Security teams should use hardware-backed passkeys to bind sensitive actions to verified human intent, not just login. That means requiring a physical approval step for high-risk operations such as production changes, payment approvals, or document signing. The control works best when paired with strong workflow design, clear approval boundaries, and logging that proves who authorised the action and when.
Why This Matters for Security Teams
Hardware-backed passkeys are useful in AI-driven workflows because the highest-risk failure is often not password theft at login, but unauthorised execution of a sensitive action after an AI system has already assembled the workflow. In practice, a human factor is still needed at the moment of approval, especially where a model, agent, or automation can draft, route, or even recommend an action. NIST’s NIST Cybersecurity Framework 2.0 remains relevant here because it pushes teams to treat authorization as an operational control, not a one-time authentication event.
That distinction matters when agents can chain tools, generate plausible requests, or trigger business processes at speed. A passkey anchored to hardware gives stronger proof that a real user approved the action at the right time, but only if the workflow enforces a narrow approval boundary and preserves evidence. NHIMG’s Ultimate Guide to NHIs — Why NHI Security Matters Now shows why this is no longer optional: organisations are increasingly exposed to automated credential abuse and identity sprawl. In practice, many security teams discover weak approval design only after an AI-assisted request has already been accepted as routine.
How It Works in Practice
The strongest pattern is to bind the passkey challenge to a specific, high-risk workflow step, not to generic interactive login. For example, a production deploy, payment release, legal signature, or privilege elevation should require a fresh, hardware-backed assertion from the designated approver before the system can continue. The approval should be time-bound, action-specific, and logged with the workflow context so the record shows what was approved, by whom, and under which conditions.
That approach works best when paired with layered controls:
- Use passkeys only for actions that warrant strong intent verification, not every low-risk task.
- Require step-up approval when an AI agent proposes an irreversible, externally visible, or financially material action.
- Keep approval tokens short-lived and single-purpose so they cannot be replayed across tasks.
- Log the human approver, the action payload, the model or agent that proposed it, and the exact time of authorization.
- Separate “approve” from “execute” where possible so the passkey gates final commit, not earlier draft generation.
For implementation, teams should align workflow policy with controls in NIST CSF and stronger identity assurance practices from NIST SP 800-53 Rev. 5 Security and Privacy Controls. Hardware-backed authenticators reduce phishing and remote approval abuse, but they do not solve workflow ambiguity. NHIMG’s LLMjacking: How Attackers Hijack AI Using Compromised NHIs is a reminder that attackers move fast once identity material is exposed, so approval controls must assume the surrounding environment may already be under pressure. These controls tend to break down when the AI workflow merges drafting, approval, and execution into one broad step because the human is then approving a bundle they cannot adequately inspect.
Common Variations and Edge Cases
Tighter approval controls often increase friction, so organisations have to balance strong intent verification against business speed. That tradeoff is real, especially when high-volume workflows need many approvals per day or when approvers are distributed across time zones. Current guidance suggests using passkeys selectively for truly material actions, while leaving routine, reversible tasks on lower-friction controls.
One edge case is delegated approval. If an executive assistant, incident commander, or on-call manager can approve on behalf of someone else, the workflow should record the delegated authority explicitly rather than treating the passkey event as personal intent by default. Another edge case is AI-generated remediation. A model may prepare a change package that is technically valid but operationally risky; in that case, the passkey should confirm the final choice, not the model’s recommendation. There is no universal standard for this yet, but best practice is evolving toward action-scoped authorization rather than user-scoped login.
Teams should also be careful not to overextend passkeys into places where they add little value, such as background service-to-service calls or unattended jobs. Hardware-backed passkeys prove human presence, which is exactly why they are well suited to privileged exceptions, not machine execution. NHIMG’s OWASP NHI Top 10 is useful for mapping where human approval, agent autonomy, and identity control intersect. The control becomes weakest when a team assumes a single passkey step can compensate for poor approval design, broad agent permissions, or vague ownership of the downstream action.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10, OWASP Non-Human Identity Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | A2 | Agentic workflows need runtime approval boundaries, not just login checks. |
| OWASP Non-Human Identity Top 10 | NHI-04 | Action approval depends on strong identity and least-privilege for non-human actors. |
| CSA MAESTRO | TRUST-02 | MAESTRO emphasizes trust, policy, and governance for autonomous AI actions. |
| NIST AI RMF | AI RMF supports governance of human oversight and accountability for AI-assisted actions. | |
| NIST CSF 2.0 | PR.AA-1 | Identity proofing and authentication strength matter for high-risk approvals. |
Define approval accountability, logging, and oversight for every AI-initiated high-risk action.
Related resources from NHI Mgmt Group
- How should security teams implement step-up for high-risk actions?
- How should security teams implement dual control for high-risk identity actions?
- How should security teams implement DLP for human error, insider risk, and AI-driven data movement?
- How should security teams implement AI agents in cloud and application security workflows without losing control over context and risk?