AI-Powered Autonomous Penetration Testing Agent
Published at USENIX Security 2024
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Warning
PentestGPT is a research prototype only
PentestGPT is a research prototype that pioneered the use of GenAI in cybersecurity. Please be aware of third-party services claiming to offer paid PentestGPT products - the original project is free and open-source.
- Autonomous Agent - Agentic pipeline for intelligent, autonomous penetration testing
- Session Persistence - Save and resume penetration testing sessions
- Docker-First - Isolated, reproducible environment with security tools pre-installed
In Progress: Multi-model support for OpenAI, Gemini, and other LLM providers
- 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
- Docker (required) - Install Docker
- LLM Provider (choose one):
- Anthropic API Key from console.anthropic.com
- Claude OAuth Login (requires Claude subscription)
- OpenRouter for alternative models at openrouter.ai
- Tutorial: Using Local Models with Claude Code
# Clone and build
git clone --recurse-submodules https://github.com/GreyDGL/PentestGPT.git
cd PentestGPT
make install
# Configure authentication (first time only)
make config
# Connect to container
make connectNote: The
--recurse-submodulesflag downloads the benchmark suite. If you already cloned without it, run:git submodule update --init --recursive
uv run pentestgpt-benchmark start XBEN-037-24 Then connect into the container and run:
pentestgpt --target http://host.docker.internal:8000| Command | Description |
|---|---|
make install |
Build the Docker image |
make config |
Configure API key (first-time setup) |
make connect |
Connect to container (main entry point) |
make stop |
Stop container (config persists) |
make clean-docker |
Remove everything including config |
# Interactive TUI mode (default)
pentestgpt --target 10.10.11.234
# Non-interactive mode
pentestgpt --target 10.10.11.100 --non-interactive
# With challenge context
pentestgpt --target 10.10.11.50 --instruction "WordPress site, focus on plugin vulnerabilities"Keyboard Shortcuts: F1 Help | Ctrl+P Pause/Resume | Ctrl+Q Quit
PentestGPT supports routing requests to local LLM servers (LM Studio, Ollama, text-generation-webui, etc.) running on your host machine.
- Local LLM server with an OpenAI-compatible API endpoint
- LM Studio: Enable server mode (default port 1234)
- Ollama: Run
ollama serve(default port 11434)
# Configure PentestGPT for local LLM
make config
# Select option 4: Local LLM
# Start your local LLM server on the host machine
# Then connect to the container
make connectEdit scripts/ccr-config-template.json to customize:
localLLM.api_base_url: Your LLM server URL (default:host.docker.internal:1234)localLLM.models: Available model names on your server- Router section: Which models handle which operations
| Route | Purpose | Default Model |
|---|---|---|
default |
General tasks | openai/gpt-oss-20b |
background |
Background operations | openai/gpt-oss-20b |
think |
Reasoning-heavy tasks | qwen/qwen3-coder-30b |
longContext |
Large context handling | qwen/qwen3-coder-30b |
webSearch |
Web search operations | openai/gpt-oss-20b |
- Connection refused: Ensure your LLM server is running and listening on the configured port
- Docker networking: Use
host.docker.internal(notlocalhost) to access host services from Docker - Check CCR logs: Inside the container, run
cat /tmp/ccr.log
PentestGPT collects anonymous usage data to help improve the tool. This data is sent to our Langfuse project and includes:
- Session metadata (target type, duration, completion status)
- Tool execution patterns (which tools are used, not the actual commands)
- Flag detection events (that a flag was found, not the flag content)
No sensitive data is collected - command outputs, credentials, or actual flag values are never transmitted.
# Via command line flag
pentestgpt --target 10.10.11.234 --no-telemetry
# Via environment variable
export LANGFUSE_ENABLED=falsePentestGPT includes 100+ vulnerability challenges for testing and development.
pentestgpt-benchmark list # List all benchmarks
pentestgpt-benchmark list --levels 1 # Filter by difficulty
pentestgpt-benchmark list --tags sqli # Filter by vulnerability type
pentestgpt-benchmark start XBEN-037-24 # Start a benchmark
pentestgpt-benchmark status # Check running benchmarks
pentestgpt-benchmark stop XBEN-037-24 # Stop a benchmarkAvailable Tags: sqli, xss, idor, ssti, ssrf, lfi, rce
- uv (required) - Python package manager:
curl -LsSf https://astral.sh/uv/install.sh | sh - Claude Code CLI - Configure with
claude loginorexport ANTHROPIC_API_KEY='your-key'
uv sync # Install dependencies
uv run pentestgpt --target 10.10.11.234 # Run locallymake test # Run pytest
make lint # Run ruff linter
make typecheck # Run mypy
make ci # Run full CI simulation (lint, format, typecheck, test, build)
make ci-quick # Quick CI without build stepThe previous multi-LLM version (v0.15) supporting OpenAI, Gemini, Deepseek, and Ollama is archived in legacy/:
cd legacy && pip install -e . && pentestgpt --reasoning gpt-4oIf you use PentestGPT in your research, please cite our paper:
@inproceedings{299699,
author = {Gelei Deng and Yi Liu and Víctor Mayoral-Vilches and Peng Liu and Yuekang Li and Yuan Xu and Tianwei Zhang and Yang Liu and Martin Pinzger and Stefan Rass},
title = {{PentestGPT}: Evaluating and Harnessing Large Language Models for Automated Penetration Testing},
booktitle = {33rd USENIX Security Symposium (USENIX Security 24)},
year = {2024},
isbn = {978-1-939133-44-1},
address = {Philadelphia, PA},
pages = {847--864},
url = {https://www.usenix.org/conference/usenixsecurity24/presentation/deng},
publisher = {USENIX Association},
month = aug
}Distributed under the MIT License. See LICENSE.md for more information.
Disclaimer: This tool is for educational purposes and authorized security testing only. The authors do not condone any illegal use. Use at your own risk.
- Gelei Deng -
- gelei.deng@ntu.edu.sg
- Yi Liu - yi009@e.ntu.edu.sg
- Yuekang Li - yuekang.li@unsw.edu.au
- Víctor Mayoral Vilches -
- Peng Liu - liu_peng@i2r.a-star.edu.sg
- Research supported by Quantstamp and NTU Singapore
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