AI agent identity breaks down when agents authenticate across OAuth, API keys and managed identities simultaneously. Learn why single-protocol solutions fail.
Instead of duplicating accounts or sharing credentials, one identity system can validate identities issued by another and grant access based on that trust.
While companies pour resources into securing employee accounts with MFA, zero trust and regular access reviews, service accounts still get created with static credentials, granted sweeping permissions and then left unmanaged. This creates a growing population of identities that operate outside traditional IAM controls.
OAuth is an authorization framework that defines how to grant access. JWT is a token format that defines how to package and transmit claims. They solve different problems, and most production systems use both.
AI agent identity security is the set of practices and controls that treat AI agents as distinct, governable identities with their own authentication, authorization and audit requirements.
Zero-trust architecture is a security framework built on a simple premise: no user, device or workload should be trusted by default, regardless of where it sits on the network.
Agentic AI guardrails are the technical controls, policy frameworks, and oversight mechanisms that define what an AI agent can do, what it can access and when it needs to stop and ask a human.
Discover verifiable agentic AI deployments in software, security, IT Ops, and logistics. Learn the essential security, identity, and governance patterns for safe production use.
As agents scale and operate continuously, MCP servers are becoming long-lived access intermediaries, concentrating privilege in ways security teams have already struggled to contain.
