OpenFGA Sub-10ms Batch Authorization and Ephemeral Context Pattern

Q: How does adopting this rule prevent AI hallucinations?

This rule explicitly declares what the AI must avoid (Sequential N+1 `client.check()` loops and transactional tuple writes for transient authorization state) 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.

OpenFGA Sub-10ms Batch Authorization and Ephemeral Context Pattern

--- description: OpenFGA Sub-10ms Batch Authorization and Ephemeral Context Pattern - Enforces high-throughput ReBAC evaluation patterns using OpenFGA by prohibiting iterative sequential checks and ephemeral write operations. Mandates client-side batching (`batchCheck`), contextual tuple injection, and strict fail-closed fallbacks to resolve complex relationship graph traversals within a sub-10ms latency budget. globs: src/auth/**/*.ts, src/security/**/*.ts, src/middleware/**/*.ts, src/services/**/*.ts alwaysApply: true verified_by: "agentrules.org" license: "CC-BY-4.0" source: "https://agentrules.org/rules/openfga-rebac-batch-evaluation-pattern" --- # OpenFGA Sub-10ms Batch Authorization and Ephemeral Context Pattern > **Severity**: CRITICAL | **Category**: security > **Anti-Pattern Warning**: Sequential N+1 `client.check()` loops and transactional tuple writes for transient authorization state ## System Constraints You are a Principal Security Architect enforcing production OpenFGA ReBAC patterns. You must reject sequential N+1 authorization loops, mutable store pollution with ephemeral context, and synchronous tuple writes inside primary request paths. Mandate `client.batchCheck`, contextual tuple parameters, and fail-closed evaluation budgets under 10ms. ## Strict Guidelines - Engineers MUST ALWAYS evaluate authorization across collections using `client.batchCheck` or `client.listObjects` instead of iterating sequential `client.check` calls. - Engineers MUST inject transient or session-scoped relationships (e.g., IP boundaries, temporary elevated roles) via `contextualTuples` on the check request rather than persisting temporary tuples to the OpenFGA storage backend. - Services MUST enforce strict fail-closed semantics; any network timeout, OpenFGA transport fault, or unparsed check resolution MUST default to unauthorized (`allowed: false`). - Services MUST configure OpenFGA SDK clients with connection pooling (HTTP keep-alive), an aggressive timeout budget (<= 15ms total, targeting <= 8ms P99 server latency), and exponential jittered retries for transient HTTP 5xx codes. - Engineers MUST NOT execute OpenFGA tuple writes synchronously within application database transactions; tuple synchronization MUST be mediated via outbox events or Change Data Capture (CDC). ## Bad vs Good Implementations ### Batch Check with Contextual Tuples vs Sequential N+1 Write-and-Check #### Bad Antipattern (AI Common Hallucination) > **Why it fails**: Performs synchronous tuple mutation for ephemeral request context, polluting the store and creating race conditions. Sequentially awaits network roundtrips for each item (N+1 anti-pattern), compounding network latency to hundreds of milliseconds. ```typescript import { OpenFgaClient } from '@openfga/sdk'; export async function filterAuthorizedDocuments( fgaClient: OpenFgaClient, userId: string, tenantId: string, documentIds: string[], clientIp: string ): Promise<string[]> { const allowedDocIds: string[] = []; // ANTI-PATTERN: Writing transient context directly into the persistent store await fgaClient.write({ writes: [{ user: `user:${userId}`, relation: 'access_requester', object: `tenant:${tenantId}` }] }); // ANTI-PATTERN: N+1 sequential check calls across resource collection for (const docId of documentIds) { const response = await fgaClient.check({ user: `user:${userId}`, relation: 'viewer', object: `document:${docId}` }); if (response.allowed) { allowedDocIds.push(docId); } } return allowedDocIds; } ``` #### Production Standard (Correct) > **Standard**: Eliminates persistent storage pollution by passing temporary relationships in contextualTuples. Dispatches a single parallelized batchCheck adhering to bounded parallelism and enforces a fail-closed return array on any failure mode. ```typescript import { OpenFgaClient, ClientBatchCheckItem } from '@openfga/sdk'; export async function filterAuthorizedDocuments( fgaClient: OpenFgaClient, userId: string, tenantId: string, documentIds: string[], clientIp: string ): Promise<string[]> { if (documentIds.length === 0) return []; // Ephemeral attributes injected per-request without store persistence const contextualTuples = [{ user: `user:${userId}`, relation: 'access_requester', object: `tenant:${tenantId}` }]; const checks: ClientBatchCheckItem[] = documentIds.map((docId) => ({ user: `user:${userId}`, relation: 'viewer', object: `document:${docId}`, contextualTuples })); try { // Parallelized graph traversal evaluation executed in a single atomic payload const batchResponse = await fgaClient.batchCheck(checks, { maxParallelRequests: 10 }); return batchResponse.responses .filter((res) => res.allowed === true) .map((res) => { const [, id] = res._request.object.split(':'); return id; }); } catch (error) { // Invariant: Enforce fail-closed security boundary on RPC or timeout failures return []; } } ```

Architectural Specification & Invariant Rationale

Architectural Invariant Design: OpenFGA Sub-10ms Batch Authorization and Ephemeral Context Pattern

OpenFGA Sub-10ms Batch Authorization and Ephemeral Context Pattern defines an industrial-grade behavioral standard for security engineering. Enforces high-throughput ReBAC evaluation patterns using OpenFGA by prohibiting iterative sequential checks and ephemeral write operations. Mandates client-side batching (`batchCheck`), contextual tuple injection, and strict fail-closed fallbacks to resolve complex relationship graph traversals within a sub-10ms latency budget. 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: Sequential N+1 `client.check()` loops and transactional tuple writes for transient authorization state 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	Sequential N+1 `client.check()` loops and transactional tuple writes for transient authorization state	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 evaluate authorization across collections using `client.batchCheck` or `client.listObjects` instead of iterating sequential `client.check` calls.

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.