OWASP introduces standards for autonomous AI penetration testing

As artificial intelligence accelerates the discovery of vulnerabilities and the speed of cyberattacks, new standards and defensive strategies are emerging to address the risks of autonomous security testing and evolving threat landscapes.

OWASP has introduced the Autonomous Penetration Testing Standard (APTS) to provide a governance framework for autonomous penetration testing platforms, including those utilizing Large Language Models (LLMs). Unlike traditional automated tools that require human judgment to manage scope and impact, APTS focuses on the unique challenges of autonomy, such as enforcing scope boundaries, ensuring safe operations, maintaining accountability, and requiring human approval for high-impact or irreversible actions.

Complementing these technical standards, industry discussions emphasize the need for proactive defense. With attackers using AI to combine leaked credentials from the dark web with information about external assets like cloud services and VPNs, organizations are encouraged to move beyond simple vulnerability management. Approaches such as Continuous Threat Exposure Management (CTEM) and cyber threat intelligence are being highlighted to help companies understand how they appear to attackers and identify signs of impending breaches before they occur.