Why do IAM programmes need to cover non-human identities as well as users?

Why This Matters for Security Teams

IAM programmes fail when they assume access is mostly human-shaped. Service accounts, API keys, CI/CD runners, bots, and workload identities often carry broader access than employees and are less visible in reviews, which makes them easier to miss and harder to retire. NHI Management Group’s Ultimate Guide to NHIs notes that NHIs outnumber human identities by 25x to 50x in modern enterprises, which changes the scale of governance entirely.

This is not just an inventory problem. It is an exposure problem: secrets are frequently embedded in code, configs, and pipelines, and compromises can persist long after human access would have been removed. The NIST Cybersecurity Framework 2.0 reinforces that identity, access, and asset visibility need to be managed as a continuous lifecycle, not a one-time admin task. In practice, many security teams encounter NHI-driven incidents only after a leaked token or over-privileged service account has already been used laterally, rather than through intentional review.

One useful indicator of the maturity gap is that 88.5% of organisations acknowledge their non-human IAM practices lag behind or merely match human IAM, according to The 2024 Non-Human Identity Security Report.

How It Works in Practice

Covering NHIs in IAM means treating them as first-class identities with their own lifecycle, not as technical leftovers. The practical model is: identify the workload, bind it to a cryptographic workload identity, issue the minimum access it needs for a bounded task, and revoke or rotate access automatically when the task ends. That is why current guidance increasingly favours short-lived credentials, secrets minimisation, and policy evaluation at request time rather than static role assignments.

In mature environments, this usually involves workload identity standards such as SPIFFE, OIDC-based federation, or cloud-native identity constructs, paired with policy-as-code and secrets automation. The goal is to remove long-lived shared secrets from code and pipelines, then make access decisions based on workload, context, and intent. That aligns with the operational direction in NHI Management Group’s NHI guidance, where lifecycle governance, rotation, offboarding, and zero-trust alignment are central rather than optional.

• Inventory every service account, API key, token, certificate, and workload principal.
• Classify each NHI by owner, purpose, privilege level, and expiry.
• Replace static secrets where possible with federated workload identity and ephemeral tokens.
• Enforce approval, rotation, and offboarding workflows for machine access paths.
• Monitor usage for drift, privilege creep, and secret reuse across environments.

For implementation detail, the NIST Cybersecurity Framework 2.0 is useful for framing governance, but the operational control plane must extend into CI/CD, cloud workloads, and automation tooling. These controls tend to break down when teams share credentials across pipelines or reuse the same secret across multiple environments because attribution, revocation, and blast-radius reduction all become unreliable.

Common Variations and Edge Cases

Tighter control over NHIs often increases operational overhead, so organisations have to balance speed of delivery against the cost of managing more identities, more policies, and more rotations. That tradeoff is real, especially in hybrid and multi-cloud estates where access paths differ across platforms and teams.

There is no universal standard for every edge case yet. Some organisations can move most workloads to short-lived tokens quickly; others still depend on static credentials for legacy apps, vendor integrations, or embedded devices. In those cases, best practice is evolving toward compensating controls such as stronger vaulting, narrower scopes, aggressive monitoring, and faster rotation. The Azure Key Vault privilege escalation exposure research shows why vault permissions themselves can become a privilege-escalation path if they are not tightly governed.

Another edge case is third-party access. When partners or SaaS tools are granted NHIs into internal systems, the ownership model becomes ambiguous and offboarding is often incomplete. That is where many programmes fail in practice. JetBrains GitHub plugin token exposure is a reminder that machine credentials can leak through normal developer workflows, not just exotic attack chains. Security teams should treat every NHI as a revocable operational dependency, not a permanent technical account.

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?