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securitycritical PriorityID: openfga-contextual-tuple-staleness-invariant

OpenFGA 1.6 Contextual Tuple Staleness and Zero-Drift ReBAC Invariant

Mandates contextual tuple injection and transactional replication-lag mitigation for OpenFGA 1.6 relationship-based access control (ReBAC). Guarantees zero authorization drift and prevents TOCTOU permission bypasses during high-throughput concurrent writes across distributed evaluation clusters.

Prohibited Anti-Pattern: Evaluating Authorization Decisions Against Asynchronously Replicated State Without Contextual Tuple Injection

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---
description: OpenFGA 1.6 Contextual Tuple Staleness and Zero-Drift ReBAC Invariant - Mandates contextual tuple injection and transactional replication-lag mitigation for OpenFGA 1.6 relationship-based access control (ReBAC). Guarantees zero authorization drift and prevents TOCTOU permission bypasses during high-throughput concurrent writes across distributed evaluation clusters.
globs: src/**/*.service.ts, src/**/*.guard.ts, src/**/authz/**/*.ts, src/**/permissions/**/*.ts
alwaysApply: true
verified_by: "agentrules.org"
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/openfga-contextual-tuple-staleness-invariant"
---

# OpenFGA 1.6 Contextual Tuple Staleness and Zero-Drift ReBAC Invariant

> **Severity**: CRITICAL | **Category**: security
> **Anti-Pattern Warning**: Evaluating Authorization Decisions Against Asynchronously Replicated State Without Contextual Tuple Injection

## System Constraints
You are a Principal Security Architect enforcing the OpenFGA 1.6 Contextual Tuple Staleness Invariant. Under high-throughput distributed mutations, relationship tuple writes experience replication lag and distributed cache propagation delays across OpenFGA evaluation nodes. You must mandate that any authorization check occurring within, immediately after, or downstream of a mutation transaction incorporates in-flight relationship state via contextual tuples to guarantee zero authorization drift.

## Strict Guidelines
- Engineers MUST ALWAYS inject active transactional mutations into `check` and `batchCheck` operations using `contextualTuples` when validating mutations or uncommitted state.
- Engineers MUST NOT issue bare `fgaClient.check()` calls immediately following `fgaClient.write()` without contextual tuples or explicit read-after-write consistency validation.
- Code SHOULD encapsulate contextual tuple generation within dedicated domain policy mappers to prevent state fragmentation across services.
- Services MUST fail closed if concurrent tuple writes and contextual checks disagree on terminal resource ownership states.
- Components NEVER assume persisted OpenFGA datastore replicas have achieved convergence immediately following write transactions in concurrent workloads.

## Bad vs Good Implementations
### Mitigating Distributed Replication Lag via Contextual Tuples in Mutation Guard

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: In a distributed OpenFGA cluster, writes are asynchronously propagated across read replicas and node caches. Calling check() immediately after write() without contextual tuples causes authorization drift, producing false negatives for the new owner or false positives for the revoked owner.
```typescript
import { OpenFgaClient } from '@openfga/sdk';

export async function transferDocumentOwnership(
  fgaClient: OpenFgaClient,
  documentId: string,
  currentOwnerId: string,
  newOwnerId: string
): Promise<void> {
  // Anti-Pattern: Tuple write followed by immediate naked check vulnerable to replica lag
  await fgaClient.write({
    writes: [{ user: `user:${newOwnerId}`, relation: 'owner', object: `doc:${documentId}` }],
    deletes: [{ user: `user:${currentOwnerId}`, relation: 'owner', object: `doc:${documentId}` }]
  });

  // Distributed cache / DB replica lag creates a race condition: old owner might still pass or new owner fails
  const { allowed } = await fgaClient.check({
    user: `user:${newOwnerId}`,
    relation: 'can_delete',
    object: `doc:${documentId}`
  });

  if (!allowed) {
    throw new Error('Authorization verification failed due to replica staleness');
  }
}
```

