PRIscope: PR Inspector for Security Concerns and Open-source Protection

PRIscope is a Python-based tool designed to analyze the history of code changes in open-source repositories primarily to address sowtware supply chain risks. It helps identify potential security risks or malicious code modifications by examining merged pull requests using an AI-powered code analysis.

<img src="_assets/sample.png" alt="example" width="800"/>

IMPORTANT DISCLAIMER: PRIscope's effectiveness may be limited when using models with small context window sizes. For optimal performance, please refer to the "Ollama Configuration for Larger Context Windows" section below.

Features

• Fetches and analyzes the most recent merged pull requests from a specified GitHub repository.
• Utilizes Ollama, a local AI model server, for intelligent code analysis.
• Provides a concise summary of potential security risks for each analyzed pull request.
• Generates an optional JSON report with detailed findings.
• Can be run as a standalone Python script or within a Docker container.

Prerequisites

• Python 3.9 or higher
• Ollama installed and running locally via ollama serve
• The mistral-small model loaded in Ollama (recommended for its code analysis capabilities)
• Docker (optional, for containerized usage)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/priscope.git
   cd priscope
   

2. Install the required Python packages:

   pip install -r requirements.txt
   

3. Ensure Ollama is installed and running with the mistral-small or similar model:

   ollama run mistral-small
   

Configuration

Edit the config.json file to set your preferences:

Usage

Running as a Python Script

To analyze a GitHub repository:

python priscope.py https://github.com/owner/repo [-n NUMBER | -s SINCE] [-j]

• Replace https://github.com/owner/repo with the target repository URL.
• -n NUMBER specifies the number of recent PRs to analyze (default is 10).
• -s SINCE analyzes PRs merged since this time (format: 2d, 3w, 1m for days, weeks, months).
• -j generates a JSON report (optional).

Running with Docker

PRIscope can also be run in a Docker container for enhanced security and isolation. This method ensures that the script runs in a controlled environment with read-only access to the filesystem.

1. Build the Docker image:

   docker build -t priscope .
   

2. Run the container:

   docker run --rm -v $(pwd):/app/output:rw --read-only -u $(id -u):$(id -g) priscope https://github.com/owner/repo -n 5 -j
   

   This command does the following:

   • Mounts the current directory to /app/output in the container for report output.
   • Sets the container's filesystem as read-only for security.
   • Runs the container as the current user to ensure proper file permissions.

Output

PRIscope provides a color-coded console output for each analyzed PR:

• Green: No issues identified
• Red: Potential security risk detected

If the JSON report option is used, a detailed report will be generated in the current directory (or /app/output when using Docker).

Why Mistral-Small?

I recommend using the mistral-small model with Ollama for several reasons:

1. It demonstrates strong capabilities in code analysis and understanding.
2. It offers a good balance between performance and resource requirements.

However, you can experiment with other models by changing the model_name in the config.json file.

Ollama Configuration for Larger Context Windows

By default, Ollama templates are configured with a context window of 2048 tokens. However, this can be quite small when analyzing larger PRs. It is highly recommended to extend this context window for better performance.

To increase the context window size:

1. Generate the model config:

   ollama show mistral-small --modelfile > ollama_conf.txt
   

2. Edit the ollama_conf.txt file by appending the following line right below the FROM ... line:

   PARAMETER num_ctx 32768
   

   This sets the context window to 128k tokens (the maximum for mistral-small).

3. Build a new model template:

   ollama create mistral-small-128K -f ollama_conf.txt
   

4. Update your config.json file with the new model name:

   {
     "model_name": "mistral-small-128K"
   }
   

A sample ollama_conf.txt file is included in the repository for reference.

Contributing

Contributions to PRIscope are welcome! Please feel free to submit pull requests, report bugs, or suggest features.

Disclaimer

PRIscope is a tool designed to assist in identifying potential security risks, but it should not be considered a comprehensive security solution. Always perform thorough code reviews and use additional security measures in your development process.