Agentless endpoint controls that classify AI agents and enforce policy on their actions

Bay Security's position is that detection and response is the wrong default for AI agents on the endpoint. An agent that has already read a credential file or pushed to a repository cannot be usefully alerted on afterwards, and the alert itself carries little meaning without knowing which agent acted, under whose session, and what it was asked to do. Bay instead classifies the AI tools present on a device automatically and derives the policy that should apply to each, building a contextual entity graph that records an agent's identity, the credentials it can reach, its configuration, and its patterns of system access.

Discovery and posture work covers shadow AI installed outside IT's knowledge, exposed credentials, and risky configurations, with the company citing more than 160 distinct alert types. Activity monitoring captures the full execution chain, so an action can be traced from the originating prompt through to the command that ran on the system. Enforcement is session-aware: each action is evaluated against the acting identity, the session's prior behaviour, and the data in scope, and resolved as allow, ask, or deny before execution rather than after. Deployment is agentless, integrating with the EDR and MDM tooling an organisation already operates instead of adding another endpoint agent, and the company reports SOC 2 and ISO 27001 certification.