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securitycritical PriorityID: openfga-zookie-freshness-sla-guardrail

OpenFGA Zanzibar Consistency Token (Zookie) Freshness SLA Enforcement

Enforces read-after-write consistency across distributed microservices by binding OpenFGA relationship-based authorization evaluations to monotonically advancing Zanzibar consistency tokens (zookies/continuation tokens). Prevents the 'New Enemy' vulnerability and unauthorized data exposure caused by evaluating permissions against stale replicated storage snapshots.

Prohibited Anti-Pattern: Executing OpenFGA Check API calls without asserting minimal consistency token freshness after state mutation

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---
description: "OpenFGA Zanzibar Consistency Token (Zookie) Freshness SLA Enforcement - Enforces read-after-write consistency across distributed microservices by binding OpenFGA relationship-based authorization evaluations to monotonically advancing Zanzibar consistency tokens (zookies/continuation tokens). Prevents the 'New Enemy' vulnerability and unauthorized data exposure caused by evaluating permissions against stale replicated storage snapshots."
globs: "src/services/**/*.ts, src/controllers/**/*.ts, src/middleware/**/*.ts, src/clients/**/*.ts, src/authz/**/*.ts"
alwaysApply: true
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/openfga-zookie-freshness-sla-guardrail"
---

# OpenFGA Zanzibar Consistency Token (Zookie) Freshness SLA Enforcement

> **Severity**: CRITICAL | **Category**: security
> **Anti-Pattern Warning**: Executing OpenFGA Check API calls without asserting minimal consistency token freshness after state mutation

## System Constraints
You are a Principal Security Architect enforcing Zanzibar consistency token (zookie) semantics in OpenFGA-backed distributed systems. You must mandate that every state-mutating authorization write captures its resulting consistency token or transaction timestamp, and that subsequent reads and authorization checks enforce an explicit freshness boundary or pass the latest known token across service boundaries via distributed context propagation.

## Strict Guidelines
- Engineers MUST ALWAYS capture and propagate the consistency token or continuation token returned by OpenFGA write or mutation operations across upstream API responses.
- Engineers MUST NOT invoke OpenFGA client `check` or `batchCheck` without specifying `consistency: ConsistencyPreference.AtLeastAsFresh` or `consistency: ConsistencyPreference.HigherConsistency` when servicing read-after-write or cross-service dependent workflows.
- Services MUST propagate client-facing consistency tokens using standardized distributed context headers (e.g., `X-Zanzibar-Consistency-Token` or W3C Baggage) across asynchronous and synchronous microservice boundaries.
- Services MUST reject or elevate consistency levels if the client-asserted consistency token is newer than the local OpenFGA read replica's checkpoint, failing closed rather than serving stale permissions.
- Components NEVER fall back to eventual consistency (`ConsistencyPreference.MinimizeLatency`) for authorization checks that follow within the defined mutational SLA freshness window (e.g., 5000ms).

## Bad vs Good Implementations
### Stale Check Vulnerability vs. Strict Zookie Consistency Boundary Check

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: Omits the consistency token generated during the write transaction. A subsequent check against a replicated OpenFGA datastore defaults to eventual consistency, permitting a revoked user to access resources during the replication lag window.
```typescript
import { OpenFgaClient } from '@openfga/sdk';

export async function handleDocumentUpdate(
  fgaClient: OpenFgaClient,
  userId: string,
  documentId: string,
  newOwnerId: string
): Promise<void> {
  // Anti-Pattern: Revoking old access and granting new access
  await fgaClient.write({
    deletes: [{ user: `user:${userId}`, relation: 'owner', object: `doc:${documentId}` }],
    writes: [{ user: `user:${newOwnerId}`, relation: 'owner', object: `doc:${documentId}` }],
  });

  // Stale Read: Default MinimizeLatency hits read replica that hasn't caught up with write
  const { allowed } = await fgaClient.check({
    user: `user:${userId}`,
    relation: 'can_edit',
    object: `doc:${documentId}`,
  });

  if (allowed) {
    // Revoked user falsely permitted due to snapshot replication lag ('New Enemy' problem)
    await performSensitiveMutation(documentId);
  }
}
```

