GraphQL Security Assessment
Specialized security assessment for GraphQL APIs
A GraphQL Security Assessment tests GraphQL APIs both against the OWASP API Security Top 10 — the access-control and business-logic flaws that dominate API breaches — and against the risks unique to GraphQL itself: schema introspection that hands an attacker the whole map, query depth, complexity and batching that turn a single request into a denial of service, and authorization that is enforced per resolver rather than per endpoint. Because one GraphQL endpoint exposes the entire graph, a missing check on a single field can expose another user's data. We test against the API's real behavior, carry every finding through to a working proof, and rate its severity with CVSS alongside the real business impact.
What's Included
Field- and object-level authorization (BOLA/BFLA) across queries and mutations
Introspection exposure and what the schema reveals in production
Query depth, complexity, and cost limits — nested-query denial of service
Batching and aliasing abuse, including brute force through a single request
Broken authentication in queries, mutations, and subscriptions
Injection reaching databases and downstream services through resolvers
Excessive data exposure and mass assignment through input types
Error handling and information disclosure in responses
Rate limiting and resource-consumption controls
Schema review against the API's real behavior
How It Works
- Executive summary with a risk overview for decision-makers
- Detailed technical report, each finding with a reproducible proof of concept
- Findings mapped to the OWASP API Security Top 10 and GraphQL-specific risks
- CVSS severity and business impact for every finding
- Query complexity, depth, and rate-limiting recommendations
- Schema and resolver hardening guidance
- Prioritized remediation roadmap with concrete steps
- Re-testing after remediation
Why HafezSecure
Frequently Asked Questions
It evaluates a GraphQL API for security weaknesses — field- and object-level authorization flaws, introspection exposure, query-complexity and batching denial of service, injection through resolvers, and information disclosure — measured against the OWASP API Security Top 10 and the OWASP GraphQL guidance, with each finding proven and rated.
A REST API exposes many endpoints; a GraphQL API usually exposes one, through which the whole graph is reachable. Authorization is enforced per resolver rather than per route, so a single missing check exposes a field everywhere it appears, and the query engine adds risks a REST test does not have — introspection, query depth and complexity, and batching. The reference is still the OWASP API Security Top 10, applied to the graph.
Introspection is GraphQL's built-in ability to describe its own schema — every type, field, and argument. It is useful in development but in production it hands an attacker a complete map of the API. Disabling it in production raises the bar; it is not a substitute for enforcing authorization, since the graph can still be explored by guessing, so we test both.
GraphQL lets a client ask for deeply nested and related data in one request. Without depth, complexity, or cost limits, a single crafted query — or many aliased queries batched together — can force the server to do a huge amount of work and fall over. We test whether those limits exist and hold, and recommend concrete thresholds.
The GraphQL endpoint and environment, the schema or introspection access if available, and test accounts for each role (at least two users per role, so we can test cross-user access). A staging environment that mirrors production is ideal. We agree the scope and any mutations to avoid before we begin.
Black-box means we test with no inside knowledge; white-box means we also have the schema, documentation, and sometimes source; grey-box sits in between, typically with credentials and the schema. For GraphQL we usually recommend grey-box: with roles and the schema we cover the per-resolver authorization flaws far more thoroughly, in less time, than a blind test.
Each finding gets a CVSS score for a common baseline, adjusted by the real business impact in your context — what data or operation it exposes, how easily it is reached, and what an attacker gains. That is why two issues with the same CVSS can be prioritized differently.
We prefer a staging environment that mirrors production. When testing must run against production, we agree limits in advance — no destructive mutations, care around complexity and batching tests that could load the server, and a contact on your side to pause immediately if anything looks wrong.
It depends on the size of the schema, the number of roles, and the complexity of the business logic; a typical assessment runs about two to three weeks. We give a firm estimate after scoping, once the schema and role count is known.
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