User access reviews break when access changes faster than the review cadence. They can confirm a historical state, but they cannot prevent ephemeral access, delegated machine actions, or short-lived privilege escalation from being used before the review happens. In modern environments, that makes UARs a validation artifact, not a control mechanism.
Why User Access Reviews Fail as the Main Control
User access reviews are useful for governance, but they are a weak primary control when identities, permissions, and execution paths change faster than a review cycle. That is especially true for NHIs, API keys, service accounts, and agentic systems, where access is often delegated, ephemeral, or hidden in automation. NHI Mgmt Group notes that only 5.7% of organisations have full visibility into their service accounts in the Ultimate Guide to NHIs, which makes retrospective review a poor substitute for live control.
The core problem is timing. A review can confirm what was assigned last month, but it cannot stop a token, key, or delegated workflow from being used today. The same gap appears in agentic AI, where an autonomous system may chain tools, request new privileges mid-task, and complete a harmful action long before the next certification happens. Guidance from the OWASP Non-Human Identity Top 10 treats excess privilege, poor visibility, and weak lifecycle control as active risk conditions, not audit findings. In practice, many security teams discover over-privilege only after a credential has already been used in production, rather than through a clean review outcome.
What Actually Breaks in Real Environments
When user access reviews are treated as the main identity control, several operational failures show up quickly:
- Ephemeral access is invisible, because the privilege exists for minutes or hours, not long enough to be meaningfully reviewed.
- Delegated machine actions are misclassified as user access, even though the risk is in the service account, token, or workflow behind the action.
- Access creep accumulates between review cycles, especially in CI/CD, cloud automation, and agent-to-tool integrations.
- Remediation is delayed, because reviews identify stale access after the fact instead of revoking it at the point of use.
Effective practice is moving toward runtime control: workload identity for the thing that is actually acting, short-lived secrets, and policy decisions made at request time. That aligns with the NIST AI Risk Management Framework, which emphasises governance, mapping, and measurement rather than relying on periodic attestations alone. In agentic environments, the more relevant question is not who reviewed access last quarter, but whether the system can prove its identity and receive the minimum permission needed for the current task. For implementation, the operational pattern is JIT issuance, automatic expiry, and policy-as-code checks against context such as workload, action, destination, and time. NHIMG research on LLMjacking: How Attackers Hijack AI Using Compromised NHIs shows how quickly exposed credentials are abused in the wild, which is why review-based control cannot be the last line of defense.
These controls tend to break down when the environment mixes human approvals, machine autonomy, and long-lived secrets in the same access path, because reviewers cannot see the effective privilege chain end to end.
Where Review-Centric Governance Still Helps, and Where It Does Not
Tighter review processes often increase administrative overhead, so organisations must balance governance evidence against real-time risk reduction. User access reviews still matter for accountability, especially for human roles, segregation-of-duties checks, and attestation of privileged ownership. Best practice is evolving, but there is no universal standard that says reviews alone can provide sufficient control for autonomous or machine-mediated access.
For NHIs, the control boundary should shift earlier in the lifecycle. The NHI Lifecycle Management Guide is the better operational model: issue identity deliberately, scope it narrowly, rotate or revoke it quickly, and remove it when the workload ends. The OWASP Non-Human Identity Top 10 and the broader NHI guidance from Ultimate Guide to NHIs both point toward the same conclusion: reviews are a supporting governance activity, not the mechanism that prevents misuse. Review-centric models also struggle in third-party integrations, multi-agent workflows, and high-churn cloud estates where access changes faster than committee cadence. In those cases, the practical answer is continuous validation, not periodic confirmation.
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 CSA MAESTRO 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-03 | Directly addresses overlong-lived NHI credentials and poor lifecycle control. |
| NIST AI RMF | AI RMF fits autonomous systems that need runtime governance, not just attestation. | |
| CSA MAESTRO | MAESTRO covers agentic control gaps where access must be evaluated dynamically. |
Replace review-only control with short-lived NHI issuance, rotation, and revocation tied to workload use.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on June 7, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
