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securitycritical PriorityID: openfga-contextual-tuple-cdc-invalidation

OpenFGA 1.8 Contextual Tuple Invalidation via Postgres CDC Guardrail

Enforces deterministic consistency between PostgreSQL relationship mutations and OpenFGA 1.8 checks by eliminating the replication-lag authorization window. Mandates that in-flight or uncommitted transactional state must be evaluated using OpenFGA Contextual Tuples derived from transactional Outbox CDC events until Postgres write-ahead log (WAL) streams guarantee monotonic OpenFGA tuple persistence.

Prohibited Anti-Pattern: Blind Trust in OpenFGA Eventual Consistency Without Contextual Tuples During Postgres Replication Lag

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---
description: OpenFGA 1.8 Contextual Tuple Invalidation via Postgres CDC Guardrail - Enforces deterministic consistency between PostgreSQL relationship mutations and OpenFGA 1.8 checks by eliminating the replication-lag authorization window. Mandates that in-flight or uncommitted transactional state must be evaluated using OpenFGA Contextual Tuples derived from transactional Outbox CDC events until Postgres write-ahead log (WAL) streams guarantee monotonic OpenFGA tuple persistence.
globs: src/authz/**/*.{ts,js}, src/services/authorization/**/*.{ts,js}, src/repositories/**/*.{ts,js}, src/cdc/**/*.{ts,js}
alwaysApply: true
verified_by: "agentrules.org"
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/openfga-contextual-tuple-cdc-invalidation"
---

# OpenFGA 1.8 Contextual Tuple Invalidation via Postgres CDC Guardrail

> **Severity**: CRITICAL | **Category**: security
> **Anti-Pattern Warning**: Blind Trust in OpenFGA Eventual Consistency Without Contextual Tuples During Postgres Replication Lag

## System Constraints
You are a Principal Security Architect enforcing zero-trust authorization consistency using OpenFGA 1.8 and Postgres CDC. Distributed systems often suffer from replication lag between the transactional database (Postgres) and OpenFGA's internal datastore, causing stale privilege escalation or unauthorized access after revocation. You must mandate that any authorization check occurring within the transactional boundary or prior to confirmed CDC ingestion must supply uncommitted/in-flight mutations as contextual tuples, or utilize monotonic CDC sequence tracking to reject stale checks.

## Strict Guidelines
- Engineers MUST ALWAYS supply pending or unacknowledged relationship state changes as `contextual_tuples` to `openfga.check()` calls within the same transaction or read-your-own-writes (RYOW) window.
- Engineers MUST NOT rely solely on asynchronous OpenFGA write mutations when immediate read-after-write authorization authorization decisions are executed.
- Services MUST publish OpenFGA tuple updates via a transactional outbox table in Postgres in the exact same database transaction that updates business domain entities.
- CDC consumer workers MUST write committed outbox tuples to OpenFGA using `client.write()` and emit high-watermark LSN (Log Sequence Number) or transaction sequence updates to distributed caches (e.g., Redis).
- Authorization check resolvers MUST compare the client session's last written LSN against the CDC ingestion watermark, and automatically inject contextual tuples if the CDC ingestion lag exceeds zero.

## Bad vs Good Implementations
### Prevent Stale Authorization Checks via Outbox Contextual Tuple Injection

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: The check directly queries OpenFGA without accounting for propagation latency between PostgreSQL and OpenFGA's backend. Immediately after revocation, a concurrent check evaluation can return `allowed: true`, creating a stale privilege escalation vulnerability.
```typescript
import { OpenFgaClient } from '@openfga/sdk';
import { db } from './database';

const fgaClient = new OpenFgaClient({ apiUrl: process.env.FGA_API_URL! });

export async function revokeMembership(workspaceId: string, userId: string): Promise<void> {
  // 1. Mutate Postgres relation
  await db.query('DELETE FROM workspace_memberships WHERE workspace_id = $1 AND user_id = $2', [workspaceId, userId]);
  
  // 2. Fire and forget to OpenFGA (or rely purely on async CDC)
  fgaClient.write({
    deletes: [{
      user: `user:${userId}`,
      relation: 'member',
      object: `workspace:${workspaceId}`
    }]
  }).catch(console.error);
}

export async function checkAccess(workspaceId: string, userId: string): Promise<boolean> {
  // Flaw: Replication lag between Postgres CDC and OpenFGA tuple store leads to stale authorization grants
  const { allowed } = await fgaClient.check({
    user: `user:${userId}`,
    relation: 'member',
    object: `workspace:${workspaceId}`
  });
  return allowed ?? false;
}
```

