No. Frontier LLMs accelerate existing attack techniques rather than creating new threat classes. AI collapses the time between vulnerability discovery and exploitation toward real time, making rapid attack execution accessible to a far broader range of threat actors.
Strategic Guide
AI automates the attack. AI-powered segmentation automates the defense.
When attackers use AI to navigate networks with unprecedented velocity, how do you stop them in their tracks? Learn how to detect and defend with machine speed in our new strategic guide to containing AI-fueled lateral movement.
Today’s threats
AI has upended cybersecurity, introducing new attack vectors and empowering old tactics with speed that traditional processes cannot match. From rogue agents to LLM-fueled ransomware, security teams must assume threats are inside and be ready to contain them automatically.
Expert Viewpoints
Frequently Asked Questions (FAQ)
Frequently Asked Questions (FAQ)
Security teams can deploy governed LLM pipelines to handle time-consuming defensive tasks at scale. These automated engines continuously analyze code for weaknesses, prioritize vulnerabilities by actual business risk, generate policy fixes, and accelerate patch deployment at the edge — allowing defenders to match the speed of AI-driven threat actors.
Traditional north-south network perimeters cannot contain threats in multiagent ecosystems because attackers can easily pivot laterally if internal services implicitly trust any caller from that network segment. Furthermore, autonomous agents expand the attack surface by using protocols like the Model Context Protocol (MCP) to access APIs and databases without requiring human intervention.
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