Cato Networks Launches Agentic Threat Prevention Against AI Attacks

Cato Networks, the converged network and security cloud for the AI era, announced the launch of Cato Agentic Threat Prevention, a new capability that deploys autonomous agents to predict likely attack paths, and automatically personalizes protections for each customer environment to prevent breaches before AI-assisted attacks can advance. Built on Cato’s cloud-native platform, Cato Agentic Threat Prevention combines network and security telemetry into a unified view of each environment, enabling AI agents to anticipate threats and continuously adapt protections. Those protections are enforced globally through every Cato Point of Presence, without service chaining or enforcement gaps.

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Frontier AI is accelerating vulnerability discovery, adaptive attack chains, and machine-speed execution beyond the limits of manual workflows and traditional security tools. AI attackers now scan millions of environments simultaneously, turn vulnerabilities into working exploits in hours, run parallel attacks across thousands of targets, and operate continuously without human oversight. Security teams relying on manual response and fragmented tools simply cannot keep pace. Organizations need autonomous defenses that match the speed, scale, and adaptability of the multi-stage threats they now face.

“Yesterday’s security cannot stop today’s AI-powered attacks,” said Shlomo Kramer, co-founder and CEO of Cato Networks. “Prediction is the new prevention. The only way to stay ahead of AI-powered attacks is to anticipate where they’ll go next and deploy protections before damage is done. It’s high time we level the playing field, and that’s precisely what we’re doing with Cato Agentic Threat Prevention.”

Cato Agentic Threat Prevention turns single data lake shared context into customer-specific protection. It combines Cato platform telemetry from security and networking, customer-specific activity, and threat intelligence to model risk across users, applications, traffic patterns, assets, and exposures. It then predicts how agentic attackers might chain techniques, exploit gaps, and evade controls, then creates protections tailored to each customer’s environment rather than relying on one-size-fits-all detections.

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“AI-assisted attacks are exposing the limits of static security controls and manual response.  An entire attack can require less time than is required to investigate an alert,” said Frank Dickson, group vice president at IDC. “As attackers adapt faster and tailor campaigns to each environment, enterprises will need prevention approaches that use shared context, automation, and cloud-scale enforcement to reduce exposure before compromise occurs.”

Frontier AI demands agentic defense on two fronts. On the protection side, Cato’s Agentic CVE Mitigation autonomously assesses and applies protections for newly disclosed vulnerabilities in as fast as 45 minutes. On the prevention side, Cato Agentic Threat Prevention predicts likely attack paths and creates customized protections before attackers can advance. Together, they close the gap that AI-assisted attackers exploit: the window between exposure and protection.

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