A $1,400 experiment in AI security auditing outperformed OpenAI’s Codex Security

A research team has built a system that teaches AI agents to hunt for software bugs by writing the audit method down as plain text. The system, called EVOHUNT, keeps the underlying AI model fixed and improves only an external “playbook” that tells the agent how to work. One result stands out for anyone buying security tools. An open-source model running an evolved playbook found real vulnerabilities at a higher rate than OpenAI’s commercial Codex … More → The post A $1,400 experiment in AI security auditing outperformed OpenAI’s Codex Security appeared first on Help Net Security.