head to head · open source
shannon vs pentest-ai
shannon has 48,105 GitHub stars, 5,515 forks, 18 open issues and last shipped 10 days ago. pentest-ai has 1,677 stars, 314 forks, 2 open issues and last shipped 5 days ago. shannon leads on adoption by 2,769% (48,105 vs 1,677 stars). shannon is written in TypeScript under AGPL-3.0; pentest-ai is written in Python under MIT. shannon has attracted 11% as many forks as stars, pentest-ai 19%. pentest-ai was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 6 topic tags (ai-penetration-testing, ai-security, appsec, cybersecurity), 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
| shannon | pentest-ai | |
|---|---|---|
| GitHub stars | ★ 48K | ★ 1.7K |
| License | AGPL-3.0 | MIT |
| Written in | TypeScript | Python |
| Last push | 2026-09-08 | 2026-09-13 |
| Forks | ⑂ 5.5K | ⑂ 314 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick shannon if
- You weight community size — 48K stars and counting
- You want the AGPL-3.0 license terms
- Your stack matches TypeScript
- 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 shannon
Shannon is an autonomous AI pentester for web applications and APIs that reads an application's source code, identifies attack paths, and executes real exploits so that only vulnerabilities with a working proof of concept are reported, built for AppSec, DevSecOps, and security engineering teams that ship code continuously.
read the full shannon overview →
About pentest-ai
Pentest AI is an open source Python project that connects an AI client or model to a penetration testing workflow. It belongs to the AI security and application security ecosystem, and it is distributed under the MIT license. The project is published as ptai on PyPI and can be used through MCP, the CLI, or CI.
read the full pentest-ai overview →
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Frequently asked questions
Is shannon or pentest-ai more popular?
shannon has 48,105 GitHub stars and pentest-ai has 1,677. shannon has the larger community by that measure.
Are shannon and pentest-ai free?
Both are open source. shannon is licensed under AGPL-3.0 and pentest-ai under MIT. Neither carries a licence fee.
What is the difference between shannon and pentest-ai?
shannon is written in TypeScript 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, shannon or pentest-ai?
Choose shannon if you want the larger community (48,105 stars) or its AGPL-3.0 licence terms. Choose pentest-ai if its feature set, stack or MIT licence fits better. Both are self-hostable.