How Impersonation and Delegation Break in Today’s CIAMs for AI-Native Use Cases

Customer Identity and Access Management (CIAM) solutions like Auth0, Firebase Authentication, Okta Customer Identity, and others have revolutionized how businesses manage user authentication and authorization. They excel at providing secure, scalable, and user-friendly login experiences for human users, along with robust API security for applications acting on their own behalf.

However, the rise of autonomous AI agents introduces a profound challenge: how do these agents act on behalf of a human user, or even another machine, within the existing CIAM framework? The concepts of impersonation and delegation, while present in some forms, often break down when applied to the highly dynamic, granular, and auditable requirements of agent-based systems.

The Mismatch: Agent Delegation vs. CIAM Capabilities

Current CIAMs are primarily designed around two core paradigms:

1. User Authentication: A human user logs in and gets a token representing their identity.

2. Application Authentication (M2M): An application uses its own credentials to access resources on its own behalf.

The problem arises when an AI agent needs to perform an action that is authorized by, and attributed to, a specific human user. This isn't just about the agent having its own access; it's about the agent temporarily assuming the permissions and context of another entity.

Here's how current CIAM approaches often fall short:

• Limited Delegation Models: While some CIAMs offer delegated authorization (e.g., OAuth 2.0 on_behalf_of flows), these are often designed for specific scenarios like a backend API calling another API with user context. They rarely provide the fine-grained, ephemeral control needed for an AI agent that might interact with multiple services, performing varied actions, all under a single user's delegated authority.

• No Native Agent Identity Primitive: CIAMs typically don't have a first-class concept of a "machine agent" that can dynamically assume different identities or scopes. Agents are often treated as just another "client," leading to the same issues of over-permissioning and static credentials discussed previously.

• Audit Trail Obfuscation: When an agent uses a generic application token, or even a token derived from a user, it's hard to distinguish in the audit logs that it was an agent acting, rather than the original user directly. This makes forensic analysis, compliance, and debugging significantly more difficult. "Who actually performed this action?" becomes an unanswerable question.

• Impersonation Challenges: True impersonation – where an agent temporarily becomes a user with all their permissions – is incredibly risky if not tightly controlled. Existing CIAMs might offer administrative impersonation tools, but these are not designed for programmatic, dynamic agent use cases where an agent needs to impersonate a specific user for a single transaction.

• Token Lifespan and Revocation: If an agent receives a token that represents a user's delegated authority, that token often inherits the user's token lifecycle. This can mean long-lived tokens that pose a risk if the agent is compromised or its task is completed. Rapid, fine-grained revocation of a specific agent's delegated token (without affecting the user's other sessions) is often not supported.

• Policy Enforcement Complexity: Applying user-specific access policies to actions performed by agents acting on their behalf becomes incredibly complex. How do you ensure that an agent only accesses data that the delegating user is authorized to access, even if the agent itself has broader permissions?

The Path Forward: Designing Auth for AI-Native Use Cases

Organizations evaluating whether their current CIAM can support their AI initiatives need to ask critical questions:

• Can our CIAM issue short-lived, precisely scoped tokens for individual agent instances?

• Does it natively support the concept of an agent acting "on behalf of" a specific user, with clear attribution?

• Can we revoke an agent's delegated authority instantly, without impacting the original user's session?

• Does the audit trail clearly differentiate between user-initiated actions and agent-delegated actions?

Without these capabilities, integrating AI agents into your existing authentication infrastructure will lead to security gaps, compliance headaches, and significant operational overhead. The future of CIAM must evolve to embrace "agent identity" as a first-class citizen, recognizing that autonomous agents require a fundamentally different approach to delegation and impersonation than traditional human or application users.

Understand the core differences and why agent identity is the necessary evolution for modern authentication.