Enterprise security teams are increasingly turning to inference security platforms as they struggle to defend against a new wave of AI-enabled runtime attacks. The shift comes as threat actors exploit vulnerabilities in AI agents operating in production environments, where the speed of attacks far outpaces traditional security measures.
According to CrowdStrike's 2025 Global Threat Report, breakout times have shrunk to as little as 51 seconds, giving security teams minimal time to respond before attackers move laterally within a network. The report also revealed that 79% of detected attacks were malware-free, relying instead on "hands-on keyboard" techniques that bypass conventional endpoint defenses.
The accelerated pace of weaponization is a key driver behind the growing adoption of inference security platforms. Mike Riemer, field CISO at Ivanti, noted that AI has dramatically reduced the time it takes for attackers to reverse engineer patches. "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."
Inference security platforms address this challenge by providing real-time visibility and control over AI agents at runtime. These platforms analyze the behavior of AI models and applications, detecting and preventing malicious activities such as data poisoning, model evasion, and unauthorized access. By focusing on the inference stage, where AI models are actively processing data, these platforms can identify threats that traditional security tools often miss.
The industry impact of these runtime attacks is significant, as enterprises increasingly rely on AI to automate critical business processes. A successful attack on an AI agent could lead to data breaches, financial losses, and reputational damage. As a result, CISOs are prioritizing the deployment of inference security platforms to protect their AI investments and maintain business continuity.
The demand for inference security platforms is expected to continue growing in 2026 as AI adoption expands and attackers become more sophisticated. Several vendors are now offering specialized solutions in this space, providing features such as anomaly detection, policy enforcement, and automated incident response. These platforms often integrate with existing security infrastructure, providing a layered defense against AI-enabled threats.
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