PentestGPT
Automated Penetration Testing Agentic Framework Powered by Large Language Models
Automate security testing of systems by using an AI agent that identifies vulnerabilities and generates reports.
From the README
git clone https://github.com/GreyDGL/PentestGPT.git cd PentestGPT make install # runs uv sync
- AI-Powered Challenge Solver - Leverages LLM advanced reasoning to perform penetration testing and CTFs
- Live Walkthrough - Tracks steps in real-time as the agent works through challenges
- Multi-Category Support - Web, Crypto, Reversing, Forensics, PWN, Privilege Escalation
- Real-Time Feedback - Watch the AI work with live activity updates
- Extensible Architecture - Clean, modular design ready for future enhancements
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeAutomated Penetration Testing Agentic Framework Powered by Large Language Models
PentestGPT has 15.2k stars on GitHub. It has been forked 2.6k times. PentestGPT is written mainly in Python. It has been in active development since 2023. PentestGPT is available under the MIT license. Its main topics are large-language-models, llm, penetration-testing, python.
What is PentestGPT?
Automated Penetration Testing Agentic Framework Powered by Large Language Models
Is PentestGPT open source?
PentestGPT is an open-source project. It is released under the MIT license.
Is PentestGPT free?
Yes. PentestGPT is free and open source — you can use, modify and self-host it.
What license does PentestGPT use?
PentestGPT is available under the MIT license.
What language is PentestGPT written in?
PentestGPT is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/greydgl-pentestgpt.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.