How should security teams evaluate hardware-backed digital signatures for passkeys and AI agent workflows?

Security teams should treat hardware-backed signatures as an identity assurance control, not just an authentication feature. The key question is whether the signature can be bound to a trusted device, verified across platforms, and used consistently in workflows such as wallets, document signing, or agent approvals. Standardized APIs matter because they reduce custom integrations and improve portability.

Why Security Teams Should Treat Hardware-Backed Signatures as Assurance, Not Convenience

Hardware-backed signatures matter because they are often the strongest practical signal that a private key stayed on a trusted device and that the signing action came from a real user or enrolled workflow. That matters for passkeys, document approval, wallet transactions, and increasingly for AI agent approvals where a system can act faster than a human can review. Standards such as the NIST AI Risk Management Framework and NHI research such as OWASP NHI Top 10 both point to the same issue: the control only works if the relying party can validate the assurance context, not just the cryptography.

Security teams should not assume all signatures are equivalent just because they validate. A signature may prove possession of a key, but not whether the key is hardware-backed, whether the device is managed, whether the assertion is replay-resistant, or whether the workflow can distinguish a high-risk approval from a routine login. That distinction becomes critical when the same identity primitive is reused across browsers, mobile wallets, SaaS approvals, and agentic automation. In practice, many security teams encounter weak trust assumptions only after a phished approval, a rogue device enrollment, or an agent misuse event has already occurred, rather than through intentional assurance testing.

How to Evaluate Portability, Binding, and Runtime Trust

The evaluation should start with three questions: what exactly is being signed, where the private key lives, and how the verifier learns that the signature came from a trusted hardware-backed credential. For passkeys, look for standards-based attestation, origin binding, phishing resistance, and support for platform and cross-platform authenticators. For AI agent workflows, the same logic should extend to task-level approvals, so the verifier can tell whether the agent is authorized to submit a specific action, not merely whether it has some valid credential.

In practice, strong implementations separate identity proof from authorization. The device or agent presents a cryptographic assertion, then policy determines whether that assertion is acceptable for the requested action. That means evaluating whether the workflow supports real-time policy checks, device state, and contextual constraints such as user presence, risk score, transaction amount, destination, and step-up requirements. It also means checking whether the signature API is standardized enough to avoid one-off integrations that cannot be ported across browsers, wallets, or agent runtimes. Where agent workflows are involved, align the design with agentic guidance from OWASP Agentic AI Top 10 and the CSA MAESTRO agentic AI threat modelling framework.

• Verify hardware backing through attestation, device binding, or platform assurance signals.
• Confirm that signatures are replay-resistant and scoped to the exact action or challenge.
• Check whether the same credential can be used safely across browsers, mobile, and agent workflows.
• Require runtime policy evaluation for approvals, not just static allow lists.

NHIMG research on agent compromise and secret abuse shows why this matters: attackers frequently target the weakest reusable credential path, not the strongest one. See CoPhish OAuth Token Theft via Copilot Studio and the LLMjacking report for examples of how identity abuse becomes workflow abuse. These controls tend to break down when a workflow accepts signed assertions without validating device trust, action scope, and replay resistance in the same request path.

Where the Real-World Tradeoffs Show Up

Tighter signature assurance often increases rollout friction, requiring organisations to balance user portability and recovery options against stronger binding and shorter-lived trust. That tradeoff is especially visible with passkeys that must work across consumer devices and with AI agents that need non-interactive operation. Current guidance suggests there is no universal standard for every approval flow yet, so teams should label the assurance level they are actually getting rather than assuming all hardware-backed signatures provide the same protection.

The biggest edge cases involve fallback paths. If a system allows weaker recovery methods, bypass approvals, or unaudited delegated signing, the hardware-backed path may be strong while the overall workflow remains weak. For agent approvals, this is even more important because an autonomous system can chain actions faster than a human can observe. Best practice is evolving toward explicit action scoping, short-lived approvals, and cryptographic proof tied to workload identity, but implementation quality varies widely. For broader context on how identity abuse escalates into operational compromise, compare the Analysis of Claude Code Security with NIST AI Risk Management Framework guidance.

Security teams should also test interoperability explicitly. A signature that works in one ecosystem but cannot be verified consistently in another creates hidden lock-in and weakens assurance portability. That is a practical problem when passkeys, wallets, and agent approvals need to coexist in the same enterprise control plane.

Related resources from NHI Mgmt Group

• How should security teams implement hardware-backed passkeys for high-risk digital actions in AI-driven workflows?
• When should security teams prioritise phishing-resistant authentication for digital transaction workflows?
• How should security teams authenticate AI agents in enterprise environments?
• How should security teams govern AI agent identities in MCP workflows?