What do organisations get wrong when they assume existing IAM controls are enough for non-human identities?

Why Existing IAM Breaks Down for Non-Human Identities

Traditional IAM assumes a person with a stable job function, predictable login times, and a bounded set of applications. Non-human identities do not behave that way. Service accounts, API keys, workload tokens, and agents operate at machine speed, across many systems, and often without a clear human owner. NHI Management Group’s Ultimate Guide to NHIs — Standards shows that 97% of NHIs carry excessive privileges, which makes static access reviews a weak control by themselves.

The main error is assuming role assignment equals risk control. For NHIs, privilege is only one part of the picture. Teams also need lifecycle ownership, secret rotation, offboarding, usage monitoring, and environment-aware policy decisions. NIST’s NIST SP 800-53 Rev 5 Security and Privacy Controls remains useful, but it does not remove the need to adapt controls to machine identities that are issued, reused, and embedded differently from human accounts. In practice, many security teams discover the gap only after a leaked token or over-privileged service account has already been used for lateral movement.

What Strong NHI Control Looks Like in Practice

Effective NHI governance starts by treating the identity itself as a workload asset, not as a human surrogate. That means every secret, token, certificate, or service account should have a named owner, a clear purpose, a defined expiry, and a revocation path. The practical model is closer to just-in-time access than to permanent entitlement. Current guidance suggests that short-lived credentials, workload identity, and runtime policy evaluation are the right direction for autonomous or automated workloads, especially where access patterns change by task.

This is where organisations should move beyond static IAM rules and toward context-aware authorization. Instead of asking, “What role does this identity have?”, teams should ask, “What is this workload trying to do right now, from where, against which resource, and under what conditions?” That question maps well to policy-as-code systems, short TTL credentials, and workload identity standards such as SPIFFE/SPIRE or OIDC-based token exchange. It also aligns with NHI research showing that insecure secret handling remains common, including JetBrains GitHub plugin token exposure and Hard-Coded Secrets in VSCode Extensions, both of which show how easily machine credentials escape normal IAM assumptions.

• Issue credentials per task, not per environment, and revoke them automatically on completion.
• Bind access to workload identity and runtime context, not just to a static role.
• Track ownership, rotation, and offboarding for every NHI artifact.
• Monitor tool chaining, unusual API calls, and cross-system movement as first-class signals.

These controls tend to break down in sprawling CI/CD, multi-cloud, or agentic environments because identities are copied, inherited, and reused faster than teams can review them.

Where Teams Misjudge the Edge Cases

Tighter controls often increase operational overhead, so organisations have to balance security gains against deployment friction and developer velocity. That tradeoff becomes obvious in environments with many ephemeral workloads, third-party integrations, or agentic systems that can chain tools without human intervention. Best practice is evolving here, and there is no universal standard for every workload pattern yet.

One common misjudgment is expecting human-style recertification to catch machine risk. It will not, especially when secrets live in code, pipelines, or plugins and are never exercised in a way that looks abnormal to traditional IAM. Another gap is assuming a service account with a narrow role is automatically safe, even when that account can call a privileged tool or inherit access through automation. The Aembit research in the 2024 Non-Human Identity Security Report found that 88.5% of organisations say NHI practices lag behind or merely match human IAM, which is a strong sign that many controls are still being ported rather than redesigned.

For autonomous or agentic workloads, the bigger issue is unpredictability. If an agent can decide which tool to invoke next, static entitlements become only a starting point. That is why current guidance increasingly favours runtime policy checks, ephemeral secrets, and workload-centric identity, especially when access paths can change after deployment. In practice, many teams discover this only after an agent, script, or pipeline has already used a legitimate credential in an unintended way.

Related resources from NHI Mgmt Group

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• What do organisations get wrong about secrets management for non-human identities?