An AI agent needs its own identity — separate from the human who deployed it and separate from the application that calls it — so that every action it takes can be attributed, audited, and revoked without touching anything else. Without that, you cannot answer basic governance questions: which agent did this, under whose authority, and can it still act right now? This article covers the identity modeling layer; for the authentication mechanics that sit on top of it, see how to authenticate AI agents. For a zero-trust framing of why per-agent identity is foundational to the broader security model, see zero trust for AI agents.
Why Human Identity Is the Wrong Model
Most teams start by giving agents the same credentials a human uses: a shared API key, a service account, or a forwarded user token. It works initially, but the problem surfaces the moment you need to answer an incident question or rotate a compromised secret.
Human and shared credentials are designed around a single principal with a known session duration. Agents operate differently. A single agent may run thousands of concurrent tasks, delegate sub-tasks to other agents, and run indefinitely without a human session to anchor it. When something goes wrong, shared service account logs give you no useful signal — you cannot distinguish the agent's actions from those of other systems using the same credential.
This is a structural problem that affects attribution, least-privilege enforcement, and your ability to contain a misbehaving agent without disrupting unrelated systems.
What First-Class Agent Identity Looks Like
Giving an agent a first-class identity means treating the agent itself as a principal in your access control model, not as an extension of a human or application. Three properties define a first-class agent identity.
Uniqueness. Each agent instance has credentials that belong to it alone. No sharing across agent types, no reuse across environments. When you see a credential in a log, you know exactly which agent used it.
Scoping. The identity carries a declared set of permissions — what services the agent may call, what data it may read or write, what tools it may invoke. That scope is expressed in the credential itself or enforced at the point of issue. An agent registered for customer-support tasks cannot acquire the permissions of a data-pipeline agent even if both use the same underlying platform.
Revocability. The credential can be invalidated instantly, affecting only that agent, without rotating secrets for other agents or services. Revocation is meaningful only if the identity is unique: a shared credential cannot be selectively revoked.
Credential Patterns That Work for Agents
Several credential patterns are compatible with first-class agent identity. They differ in the trust they confer and the operational overhead they require.
Client credentials (client ID + secret). The agent authenticates to a token endpoint using a registered identifier and a secret, and receives a short-lived access token. This is the OAuth 2.0 client credentials flow adapted for machine principals. It works well when the agent operates synchronously and can re-authenticate on a regular interval. The secret must be stored in a secrets manager, never in source code, and rotated on a defined schedule.
Asymmetric key pairs. The agent holds a private key; the platform stores and trusts the corresponding public key. Authentication is a signed assertion rather than a transmitted secret. This eliminates the risk of the shared secret being intercepted in transit and is the basis for standards such as JWT-based client authentication (RFC 7523). Asymmetric credentials are particularly useful when an external auditor or certification body needs to attest to an agent's behavior, because the attestation itself can be cryptographically signed and verified later.
Short-lived capability tokens. The agent receives a token scoped to a specific task, with a narrow expiry and a bounded permission set. Even if captured, its usefulness is limited to the issuance window. This pattern suits agents that operate in untrusted environments or interact with high-sensitivity services.
Rotating API keys with tight TTLs. API keys issued per agent and refreshed automatically before expiry. Less expressive than OAuth flows but operationally straightforward for teams without a full token-issuance pipeline.
These patterns are not mutually exclusive. A production deployment might use client credentials for baseline identity, short-lived capability tokens for elevated-privilege tasks, and key-pair attestations as a third-party verification layer.
Modeling Identity So Actions Are Attributable
Attribution requires that the identity is carried through the full request chain and recorded durably.
Every action an agent takes should carry the agent's identifier in the audit record — not the user's, not the application's. When an agent calls a downstream service, the agent identity should be propagated in the request headers so the downstream service records who actually made the call.
In agent-to-agent scenarios, the delegation chain needs to be represented. A flat audit log that records only the leaf agent loses the lineage. The right model records the full chain: human → application → orchestrating agent → sub-agent → action. This delegation structure is also the primary attack surface covered in threat model: agent-to-agent delegation abuse.
