Autonomous launches endpoint security platform for AI agents

The emergence of Autonomous Security reflects a widening gap in enterprise security infrastructure. Traditional endpoint detection and response (EDR) and endpoint protection platforms were designed to monitor human and application behavior—not the autonomous, tool-executing, credential-accumulating actions of AI agents. As enterprises adopt agentic AI systems (AI agents that can autonomously decide what tools to use and execute actions), employees are deploying unvetted agents and MCPs without central oversight, creating what Autonomous calls "shadow AI" blind spots. The body identifies a critical escalation pathway: a single compromised MCP server, skill, or plugin can become a backdoor; a single prompt injection or off-script agent behavior can trigger a full enterprise breach. Agents also accumulate unmanaged credentials and permissions, expanding attack surface while continuously accessing sensitive corporate data and source code.

Autonomous's three-layer control stack—governance, control, and runtime enforcement—directly addresses these threats by making agent activity visible and governable at the endpoint. The ability to discover shadow AI in 10 minutes and centralize policy across identity, audit, and agentic activity suggests the platform is positioned to help security teams move from a reactive posture (finding threats after deployment) to a proactive one (enforcing what agents are allowed to do before they execute).