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PentestGPT

AI-Powered Autonomous Penetration Testing Agent
Published at USENIX Security 2024

Research Paper · Report Bug · Request Feature

GreyDGL%2FPentestGPT | Trendshift > [!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. --- ## Demo ### Installation [![Installation Demo](https://asciinema.org/a/761661.svg)](https://asciinema.org/a/761661) [Watch on YouTube](https://www.youtube.com/watch?v=RUNmoXqBwVg) ### PentestGPT in Action [![PentestGPT Demo](https://asciinema.org/a/761663.svg)](https://asciinema.org/a/761663) [Watch on YouTube](https://www.youtube.com/watch?v=cWi3Yb7RmZA) --- ## What's New in v1.0 (Agentic Upgrade) - **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 --- ## Features - **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 --- ## Quick Start ### Prerequisites - **Docker** (required) - [Install Docker](https://docs.docker.com/get-docker/) - **LLM Provider** (choose one): - Anthropic API Key from [console.anthropic.com](https://console.anthropic.com/) - Claude OAuth Login (requires Claude subscription) - OpenRouter for alternative models at [openrouter.ai](https://openrouter.ai/keys) - [Tutorial: Using Local Models with Claude Code](https://docs.google.com/document/d/1ixK7x-wlr5t5TYZJdfm75UME5KnPCpS46boLkUXKg1w/edit?usp=sharing) ### Installation ```bash # 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 connect ``` > **Note**: The `--recurse-submodules` flag downloads the benchmark suite. If you already cloned without it, run: `git submodule update --init --recursive` ### Try a Benchmark ```bash uv run pentestgpt-benchmark start XBEN-037-24 ``` Then connect into the container and run: ```bash pentestgpt --target http://host.docker.internal:8000 ``` ### Commands Reference | 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 | --- ## Usage ```bash # 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 --- ## Using Local LLMs PentestGPT supports routing requests to local LLM servers (LM Studio, Ollama, text-generation-webui, etc.) running on your host machine. ### Prerequisites - Local LLM server with an OpenAI-compatible API endpoint - **LM Studio**: Enable server mode (default port 1234) - **Ollama**: Run `ollama serve` (default port 11434) ### Setup ```bash # 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 connect ``` ### Customizing Models Edit `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 | ### Troubleshooting - **Connection refused**: Ensure your LLM server is running and listening on the configured port - **Docker networking**: Use `host.docker.internal` (not `localhost`) to access host services from Docker - **Check CCR logs**: Inside the container, run `cat /tmp/ccr.log` --- ## Telemetry PentestGPT collects anonymous usage data to help improve the tool. This data is sent to our [Langfuse](https://langfuse.com) 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. ### Opting Out ```bash # Via command line flag pentestgpt --target 10.10.11.234 --no-telemetry # Via environment variable export LANGFUSE_ENABLED=false ``` --- ## Benchmarks PentestGPT includes 100+ vulnerability challenges for testing and development. ```bash 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 benchmark ``` **Available Tags:** `sqli`, `xss`, `idor`, `ssti`, `ssrf`, `lfi`, `rce` --- ## Development ### Prerequisites - **uv** (required) - Python package manager: `curl -LsSf https://astral.sh/uv/install.sh | sh` - **Claude Code CLI** - Configure with `claude login` or `export ANTHROPIC_API_KEY='your-key'` - [Tutorial: Using Local Models with Claude Code](https://docs.google.com/document/d/1ixK7x-wlr5t5TYZJdfm75UME5KnPCpS46boLkUXKg1w/edit?usp=sharing) ### Local Development ```bash uv sync # Install dependencies uv run pentestgpt --target 10.10.11.234 # Run locally ``` ### Project Commands ```bash make 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 step ``` --- ## Legacy Version The previous multi-LLM version (v0.15) supporting OpenAI, Gemini, Deepseek, and Ollama is archived in [`legacy/`](legacy/): ```bash cd legacy && pip install -e . && pentestgpt --reasoning gpt-4o ``` --- ## Citation If you use PentestGPT in your research, please cite our paper: ```bibtex @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 } ``` --- ## License 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. --- ## Contact - **Gelei Deng** - [![LinkedIn][linkedin-shield]][linkedin-url] - gelei.deng@ntu.edu.sg - **Yi Liu** - yi009@e.ntu.edu.sg - **Yuekang Li** - yuekang.li@unsw.edu.au - **Víctor Mayoral Vilches** - [![LinkedIn][linkedin-shield]][linkedin-url2] - v.mayoralv@gmail.com - **Peng Liu** - liu_peng@i2r.a-star.edu.sg --- ## Acknowledgments - Research supported by [Quantstamp](https://www.quantstamp.com/) and [NTU Singapore](https://www.ntu.edu.sg/)

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