Quick Summary: 📝
PentestAgent is an AI-powered framework designed for automated black-box security testing. It supports various penetration testing workflows, including bug bounty hunting and red-teaming, by leveraging AI agents to interact with systems and identify vulnerabilities.
Key Takeaways: 💡
✅ PentestAgent uses LLMs to automate complex security assessments and penetration testing workflows.
✅ It supports multi-agent "Crew" mode, allowing specialized AI workers to collaborate autonomously on large security tasks.
✅ Tool execution is isolated using Docker containers, including specialized Kali images, enhancing safety and environment control.
✅ Prebuilt "Playbooks" enable structured, repeatable, and comprehensive black-box security testing with minimal manual effort.
✅ Integration with LiteLLM ensures flexibility, supporting major LLM providers like OpenAI and Anthropic.
Project Statistics: 📊
- ⭐ Stars: 1138
- 🍴 Forks: 305
- ❗ Open Issues: 4
Tech Stack: 💻
- ✅ Python
Imagine having a highly skilled security expert available 24/7, ready to execute complex penetration tests with minimal supervision. That is the core promise of PentestAgent. This project leverages the power of large language models to automate and streamline the entire security assessment process, moving far beyond simple vulnerability scanners. It acts as an intelligent layer that understands security goals and translates them into actionable commands for industry-standard tools like Nmap, Metasploit, and SQLMap.
The architecture is designed for flexibility and safety. PentestAgent integrates seamlessly with various LLM providers, such as OpenAI and Anthropic, using LiteLLM. Crucially, it supports running all underlying security tools within isolated Docker containers. This isolation is a huge win for developers and security teams, ensuring that potentially dangerous testing activities are contained and don't affect the host system environment. You can even spin up a specialized Kali Linux container pre-loaded with advanced tools, giving the agent access to a massive arsenal instantly.
Developers should be excited about the operational modes offered. The default "Assist" mode lets you chat and guide the agent, like a smart co-pilot, perfect for learning or targeted tasks. For more complex, defined tasks, the "Agent" mode allows for autonomous execution of a single objective. But the real game-changer is the "Crew" mode. Here, PentestAgent acts as an orchestrator, spawning specialized worker agents—each focusing on a different aspect of the test, such as reconnaissance or vulnerability exploitation—to tackle large tasks collaboratively. This multi-agent approach mimics a professional security team structure, significantly accelerating the discovery process.
Furthermore, PentestAgent introduces the concept of "Playbooks." These are prebuilt, structured attack sequences for black-box testing, ensuring comprehensive and repeatable security assessments. Instead of manually scripting a dozen steps, you simply select a playbook tailored for, say, web application testing, and the agent executes the entire flow intelligently. This dramatically lowers the barrier to entry for thorough security testing and guarantees consistent results across different targets and sessions. By offloading the tedious, repetitive execution and decision-making to the AI, developers and security engineers can focus their valuable time on remediation and higher-level architectural security concerns.
Learn More: 🔗
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