OIHK Pentesting Agent Learns from Past Failures to Improve Future Security Scans

A developer has released a major rebuild of OIHK-Pentesting, an open-source multi-agent framework designed to run authorized penetration tests using a large language model planner called Baron. The updated system can split assessment plans into parallel subtasks, launching up to seven simultaneous AI agent loops inside a governed Kali Linux sandbox. A key new feature records missed or failed scan attempts into a local JSONL ledger, automatically injecting weighted lessons into Baron's future prompts so the agent improves over time without retraining. Safety guardrails include strict scope enforcement, a closed-egress network allowlist, mandatory evidence for every finding, and a resource budget system that prevents hardware overload by capping active Docker containers. The tool is intended solely for use by security professionals with written authorization over their target systems.