ADR: An Agentic Detection System for Enterprise Agentic AI Security
We present the Agentic AI Detection and Response (ADR) system, the first large-scale, production-proven enterprise framework for securing AI agents operating through the Model Context Protocol (MCP). We identify three persistent challenges in this domain: (1) limited observability -- existing Endpoint Detection and Response (EDR) tools see file writes but not the agent reasoning, prompts, or causal chains linking intent to execution; (2) insufficient robustness -- static defenses constrained by pre-defined rules fail to generalize across diverse attack techniques and enterprise contexts; and (3) high detection costs -- LLM-based inference is prohibitively expensive at scale. ADR addresses...
| Authors | Chenning Li, Pan Hu, Justin Xu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 17 May 2026 |
| Last updated at source | 17 May 2026 |
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