Use two measures. One should track current exposure, such as exposed secrets, stale credentials, and overprivileged identities. The other should track whether the architecture is becoming less dependent on persistent trust. If remediation improves while persistent credential creation stays high, the programme is cleaning up symptoms rather than reducing the cause.
Why This Matters for Security Teams
Risk scores are useful for prioritisation, but they can hide whether nhi governance is actually improving. A programme can reduce exposed secrets today while still creating the same volume of new long-lived credentials tomorrow. That means the organisation is treating symptoms, not the trust model that keeps producing them. Current guidance from the NIST Cybersecurity Framework 2.0 and NHIMG research both point toward measuring control effectiveness, not just residual risk.
NHIMG’s Ultimate Guide to NHIs frames NHI management as a lifecycle problem, which is the right lens for progress measurement. If lifecycle hygiene does not improve, risk scores can drift downward for the wrong reason, such as a temporary cleanup or a narrower scope. One useful benchmark is that lack of credential rotation is cited as the top cause of NHI-related attacks by 45% of organisations in The State of Non-Human Identity Security. In practice, many security teams discover the gap only after a stale secret or overprivileged identity has already been used in an incident.
How It Works in Practice
The most useful measurement model separates exposure from architectural dependency. Exposure shows what is currently at risk: exposed secrets, stale credentials, dormant service accounts, excessive permissions, and identities that have not been rotated or revalidated on schedule. Architectural dependency shows whether the environment is becoming less reliant on persistent trust, meaning fewer static secrets, fewer always-on credentials, and more ephemeral or workload-bound identity assertions.
Teams usually track both through a small set of operational indicators:
- Count of exposed secrets by system, owner, and age band
- Percentage of NHIs with credentials older than policy TTL
- Number of overprivileged identities and entitlements reduced per cycle
- Share of workloads using short-lived tokens versus persistent secrets
- Rate of new persistent credential issuance compared with decommissioning
- Time to revoke, rotate, or quarantine compromised NHIs
This is where NIST CSF 2.0 helps with outcome thinking, while NHIMG’s Top 10 NHI Issues provides the operational categories teams should monitor. Mature programmes also tie these measures to change records and deployment pipelines so that every new integration is scored against its identity footprint. The practical question is not only “how risky is this identity today?” but “is the organisation reducing the number of identities that need standing trust at all?” These controls tend to break down in environments with many unmanaged third-party integrations because credential sprawl outpaces inventory and ownership discipline.
Common Variations and Edge Cases
Tighter NHI measurement often increases reporting overhead, requiring organisations to balance precision against operational speed. That tradeoff is real: a highly detailed dashboard can become expensive to maintain if identity sources, cloud accounts, and CI/CD systems are fragmented.
Best practice is evolving around which leading indicators matter most. Some teams focus on secret age and rotation cadence; others emphasise the ratio of ephemeral to persistent credentials. There is no universal standard for this yet, so the chosen metrics should match the architecture. For a cloud-native platform, workload identity adoption may be the clearest signal. For a legacy estate, overprivilege reduction and stale credential elimination may tell the truer story. The key is that the metrics must show a shrinking dependence on standing access, not just fewer findings on a quarterly report.
Edge cases matter. Break-glass accounts, vendor-managed integrations, and long-lived certificates may remain necessary in some systems, but they should be explicitly tracked as exceptions with owners, expiry dates, and compensating controls. NHIMG’s 2024 ESG Report on Managing Non-Human Identities reinforces why this matters: organisations that have experienced a compromised NHI averaged 2.7 separate incidents in the past 12 months. Progress is real only when exposure falls and the need for persistent trust falls with it.
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 address the attack and risk surface, while NIST CSF 2.0 and 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 | Credential rotation and age are core indicators of NHI exposure. |
| NIST CSF 2.0 | PR.AC-4 | Measures least-privilege and access reduction as operational outcomes. |
| NIST AI RMF | GOVERN | Progress measurement needs governance metrics, not only residual risk scores. |
Define governance KPIs that prove the system is reducing persistent trust over time.
Related resources from NHI Mgmt Group
- How should security teams use IAST and RASP in NHI governance?
- How should security teams prioritise NHI remediation in cloud environments?
- How should security teams make NHI best practices usable across the business?
- What is the difference between role-based access and API key governance for NHI security?
Deepen Your Knowledge
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
