
How to Build an AI Agent for Pentesting Without Turning It Into a Black Box
Most security specialists use language models as advanced references where the human reviews every suggestion before execution. With autonomous AI agents the workflow changes dramatically as the agent plans steps, calls tools, analyzes outputs and maintains memory across multiple iterations. This automation introduces serious risks because specialists may see only the final result without understanding which hypotheses were tested or why specific commands were chosen. CyberED and Standoff Hackbase are running a practical AI pentesting challenge to help participants build controllable agents. The event includes a live webinar on 10 September followed by a week-long hands-on period on the Standoff Hackbase training range. Experts emphasize defining strict technical boundaries, logging every decision, and keeping high-risk actions under human oversight.
SecuritylabSep 9, 2026Translated from Russian
