I’ve been testing a few so-called agentic AI pentesting tools lately. On paper, they sound impressive. Autonomous recon. Multi-step exploitation. Self-reasoning workflows.
In practice, I’ve seen mixed results.
They provide me with the results really quickly. But when I manually validate the findings, many are shallow. Some miss obvious logic flaws. A few break the app in ways a real attacker wouldn’t even bother with. It feels like speed has improved, but depth is still questionable.
What concerns me more is the confidence these tools create. Clean dashboards. Smart-looking attack chains. It’s easy for teams to assume coverage is complete.
I’m not against the idea. I actually think agentic AI can help reduce repetitive testing and surface patterns faster than we can. But right now, it feels like we’re still in the demo phase more than the actual working model.
So I’m curious, are you seeing real depth from agentic AI pentesting, or does it still need a lot of manual validation to be trusted?