Agent Identity Security: Authentication, Authorization, and Trust in AI Systems

Agent identity security is a critical discipline focusing on the authentication and authorization of AI systems, ensuring that actions performed by agents align with their intended purpose and are authorized within the correct workflow context. This requires a clear distinction between workload identity, which authenticates a software's runtime using cryptographic credentials like SPIFFE/SVID, and agentic identity, which includes details about the delegating human, task scope, session, and declared intent. Effective security practices involve using standards like OAuth to issue narrow, short-lived, and resource-specific tokens, preventing broad access and potential misuse by unauthorized entities. Prompt injection is highlighted as an authority confusion problem, where untrusted text can lead an agent to perform unintended actions if data and authority are not properly separated. Multi-agent systems need careful management to prevent cascading trust attacks, requiring explicit delegation chains and reduced authority at each step. The operational security model should include detailed audit logs that reconstruct authority paths, and authorization must be enforced at runtime, considering dynamic factors like task, tenant, and resource context, rather than relying solely on static RBAC models.