Autonomous launches endpoint security platform for AI agents

Autonomous Security has introduced a complete security platform purpose-built for AI agents operating on enterprise endpoints. The product addresses what the company identifies as a fundamental blind spot in traditional cybersecurity: endpoint security tools designed for human users and conventional applications cannot see or control the behavior of autonomous AI agents.

The core problem, as Autonomous frames it, is that employees are deploying unvetted agentic capabilities—including MCPs (model context protocols) and skills—without central approval or visibility. Agents pose distinct risks because they can execute actions autonomously, without explicit human approval, and can operate even without malicious intent from the user. A single compromised MCP server or plugin effectively opens a backdoor into the enterprise network. Additionally, agents accumulate unmanaged credentials and permissions, directly accessing core enterprise systems while continuously utilizing sensitive corporate data and source code—creating both access-control and data-leakage risks. Prompt injection attacks or off-script agent behavior can escalate into full enterprise breaches in the absence of inline controls.

Autonomous's solution is structured around three integrated layers. The governance plane defines what agents are allowed to do and enforces policy at runtime. The platform automatically maps all AI assets and uncovers hidden risks in 10 minutes, allowing security teams to discover shadow AI and assess risks across endpoints. It secures over 50 popular AI agents. The control layer manages various activity operations, tools, MCP servers, and authentication methods. The platform automates approvals of prompts, command shells, and tools based on security risk assessment. It integrates with existing enterprise infrastructure including SSO/SCIM (identity management), SIEM (security information and event management), and enterprise compliance requirements, centralizing policy and audit across all agentic activity. The company is located at 135 W. 50th St. Suite 200, New York, NY 10020.

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).

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