I’ve been spending some time recently testing the alpha version of an agentic pentesting setup we’ve been developing internally, and it’s been an interesting shift from the usual automated scanning approach.
One thing that stood out early is how much effort typically goes into validating false positives from traditional scanners. With an agent-driven model, the system attempts to verify findings before surfacing them, which has noticeably reduced that noise in my testing flow so far.
It’s still early, and I don’t see it replacing manual testing anytime soon, especially for logic gaps that AI is certainly incapable of analyzing. But it does feel like a practical step toward making automated testing more reliable and helpful.
I’m curious if anyone else here has started experimenting with agentic workflows or similar approaches. Are you seeing real value with the current tools in the market?