This isn't surprising; the majority of programmers are using LLMs, and Claude is pretty good for coding. Penetration testing is also a pretty good fit for an agentic loop - you run a tool, read the output, and decide on your next move, rinse and repeat.
In VSCode + GitHub Copilot, agent mode it can propose bash command to run, and when you confirm it runs it in a console and can see the loop, so it can fix errors immediately if any. It tends to go off the rails pretty quickly if things start going badly wrong, but it can complete simple tasks with supervision.
Over two years ago, when this LLM stuff was pretty new, I saw a demo that put ChatGPT in a loop with Metasploit that could crack some of the easy HTB challeges automatically - I remember thinking it was the single most irresponsible use of AI I'd ever seen. While everybody else was trying to sandbox these things for safety, this project was just handing it command line access to the tools it would need to break confinement.
It seems there's actually a whole bunch of similar tools these days, marketed as "automated penetration testing," such as Cybersecurity AI[1]. I used to think the whole cyberpunk "hackers can get in anywhere if they just type hard enough" trope was stupid because with cryptography the defender always has a huge advantage, but now we're looking at a world where AI is automating attacks at scale, while the defenders are vibe coding slop they have no idea how to secure, so maybe Gibson was right all along.
[1]: https://github.com/aliasrobotics/cai
