GraphQL is flexible. That’s exactly the problem.
GraphQL lets clients ask for precisely the data they want, through a single endpoint, in whatever shape they need. It’s genuinely great for building fast, flexible apps. It’s also a very different security problem than anything REST ever gave you.
That flexibility means one endpoint now handles everything, and if authentication, authorisation, and query controls aren’t locked down carefully at every layer, a single query can quietly reach data it was never supposed to touch. GraphQL Security Testing is us finding those gaps before an attacker does.
We combine automated tools with manual testing, because GraphQL’s problems tend to live in places automation just doesn’t understand: your schema, your resolvers, your business logic.
What this actually is
Traditional REST APIs spread things across dozens of endpoints. GraphQL usually squeezes everything through one, and lets the client decide what data to ask for. That’s powerful, and it also means traditional security controls, the kind built around “this endpoint does this one thing,” don’t map cleanly onto GraphQL at all.
Depending on your setup, our assessment can look at authentication, authorisation, query validation, schema exposure, introspection, query depth, query complexity, resource consumption, input validation, sensitive data exposure, error handling, business logic, rate limiting, session and token management, and configuration.
The core question: can someone request data or perform an action they have no business touching?
Why this deserves its own testing approach
GraphQL lets clients request specific fields through queries. If access control isn’t enforced at the resolver level, at the level where the actual data gets fetched, someone can ask for a field they shouldn’t see, and the API will happily hand it over. Poorly configured GraphQL setups are also vulnerable to overly complex queries, information leaking through introspection, weak authentication, and business logic that nobody stress-tested.
Testing helps you catch object-level authorisation problems, schema exposure, uncontrolled introspection, excessive data access, runaway query complexity, weak input validation, business logic flaws, and error responses that reveal too much.
What we actually test
Mapping the GraphQL surface. Before anything else, we need to understand what’s actually there: endpoints, queries, mutations, subscriptions, authentication mechanisms, and the schema itself. This tells us where the real attack surface is.
Authentication. We test login mechanisms, tokens, JWT handling, session management, expiration, and whether GraphQL requests can slip through without proper authentication at all.
Authorisation. Different roles, different permissions, tested against what people can actually reach. We look for object-level and function-level authorisation problems, role bypass, privilege escalation, unauthorised mutations, and access to someone else’s data.
Introspection. GraphQL’s introspection feature can hand over a full map of your schema, every type, query, mutation, and field available. We check whether that’s appropriately configured, or whether it’s quietly exposing more than it should, including sensitive functionality nobody meant to advertise.
Schema and query analysis. We go through the schema itself, queries, mutations, fields, arguments, relationships, hunting for sensitive fields, unrestricted queries, unprotected mutations, and hidden admin functionality that’s technically reachable if you know where to look.
Query depth. Nested queries can chain through relationships several layers deep. Left uncontrolled, an attacker can build a query so deep it eats significant server resources just answering it.
Query complexity. Not every query costs the same to process. We check whether there are real limits on complexity and cost, or whether someone can send a single request expensive enough to strain your backend.
Batch queries. Some GraphQL setups allow multiple operations in one request. We check whether that batching can be abused to bypass controls, spike request volume, or overload backend systems.
Input validation. Arguments and variables should be validated before they ever reach your backend. We test for invalid input, unexpected data types, injection, boundary issues, and outright validation bypass.
Data exposure. Because GraphQL lets clients request specific fields, it’s remarkably easy to accidentally expose personal information, financial data, internal IDs, credentials, tokens, or admin-only data through a field that should never have been reachable.
Mutations. Mutations change data, which makes them worth testing carefully. We check whether they enforce proper authentication and authorisation, and whether they can be used for unauthorised updates, deletions, privilege changes, or bypassing the rules they’re supposed to follow.
Business logic. Sometimes the problem isn’t technical at all, it’s that a workflow can be manipulated: steps skipped, transaction values changed, actions repeated that should only happen once, someone else’s data quietly modified.
Error handling. GraphQL errors can leak more than intended, stack traces, database details, internal paths, debug info, configuration, service details. We check what your errors are actually revealing.
How we run this
Scope and planning. We start by understanding your GraphQL implementation, architecture, authentication, user roles, and endpoints, then agree the testing boundaries.
Discovery. We map the endpoint, schema, queries, mutations, subscriptions, and key workflows wherever they’re accessible.
Authentication and authorisation testing. Using the roles and permissions available, we test for unauthorised access and privilege escalation.
Query and schema testing. Queries, mutations, fields, arguments, and relationships all get tested for weaknesses.
Validation. We manually confirm which findings are genuinely exploitable and understand their real impact.
Risk prioritisation. We rank findings by severity, exploitability, affected data, and business impact.
Reporting. A detailed report covering each vulnerability, the affected GraphQL operation, the evidence, and how to fix it.
