Architectural Invariant Design: Hardware-Bound Zero-Knowledge Key Derivation via WebAuthn PRF Extension
Hardware-Bound Zero-Knowledge Key Derivation via WebAuthn PRF Extension defines an industrial-grade behavioral standard for security engineering. Enforces strict cryptographic hygiene when using the WebAuthn Pseudo-Random Function (PRF) extension (hmac-secret) for zero-knowledge client-side encryption. Mandates domain-separated HKDF salt isolation, prevents PRF output transmission to relying parties, and ensures ephemerality of unpadded raw symmetric keys in browser memory. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.
Hazard Analysis: What Breaks Without This Rule
The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:
| Failure Mode | AI Symptom (The Anti-Pattern) | Severity | Production Impact & Remedy |
|---|---|---|---|
| AI Hallucination & Deprecation Drift | Directly Utilizing Raw PRF Outputs as Symmetric Cipher Keys or Leaking PRF Secrets to Relying Parties | Critical | Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production. Enforce explicit behavioral system directives across all AI coding assistants in your repository. |
| Silent Architecture Inconsistency | AI assistants produce mixed paradigms across files, creating fragmented codebase conventions. | Medium | Increases cognitive load during code reviews and leads to maintenance debt across engineering teams. Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails. |
Step-by-Step Production Directives
Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:
Engineers MUST ALWAYS run PRF outputs through an HKDF-Extract-and-Expand step (RFC 5869) with explicit context/info strings and client-side salts before instantiating symmetric encryption keys.
Engineers MUST ALWAYS run PRF outputs through an HKDF-Extract-and-Expand step (RFC 5869) with explicit context/info strings and client-side salts before instantiating symmetric encryption keys.
Engineers MUST NOT expose the derived PRF output (raw evaluation bytes) to relying party assertion responses or serialize it over network boundaries.
Engineers MUST NOT expose the derived PRF output (raw evaluation bytes) to relying party assertion responses or serialize it over network boundaries.
Engineers MUST instantiate derived symmetric keys as non-extractable Web Cryptography API `CryptoKey` handles (`extractable
Engineers MUST instantiate derived symmetric keys as non-extractable Web Cryptography API `CryptoKey` handles (`extractable: false`).
Services MUST verify client PRF capability flags (`prf
Services MUST verify client PRF capability flags (`prf: { eval: { first: ... } }`) in `getClientCapabilities()` or fallback gracefully without compromising downstream encryption.
Components NEVER store derived master keys or evaluation outputs in persistent storage (e.g., localStorage, IndexedDB, sessionStorage)
Components NEVER store derived master keys or evaluation outputs in persistent storage (e.g., localStorage, IndexedDB, sessionStorage); only public salts and wrapped credentials may persist.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is Hardware-Bound Zero-Knowledge Key Derivation via WebAuthn PRF Extension critical for AI coding assistants?
Enforces strict cryptographic hygiene when using the WebAuthn Pseudo-Random Function (PRF) extension (hmac-secret) for zero-knowledge client-side encryption. Mandates domain-separated HKDF salt isolation, prevents PRF output transmission to relying parties, and ensures ephemerality of unpadded raw symmetric keys in browser memory. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.
Q:How does adopting this rule prevent AI hallucinations?
This rule explicitly declares what the AI must avoid (Directly Utilizing Raw PRF Outputs as Symmetric Cipher Keys or Leaking PRF Secrets to Relying Parties) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.
Q:Which AI coding environments are supported?
This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).
Q:Can I combine this rule with other technology stacks?
Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.