JWT claims-based access control in distribution management enabled granular permissions for regional warehouses

SCM Manhattan Active Supply Chain
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1

We recently implemented JWT claims-based access control for our distribution management APIs to enforce granular permissions across our multi-tenant environment. The challenge was moving beyond simple role-based access to attribute-based control where user claims determine what distribution centers, order types, and inventory zones they can access.

Our approach involved customizing JWT claim structure to include tenant_id, dc_access_list, and operation_scope attributes. We then built middleware that intercepts API requests and validates claims against the requested resource before allowing the operation. Here’s our claim validation logic:

String dcRequested = request.getParameter("dcId");
List<String> allowedDCs = jwtClaims.getStringListClaim("dc_access_list");
if (!allowedDCs.contains(dcRequested)) {
    throw new UnauthorizedException("Access denied to DC: " + dcRequested);
}

For audit compliance, every access decision is logged with claim details, requested resource, and outcome. This has significantly improved our security posture while maintaining API performance. The implementation handles claim refresh, token expiration, and graceful degradation when claims are missing. Anyone else implementing similar JWT-based access patterns in Manhattan SCALE?

2

The audit logging you mentioned is critical. We’re implementing similar patterns and found that structured logging with claim snapshots at decision points is essential. Do you use any specific audit trail format or integrate with SIEM tools? Also handling PII in claims - are you encrypting sensitive attributes within the JWT payload itself?

3

This is exactly the direction we’re heading. Currently using basic API keys but need finer control as we expand to more distribution partners. How are you handling claim updates when user permissions change? Do you force token refresh or wait for natural expiration? Also curious about your token lifetime settings.

4

Great questions on audit compliance and implementation details. Let me address the key aspects comprehensively.

JWT Claim Customization Strategy: Our JWT payload structure separates standard claims (iss, sub, exp) from custom Manhattan-specific claims in a nested object. We include: tenant_id, dc_access_list (array), operation_scope (read/write/admin), inventory_zones (array), and order_type_permissions. Claims are validated against a schema on token generation to prevent malformed data. For PII concerns, we use claim references rather than actual data - for example, storing role_id instead of role names with detailed descriptions.

API-Level Access Enforcement Architecture: We implemented a Spring interceptor that runs before Manhattan API controllers. The validation flow: 1) Extract JWT from Authorization header, 2) Verify signature using cached public keys (rotated monthly), 3) Check expiration and not-before timestamps, 4) Validate claims against requested resource parameters, 5) Check token blacklist for revocations, 6) Log decision with full context. The interceptor adds validated claims to request context for downstream use. Performance impact is 2-3ms per request with Redis caching for blacklist checks.

Audit Compliance Implementation: For SOC2 and ISO27001 compliance, we log every access decision (allow/deny) with structured JSON format including: timestamp, user_id, requested_resource, operation_type, claim_snapshot (sanitized), decision_outcome, decision_reason, source_ip, and correlation_id. Logs flow to our ELK stack with 90-day hot retention and 7-year cold storage. Access denials trigger real-time alerts in PagerDuty. We also generate monthly compliance reports showing access patterns, denial rates, and claim usage statistics. For SIEM integration, we push audit events to Splunk using HTTP Event Collector with custom source types for Manhattan-specific events.

Code Example - Complete Validation Flow:

// Pseudocode - JWT validation and enforcement:
1. Extract JWT token from Authorization Bearer header
2. Verify signature using cached RSA public key (refresh every 24h)
3. Parse claims and validate required fields exist
4. Check token expiration and not-before timestamps
5. Query Redis blacklist cache for revoked tokens
6. Extract resource constraints from API request parameters
7. Match dc_access_list claim against requested dcId
8. Validate operation_scope claim against HTTP method
9. Log access decision with claim snapshot and outcome
10. Return 403 with detailed error if validation fails
// See implementation: SecurityInterceptor.java:validateJWTClaims()

Key Lessons Learned:

  • Keep tokens short-lived (15 min access, 7 day refresh) to limit exposure window
  • Implement claim versioning from day one - we’re on v2 already
  • Cache validation results per request to avoid duplicate checks
  • Monitor token validation latency - it can become a bottleneck
  • Build admin tools for claim inspection and troubleshooting
  • Test token expiration and refresh flows thoroughly in load testing

The system has been production-stable for 8 months handling 2M+ API requests daily. Audit findings have been clean and the granular access control prevented several potential security incidents where users attempted to access unauthorized distribution centers.

5

We use short-lived access tokens (15 minutes) with longer refresh tokens (7 days). When permissions change in our identity provider, we invalidate the refresh token which forces full re-authentication on next access token renewal. For emergency revocations, we maintain a token blacklist cache checked on every request. The performance hit is minimal - about 2ms per validation. We also implemented a claim versioning system so gradual rollouts of new claim structures don’t break existing tokens. The key is keeping JWT validation stateless while having a lightweight revocation mechanism for critical scenarios.

6

How does this integrate with Manhattan’s native security model? Are you bypassing their authorization layer completely or layering on top? We’re concerned about maintaining upgrade compatibility if we customize too deeply.

7

From an audit perspective, what’s your logging granularity? Are you capturing enough detail to satisfy SOC2 and ISO27001 requirements? Specifically around access denials and claim mismatches.