Microservice mesh boundary audit

A microservice mesh boundary audit validates the exposed surface where services communicate across network segments, clusters, and zones. The goal is to confirm that ingress and egress controls, routing rules, and identity verification mechanisms align with intended policy rather than accidental permissiveness. Unlike monolith pen tests that focus on a single host, a mesh audit examines API contracts, transport security, and authorization decisions across multiple hops.

Teams that skip a boundary audit often expose internal endpoints to the wider network, allow unverified service-to-service calls, and permit overly permissive CORS or wildcard policies. These gaps enable lateral movement, data exposure through over-fetching, and bypass of intended rate limits. Without visibility into routing and policy enforcement, misconfigurations remain until an incident reveals them.

A practical workflow starts with inventory: enumerate public entrypoints, service gateways, and ingress controllers. Next, validate transport security by checking HTTPS redirect, HSTS, and cookie flags for each endpoint. Then verify authorization boundaries by testing IDOR patterns, privilege escalation paths, and role/permission field exposure. Finally, confirm that rate limiting, input validation, and error handling behave as designed across the mesh. Record findings with request and response samples to support remediation and regression testing.

middleBrick scans public entrypoints to detect authentication bypass methods, JWT misconfigurations such as alg=none and missing claims, and security header deficiencies. It identifies BOLA and IDOR via sequential ID enumeration and active adjacent-ID probing, and flags BFLA indicators like admin endpoint exposure and role/permission leakage. The scanner surfaces input validation issues including CORS wildcard usage with credentials, dangerous HTTP methods, and debug endpoints, while mapping findings to OWASP API Top 10 (2023), PCI-DSS 4.0, and SOC 2 Type II controls.

For teams integrating LLM-based tooling into CI/CD or development workflows, middleBrick includes targeted probes for prompt injection, jailbreak attempts, and data exfiltration scenarios relevant to API surfaces. These checks run as part of the Standard and Deep scan tiers, exercising text-only POST methods to assess model handling of untrusted input. Results highlight risky patterns without requiring access to proprietary model internals or training data.