Intrusion Detection Patterns for Agentic AI Systems
Agents need per-agent baselines because their threat surface is fundamentally different.
Agents need per-agent baselines because their threat surface is fundamentally different.
Autonomous AI agents hide inside approved apps, evading detection for months.
A legally binding EU framework now carries €35 million fines for AI violations.
Most enterprises can't detect which AI agents are already running in their systems.
Most enterprises have documented governance frameworks they don't actually use in practice.
Attackers exploit browser agents' inherited access to steal data through hidden instructions.
Organizations deploying AI agents lack the logging infrastructure to investigate what they do.
Classical monitoring misses the reasoning loops and behavioral patterns that define agent risk.
Monitoring must watch what agents do between input and output.
Logging catches agent breaches too late; enforcement prevents them first.
Most enterprises lack controls built for how agents actually exfiltrate data.
Agents routinely hold excessive access with minimal governance.