Treat the registry as discovery and lifecycle visibility, and treat Entra Agent ID as the enforcement layer for authentication and permissions. The two controls answer different questions, so governance needs separate ownership, separate evidence, and separate response paths. If teams collapse them into one process, blocked agents, disabled identities, and registry-only agents will be misclassified.
How should teams separate registry governance from enforcement governance?
The core governance mistake is treating “the list of agents” and “the identity that can act” as the same control. The registry is best used for discovery, ownership, and lifecycle visibility, while the enforcement plane decides whether an agent can authenticate, obtain permissions, and keep them. That split matters because a complete inventory does not guarantee a valid runtime identity, and a valid runtime identity does not guarantee the registry is current.
Teams should define the registry as the system of record for intake, ownership, status, and retirement, then define the identity system as the authority for sign-in and authorization. That separation makes it easier to detect shadow agents, blocked agents, orphaned entries, and active identities that were never fully registered. It also keeps audit evidence from becoming ambiguous when an agent is disabled in one plane but still visible in the other.
In practice, the registry should answer “what exists, who owns it, and what stage is it in?” The identity layer should answer “what is this agent allowed to prove, request, or execute right now?” Once teams make that distinction explicit, approval workflows, offboarding, and exception handling stop colliding. For agent identity lifecycle detail, see Agentic AI Identity Guide.
Where do ownership and evidence usually go wrong?
Split-control governance fails when one team owns discovery but another owns enforcement, yet neither is asked to reconcile the two views. The registry team may close a ticket because the agent is catalogued, while the identity team may disable access without removing the registry record. Both outcomes can look “resolved” locally while the overall control posture remains inconsistent.
Evidence has to be separate as well. Registry evidence should show registration state, owner, purpose, and review cadence. Enforcement evidence should show authentication method, permission scope, and whether access is active, suspended, or expired. If a team only retains one class of evidence, incident response will struggle to tell whether an agent was merely discovered, actually empowered, or already remediated.
Teams also need a clear rule for which system wins during conflicts. If the registry says an agent exists but the identity plane has no live entitlement, treat it as discovered but non-operational. If the identity plane shows active permissions but the registry has no approved record, treat it as an unmanaged runtime exception. The distinction is operationally important because it determines whether the fix is cleanup, access removal, or both. For governance and inventory discovery patterns, compare this with Shadow AI and AI Agent Discovery Guide.
What operating model keeps split controls from creating blind spots?
The cleanest model is a two-lane process with one intake path and one enforcement path. Intake creates the registry record, assigns ownership, and confirms why the agent exists. Enforcement then issues, constrains, or revokes the ability to act. Reviews should be synchronized, but the controls should not be merged into a single approval checkbox because discovery and authorization age at different speeds.
This becomes especially important when agents are blocked, disabled, or partially retired. A blocked agent may still appear in the registry, and a registry-only agent may still be waiting for enforcement to be granted. If teams do not classify those states separately, they will misread a disabled identity as a removed agent, or a registered agent as an approved one. The result is weak operational hygiene and bad reporting.
A sound operating model also defines escalation paths. Registry anomalies should go to the team that manages ownership and lifecycle. Enforcement anomalies should go to the team that manages sign-in, permissions, and revocation. When a single queue handles both, the ticket may be “closed” without anyone confirming that the agent can still act. For runtime control and permission design, use AI Agent Authorisation Guide.
Risk and Threat Considerations
Split inventory and identity controls create a classic governance gap: the organisation can know an agent exists without knowing whether it can still authenticate and perform actions, or it can revoke access without removing the registry record. That mismatch increases the chance of unmanaged runtime access, stale approvals, and false confidence during reviews.
Failure mechanism: Control teams reconcile the wrong object, so discovery state and enforcement state drift apart. An attacker, or simply an over-permissioned workflow, can exploit that drift by using an identity that remains active after the registry has been updated, or by hiding inside a registry-only record that was never fully governed.
Impact: The organisation may miss unauthorized action, mis-handle incident response, or leave orphaned access paths in place. Over time, the mismatch increases blast radius because blocked agents, disabled identities, and unregistered live agents are all likely to be classified incorrectly.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10 addresses the attack surface, NIST SP 800-53 Rev 5 and NIST CSF 2.0 set the technical controls, and ISO/IEC 27001:2022 defines the regulatory obligations.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | Agent registries and runtime identities depend on lifecycle control of authenticators and revocation. |
| AC-2 — Account Management | The question concerns governing which agent identities exist and which are active. | |
| AC-6 — Least Privilege | The enforcement layer must constrain what an authenticated agent can do. | |
| Recommendation — Manage agent credentials with rotation, revocation, and expiration rules that match lifecycle status. Keep account status authoritative and reconcile active, suspended, and disabled agent identities. Limit each agent to the minimum permissions needed for its approved purpose. | ||
| NIST CSF 2.0 | GV.OC-03 — Legal, Regulatory, and Organizational Requirements | Split ownership between registry and identity control requires clear governance accountability. |
| ID.AM-01 — Physical devices and systems within the organization are inventoried | The registry is functioning as an inventory and discovery control for agents. | |
| Recommendation — Define ownership and accountability for discovery, approval, and enforcement controls. Maintain an accurate agent inventory with ownership and status metadata. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Misaligned registry and enforcement controls can leave agents overprivileged or misclassified. |
| Recommendation — Enforce separate authorization checks so agent identity and privilege cannot drift. | ||
| ISO/IEC 27001:2022 | A.5.9 — Inventory of information and other associated assets | The registry is an asset inventory and lifecycle visibility mechanism for AI agents. |
| A.5.15 — Access control | Entra Agent ID is the enforcement layer for authentication and permissions. | |
| Recommendation — Keep the agent registry current and tied to accountable ownership. Use access control to enforce runtime permissions independently of registry status. | ||
Practitioner Guidance
What to prioritise: Decide which team owns discovery, which team owns enforcement, and which system is authoritative for each decision. If that split is not documented, every downstream review will be ambiguous.
What to verify: For each agent, verify the registry record, the live identity state, and the current permission set against each other. If those three views do not align, treat the discrepancy as a control failure rather than a paperwork issue.
Decision rule: If the registry says an agent exists but the identity plane cannot authenticate it, treat it as dormant or blocked; if the identity plane can still act but the registry has no approved record, treat it as unmanaged and escalate immediately.
Practitioner takeaway: Good governance for ai agents is not one control with two names, it is two controls with a reconciliation rule, so that lifecycle visibility and runtime authority never get confused.
Related resources from NHI Mgmt Group
- How should security teams govern API keys used for generative AI access?
- How should security teams govern AI agents that use multiple identity layers?
- How should IAM teams govern AI agents as identity programmes mature?
- How should security teams govern identity observability across humans, workloads, and AI agents?
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Reviewed and updated by the NHIMG editorial team on October 13, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org