How do I give an AI agent its own identity and authenticate it to downstream services?

To give an AI agent its own identity and authenticate it to downstream services, it is crucial to establish a clear identity for each agent and manage its access through a secure harness that integrates identity, context, and intent. This involves using token exchange for derived agent credentials and short-lived, narrowly scoped capability tokens for downstream services.

Here are concrete controls for managing AI agent identity and authentication:

• Establish a clear agent identity: Every agent must have a defined identity that specifies what it represents, its delegated authority, and its permitted scope of action. This identity should be consumed from an enterprise Identity Provider (IdP) via OIDC/SAML with token exchange to derived agent credentials. This addresses the NIST AI RMF function of Govern.
• Implement continuous agent posture management: Rather than static identity assignment, continuously inventory agents, map their tool and data access relationships, and identify over-permissioned agents as their access changes. This ongoing process adapts as agents integrate into new business tools, data access patterns evolve, and organizational policies change. This helps mitigate the OWASP LLM Top 10 risk of LLM07: Excessive Agency.
• Utilize short-lived, narrowly scoped capability tokens: For every consequential action, bind the workload identity, delegated user identity, active intent token, and a per-action capability token. This capability token, which passes to downstream services, should be short-lived, narrowly scoped, and embed the intent ID. This helps prevent privilege escalation through tool composition and confused deputy scenarios.
• Employ token exchange for delegated credentials: Avoid passing user credentials directly to the agent. Instead, use token exchange to obtain narrower, delegated credentials. This maintains delegation hygiene and reduces credential exposure.
• Authenticate calling agents to MCP servers: Model Context Protocol (MCP) servers, which expose tool capabilities to agents, must authenticate calling agents, as anonymous MCP is not suitable for sensitive operations. This addresses the NIST AI RMF function of Protect.
• Implement mutual authentication for agent-to-agent interactions: For agent-to-agent (A2A) protocols, mutual authentication is necessary, along with capability attenuation and monitoring for unusual agent-to-agent patterns. This helps mitigate the OWASP LLM Top 10 risk of LLM07: Excessive Agency and addresses the NIST AI RMF function of Protect.
• Issue cryptographically signed transaction tokens for cross-trust boundary calls: When an agent call crosses a trust boundary, issue a short-lived, cryptographically signed transaction token that carries the user's verified identity, the agent chain, and the session's original declared intent. Receiving services should validate calls against this intent without re-authenticating the upstream identity, closing the "Confused Deputy" gap. This addresses the NIST AI RMF function of Protect.