Because devices, applications, and systems authenticate differently from people and often exist at much larger scale. They need their own lifecycle controls for onboarding, renewal, rotation, and decommissioning, otherwise hidden machine identities accumulate and widen the attack surface.
Why This Matters for Security Teams
Non-person entities are not just “more accounts.” They are a different identity class with different trust assumptions, different credential lifecycles, and different failure modes. A service account, API token, workload identity, or automation secret can be created faster than it can be reviewed, and it often operates continuously across systems. That is why separate governance is necessary: human IAM controls are built around interactive users, while machine identities need lifecycle, rotation, and revocation discipline.
The risk shows up quickly when teams let application access accrete informally. The Top 10 NHI Issues research highlights how hidden and overextended NHIs become part of the attack surface, and NIST’s NIST Cybersecurity Framework 2.0 reinforces the need to identify, protect, detect, respond, and recover across all identity types, not just people. In the 2024 Non-Human Identity Security Report, only 19.6% of security professionals expressed strong confidence in their organisation’s ability to securely manage non-human workload identities, which shows how wide the maturity gap remains.
In practice, many security teams encounter NHI exposure only after a secret has been leaked, a token has persisted past its useful life, or an automation account has been granted permissions no one can fully explain.
How It Works in Practice
Separate NHI governance starts with inventory and ownership. Security teams need to know what the identity is, what system created it, what it is allowed to do, how long it should exist, and who owns its renewal or removal. That means treating onboarding, approval, rotation, monitoring, and decommissioning as explicit controls rather than ad hoc engineering tasks. The lifecycle guidance in the Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs is directly relevant here because machine identities often outlive the workloads they were created for.
In mature environments, governance also separates interactive access from workload access. That usually means:
- Using distinct policy paths for users, services, devices, and automation
- Requiring short-lived credentials or tokens where possible instead of static secrets
- Binding access to workload identity, not only to network location or human approval
- Evaluating access at runtime based on application context, environment, and task
- Logging issuance, use, and revocation so secrets can be traced end to end
That pattern aligns with the NIST AI and security direction, but it is still evolving across vendors and cloud stacks. Where teams lack central discovery, the problem is often not policy design but simple visibility. The Ultimate Guide to NHIs — Regulatory and Audit Perspectives frames the audit challenge well: if an organisation cannot prove who owns an NHI, why it exists, and when it was last rotated, separate governance is already overdue. These controls tend to break down in highly ephemeral, multi-cloud environments because identity sprawl and rapid deployment outpace manual review.
Common Variations and Edge Cases
Tighter NHI governance often increases operational overhead, requiring organisations to balance security gain against deployment speed and engineering convenience. That tradeoff is real, especially for DevOps pipelines, third-party integrations, and legacy workloads that cannot easily adopt modern workload identity patterns.
Current guidance suggests three common exceptions deserve special handling. First, shared service identities may remain necessary in older systems, but they should be time-bound, monitored, and wrapped with compensating controls rather than treated as permanent exceptions. Second, third-party OAuth or delegated access may look “user-like” while behaving like an NHI risk; teams should not assume human IAM review is sufficient. Third, emergency access paths often bypass normal lifecycle discipline, so they need explicit expiration and post-use review.
NHIMG’s research also shows why the baseline matters: the Non-Human Identity Security Report found that 88.5% of organisations say their NHI practices lag behind or only match their human IAM efforts. That gap is why separate governance is not a maturity signal, it is a minimum control expectation. Best practice is evolving, but the direction is clear: if an identity can act autonomously or at machine speed, it needs its own governance model, not a recycled human access process.
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-01 | Inventory and ownership are core to separate governance for machine identities. |
| NIST CSF 2.0 | PR.AA | Identity management applies to all identity types, including non-person entities. |
| NIST AI RMF | Autonomous systems need governance for risk, accountability, and lifecycle control. |
Define accountability and ongoing risk oversight for every AI-enabled or automated identity.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on June 12, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
