Enterprise security teams are increasingly deploying inference security platforms to combat a new wave of AI-enabled runtime attacks, driven by the shrinking window of opportunity for attackers and the limitations of traditional security measures. These attacks exploit vulnerabilities during the execution phase of AI agents, where breakout times are measured in seconds, far outpacing the hours or days it takes to implement patches.

The shift is prompting CISOs to seek solutions that provide real-time visibility and control over AI applications in production. According to CrowdStrike's 2025 Global Threat Report, breakout times have dropped to as little as 51 seconds, meaning attackers can move from initial access to lateral movement within a network before security teams even receive an alert. The report also revealed that 79% of detected attacks were malware-free, relying instead on "hands-on keyboard" techniques that bypass traditional endpoint defenses.

Mike Riemer, field CISO at Ivanti, highlighted the accelerating pace of weaponization following patch releases. "Threat actors are reverse engineering patches within 72 hours," Riemer told VentureBeat. "If a customer doesn't patch within 72 hours of release, they're open to exploit. The speed has been enhanced greatly by AI." This rapid exploitation cycle is forcing organizations to rethink their patching strategies and adopt more proactive security measures.

Traditional security solutions often lack the visibility and control needed to effectively monitor and protect AI applications at runtime. Inference security platforms address this gap by providing real-time monitoring of AI model behavior, detecting anomalies, and preventing unauthorized access or manipulation. These platforms typically employ techniques such as behavioral analysis, anomaly detection, and access control to safeguard AI applications from runtime attacks.

The increasing sophistication and speed of AI-enabled attacks are expected to further drive the adoption of inference security platforms in the coming years. As AI becomes more deeply integrated into critical business processes, the need for robust runtime security will only intensify. Companies that fail to adapt to this evolving threat landscape risk exposing themselves to significant financial and reputational damage.