They should apply the same lifecycle discipline to both populations while preserving identity-specific review logic. That means ownership, offboarding, recertification, and entitlement scope must be defined consistently, even if the workflow steps differ between people and non-human identities.
Why This Matters for Security Teams
When IAM governance spans people and machines, the failure mode is usually not a missing policy. It is inconsistent lifecycle control: human joiners and movers are reviewed, while service accounts, API keys, OAuth grants, and workload tokens drift outside the same governance rhythm. That gap matters because machine identities often outlive the teams that created them and can retain access long after business need has changed. Current guidance from NIST Cybersecurity Framework 2.0 still points to asset, access, and governance discipline as the foundation, but non-human identity inventories are typically less complete than human directories.
NHIMG research shows why this is urgent: in The 2024 ESG Report: Managing Non-Human Identities, 72% of organisations said they have experienced or suspect a breach of non-human identities. That is a governance problem as much as a security problem, because one review model cannot be blindly copied across both identity classes. The right answer is to align lifecycle controls, then tailor the review logic to how each identity is actually used. In practice, many security teams discover the gap only after an over-privileged token, stale integration, or forgotten secret has already been abused.
How It Works in Practice
Security teams should build one governance standard and two review paths. The standard is consistent: every identity needs an owner, a purpose, a defined entitlement scope, a lifecycle state, and an offboarding trigger. The review path differs because humans and machines behave differently. Human identities are usually reviewed for role fit, employment status, and segregation of duties. Machine identities are reviewed for workload necessity, secret hygiene, scope creep, and dependency chains across applications and pipelines.
A useful operating model is to treat machine access as part of the same entitlement catalog as human access, then add identity-specific controls for issuance and renewal. That includes:
- Mapping each service account, token, or key to a business owner and a technical custodian.
- Requiring expiration or rotation rules for secrets, especially where standing access is not essential.
- Recertifying machine entitlements on a schedule tied to application change, not just calendar cadence.
- Revoking access automatically when the workload, vendor integration, or pipeline is retired.
This is where the Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs is especially relevant: lifecycle discipline is the bridge between identity governance and operational reality. For broader identity governance patterns, NIST Cybersecurity Framework 2.0 reinforces the need to know what exists, who owns it, and how it is controlled. These controls tend to break down when machine identities are embedded in CI/CD systems with no central inventory, because local pipeline logic hides the true owner and purpose.
Common Variations and Edge Cases
Tighter governance often increases operational overhead, so organisations need to balance consistency against developer friction and service uptime. The hardest cases are not obvious human-like accounts, but shared automation identities, third-party OAuth grants, long-lived integration secrets, and break-glass accounts used only during outages. Best practice is evolving here, and there is no universal standard for every workflow yet.
In these edge cases, the review question should change from “Who used this last?” to “What workload still depends on this, and is the scope still justified?” That is where identity-specific logic matters. A human recertification may ask a manager to confirm access. A machine recertification may require application owners, pipeline maintainers, and security reviewers to validate the exact secret, token, or certificate in use. NHIMG’s Top 10 NHI Issues highlights how stale credentials and excessive permissions commonly persist when governance is fragmented. The practical rule is simple: one policy framework, separate evidence standards. Anything less creates blind spots in audit, incident response, and offboarding.
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 | Covers NHI inventory and ownership, essential for mixed human-machine governance. |
| NIST CSF 2.0 | GV.OC, PR.AA | Maps to governance and identity access management across all identity types. |
| NIST AI RMF | GOVERN | Supports accountability and lifecycle oversight for autonomous or machine-driven access. |
Inventory every non-human identity and tie each one to an accountable owner and business purpose.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on June 27, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
