OpenFGA 1.8+ Snapshot Token Read-After-Write Causality Guardrail

--- description: OpenFGA 1.8+ Snapshot Token Read-After-Write Causality Guardrail - Mandates strict capture, propagation, and consumption of OpenFGA snapshot consistency tokens across distributed write-to-check boundaries. Eliminates authorization race conditions caused by database read-replica lag where authorization checks falsely deny legitimate requests immediately following tuple writes. globs: src/**/*.ts, src/**/*.controller.ts, src/**/*.service.ts, src/auth/**/*.ts, src/middleware/**/*.ts alwaysApply: true verified_by: "agentrules.org" license: "CC-BY-4.0" source: "https://agentrules.org/rules/openfga-snapshot-token-causality-guardrail" --- # OpenFGA 1.8+ Snapshot Token Read-After-Write Causality Guardrail > **Severity**: CRITICAL | **Category**: security > **Anti-Pattern Warning**: Ignoring OpenFGA Write Consistency Tokens Leading to Read-After-Write Stale Authorization Failures ## System Constraints You are a Principal Security Architect enforcing strict transactional causality in OpenFGA 1.8+ authorization pipelines. You must mandate that every OpenFGA relationship tuple mutation extracts the returned consistency/snapshot token, propagates it across microservice network boundaries (via HTTP headers, gRPC metadata, or message envelopes), and supplies it to downstream check evaluations to prevent replica-lag authorization bypasses or false negatives. ## Strict Guidelines - Engineers MUST ALWAYS capture the consistency token (or snapshot token) returned from OpenFGA write or delete tuple operations. - Engineers MUST NOT issue OpenFGA check, expand, or list-objects calls under immediate causal dependency without passing the recorded consistency token. - Services MUST propagate the consistency token upstream to callers using standard boundary envelopes, such as the 'X-OpenFGA-Consistency-Token' HTTP response header or CloudEvents metadata. - Downstream consumers MUST extract the consistency token from incoming request contexts and feed it into the OpenFGA client check request configuration. - Components NEVER fall back to uncoordinated MINIMIZE_LATENCY checks when evaluating access right after resource creation or membership assignment. ## Bad vs Good Implementations ### Tuple Mutation and Subsequent Check across Distributed Context #### Bad Antipattern (AI Common Hallucination) > **Why it fails**: The write operation discards the consistency token returned by OpenFGA. When a client performs an immediate follow-up read or check, the check evaluates against an asynchronous read replica that may not have ingested the write, causing transient false negatives (unauthorized errors). ```typescript import { OpenFgaClient } from '@openfga/sdk'; import { Request, Response } from 'express'; const fgaClient = new OpenFgaClient({ apiUrl: process.env.FGA_API_URL, storeId: process.env.FGA_STORE_ID, }); export async function grantAccess(req: Request, res: Response) { const { userId, documentId } = req.body; // BAD: Ignoring the response containing the snapshot/consistency token await fgaClient.write({ writes: [{ user: `user:${userId}`, relation: 'editor', object: `doc:${documentId}`, }], }); return res.status(200).json({ success: true }); } export async function verifyAccess(req: Request, res: Response) { const { userId, documentId } = req.params; // BAD: Default check reads from read-replica without consistency constraints. // Immediate check right after grantAccess can result in false 403 due to replica lag. const { allowed } = await fgaClient.check({ user: `user:${userId}`, relation: 'editor', object: `doc:${documentId}`, }); if (!allowed) { return res.status(403).json({ error: 'Forbidden' }); } return res.status(200).json({ content: 'Document content' }); } ``` #### Production Standard (Correct) > **Standard**: The write operation extracts the OpenFGA consistency token and returns it through HTTP headers. The authorization check consumes this token via client options, enforcing transactional causality and ensuring replica reads satisfy read-after-write guarantees. ```typescript import { OpenFgaClient, ConsistencyPreference } from '@openfga/sdk'; import { Request, Response } from 'express'; const fgaClient = new OpenFgaClient({ apiUrl: process.env.FGA_API_URL, storeId: process.env.FGA_STORE_ID, }); const CONSISTENCY_HEADER = 'x-openfga-consistency-token'; export async function grantAccess(req: Request, res: Response) { const { userId, documentId } = req.body; // GOOD: Extract consistency_token from OpenFGA 1.8+ write response const writeResult = await fgaClient.write({ writes: [{ user: `user:${userId}`, relation: 'editor', object: `doc:${documentId}`, }], }); // Propagate snapshot token downstream via response header if (writeResult.consistency_token) { res.setHeader(CONSISTENCY_HEADER, writeResult.consistency_token); } return res.status(200).json({ success: true, consistencyToken: writeResult.consistency_token, }); } export async function verifyAccess(req: Request, res: Response) { const { userId, documentId } = req.params; const consistencyToken = req.headers[CONSISTENCY_HEADER] as string | undefined; // GOOD: Apply consistency token or fallback to HIGHER_CONSISTENCY if causal dependency exists const { allowed } = await fgaClient.check( { user: `user:${userId}`, relation: 'editor', object: `doc:${documentId}`, consistency: consistencyToken ? undefined : ConsistencyPreference.HigherConsistency, }, { consistencyToken: consistencyToken, } ); if (!allowed) { return res.status(403).json({ error: 'Forbidden' }); } return res.status(200).json({ content: 'Document content' }); } ```

Architectural Specification & Invariant Rationale

Architectural Invariant Design: OpenFGA 1.8+ Snapshot Token Read-After-Write Causality Guardrail

OpenFGA 1.8+ Snapshot Token Read-After-Write Causality Guardrail defines an industrial-grade behavioral standard for security engineering. Mandates strict capture, propagation, and consumption of OpenFGA snapshot consistency tokens across distributed write-to-check boundaries. Eliminates authorization race conditions caused by database read-replica lag where authorization checks falsely deny legitimate requests immediately following tuple writes. 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: Ignoring OpenFGA Write Consistency Tokens Leading to Read-After-Write Stale Authorization Failures 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 Mode	AI Symptom (The Anti-Pattern)	Severity	Production Impact & Remedy
AI Hallucination & Deprecation Drift	Ignoring OpenFGA Write Consistency Tokens Leading to Read-After-Write Stale Authorization Failures	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.

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:

Engineers MUST ALWAYS capture the consistency token (or snapshot token) returned from OpenFGA write or delete tuple operations.

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.