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Who should own passwordless governance across human and machine identities?

NHI Mgmt Group should own passwordless governance through a joint identity-security operating model led by IAM, with security architecture, platform engineering, and GRC as core partners. Human IAM handles user authn, device trust, recovery, and policy. NHI governance covers service accounts, workloads, API keys, certificates, and AI agents. A single control plane should define standards, assurance, lifecycle controls, exception handling, and audit evidence across both identity types.

Why ownership has to be joint, not split by identity type

Passwordless governance fails when human login, machine authentication, recovery, and audit expectations are run as separate programmes. The control problem is the same even when the identity type differs: define what strong authentication looks like, who can approve exceptions, how recovery is handled, and what evidence proves the control is working. That is why IAM should lead, with security architecture, platform engineering, and GRC as core partners, rather than leaving ownership to a single delivery team.

A useful mental model is that humans and machines share the same governance spine but not the same operating details. Human identities need device trust, recovery paths, and user experience decisions; machine identities need service-to-service trust, secret or key lifecycle, and workload-specific rotation or attestation. The owner has to understand both the policy layer and the implementation layer, or the programme will drift into inconsistent standards.

The practical reason to keep one operating model is that passwordless is not just an authentication project. It changes enrollment, recovery, policy exception handling, assurance, and the way teams prove ongoing compliance. If those pieces are owned by different groups without a common control plane, the organisation usually gets uneven rollout, inconsistent recovery standards, and weak evidence for audit or incident review.

What the governance scope must cover across humans and machines

For human identities, governance should cover phishing-resistant sign-in, recovery assurance, device binding, step-up policy, and the conditions under which fallback methods are allowed. If recovery is weaker than primary authentication, the programme inherits the weakest path. The owner must therefore treat recovery as part of authentication governance, not as an afterthought handled only by support teams.

For machine identities, governance needs to cover service accounts, workload identities, API keys, certificates, OAuth client credentials, and AI agents that act with execution authority. The key governance questions are who owns each identity, what it is allowed to do, how long its credential can live, how it is rotated or revoked, and what proof exists that those controls are enforced. NHIMG’s Ultimate Guide to NHIs is the broader reference point for that lifecycle view.

That scope should also include the shared edge cases where humans and machines intersect, such as delegated access, consent grants, shared credentials, and human use of machine access paths. Human vs Non-Human Identity is useful here because it frames the ownership boundary where governance often breaks down: one team owns the human experience, another owns the machine credential, and nobody owns the end-to-end access path.

How to run passwordless governance as a single control plane

Successful governance starts with a single standard for allowed authenticators, recovery methods, exception handling, and evidence collection. IAM should own the standard and the policy exceptions, security architecture should set the control requirements, platform engineering should implement the reference patterns, and GRC should define the assurance cadence and documentation requirements. That division gives you one policy spine without forcing one team to own every technical decision.

For the machine side, governance should be explicit about lifecycle ownership and rotation discipline. The issue is not only whether a secret or certificate exists, but whether the organisation can discover it, assign an owner, rotate it on time, and prove it is not being reused outside its intended scope. A focused reference such as Service Account Security Guide helps anchor those operational controls in service-account practice.

For the human side, the control plane should define when passwordless is mandatory, what recovery path is acceptable, and what device or assurance signals must be present before sign-in is trusted. The most common failure is to implement the primary sign-in flow well, then leave recovery, fallback, and exception approval loosely governed. That creates a weaker alternate path that attackers and careless administrators can both exploit.

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 and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST SP 800-53 Rev 5 and NIST SP 800-57 set the governance and control requirements practitioners need to meet.

Framework Control / Reference Relevance
NIST SP 800-53 Rev 5 IA-2 — Identification and Authentication (Organizational Users) Passwordless governance must define strong human authentication and recovery controls.
IA-5 — Authenticator Management The question covers lifecycle control of credentials, tokens, keys, and certificates.
IA-9 — Identification and Authentication (Non-Organizational Users) Machine identities, service accounts, and external automated actors need governed authentication.
Recommendation — Enforce strong authenticator requirements and recovery governance for workforce sign-in. Govern credential, rotation, revocation, and replacement requirements centrally. Apply controlled authentication requirements to services, workloads, and other non-human actors.
OWASP Non-Human Identity Top 10 NHI-01 — Improper Offboarding Machine identities must be revoked cleanly when ownership or use ends.
NHI-05 — Overprivileged NHI Passwordless governance must limit what machine identities can do after authentication.
NHI-07 — Long-Lived Secrets The subject includes credential lifecycle, especially for machine access material.
Recommendation — Build offboarding into the lifecycle so stale machine access is removed promptly. Constrain machine identity privilege to the minimum needed for each workload. Shorten secret lifetimes and rotate credential material on a defined schedule.
OWASP Agentic AI Top 10 ASI03 — Identity & Privilege Abuse AI agents are included in the governance scope because they may act with delegated authority.
Recommendation — Limit agent authority and review delegated access before production use.
NIST SP 800-57 Key Management Certificates and key-based machine authentication require lifecycle governance.
Recommendation — Manage cryptographic key lifecycle centrally for machine authentication material.

Practitioner Guidance

What to prioritise: Put one accountable owner in charge of the policy and assurance model, then assign execution responsibilities by domain. If no one team can answer who approves exceptions, who owns recovery, and who can revoke access, the governance model is not ready.

What to verify: Check that the same control plane covers enrollment, recovery, rotation, revocation, and evidence for both humans and machines. Also verify that service accounts, workload identities, certificates, and AI-agent access are mapped to named owners rather than left to platform defaults.

Common mistake: Treating passwordless as a login technology choice instead of an identity governance programme. That mistake usually produces a good front door and a weak back door, especially where fallback paths, shared machine credentials, or ad hoc exceptions are concerned.

Practitioner takeaway: The right owner is the team that can govern the whole access lifecycle, not just the sign-in method. In practice, that means IAM leads the operating model, while architecture, platform engineering, and GRC enforce consistency across human and machine identities.