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Glossary
AI agent detection is the ability to identify when an AI agent is interacting with a system and to judge whether it is a legitimate, authorized agent or a malicious or hijacked one. It extends beyond traditional bot detection, because the goal is no longer to block all automation but to tell good agents from bad.
Classic bot detection asks whether traffic is automated. Agent detection has to go further and ask whose agent it is and whether it is behaving within bounds.
AI agent detection draws on signals about the agent’s identity (is it a recognized, authorized agent bound to a real user?), its authorization (is it doing only what it is permitted to?), and its behavior and intent (does its activity match a legitimate task, or show signs of hijack or malice?). Because a sanctioned agent and a malicious one can both look like fast, capable automation, intent and authorization, not just "is this a bot," are the deciding signals.
As agents begin to browse, transact, and act for customers, businesses need to welcome legitimate agents while stopping malicious ones. Blocking all agents loses the customers who use them; allowing all agents invites agentic fraud. AI agent detection is what makes the middle path possible, and it is an emerging capability, closely tied to agent identity, delegated authority, and agentic-fraud defense. Platforms built for the agentic era, like Mosaic, are introducing detection aimed specifically at anticipating malicious agent intent.
What is AI agent detection?
Identifying when an AI agent is acting and judging whether it’s authorized or malicious.
How is it different from bot detection?
Bot detection asks if traffic is automated; agent detection asks whose agent it is and whether it’s acting within bounds.
What signals does it use?
Agent identity, authorization scope, and behavioral/intent signals, since good and bad agents both look like capable automation.
Related: AI Agents / Agentic AI · Agentic Fraud · AI Agents vs. Bots · Agent Identity · Bot Detection
