Enterprise security teams are increasingly turning to inference security platforms to combat a new wave of AI-driven runtime attacks, as traditional security measures struggle to keep pace with rapidly evolving threats. The shift is driven by attackers exploiting weaknesses in AI agents operating in production environments, where breakout times are measured in seconds, patch windows in hours, and conventional security systems lack adequate visibility and control.
CrowdStrike's 2025 Global Threat Report highlighted the severity of the situation, documenting breakout times as short as 51 seconds. This speed allows attackers to move from initial access to lateral movement within a network before security teams can even issue an alert. The report also revealed that 79% of detected attacks were malware-free, with adversaries employing hands-on keyboard techniques to bypass traditional endpoint defenses.
The speed at which attackers are weaponizing vulnerabilities is also accelerating, according to Mike Riemer, field CISO at Ivanti. "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 shrinking window of opportunity puts immense pressure on security teams, who often require weeks or months to manually deploy patches across their systems.
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 such as data poisoning, model evasion, and unauthorized access. By focusing on the runtime environment, inference security platforms offer a layer of defense that complements traditional security measures.
The growing adoption of inference security platforms reflects a fundamental shift in the threat landscape. As AI becomes more deeply integrated into business operations, the attack surface expands, and traditional security tools are no longer sufficient to protect against sophisticated AI-driven attacks. The industry impact is expected to be significant, with increased investment in AI security solutions and a greater emphasis on proactive threat detection and response.
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