This has security value beyond attribution. You can walk the chain to identify which link introduced bad behavior, and express policy in terms of the chain — for example, permitting an action only when the orchestrating agent meets a trust threshold and the sub-agent was registered by the same organization.
Trust Scores as a Dynamic Layer on Top of Identity
Static credentials answer "is this agent allowed to act at all?" Dynamic trust signals answer "how much confidence do we have in this specific agent right now?"
A trust score aggregates signals across multiple dimensions: how consistently the agent has behaved against its declared purpose, whether it has generated policy violations or guardrail hits, whether its credential posture is current, and whether third parties have attested to its behavior. The score produces a level — from untrusted through to fully trusted — that dispatch and policy gates can consume. The trust scores and attestations post explains how these signals are weighted and how external attestations are verified.
An agent that starts behaving anomalously — making unusual tool calls, generating a spike in guardrail violations, or reaching outside its declared scope — will have its trust score fall before a human notices. Policy gates that consume the score can reduce permissions or pause task delivery automatically.
Third-party attestations feed external evidence into the score. An auditor signs an attestation covering a specific aspect of the agent's behavior, and the platform verifies the signature against a set of trusted signer keys before incorporating that evidence. The trust signal is not purely self-reported.
Praesidia combines these layers: a registered agent principal with scoped credentials, a computed trust score built from behavioral and attestation signals, and enforcement of both the static identity check and the dynamic trust level before any task is assigned.
Revocation Without Collateral Damage
Revocation is where unique, scoped identity delivers its clearest value. When an agent's credentials are compromised, you need to invalidate only that agent's credentials, stop it from receiving new tasks immediately, optionally drain or terminate in-flight work depending on severity, and preserve the audit record for post-incident review.
None of these steps work if identity is shared. With a unique principal, each step is a targeted operation and the blast radius is bounded by the credential's scope.
Credential rotation — proactively changing a valid credential before compromise — is a related discipline. Short-lived tokens handle this automatically. For longer-lived secrets, automated issuance on a defined cadence keeps the exposure window predictable without manual intervention.
Putting It Together: An Identity Design Checklist
Before you register an agent for production use, work through these questions.
| Question | Why it matters |
|---|---|
| Does this agent have its own registered principal, separate from any human or service account? | Attribution and selective revocation both depend on it. |
| Is the credential scoped to the minimum set of services and permissions this agent needs? | Least privilege limits blast radius if the credential is misused. |
| What is the credential TTL, and is rotation automated? | Long-lived, manually-rotated credentials are a liability. |
| Is the agent's identity propagated through every downstream call it makes? | Without propagation, the audit trail breaks at the first hop. |
| Is there a mechanism to revoke the credential immediately, and have you tested it? | Untested revocation is not a real control. |
| Is the agent's trust level checked at dispatch, or only at registration? | Behavioral drift after registration is the common failure mode. |
Not every question needs to be resolved on day one. A low-risk internal agent with read-only access can start with a simpler model. Requirements harden as the agent's access to sensitive data or consequential actions grows.
Common questions
Can I use an existing service account for my agents instead of creating new principals?
You can, but the problems compound as you scale. Shared service accounts lose attribution, accumulate permissions across all agents using them, and make revocation disruptive for every consumer. The operational cost of issuing separate credentials per agent is lower than it appears, particularly when your platform supports programmatic registration.
How is agent identity different from API key management?
API key management focuses on issuing and rotating credentials for applications. Agent identity extends that with a richer principal model: a registered agent has a declared purpose, a scope of permitted actions, a behavioral history, and a trust level derived from that history. An API key is a secret; an agent identity is a durable principal that a key is one part of. The distinction matters for governance: you can query the identity record to understand what an agent is supposed to do, not just whether its key is valid.
How do I handle agents that call other agents?
Agent-to-agent calls require that both sides of the call have registered identities and that the call carries the identity of the calling agent (not just a generic service credential). The receiving agent or its platform should verify the caller's identity and check that the calling agent is authorized to delegate to it. The full delegation chain — from the originating authority down to the leaf action — should appear in audit records. See agent-to-agent communication, governed for how A2A credential verification and delegation logging work in practice.