#### Production Standard (Correct)
> **Standard**: Injecting uncommitted state as contextualTuples enables deterministic evaluation without relying on distributed replica convergence. This eliminates TOCTOU races and maintains strict zero-drift invariants across evaluation nodes.
```typescript
import { OpenFgaClient, ClientTupleKey } from '@openfga/sdk';

export async function transferDocumentOwnership(
  fgaClient: OpenFgaClient,
  documentId: string,
  currentOwnerId: string,
  newOwnerId: string
): Promise<void> {
  const uncommittedTuples: ClientTupleKey[] = [
    { user: `user:${newOwnerId}`, relation: 'owner', object: `doc:${documentId}` }
  ];

  // 1. Contextual pre-flight check guarantees invariant validity before state persistence
  const { allowed } = await fgaClient.check({
    user: `user:${newOwnerId}`,
    relation: 'can_delete',
    object: `doc:${documentId}`,
    contextualTuples: uncommittedTuples
  });

  if (!allowed) {
    throw new Error('Authorization policy violation: target principal cannot satisfy required relations');
  }

  // 2. Persist relationship changes atomically
  await fgaClient.write({
    writes: uncommittedTuples,
    deletes: [{ user: `user:${currentOwnerId}`, relation: 'owner', object: `doc:${documentId}` }]
  });
}
```

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Architectural Specification & Invariant Rationale

Architectural Invariant Design: OpenFGA 1.6 Contextual Tuple Staleness and Zero-Drift ReBAC Invariant

OpenFGA 1.6 Contextual Tuple Staleness and Zero-Drift ReBAC Invariant defines an industrial-grade behavioral standard for security engineering. Mandates contextual tuple injection and transactional replication-lag mitigation for OpenFGA 1.6 relationship-based access control (ReBAC). Guarantees zero authorization drift and prevents TOCTOU permission bypasses during high-throughput concurrent writes across distributed evaluation clusters. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.

Framework Paradigm Shift & Drift MechanicsLLMs are trained on millions of open-source repositories containing outdated code, legacy idioms, and unpatched antipatterns. When coding assistants generate implementations for this stack, they default to common statistical tokens: Evaluating Authorization Decisions Against Asynchronously Replicated State Without Contextual Tuple Injection Without an explicit system instruction file, developers spend hours debugging silent failures.
Failure Modes & Production Blast Radius

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 ModeAI Symptom (The Anti-Pattern)SeverityProduction Impact & Remedy
AI Hallucination & Deprecation DriftEvaluating Authorization Decisions Against Asynchronously Replicated State Without Contextual Tuple InjectionCritical
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 InconsistencyAI 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.
Architectural Directives in Detail

Step-by-Step Production Directives

Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:

1

Engineers MUST ALWAYS inject active transactional mutations into `check` and `batchCheck` operations using `contextualTuples` when validating mutations or uncommitted state.

Engineers MUST ALWAYS inject active transactional mutations into `check` and `batchCheck` operations using `contextualTuples` when validating mutations or uncommitted state.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
2

Engineers MUST NOT issue bare `fgaClient.check()` calls immediately following `fgaClient.write()` without contextual tuples or explicit read-after-write consistency validation.

Engineers MUST NOT issue bare `fgaClient.check()` calls immediately following `fgaClient.write()` without contextual tuples or explicit read-after-write consistency validation.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
3

Code SHOULD encapsulate contextual tuple generation within dedicated domain policy mappers to prevent state fragmentation across services.

Code SHOULD encapsulate contextual tuple generation within dedicated domain policy mappers to prevent state fragmentation across services.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
4

Services MUST fail closed if concurrent tuple writes and contextual checks disagree on terminal resource ownership states.

Services MUST fail closed if concurrent tuple writes and contextual checks disagree on terminal resource ownership states.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
5

Components NEVER assume persisted OpenFGA datastore replicas have achieved convergence immediately following write transactions in concurrent workloads.

Components NEVER assume persisted OpenFGA datastore replicas have achieved convergence immediately following write transactions in concurrent workloads.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
Technical Questions & Answers

Frequently Asked Technical Questions

Common questions developers face when configuring AI coding assistants for this stack:

Q:Why is OpenFGA 1.6 Contextual Tuple Staleness and Zero-Drift ReBAC Invariant critical for AI coding assistants?

Mandates contextual tuple injection and transactional replication-lag mitigation for OpenFGA 1.6 relationship-based access control (ReBAC). Guarantees zero authorization drift and prevents TOCTOU permission bypasses during high-throughput concurrent writes across distributed evaluation clusters. 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 (Evaluating Authorization Decisions Against Asynchronously Replicated State Without Contextual Tuple Injection) 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.

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