OpenFGA 0.6 Contextual Tuple ReBAC Transactional Consistency Guardrail

--- description: OpenFGA 0.6 Contextual Tuple ReBAC Transactional Consistency Guardrail - Enforces strict transactional consistency in OpenFGA 0.6+ relationship-based authorization checks across distributed microservice boundaries. Mandates the use of contextual tuples and calibrated consistency preferences during mutation lifecycles to eliminate read-after-write authorization race conditions and Time-of-Check to Time-of-Use (TOCTOU) security bypasses. globs: src/**/*.ts, src/**/*.service.ts, src/auth/**/*.ts, src/guards/**/*.ts alwaysApply: true verified_by: "agentrules.org" license: "CC-BY-4.0" source: "https://agentrules.org/rules/openfga-contextual-tuple-rebac-consistency" --- # OpenFGA 0.6 Contextual Tuple ReBAC Transactional Consistency Guardrail > **Severity**: CRITICAL | **Category**: security > **Anti-Pattern Warning**: Stale ReBAC Evaluation Due to Asynchronous Tuple Ingestion Lag ## System Constraints You are a Principal Security Architect enforcing the OpenFGA 0.6 Contextual Tuple ReBAC Consistency Invariant. In distributed architectures, database transactions and OpenFGA tuple writes occur across distinct systems, creating eventual consistency lag. You must enforce that all in-flight, transient, or read-after-write authorization checks supply contextual tuples directly in the check request to guarantee zero-latency authorization consistency without risking replication race conditions. ## Strict Guidelines - Engineers MUST ALWAYS provide `contextual_tuples` in `client.check()` or `client.batchCheck()` calls when evaluating permissions immediately following or during transactional domain entity mutations. - Engineers MUST NOT rely on asynchronous outbox workers or event bus handlers to persist OpenFGA tuples prior to performing atomic authorization decisions on recently modified entities. - Services MUST explicitly specify the `consistency` parameter (`ConsistencyPreference.HIGHEST_CONSISTENCY` or `ConsistencyPreference.MINIMIZE_LATENCY`) on `CheckRequest` based on operational risk profile, avoiding client default ambiguities. - Components NEVER evaluate authorization against stale database entities without passing the tenant, session, or temporal relationship as contextual tuples if those relations have not been acknowledged by OpenFGA's storage engine. - Code SHOULD sanitize and structurally validate all ephemeral user-object tuples before injecting them into contextual check payloads to prevent contextual injection attacks. ## Bad vs Good Implementations ### In-flight Resource Transfer Authorization Check #### Bad Antipattern (AI Common Hallucination) > **Why it fails**: The check relies on the persisted state in the OpenFGA datastore immediately after a write. Under distributed replication or CDC pipeline lag, this causes read-after-write inconsistency, leading to false negatives or unauthorized fallback executions. ```typescript import { OpenFgaClient } from '@openfga/sdk'; export async function transferOwnership( fgaClient: OpenFgaClient, documentId: string, currentOwnerId: string, newOwnerId: string ): Promise<boolean> { // Anti-pattern: Async write followed by un-contextualized check induces TOCTOU race await fgaClient.write({ writes: [{ user: `user:${newOwnerId}`, relation: 'owner', _object: `document:${documentId}` }], deletes: [{ user: `user:${currentOwnerId}`, relation: 'owner', _object: `document:${documentId}` }], }); // Stale check: Storage replication lag causes this check to potentially return false or evaluate outdated owners const { allowed } = await fgaClient.check({ user: `user:${newOwnerId}`, relation: 'can_delete', _object: `document:${documentId}`, }); return allowed ?? false; } ``` #### Production Standard (Correct) > **Standard**: By injecting ephemeral contextual tuples into the check request and setting HIGHEST_CONSISTENCY, the authorization engine evaluates the permission graph incorporating the latest state in memory, completely bypassing replication delays. ```typescript import { OpenFgaClient, ConsistencyPreference, ClientCheckRequest } from '@openfga/sdk'; export async function verifyTransferEligibility( fgaClient: OpenFgaClient, documentId: string, candidateOwnerId: string, organizationId: string ): Promise<boolean> { // Invariant Fix: Pass proposed/in-flight relation as a contextual tuple with HIGHEST_CONSISTENCY const checkRequest: ClientCheckRequest = { user: `user:${candidateOwnerId}`, relation: 'can_manage', _object: `document:${documentId}`, contextualTuples: [ { user: `user:${candidateOwnerId}`, relation: 'owner', _object: `document:${documentId}`, }, { user: `organization:${organizationId}`, relation: 'parent', _object: `document:${documentId}`, }, ], consistency: ConsistencyPreference.HIGHEST_CONSISTENCY, }; const { allowed } = await fgaClient.check(checkRequest); return allowed ?? false; } ```

Architectural Specification & Invariant Rationale

Architectural Invariant Design: OpenFGA 0.6 Contextual Tuple ReBAC Transactional Consistency Guardrail

OpenFGA 0.6 Contextual Tuple ReBAC Transactional Consistency Guardrail defines an industrial-grade behavioral standard for security engineering. Enforces strict transactional consistency in OpenFGA 0.6+ relationship-based authorization checks across distributed microservice boundaries. Mandates the use of contextual tuples and calibrated consistency preferences during mutation lifecycles to eliminate read-after-write authorization race conditions and Time-of-Check to Time-of-Use (TOCTOU) security bypasses. 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: Stale ReBAC Evaluation Due to Asynchronous Tuple Ingestion 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 Mode	AI Symptom (The Anti-Pattern)	Severity	Production Impact & Remedy
AI Hallucination & Deprecation Drift	Stale ReBAC Evaluation Due to Asynchronous Tuple Ingestion Lag	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 provide `contextual_tuples` in `client.check()` or `client.batchCheck()` calls when evaluating permissions immediately following or during transactional domain entity mutations.

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.