Enterprise security teams are increasingly turning to inference security platforms to combat a new wave of AI-driven runtime attacks, according to a recent report. These attacks exploit vulnerabilities in AI agents operating in production environments, where traditional security measures struggle to provide adequate visibility and control.

The shift is driven by the speed and sophistication of modern attacks. CrowdStrike's 2025 Global Threat Report revealed that breakout times, the time it takes for an attacker to move from initial access to lateral movement within a network, can be as short as 51 seconds. This rapid pace often allows attackers to compromise systems before security teams can even react. The report also highlighted that 79% of detections were malware-free, indicating a rise in "hands-on keyboard" techniques that bypass conventional endpoint defenses.

Mike Riemer, field CISO at Ivanti, emphasized the shrinking window of opportunity for patching vulnerabilities. "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 accelerated weaponization of vulnerabilities puts immense pressure on enterprises, many of which take weeks or months to deploy patches manually.

Inference security platforms are designed to address these challenges by providing real-time monitoring and protection for AI applications. These platforms analyze the behavior of AI models and their interactions with other systems, detecting and preventing malicious activities that traditional security tools might miss. By focusing on the runtime environment, inference security platforms offer a layer of defense against attacks that exploit vulnerabilities in AI models themselves or in the infrastructure they rely on.

The increasing adoption of AI across various industries has expanded the attack surface, making it more challenging for security teams to keep pace with emerging threats. As AI agents become more integrated into critical business processes, the potential impact of successful attacks grows significantly. This has led CISOs to prioritize investments in specialized security solutions that can effectively protect their AI assets.

The deployment of inference security platforms is expected to continue to rise in 2026 as organizations seek to mitigate the risks associated with AI-powered attacks. The focus will likely be on platforms that offer automated threat detection, incident response, and integration with existing security infrastructure. The ability to proactively identify and neutralize threats in real-time will be crucial for organizations looking to maintain a strong security posture in the face of increasingly sophisticated attacks.