What breaks when organisations use one IAM model for humans and non-human identities?

Why This Matters for Security Teams

One IAM model for humans and non-human identities often fails because the control assumptions are different. Human access is usually session-based, reviewable, and tied to a person’s intent. Non-human identities, especially service accounts and agents, can authenticate repeatedly, act at machine speed, and chain tools in ways a human reviewer never sees. That mismatch turns “least privilege” into a paper policy unless runtime behavior, secret handling, and revocation are handled separately. NIST’s NIST Cybersecurity Framework 2.0 helps with governance structure, but it does not eliminate the need for NHI-specific controls.

NHI Management Group’s research shows how large the gap already is: in The Ultimate Guide to NHIs, 97% of NHIs are reported to carry excessive privileges, and 80% of identity breaches involved compromised non-human identities such as service accounts and API keys. In practice, teams often discover the mismatch only after a secret leaks or a workload starts moving laterally through an environment, as seen in cases like JetBrains GitHub plugin token exposure.

The real problem is not that human IAM is wrong. It is that it was never designed to contain autonomous or semi-autonomous workload behavior. In practice, many security teams encounter the failure only after an API key, token, or service account has already been used beyond its intended scope.

How It Works in Practice

Effective NHI governance separates identity types and applies controls based on runtime context, not just onboarding approval. For humans, the focus is usually authentication, role assignment, and periodic access review. For non-human identities, the focus shifts to workload identity, ephemeral credentials, secret distribution, and automatic revocation. Current guidance suggests treating the workload as the identity primitive, because the system needs cryptographic proof of what the workload is, not just a static secret it can present.

That is why modern patterns increasingly use short-lived credentials, just-in-time issuance, and policy evaluation at request time. If a service or agent needs access to a database, queue, or API, the credential should be scoped to that task and expire when the task is done. A central secrets store still matters, but storage alone is not enough. The operational question is whether the secret can be created, observed, and revoked fast enough to match machine execution.

• Use separate IAM paths for humans and NHIs instead of one shared approval workflow.
• Issue short-lived tokens or certificates for workloads rather than long-lived static secrets.
• Bind access to workload identity and environment context, not only to a role name.
• Automate revocation when the workload ends, changes state, or exceeds its intended use.

NHIMG’s 2024 Non-Human Identity Security Report notes that only 19.6% of security professionals are strongly confident in their organisation’s ability to securely manage non-human workload identities, which is consistent with the operational drift seen when human-centric processes are reused for machine access. The pattern is similar to exposed credential cases such as Azure Key Vault privilege escalation exposure. These controls tend to break down when workloads are deployed across hybrid or multi-cloud environments because identity, secret storage, and revocation are no longer managed in one place.

Common Variations and Edge Cases

Tighter separation between human and non-human IAM often increases operational overhead, so organisations have to balance stronger containment against deployment speed and platform complexity. That tradeoff is real, especially where legacy applications cannot use workload identity cleanly or where teams still depend on static service accounts for vendor integrations. Best practice is evolving, and there is no universal standard for every environment yet.

One common edge case is the “service account that behaves like a user,” such as a shared integration account with broad privileges and no clear owner. Another is AI agents that need tool access, where static RBAC often fails because the agent’s next action is not fully predictable in advance. In those environments, runtime policy decisions and explicit task scoping matter more than a long pre-approved entitlement list. NIST’s framework and the NHI guidance from NHIMG are useful together, but they address different layers of the problem: governance versus containment.

Organisations also need to watch for hidden exposure paths, such as secrets embedded in code, CI/CD systems, or cloud roles that can be escalated later. Where machine access is shared across teams or tenants, a single IAM model usually fails to preserve evidence, ownership, and revocation boundaries. For a practical security baseline, align human IAM to workforce governance and NHI controls to workload containment, then review both as separate attack surfaces rather than one merged identity estate.

Related resources from NHI Mgmt Group

• Should organisations use the same policy model for humans and non-human identities?
• When should organisations prioritise Zero Standing Privilege for non-human identities?
• How should organisations govern non-human identities in a federated IAM model?
• What breaks when organisations use human IGA for non-human identities?