head to head · open source
PyRIT vs pentest-ai
PyRIT has 4,740 GitHub stars, 1,025 forks, 281 open issues and last shipped yesterday. pentest-ai has 1,799 stars, 329 forks, 2 open issues and last shipped 2 days ago. PyRIT leads on adoption by 163% (4,740 vs 1,799 stars). PyRIT is written in Python under MIT; pentest-ai is written in Python under MIT. PyRIT has attracted 22% as many forks as stars, pentest-ai 18%. PyRIT was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai-security), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| PyRIT | pentest-ai | |
|---|---|---|
| GitHub stars | ★ 4.7K | ★ 1.8K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-11-04 | 2026-11-03 |
| Forks | ⑂ 1.0K | ⑂ 329 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick PyRIT if
- You weight community size — 4.7K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick pentest-ai if
- You want the pentest-ai feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and pentest-ai fits your workflow better
About PyRIT
Python Risk Identification Tool for generative AI (PyRIT) The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems. Check out our website for more information about how to use, install, or contribute to PyRIT. Review our security policy to report vulnerabilities privately through the Microsoft Security Response Center. Visit our Discord server to chat with the team and community. Trademarks and Citations This project may contain trademarks or logos for projects, products…
read the full PyRIT overview →
About pentest-ai
Website · Quick start · Verification · Documentation · Issues Pentest AI connects an AI client or model to a penetration testing workflow. It investigates applications, records findings, and uses machine oracles to check whether an exploit can be reproduced . Verified findings carry evidence you can replay. Use it through MCP , from the CLI , or in CI . The model helps drive the investigation; an oracle determines whether a finding earns a verified verdict. Test only systems you own or have explicit authorization to assess. Read the acceptable use policy and terms before running an engagement. Quick start…
read the full pentest-ai overview →
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Frequently asked questions
Is PyRIT or pentest-ai more popular?
PyRIT has 4,740 GitHub stars and pentest-ai has 1,799. PyRIT has the larger community by that measure.
Are PyRIT and pentest-ai free?
Both are open source. PyRIT is licensed under MIT and pentest-ai under MIT. Neither carries a licence fee.
What is the difference between PyRIT and pentest-ai?
PyRIT is written in Python and pentest-ai in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, PyRIT or pentest-ai?
Choose PyRIT if you want the larger community (4,740 stars) or its MIT licence terms. Choose pentest-ai if its feature set, stack or MIT licence fits better. Both are self-hostable.