Use case ยท API infrastructure

Continuous correctness audits for API infrastructure.

For GraphQL routers, gateways, parsers, SDKs, protocol engines, and OSS infrastructure where one edge-case regression can affect many downstream users.

Apollo Router / WunderGraph / Hive style systems
Risk profileBest fit
Risk

Parser, validation, routing, execution, federation, and SDK behavior drift silently across releases.

Buyer

Founder, maintainer, CTO, platform lead, security owner.

Evidence

Private reports, reproducible findings, patch verification, and public field notes only when approved.

What Proof checks

Behavior that sits between users and every request.

Parsing and validation

Inputs, directives, schema behavior, normalization, validation, and edge-case failure modes.

Execution and routing

Planner behavior, subscription paths, federation, retries, cancellation, concurrency, and state handling.

Release regression

Version-to-version behavior changes backed by reproducers and evidence that can run again.

Technical lenses

API infrastructure fails in specific ways.

Spec conformance

GraphQL, protocol, schema, and SDK behavior compared against documented expectations.

Federation and planning

Subgraph routing, query planning, fallback behavior, and equivalent-operation consistency.

Streaming and cancellation

Subscription, defer/stream, timeout, cancellation, and resource-cleanup paths.

Negative paths

Malformed input, invalid state, unknown directives, authorization failures, and fail-closed behavior.

Concurrency

Shared caches, persisted queries, request deduplication, retries, and race-sensitive state.

Resource exhaustion

Recursive input, query fan-out, parser limits, resolver amplification, and memory or CPU ceilings.

Offer

Start with one package, path, or release risk.

  • Scope one parser, router, planner, policy, or SDK surface.
  • Build a risk model and initial evidence corpus.
  • Deliver confirmed findings with reproducers where feasible.
  • Set cadence for weekly, per-release, or fast-cycle review.
  • Convert strong findings into disclosure-safe field notes when approved.

Engagement mechanics

How this works for OSS and API teams.

QuestionAnswer
Do you need private repo access?No, not always. Public-source reviews can start from public code, issues, docs, release notes, and tests. Private access is useful for unreleased paths and customer-specific evidence.
How are findings delivered?Private report first. Public issues, advisories, field notes, or PRs happen only after approval and coordinated disclosure where applicable.
Who owns reproducers?Customer-facing reproducers, regression tests, and report artifacts are inspectable and can be handed off for customer CI or internal regression suites where practical.
How much maintainer time?Initial scoping, access approval, finding review, and patch/retest coordination. Proof should reduce triage load, not create another automated backlog.
Can a company sponsor an OSS review?Yes. The paying company can fund the review while publication and maintainer notification remain coordinated and approval-based.

Starting point

Bring one request path or release window.

  • GraphQL gateways, API routers, SDKs, parsers, planners, and protocol engines.
  • Review parser, validation, routing, execution, federation, cancellation, or concurrency behavior.
  • Receive confirmed findings with reproducers and regression evidence where feasible.
  • Turn critical findings into disclosure-safe field notes only after approval.

Do not submit secrets or private source code here. See Trust.