Architectural Invariant Design: OpenFGA Monotonic Read Fence and Consistency Token Propagation
OpenFGA Monotonic Read Fence and Consistency Token Propagation defines an industrial-grade behavioral standard for security engineering. Enforces strict monotonic read consistency fences on OpenFGA authorization checks following relationship tuple mutations. Prevents transient authorization bypasses, permission leakage, and stale evaluation states across distributed database read replicas by mandating write-to-read consistency token propagation or HIGHER_CONSISTENCY read 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 | Executing un-fenced authorization checks or default MINIMIZE_LATENCY reads immediately after relationship tuple mutations | 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 configure `consistency
Engineers MUST ALWAYS configure `consistency: ConsistencyPreference.HIGHER_CONSISTENCY` on OpenFGA `check`, `expand`, and `listObjects` calls whenever the operation immediately follows a tuple write or revocation within the same logical workflow.
Engineers MUST NOT rely on OpenFGA's default `MINIMIZE_LATENCY` consistency mode in post-mutation validation guards or access revocation flows.
Engineers MUST NOT rely on OpenFGA's default `MINIMIZE_LATENCY` consistency mode in post-mutation validation guards or access revocation flows.
Services MUST propagate write transaction fences or consistency tokens across service boundaries via HTTP headers (e.g., `x-rebac-fence-token`) when client requests trigger dependent authorization queries.
Services MUST propagate write transaction fences or consistency tokens across service boundaries via HTTP headers (e.g., `x-rebac-fence-token`) when client requests trigger dependent authorization queries.
Components NEVER assume read-after-write consistency in distributed datastores (PostgreSQL, CockroachDB, MySQL) without explicitly signaling consistency requirements to the OpenFGA query engine.
Components NEVER assume read-after-write consistency in distributed datastores (PostgreSQL, CockroachDB, MySQL) without explicitly signaling consistency requirements to the OpenFGA query engine.
Security guards MUST fail closed with a transient 503 or retry with exponential backoff if a `HIGHER_CONSISTENCY` check fails to contact the primary database node or master replica.
Security guards MUST fail closed with a transient 503 or retry with exponential backoff if a `HIGHER_CONSISTENCY` check fails to contact the primary database node or master replica.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is OpenFGA Monotonic Read Fence and Consistency Token Propagation critical for AI coding assistants?
Enforces strict monotonic read consistency fences on OpenFGA authorization checks following relationship tuple mutations. Prevents transient authorization bypasses, permission leakage, and stale evaluation states across distributed database read replicas by mandating write-to-read consistency token propagation or HIGHER_CONSISTENCY read 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 (Executing un-fenced authorization checks or default MINIMIZE_LATENCY reads immediately after relationship tuple mutations) 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.