Architectural Invariant Design: Tauri 2.0 Mobile IPC Capability ACL Sandboxing
Tauri 2.0 Mobile IPC Capability ACL Sandboxing defines an industrial-grade behavioral standard for mobile engineering. Enforces principle-of-least-privilege Access Control Lists (ACL) and compile-time capability sandboxing for Tauri 2.0 mobile bridges. Restricts hybrid WebView IPC access to prevent cross-context script injection and unauthorized native capability invocation on iOS and Android targets. 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 | Exposing Wildcard IPC Capabilities or Global Plugin Grants to Mobile WebViews | 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 isolate mobile capabilities into dedicated JSON definitions under `src-tauri/capabilities/` scoped exclusively to explicit window labels (e.g., `windows
Engineers MUST ALWAYS isolate mobile capabilities into dedicated JSON definitions under `src-tauri/capabilities/` scoped exclusively to explicit window labels (e.g., `windows: ["main"]`).
Engineers MUST NOT grant wildcard permissions (`*
Engineers MUST NOT grant wildcard permissions (`*:*`, `core:default`, or unconstrained plugin roots like `fs:default` or `shell:default`) in mobile capabilities.
Engineers MUST ALWAYS scope filesystem, network, and hardware permissions to explicit path prefixes and host whitelists using granular permission objects rather than blanket flags.
Engineers MUST ALWAYS scope filesystem, network, and hardware permissions to explicit path prefixes and host whitelists using granular permission objects rather than blanket flags.
Code SHOULD enforce strict type-safe wrappers around `@tauri-apps/api/core` `invoke()` calls to prevent arbitrary string command invocation from the DOM.
Code SHOULD enforce strict type-safe wrappers around `@tauri-apps/api/core` `invoke()` calls to prevent arbitrary string command invocation from the DOM.
Services MUST validate IPC caller origins and reject dynamic command execution or string evaluation received from hybrid WebView events.
Services MUST validate IPC caller origins and reject dynamic command execution or string evaluation received from hybrid WebView events.
Components NEVER expose native bridge invocation primitives directly to the global `window` object or accept unvalidated postMessage payloads.
Components NEVER expose native bridge invocation primitives directly to the global `window` object or accept unvalidated postMessage payloads.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is Tauri 2.0 Mobile IPC Capability ACL Sandboxing critical for AI coding assistants?
Enforces principle-of-least-privilege Access Control Lists (ACL) and compile-time capability sandboxing for Tauri 2.0 mobile bridges. Restricts hybrid WebView IPC access to prevent cross-context script injection and unauthorized native capability invocation on iOS and Android targets. 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 (Exposing Wildcard IPC Capabilities or Global Plugin Grants to Mobile WebViews) 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.