#### Production Standard (Correct)
> **Standard**: Captures the write mutation's continuation token and asserts `ConsistencyPreference.HigherConsistency` during permission checks, guaranteeing linearizability and eliminating the Zanzibar 'New Enemy' stale replica vulnerability.
```typescript
import { OpenFgaClient, ConsistencyPreference, ClientCheckResponse } from '@openfga/sdk';

interface AuthorizationContext {
  consistencyToken?: string;
}

export async function handleDocumentUpdate(
  fgaClient: OpenFgaClient,
  userId: string,
  documentId: string,
  newOwnerId: string,
  authContext: AuthorizationContext
): Promise<{ consistencyToken: string }> {
  // Capture the monotonic continuation token/zookie resulting from the mutation
  const writeResponse = await fgaClient.write({
    deletes: [{ user: `user:${userId}`, relation: 'owner', object: `doc:${documentId}` }],
    writes: [{ user: `user:${newOwnerId}`, relation: 'owner', object: `doc:${documentId}` }],
  });

  const freshToken = writeResponse.continuation_token ?? '';
  authContext.consistencyToken = freshToken;

  // Enforce monotonic consistency boundary matching the write's snapshot level
  const checkResponse: ClientCheckResponse = await fgaClient.check(
    {
      user: `user:${userId}`,
      relation: 'can_edit',
      object: `doc:${documentId}`,
    },
    {
      consistency: ConsistencyPreference.HigherConsistency,
    }
  );

  if (checkResponse.allowed) {
    await performSensitiveMutation(documentId);
  }

  return { consistencyToken: freshToken };
}
```
Recommended MCP Servers (mcp-serverlist.com)

Equip agent with system tools to verify code for this stack.

OpenFGA Policy & Model Inspector MCP
Inspects authorization models, validates relationship tuples, and tests evaluation consistency constraints against live OpenFGA stores.
Recommended Agent Skills (askills.dev)

Ready-to-use executable skill functions tailored to this stack.

OpenFGA Command Line Interface
Validates FGA authorization models, runs automated test assertions, and verifies tuple consistency boundaries.
Architectural Specification & Invariant Rationale

Architectural Invariant Design: OpenFGA Zanzibar Consistency Token (Zookie) Freshness SLA Enforcement

OpenFGA Zanzibar Consistency Token (Zookie) Freshness SLA Enforcement defines an industrial-grade behavioral standard for security engineering. Enforces read-after-write consistency across distributed microservices by binding OpenFGA relationship-based authorization evaluations to monotonically advancing Zanzibar consistency tokens (zookies/continuation tokens). Prevents the 'New Enemy' vulnerability and unauthorized data exposure caused by evaluating permissions against stale replicated storage snapshots. 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: Executing OpenFGA Check API calls without asserting minimal consistency token freshness after state mutation 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 DriftExecuting OpenFGA Check API calls without asserting minimal consistency token freshness after state mutationCritical
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 capture and propagate the consistency token or continuation token returned by OpenFGA write or mutation operations across upstream API responses.

Engineers MUST ALWAYS capture and propagate the consistency token or continuation token returned by OpenFGA write or mutation operations across upstream API responses.

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 invoke OpenFGA client `check` or `batchCheck` without specifying `consistency

Engineers MUST NOT invoke OpenFGA client `check` or `batchCheck` without specifying `consistency: ConsistencyPreference.AtLeastAsFresh` or `consistency: ConsistencyPreference.HigherConsistency` when servicing read-after-write or cross-service dependent workflows.

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 propagate client-facing consistency tokens using standardized distributed context headers (e.g., `X-Zanzibar-Consistency-Token` or W3C Baggage) across asynchronous and synchronous microservice boundaries.

Services MUST propagate client-facing consistency tokens using standardized distributed context headers (e.g., `X-Zanzibar-Consistency-Token` or W3C Baggage) across asynchronous and synchronous microservice boundaries.

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 reject or elevate consistency levels if the client-asserted consistency token is newer than the local OpenFGA read replica's checkpoint, failing closed rather than serving stale permissions.

Services MUST reject or elevate consistency levels if the client-asserted consistency token is newer than the local OpenFGA read replica's checkpoint, failing closed rather than serving stale permissions.

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 fall back to eventual consistency (`ConsistencyPreference.MinimizeLatency`) for authorization checks that follow within the defined mutational SLA freshness window (e.g., 5000ms).

Components NEVER fall back to eventual consistency (`ConsistencyPreference.MinimizeLatency`) for authorization checks that follow within the defined mutational SLA freshness window (e.g., 5000ms).

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 Zanzibar Consistency Token (Zookie) Freshness SLA Enforcement critical for AI coding assistants?

Enforces read-after-write consistency across distributed microservices by binding OpenFGA relationship-based authorization evaluations to monotonically advancing Zanzibar consistency tokens (zookies/continuation tokens). Prevents the 'New Enemy' vulnerability and unauthorized data exposure caused by evaluating permissions against stale replicated storage snapshots. 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 (Executing OpenFGA Check API calls without asserting minimal consistency token freshness after state mutation) 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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