Enhance Agentic Security with Runtime Protection
Agentic AI represents a new class of digital insider — one that existing security tools were never designed to secure. This document describes the technical approach and system architecture behind Cogility's Agentic Security and Behavioral Enforcement solution, which extends two decades of insider-risk taxonomy to agentic systems. Cogynt.ai pairs two complementary decision systems: the Edge component performs deterministic policy checks in sub-millisecond time — deciding whether to forward, redact, block, or escalate while the Enterprise component runs continuously in the background, correlating activity across sessions and actors to transform behavioral patterns for complete visibility of human and agent activity.
Why Point-in-Time Evaluation Isn’t Enough
A meaningful body of research shows that deception and misalignment can often be caught in a single turn. Scenarios such as internal activation probing, outcome-property tests, and architecture exploiting traps all achieve strong single-turn results. But every snapshot method shares the same structural blind spot: each evaluates a system at one moment, under one set of conditions. Even a very high catch rate leaves a meaningful residual miss rate and every snapshot method is blind to sequences of behavior.
Read the fact sheet to learn more.