A summary of common security vulnerabilities in GraphQL and their mitigation strategies.

GraphQL provides superior flexibility and efficiency compared to traditional REST APIs by allowing clients to request exactly the data they need. However, this flexibility introduces unique security challenges. If not addressed properly, these can lead to data leaks, denial of service vulnerabilities, and privilege escalation issues.

In this post, I'll explain the major security threats related to GraphQL and provide practical strategies to protect GraphQL-based applications. The core principle is implementing security controls not only at the network boundary but deep within the application logic as well.

The GraphQL Request Lifecycle

A secure GraphQL request processing flow includes several layers of validation and verification.

 graph TD
    A[Client Request] --> B{HTTP Middleware};
    B --> C{Authentication};
    C -- Authenticated --> D[Parse Query];
    C -- Failed --> Z[Reject Request];
    D --> E{Validation};
    E -- Cost/Depth OK --> F[Execute Resolvers];
    E -- Invalid Query --> Z;
    F -- For each field --> G{Authorization Check};
    G -- Authorized --> H[Fetch Data];
    G -- Unauthorized --> I[Return Null/Error];
    H --> J[Format Response];
    I --> J;
    J --> K[Return to Client];

    subgraph "Pre-Execution"
        B
        C
        D
        E
    end

    subgraph "Execution"
        F
        G
        H
        I
    end

Abusing Introspection

• Problem: Introspection allows clients to query the GraphQL schema itself, exposing all types, fields, queries, and mutations. While useful for development tools, it gives attackers a map of your API's entire structure.
• Mitigation: Disable introspection in production environments. This is typically available as a configuration flag in your GraphQL server library. For example, in apollo-server, you can set it when instantiating the server:

const server = new ApolloServer({
  typeDefs,
  resolvers,
  introspection: process.env.NODE_ENV !== 'production'
});

Denial of Service (DoS)

• Problem: Attackers can craft deeply nested or complex queries that consume excessive server resources, causing denial of service for legitimate users.
• Mitigations:
  • Query Depth Limiting: Restrict the maximum nesting level of queries. For example, reject queries nested more than 10 levels deep.
  • Query Cost Analysis: Assign numeric "costs" to each field based on computational complexity. Calculate the total cost before executing queries and reject them if they exceed a predefined threshold.
  • Timeouts: Set enforced timeouts on query execution to prevent long-running queries from indefinitely occupying server resources.
  • Amount Limiting (Pagination): Always limit the number of records that can be returned from a list. Never allow clients to request unlimited items.

• Problem: GraphQL resolvers fetch data for specific fields. If permission checks aren't performed at the resolver level for each object, attackers may access data they shouldn't have permission to see. This is a classic Insecure Direct Object Reference (IDOR) vulnerability path.
• Mitigation: Implement permission checks within each relevant resolver or as middleware layers. For every piece of data requested, the application should verify that the currently authenticated user has permission to view or modify that data. It's not sufficient to check authentication only at the endpoint level.

const resolvers = {
  Query: {
    user: (parent, { id }, context) => {
      // Permission check: Does the logged-in user have rights to view this profile?
      if (context.user.id !== id && !context.user.isAdmin) {
        throw new Error('You do not have permission to view this user');
      }
      return db.users.find({ id: id });
    }
  }
};

Insufficient Error Handling

• Problem: Detailed error messages such as stack traces or database errors can leak sensitive information about your backend infrastructure, libraries used, and database schema.
• Mitigation: Implement global error handlers that catch all exceptions. Log detailed errors for internal debugging purposes but return sanitized, generic error messages to clients. Libraries like graphql-errors can help formalize this process.

Authentication

• Problem: GraphQL is transport-layer independent and doesn't enforce any particular authentication mechanism. It's up to developers to implement this correctly.
• Mitigation: Treat GraphQL endpoints like any other sensitive API endpoint. Implement standard authentication mechanisms such as OAuth 2.0 or JWTs. Tokens should be passed via the Authorization HTTP header and validated in a middleware layer before queries are processed. The validated user information should be stored in the GraphQL context object for resolvers to use.

Conclusion

Securing GraphQL APIs requires a shift in thinking from traditional endpoint-based security models. The flexible nature of GraphQL means that security must be an integral part of the core application logic.

By disabling introspection in production environments, implementing strong controls against resource exhaustion attacks, enforcing object-level authorization within resolvers, and carefully managing error responses, developers can build robust and secure GraphQL applications. Security is not a feature to add at the end, but a fundamental requirement to consider throughout the development lifecycle.