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.
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.
- 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.
- 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)
-
Clone the repository:
git clone https://github.com/yourusername/priscope.git cd priscope
-
Install the required Python packages:
pip install -r requirements.txt
-
Ensure Ollama is installed and running with the
mistral-small
or similar model:ollama run mistral-small
Edit the config.json
file to set your preferences:
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).
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.
-
Build the Docker image:
docker build -t priscope .
-
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.
- Mounts the current directory to
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).
I recommend using the mistral-small
model with Ollama for several reasons:
- It demonstrates strong capabilities in code analysis and understanding.
- 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.
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:
-
Generate the model config:
ollama show mistral-small --modelfile > ollama_conf.txt
-
Edit the
ollama_conf.txt
file by appending the following line right below theFROM ...
line:PARAMETER num_ctx 32768
This sets the context window to 128k tokens (the maximum for mistral-small).
-
Build a new model template:
ollama create mistral-small-128K -f ollama_conf.txt
-
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.
Contributions to PRIscope are welcome! Please feel free to submit pull requests, report bugs, or suggest features.
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.