#### Production Standard (Correct)
> **Standard**: Implements the transactional outbox pattern and monotonic Log Sequence Number (LSN) tracking. If the CDC worker has not acknowledged ingestion up to `clientLsn`, contextual state is evaluated to invalidate stale grants before calling OpenFGA.
```typescript
import { OpenFgaClient, ClientCheckRequest } from '@openfga/sdk';
import { db } from './database';
import { redis } from './cache';

const fgaClient = new OpenFgaClient({ apiUrl: process.env.FGA_API_URL! });

export async function revokeMembershipTransactional(workspaceId: string, userId: string): Promise<{ lsn: string }> {
  return await db.transaction(async (tx) => {
    await tx.query('DELETE FROM workspace_memberships WHERE workspace_id = $1 AND user_id = $2', [workspaceId, userId]);
    
    // Write to CDC Outbox within the same atomic transaction
    const result = await tx.query(
      `INSERT INTO fga_outbox (operation, tuple_user, tuple_relation, tuple_object) 
       VALUES ('DELETE', $1, 'member', $2) 
       RETURNING pg_current_wal_lsn()::text AS lsn`,
      [`user:${userId}`, `workspace:${workspaceId}`]
    );
    
    return { lsn: result.rows[0].lsn };
  });
}

export async function checkAccessConsistent(
  workspaceId: string,
  userId: string,
  clientLsn?: string
): Promise<boolean> {
  const currentCdcLsn = await redis.get('fga:cdc:watermark_lsn') ?? '0/0';
  const isStale = clientLsn && clientLsn > currentCdcLsn;

  const checkPayload: ClientCheckRequest = {
    user: `user:${userId}`,
    relation: 'member',
    object: `workspace:${workspaceId}`
  };

  // Invalidate stale OpenFGA state via Contextual Tuples if CDC has not caught up
  if (isStale) {
    const activeOutboxPending = await db.query(
      `SELECT operation, tuple_user, tuple_relation, tuple_object 
       FROM fga_outbox WHERE tuple_object = $1 AND tuple_user = $2 AND processed = false`,
      [`workspace:${workspaceId}`, `user:${userId}`]
    );

    if (activeOutboxPending.rows.some((row: { operation: string }) => row.operation === 'DELETE')) {
      // Explicit negative assertion: OpenFGA evaluation considers in-flight contextual overrides
      return false;
    }
  }

  const { allowed } = await fgaClient.check(checkPayload);
  return allowed ?? false;
}
```

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Architectural Specification & Invariant Rationale

Architectural Invariant Design: OpenFGA 1.8 Contextual Tuple Invalidation via Postgres CDC Guardrail

OpenFGA 1.8 Contextual Tuple Invalidation via Postgres CDC Guardrail defines an industrial-grade behavioral standard for security engineering. Enforces deterministic consistency between PostgreSQL relationship mutations and OpenFGA 1.8 checks by eliminating the replication-lag authorization window. Mandates that in-flight or uncommitted transactional state must be evaluated using OpenFGA Contextual Tuples derived from transactional Outbox CDC events until Postgres write-ahead log (WAL) streams guarantee monotonic OpenFGA tuple persistence. 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: Blind Trust in OpenFGA Eventual Consistency Without Contextual Tuples During Postgres Replication Lag 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 DriftBlind Trust in OpenFGA Eventual Consistency Without Contextual Tuples During Postgres Replication LagCritical
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 supply pending or unacknowledged relationship state changes as `contextual_tuples` to `openfga.check()` calls within the same transaction or read-your-own-writes (RYOW) window.

Engineers MUST ALWAYS supply pending or unacknowledged relationship state changes as `contextual_tuples` to `openfga.check()` calls within the same transaction or read-your-own-writes (RYOW) window.

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 rely solely on asynchronous OpenFGA write mutations when immediate read-after-write authorization authorization decisions are executed.

Engineers MUST NOT rely solely on asynchronous OpenFGA write mutations when immediate read-after-write authorization authorization decisions are executed.

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

Services MUST publish OpenFGA tuple updates via a transactional outbox table in Postgres in the exact same database transaction that updates business domain entities.

Services MUST publish OpenFGA tuple updates via a transactional outbox table in Postgres in the exact same database transaction that updates business domain entities.

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

CDC consumer workers MUST write committed outbox tuples to OpenFGA using `client.write()` and emit high-watermark LSN (Log Sequence Number) or transaction sequence updates to distributed caches (e.g., Redis).

CDC consumer workers MUST write committed outbox tuples to OpenFGA using `client.write()` and emit high-watermark LSN (Log Sequence Number) or transaction sequence updates to distributed caches (e.g., Redis).

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

Authorization check resolvers MUST compare the client session's last written LSN against the CDC ingestion watermark, and automatically inject contextual tuples if the CDC ingestion lag exceeds zero.

Authorization check resolvers MUST compare the client session's last written LSN against the CDC ingestion watermark, and automatically inject contextual tuples if the CDC ingestion lag exceeds zero.

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 1.8 Contextual Tuple Invalidation via Postgres CDC Guardrail critical for AI coding assistants?

Enforces deterministic consistency between PostgreSQL relationship mutations and OpenFGA 1.8 checks by eliminating the replication-lag authorization window. Mandates that in-flight or uncommitted transactional state must be evaluated using OpenFGA Contextual Tuples derived from transactional Outbox CDC events until Postgres write-ahead log (WAL) streams guarantee monotonic OpenFGA tuple persistence. 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 (Blind Trust in OpenFGA Eventual Consistency Without Contextual Tuples During Postgres Replication Lag) 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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