Keeper Security Brings Autonomous AI Agents Under Endpoint Governance

Most current security frameworks rely on the Model Context Protocol to manage AI, leaving any actions taken outside that specific layer invisible to administrators. Keeper Security aims to bypass this architectural limitation by shifting governance directly to the operating system. By monitoring activity at the machine level, the platform can block or approve an agent's attempt to invoke local shells, access sensitive files, or elevate privileges, regardless of the path the agent uses to execute.

According to CEO Darren Guccione, the industry currently faces a critical security blind spot, as many organizations treat AI tools as simple assistants rather than autonomous principals. Keeper’s solution detects both known agents—such as GitHub Copilot and Claude Code—and unidentified software through a proprietary scoring algorithm. Once detected, administrators apply granular policies to control which agents run, what data they touch, and how they request administrative rights.

This update introduces a monitor-first lifecycle, allowing security teams to observe agent behavior before transitioning to active enforcement. By unifying audit trails for both human and machine identities, the platform provides a single source of truth for compliance reporting, specifically helping firms operationalize the NIST AI Risk Management Framework. The governance features are available immediately as part of the KeeperPAM platform or as a standalone addition to the Endpoint Privilege Manager.