Architectural Invariant Design: Strict CSP L3 Nonce Injection, Strict-Dynamic, and Trusted Types Enforcement
Strict CSP L3 Nonce Injection, Strict-Dynamic, and Trusted Types Enforcement defines an industrial-grade behavioral standard for security engineering. Enforces dynamic, cryptographically secure per-request nonce generation for Content Security Policy Level 3 compliance across all SSR/edge layers. Mandates the elimination of 'unsafe-inline' and 'unsafe-eval' via 'strict-dynamic' and prevents client-side DOM-XSS sinks by enforcing Trusted Types policies. 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 | Reusing static nonces, allowing 'unsafe-inline', or bypassing Trusted Types sanitization sinks | 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 generate an unguessable, cryptographically random nonce (at least 128 bits of entropy, e.g., base64-encoded crypto.randomBytes(16)) per unique HTTP request lifecycle.
Engineers MUST ALWAYS generate an unguessable, cryptographically random nonce (at least 128 bits of entropy, e.g., base64-encoded crypto.randomBytes(16)) per unique HTTP request lifecycle.
Engineers MUST NOT cache responses containing nonces across multiple users or requests
Engineers MUST NOT cache responses containing nonces across multiple users or requests; dynamic nonce headers must always be accompanied by 'Cache-Control: no-store, private' or applied exclusively via edge/runtime middleware.
Engineers MUST eliminate 'unsafe-inline' and 'unsafe-eval' from 'script-src' and pair nonces with ''strict-dynamic'' to allow trusted root scripts to load dependencies transitively.
Engineers MUST eliminate 'unsafe-inline' and 'unsafe-eval' from 'script-src' and pair nonces with ''strict-dynamic'' to allow trusted root scripts to load dependencies transitively.
Services MUST emit CSP headers containing 'require-trusted-types-for 'script'' and restrict policy creation using 'trusted-types <policy-name>' to prevent untrusted string assignments to executable sinks.
Services MUST emit CSP headers containing 'require-trusted-types-for 'script'' and restrict policy creation using 'trusted-types <policy-name>' to prevent untrusted string assignments to executable sinks.
Components NEVER bind user-controlled input directly into inline script execution blocks or DOM sinks (e.g., innerHTML, eval, Function, setTimeout strings) without passing through a registered Trusted Types policy.
Components NEVER bind user-controlled input directly into inline script execution blocks or DOM sinks (e.g., innerHTML, eval, Function, setTimeout strings) without passing through a registered Trusted Types policy.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is Strict CSP L3 Nonce Injection, Strict-Dynamic, and Trusted Types Enforcement critical for AI coding assistants?
Enforces dynamic, cryptographically secure per-request nonce generation for Content Security Policy Level 3 compliance across all SSR/edge layers. Mandates the elimination of 'unsafe-inline' and 'unsafe-eval' via 'strict-dynamic' and prevents client-side DOM-XSS sinks by enforcing Trusted Types policies. 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 (Reusing static nonces, allowing 'unsafe-inline', or bypassing Trusted Types sanitization sinks) 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.