Governance becomes performative. Teams may optimise for survey completion or policy documentation while leaving privilege scope, lifecycle offboarding, and access evidence unresolved. The result is a measurement programme that looks mature on paper but does not materially reduce identity risk.
Why This Matters for Security Teams
A maturity score can be useful as a checkpoint, but it becomes misleading when leaders treat the score itself as the outcome. Teams then optimise for documentation, survey responses, and tool coverage instead of the controls that actually reduce exposure. That is especially dangerous in NHI programs, where secrets, service accounts, and API keys create risk even when policy evidence looks strong.
NHI Management Group’s Ultimate Guide to NHIs shows why this gap matters: 97% of NHIs carry excessive privileges, and 71% are not rotated within recommended time frames. Those are operational failures, not scoring failures. A high maturity rating can coexist with stale credentials, weak offboarding, and poor visibility, which is why score chasing often hides the real attack surface. Current guidance in the NIST Cybersecurity Framework 2.0 is to measure outcomes and risk reduction, not just control presence.
In practice, many security teams discover that the programme has become a reporting exercise only after a secrets leak, privilege abuse, or failed offboarding reveals how little the score reflected reality.
How It Works in Practice
When maturity is the goal, the organisation begins to optimise the measurement system rather than the environment. That usually means policies get written, exceptions get recorded, and dashboards turn green, while the underlying NHI estate remains full of long-lived credentials and excessive access. The better pattern is to define maturity as a by-product of measurable operational outcomes: shorter secret lifetimes, fewer standing privileges, better visibility, and faster revocation.
This is where NHI governance should connect scorecards to concrete control evidence. For example, a team can require proof that service accounts are inventoried, secrets are stored in approved systems, rotation is enforced, and access is revoked on offboarding. The Ultimate Guide to NHIs highlights the scale of the problem: 96% of organisations store secrets outside secrets managers in vulnerable locations, and only 20% have formal processes for offboarding and revoking API keys. Those are the kinds of gaps a maturity score must surface, not conceal.
- Track whether identities are inventoried, not just whether a policy exists.
- Measure secret rotation cadence, not just whether rotation is documented.
- Verify revocation after role change, service retirement, or incident response.
- Use evidence from systems of record, not survey responses alone.
Best practice is to align score thresholds with specific control outcomes and review them regularly through an evidence-based programme. The NIST Cybersecurity Framework 2.0 supports this shift by framing governance around continuous risk management rather than static assessment. These controls tend to break down when the environment is highly distributed and secrets live across code, CI/CD, cloud consoles, and third-party tools because evidence collection becomes fragmented and incomplete.
Common Variations and Edge Cases
Tighter maturity scoring often increases reporting overhead, requiring organisations to balance executive visibility against operational accuracy. That tradeoff matters because not every framework failure is the same: some programmes are weak on evidence quality, while others are strong on evidence but weak on enforcement. Best practice is evolving, but there is no universal standard for turning a maturity score into a reliable proxy for security outcome.
One common edge case is the organisation that scores well because it has formal processes, yet those processes do not materially change behaviour. Another is the team that inherits multiple cloud platforms and toolchains, where access reviews are performed but not connected to actual credential lifecycle controls. NHIMG research notes that 88.5% of organisations believe non-human IAM lags behind or only matches human IAM, which suggests many programmes are still adapting their scoring models to a very different identity population. For these environments, scorecards should be treated as directional, while revocation speed, privilege scope, and secrets hygiene remain the true performance indicators.
In other words, maturity scoring is useful only when it rewards reduced exposure rather than the appearance of control. If the metric does not force correction of excessive privilege, stale credentials, and incomplete offboarding, it will reward theatre instead of security.
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 | Maturity scores often hide stale secrets and poor rotation. |
| NIST CSF 2.0 | GV.RM-01 | Governance should measure risk reduction, not score completion. |
| NIST AI RMF | GOVERN | Outcome-based governance prevents metrics from becoming performative. |
Tie scores to secret rotation evidence and revoke credentials that exceed approved lifetimes.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on June 23, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
