关于
PentestThinking is an AI-powered penetration testing reasoning engine designed to assist pentesters in attack path planning. It leverages Beam Search and Monte Carlo Tree Search (MCTS) to explore potential attack vectors, score and prioritize attack steps, and recommend relevant tools. It's suitable for CTFs, Hack The Box (HTB) challenges, and real-world pentest workflows, bridging the gap between AI and offensive security.
主要功能
- Automated attack path planning using Beam Search and MCTS
- 0 GitHub stars
- Step-by-step reasoning for CTFs, HTB, and real-world pentests
- Tree-based reasoning for reporting and documentation
- Attack step scoring and prioritization
- Tool recommendations for each step (e.g., nmap, metasploit, linpeas)
使用案例
- Red teaming strategy development and refinement
- Exploit pathfinding and optimization
- Automated vulnerability identification and chaining
Sponsored