AI agents operating in security-sensitive environments generate telemetry, command patterns, and execution traces that are forensically indistinguishable from attack activity, causing legitimate remediation to trigger defensive systems. Current agent frameworks produce no defender-identifiable execution signatures, and no industry standard exists for agents to cryptographically or structurally assert their identity and intent to security tooling. This gap means agents and human defenders are blind to each other, compounding incident response failures.

AI agents performing legitimate operations (patching, remediation, scanning) trigger SIEM alerts, EDR quarantines, and SOC escalations because their behavior is indistinguishable from attacker TTPs — wasting thousands of analyst hours and blocking autonomous ops.

Security engineering leads at mid-to-large enterprises deploying AI agents for IT operations, DevSecOps, or incident remediation alongside CrowdStrike/Sentinel/Splunk stacks.

Enterprises already pay heavily for SOAR, allowlisting, and false-positive triage; this directly eliminates a new and growing class of false positives that scales with agent adoption — and no incumbent addresses agent-specific identity attestation.

MVP: an open-source sidecar that wraps agent processes with a signed execution manifest (agent ID, intent declaration, expected actions, TTL) queryable by SIEM/EDR via a lightweight API; ship integrations for 2-3 top security platforms (Sentinel, Splunk, CrowdStrike) and 2-3 agent frameworks (LangChain, CrewAI, AutoGen).

Subset of the $18B SIEM/SOAR market; even capturing coordination-layer spend for the ~40% of enterprises piloting agentic automation suggests a $1B+ wedge within 3 years.