Architectural Invariant Design: Capacitor 7 Hardware-Backed WebAuthn PRF Invariant
Capacitor 7 Hardware-Backed WebAuthn PRF Invariant defines an industrial-grade behavioral standard for mobile engineering. Enforces client-side deterministic key derivation via WebAuthn Pseudo-Random Function (PRF) extensions in Capacitor 7 hybrid applications. Mandates that local encryption keys are transiently derived on-demand from secure hardware authenticators without ever persisting raw master secrets or encryption keys in WebView storage, secure storage plugins, or client-side disk caches. 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 | Persisting Raw Symmetric Encryption Keys in Local Storage or Keystore Plugins | 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 invoke `navigator.credentials.get()` with `extensions
Engineers MUST ALWAYS invoke `navigator.credentials.get()` with `extensions: { prf: { eval: { first: saltBuffer } } }` to derive storage encryption keys dynamically.
Engineers MUST NOT persist derived WebAuthn PRF symmetric keys (`CryptoKey` or raw buffers) to persistent storage, SQLite, IndexedDB, or Keychain/Keystore plugins.
Engineers MUST NOT persist derived WebAuthn PRF symmetric keys (`CryptoKey` or raw buffers) to persistent storage, SQLite, IndexedDB, or Keychain/Keystore plugins.
Code MUST pass the derived PRF output through HKDF-SHA-256 with an app-specific context salt before utilizing it as an AES-GCM-256 key for local database encryption.
Code MUST pass the derived PRF output through HKDF-SHA-256 with an app-specific context salt before utilizing it as an AES-GCM-256 key for local database encryption.
Services MUST clear sensitive buffers in memory (`Uint8Array.fill(0)`) immediately after wrapping or unwrap operations complete.
Services MUST clear sensitive buffers in memory (`Uint8Array.fill(0)`) immediately after wrapping or unwrap operations complete.
Components NEVER accept raw passwords or static tokens to unlock client databases
Components NEVER accept raw passwords or static tokens to unlock client databases; credential unlock MUST be gated by hardware biometrics via the platform authenticator.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is Capacitor 7 Hardware-Backed WebAuthn PRF Invariant critical for AI coding assistants?
Enforces client-side deterministic key derivation via WebAuthn Pseudo-Random Function (PRF) extensions in Capacitor 7 hybrid applications. Mandates that local encryption keys are transiently derived on-demand from secure hardware authenticators without ever persisting raw master secrets or encryption keys in WebView storage, secure storage plugins, or client-side disk caches. 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 (Persisting Raw Symmetric Encryption Keys in Local Storage or Keystore Plugins) 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.