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Open-source red-teaming framework that stress-tests LLMs and AI agents.
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View guide →Microsoft's open framework for red-teaming generative AI systems.
PyRIT is an open-source ai agents project by microsoft (microsoft/PyRIT on GitHub). It has 4,592 GitHub stars and 936 forks, is released under the MIT license, and was last updated on GitHub on 8 October 2026.
Start with one concrete task rather than a grand architecture.
Clone the repo and check the examples folder for a quickstart.
Install packages, set environment variables, and point it at your model.
Execute the demo workflow, then adapt it to your own data.
Systematic attack generation.
Find issues before deployment.
Built by Microsoft's AI red team.
Add your own attack strategies.
Aligned with RAI practices.
Free for commercial security work.
Download the source and move into the project folder.
git clone https://github.com/microsoft/PyRIT.git
cd PyRITCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtTreat these as starting points - the README documents the exact commands.
python examples/quickstart.pymicrosoft/PyRIT is its home on GitHub, with 936 forks so far. The contributors tab and recent commits show how actively it is maintained.
Yes - it is MIT licensed, so you can use, modify, and distribute it freely, including in commercial projects.
The toolkit is free; only the models it guards might come from a paid provider.
PyRIT finds vulnerabilities; Guardrails enforces runtime protections. Use PyRIT during security review and Guardrails in production - they complement each other.
Follow the README quickstart, then browse the examples directory for patterns that match what you want to build.
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