Retesting. Once fixes are in place, we check they actually held.
What tends to show up
Broken object-level authorisation. Broken authentication. Unauthorised data access. Excessive data exposure. Insecure mutations. Schema information exposure. Unrestricted introspection. Query depth abuse. Query complexity abuse. Excessive resource consumption. Batch query abuse. Injection vulnerabilities. Weak input validation. Weak rate limiting. Business logic vulnerabilities. Privilege escalation. Sensitive field exposure. Insecure error handling. Weak session management. Security misconfiguration.
What actually shows up depends entirely on how your GraphQL implementation is built.
GraphQL vs. REST testing
They’re related, but the shape of the risk is different. REST spreads its attack surface across many endpoints. GraphQL concentrates it into one, and shifts the burden onto queries, schema design, and resolver-level logic.
That means GraphQL testing puts extra weight on schema security, introspection, query depth, query complexity, nested queries, resolver-level authorisation, mutations, and batch operations. Both still need solid authentication, authorisation, input validation, data protection, and business logic controls underneath all of that.
Not the same as automated scanning
Tools can catch some of the obvious GraphQL issues, but they generally have no concept of your specific permissions or business workflows. They can’t tell that one user viewing another user’s private data through a resolver is actually a problem, they just see a valid response.
That’s where manual testing earns its keep: access control, resolver permissions, sensitive data exposure, business logic, mutation security, query abuse, and the workflows that are unique to your application.
Who this is for
SaaS platforms. E-commerce applications. Banking and fintech platforms. Healthcare applications. Mobile apps. Customer portals. Enterprise applications. Cloud platforms. Social platforms. Business applications. Microservice environments.
It matters most anywhere GraphQL is a direct line to sensitive data or critical business functions, which, given how popular GraphQL has become, is a lot of places.
When to test
Before launching a new GraphQL API. Before a major update. After adding new queries or mutations. After changing authentication or user permissions. When adding sensitive data fields. After integrating a new backend service. Following a security incident. Before a customer security review. As part of regular testing, or as a piece of a broader VAPT programme.
Testing after significant changes matters most, since that’s usually when something risky slips through unnoticed.
What you actually get out of it
A more secure GraphQL API. Better-protected sensitive information. Authentication and authorisation that actually hold up under testing. Query complexity and depth kept under control. Reduced data exposure. Mutations that don’t quietly bypass business rules. Cleaner configuration. Lower risk of resource exhaustion. Prioritised, actionable findings your team can genuinely use.
Why work with us
We look at how your GraphQL API actually behaves across different roles, queries, mutations, and workflows, not just what a scanner reports back. That means GraphQL-specific testing, real authentication and authorisation checks, schema and query analysis, manual validation, and business logic testing, all backed by clear evidence and practical fixes. Once you’ve made changes, we come back and confirm they worked.
Bottom line
GraphQL gives modern applications real flexibility and efficiency, but that same query-based architecture creates security considerations REST never had to worry about. Strong authentication isn’t enough on its own. Schema exposure, resolver-level authorisation, query complexity, mutations, and business logic all need dedicated attention. This assessment finds where they’re falling short, before it becomes someone else’s discovery instead of yours.
FAQs
What is GraphQL Security Testing?
A security assessment built specifically for GraphQL APIs, checking authentication, authorisation, schema exposure, query handling, data protection, and business logic.
Is this different from REST API testing?
Yes. Both need solid authentication, authorisation, input validation, and data protection, but GraphQL testing also has to dig into schemas, introspection, query depth, query complexity, mutations, and resolver-level permissions.
Can you test GraphQL authentication?
Yes. JWT, sessions, API keys, OAuth, whatever your app uses, tested against your actual architecture.
Can you test GraphQL authorisation?
Yes. We test different roles to see whether users can reach restricted fields, objects, queries, or mutations.
What exactly is GraphQL introspection?
It’s a feature that can expose your entire schema, types, queries, mutations, fields. Whether that’s a security problem depends entirely on how it’s configured.
Can GraphQL queries actually strain a server?
Yes. Deeply nested or highly complex queries can eat significant resources if there’s nothing stopping them.
Can you test mutations?
Yes. Authentication, authorisation, input validation, business logic, and whether they can lead to unauthorised data changes.
Can GraphQL leak sensitive information?
Yes, easily, if field-level or object-level access controls aren’t tight, users can simply ask for data they shouldn’t have.
Do you provide a report?
Yes. Vulnerabilities found, affected operations, evidence, risk information, and remediation steps.
Can you retest after fixes?
Yes. We confirm previously identified issues have actually been resolved.
Secure your GraphQL APIs with security testing
Talk to Sunvak Boreal about your GraphQL setup. Let’s find out what your schema is quietly exposing before someone else does.