also apply the unmasking policies by specifying below post-hook OR on-run-end to dbt_project.yml

  Example : dbt_project.yml

(For models)

models:
  post-hook: 
    - "{{ dbt_snow_mask.unapply_masking_policy('models') }}"

(For snapshots)

  snapshots:
    post-hook: 
      - "{{ dbt_snow_mask.unapply_masking_policy('snapshots') }}"

How to validate masking policy ?

-- Show masking policy
SHOW MASKING POLICIES;

-- Describe masking policy
DESCRIBE MASKING POLICY <masking-policy-name>;

-- Show masking policy references
USE DATABASE <database-name>;

USE SCHEMA INFORMATION_SCHEMA;

SELECT *
  FROM TABLE(INFORMATION_SCHEMA.POLICY_REFERENCES(POLICY_NAME => '<database-name>.<schema-name>.<masking-policy-name>'));

Process flow

Create masking policy

graph TD
    A[create_masking_policy] --> |resource_type='sources',meta_key='masking_policy'| B[get_masking_policy_list_for_sources]
    A[create_masking_policy] --> |resource_type='models',meta_key='masking_policy'| C[get_masking_policy_list_for_models]
    B --> |database, schema| D[create_schema]
    C --> |database, schema| D[create_schema]
    D --> |policy_name| E[call_masking_policy_macro]

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Apply masking policy

graph TD
    A[apply_masking_policy] --> |resource_type='sources',meta_key='masking_policy'| B[apply_masking_policy_list_for_sources]
    A[apply_masking_policy] --> |resource_type='models',meta_key='masking_policy'| C[apply_masking_policy_list_for_models]
    B --> |meta_key| D[confirm masking policy is avaliable in db]
    C --> |meta_key| D[confirm masking policy is avaliable in db]
    D --> E[alter statement to set masking policy]

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Known Errors and Solutions

Error	Solution
dict object' has no attribute 'create_masking_policy_mp_encrypt_pi'	Typo in yaml for masking_policy, mp_encrypt_pi instead of mp_encrypt_pii

Credits

This package was created using examples from Serge and Matt. Please see the contributors for full list of users who have contributed to this project.

References

• https://docs.snowflake.com/en/user-guide/security-column-ddm-intro.html
• https://getdbt.slack.com/archives/CJN7XRF1B/p1609177817234800
• https://docs.snowflake.com/en/sql-reference/functions/policy_references.html
• https://docs.snowflake.com/en/user-guide/security-column-ddm-use.html

Contributions

Contributions to this package are welcomed. Please create issues for bugs or feature requests for enhancement ideas or PRs for any enhancement contributions.

How to do an integration test ?

• This is applicable only to contributors
• cd into dbt-snow-mask/integration_tests
• Run dbt deps
• Run dbt seed
• Adjust the vars in integration_tests\dbt_project.yml and run dbt run