Many companies have quickly moved to adopt artificial intelligence in their systems, embedding it into virtually everything from customer apps to internal systems. That speed has created new pressure for security teams, because AI-enabled applications can introduce unfamiliar attack surfaces, unpredictable behavior, and new ways for attackers to manipulate inputs, access data, or chain weaknesses across systems. Traditional security approaches still matter, but static checks, periodic penetration tests, and basic vulnerability scans were not built for this pace of change. They can miss issues that only appear when applications are tested dynamically, in context, and from an attacker’s perspective. As AI accelerates development and expands the attack surface, platforms like XBOW are becoming more important. With continuous pentesting and autonomous offensive security, XBOW helps teams find, validate, and prioritize exploitable vulnerabilities before attackers do.
Protecting AI Systems Through Continuous Testing
Washington State University explains how AI can be a double-edged sword. “Adversarial attacks exploit vulnerabilities in AI models to manipulate their behavior. By making subtle modifications to input data, attackers can deceive AI systems, leading to incorrect outputs or decisions.”
