A registry is a structured control record for AI agents that captures identity posture, trust signals, and governance metadata before production approval. In practice, it turns agent review into a repeatable decision process rather than a one-off judgment based on vendor claims or informal owner knowledge.
Expanded Definition
An Agent trust registry is the governance record that sits between agent development and production use. It captures an AI agent’s identity, owner, intended scope, tool permissions, approved data access, risk rating, and review status so trust is based on evidence rather than assertion. In NHI and agentic AI programs, this is distinct from a simple inventory because the registry is meant to support control decisions, not just discovery.
Usage in the industry is still evolving, and definitions vary across vendors. Some treat the registry as part of an agent lifecycle platform, while others place it inside IAM, GRC, or secrets governance workflows. The practical NHI lens is closer to OWASP Agentic AI Top 10 and NIST AI Risk Management Framework thinking: an agent should not be trusted because it exists, but because its identity posture and controls are continuously evidenced.
The most common misapplication is using the registry as a naming database, which occurs when teams record agent labels without validating permissions, ownership, or revocation paths.
Examples and Use Cases
Implementing an Agent Trust Registry rigorously often introduces approval and upkeep overhead, requiring organisations to weigh faster deployment against stronger control, traceability, and revocation discipline.
- A customer-support agent is added to the registry only after its tool calls, data scopes, and escalation limits are reviewed against business justification.
- A coding agent is blocked from production until the registry shows approved repository access, secret handling rules, and a named human owner for rollback decisions.
- A procurement agent is re-certified quarterly after its integration list changes, with the registry capturing new APIs, data classes, and exception approvals.
- A high-risk agent is flagged because the registry shows no revocation workflow, echoing patterns seen in the Moltbook AI agent keys breach and related NHI compromise cases.
- A platform team maps registry fields to external controls using the CSA MAESTRO agentic AI threat modeling framework to standardise intake and review.
NHIMG’s Ultimate Guide to NHIs — 2025 Outlook and Predictions reports that 90% of IT leaders say properly managing NHIs is essential for successful zero-trust implementation, which is why registries increasingly function as the intake gate for agents that can act, call tools, and touch secrets.
Why It Matters in NHI Security
An Agent Trust Registry matters because agents often inherit real access before they earn real trust. Without a structured registry, organisations lose sight of which agent can use which credentials, which data paths are approved, and which human remains accountable when behavior changes. That failure is especially dangerous in environments where secrets are embedded in code, CI/CD, or workflow tools, because registry gaps can turn a routine deployment into an access sprawl event.
NHIMG reports that only 5.7% of organisations have full visibility into their service accounts, a reminder that agent governance collapses quickly when identity records are incomplete or stale. The registry becomes the operational anchor for detection, review, and shutdown, especially when paired with NIST AI Risk Management Framework practices and the OWASP NHI Top 10 governance model for agent controls.
Organisations typically encounter the need for an Agent Trust Registry only after an agent is over-privileged, misused, or impossible to revoke cleanly after an incident, at which point the registry becomes operationally unavoidable to address.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-02 | Addresses improper secret and identity governance for non-human workloads. |
| OWASP Agentic AI Top 10 | Covers agent lifecycle, tool access, and governance risks in agentic systems. | |
| NIST AI RMF | Frames AI risk identification, mapping, and monitoring for governed deployment. |
Record each agent’s ownership, scope, and secret access, then block production until controls are verified.
