Why do non-human identities make maturity assessments less reliable?

Why This Matters for Security Teams

Non-human identities make maturity assessments less reliable because the usual measurement model assumes identities are created, reviewed, and retired through predictable human workflows. That assumption breaks when service accounts, API keys, workload tokens, and agent credentials are issued by automation, embedded in pipelines, or inherited across systems. NHI Management Group has documented how hidden credentials can persist long after the business owner thinks a system is gone, which distorts both inventory quality and control coverage. See the Ultimate Guide to NHIs and the NIST Cybersecurity Framework 2.0 for the governance baseline.

The problem is not just missing records. It is that maturity scores often reward process existence rather than real operational visibility, so teams can report strong lifecycle controls while still leaving secrets in code, CI/CD tools, or stale integrations. That creates false confidence, especially in environments where service accounts outnumber humans by orders of magnitude. The assessment may look stable while the attack surface keeps expanding underneath it. In practice, many security teams encounter the gap only after an incident reveals accounts that were never in scope for the original review.

How It Works in Practice

A reliable maturity assessment for NHIs has to start with discovery, not policy. If the inventory is incomplete, every downstream metric becomes suspect. Current guidance suggests separating human identity controls from workload identity controls, because the control objectives are different: humans follow joiner-mover-leaver processes, while NHIs need machine-driven lifecycle management, ownership mapping, and continuous validation. The 2024 Non-Human Identity Security Report notes that only 19.6% of security professionals express strong confidence in their ability to securely manage workload identities, which is consistent with the visibility problem many programs face.

In practice, a mature assessment should test whether the organisation can answer four questions at runtime:

• What NHIs exist, including those created by CI/CD, cloud services, and SaaS integrations?
• Who owns each identity, and who can revoke it?
• Where are the secrets stored, and how quickly can they be rotated?
• Can the team prove access is least privilege, time-bound, and tied to actual usage?

This is where external controls matter. The NIST Cybersecurity Framework 2.0 supports the governance structure, while the assessment logic should be tied to evidence such as secret scans, vault telemetry, cloud IAM exports, and workload attestations. NHI Management Group research also shows why this matters operationally: the JetBrains GitHub plugin token exposure illustrates how a single exposed token can invalidate an otherwise strong-looking maturity score. These controls tend to break down when identities are created outside central platforms because there is no dependable system of record to compare against the assessment baseline.

Common Variations and Edge Cases

Tighter NHI control measurement often increases operational overhead, requiring organisations to balance better assurance against the cost of continuous discovery and frequent remediation. That tradeoff is real, especially in large hybrid estates where teams still rely on shared service accounts, legacy schedulers, or vendor-managed integrations. Best practice is evolving, and there is no universal standard for how to score every NHI category with equal weight.

One common edge case is ephemeral infrastructure. Short-lived workloads can make an assessment look healthier than it is if the program counts “short-lived” as automatically “low risk” without checking whether the issuing mechanism is actually governed. Another is third-party access, where external systems may hold NHIs that are invisible to internal IAM reports. A third is agentic AI and autonomous tooling, where access patterns are dynamic and the real control question is whether runtime authorization can constrain what the agent is trying to do, not just what account it uses.

For that reason, maturity scoring should distinguish between documentation maturity and operational maturity. A team may have policies for rotation, offboarding, and vaulting, yet still fail if secrets are stored in code or if revocation is not enforced quickly. In other words, the assessment should reward evidence, not intention. That distinction is what keeps a maturity model from overstating readiness while the actual exposure remains unmanaged.

Related resources from NHI Mgmt Group

• How should security teams govern non-human identities at scale?
• How should security teams govern non-human identities for compliance?
• Why do non-human identities create more audit risk than human accounts?
• How should security teams govern non-human identities in Salesforce?