Frida Script Runner

Frida Script Runner v1.3 is a versatile web-based tool designed for Android and iOS penetration testing purposes.

This tool simplifies the process of interacting with Frida, providing a user-friendly interface through Flask, a Python framework, to enhance the efficiency of penetration testing tasks.

Features

• Run Frida Scripts: Execute custom Frida scripts on selected mobile applications to analyze and manipulate their behavior.
• Real-time Output: View real-time output generated by the Frida process, allowing instant feedback on script execution.
• Script Organization: Organize Frida scripts into different directories for efficient management and easy selection.
• Custom Scripting: Easily create and run custom Frida scripts by copy-pasting the script code directly into the tool.

Feature Details

How to Use for Android & Custom Script

How to Use for iOS

Prerequisites

• Python 3.11.x (required)
• Flask
• Frida
• ADB (for Android and installation click this link)
• Ideviceinfo (for iOS and installation click this link)

Installation

1. Clone the repository:

   git clone https://github.com/z3n70/Frida-Script-Runner.git
   

2. Install Dependencies:

   pip3 install -r requirements.txt
   

3. Run The Application

   python3.11 frida_script.py
   

4. Open Your Browser

   http://127.0.0.1:5000
   

Usage

1. Connect your USB device and run Frida Server. (root or jailbreak required) and if you use iphone make sure you have Frida installed on Cydia, Sileo, Zebra or another tool

2. Open the web interface and select the target package and script.

3. Click "Run Frida" to start the Frida process.

4. View real-time output in the output container.

Note: If you intend to modify or add frida script files, ensure file are placed in the correct directory. Script Directory 1 For Android and Script Directory 2 For iOS, and you can see script.json for structure file and name

Contributing

Contributions are welcome! Please contact me

Thanks and Support

Pawang Uler, Om-Yud, Mas Gondrong, Alfan, Revan

Acknowledgments

Special thanks to the Frida project for providing an exceptional instrumentation toolkit.