Graphql Introspection in Feathersjs with Dynamodb

GraphQL introspection is a standard feature that allows clients to query the schema for type information, which is valuable for development tools but can expose sensitive design details in production. When using FeathersJS with DynamoDB as the persistence layer, introspection can reveal the structure of your service definitions, field names, and relationships that map to DynamoDB table schemas. This combination can unintentionally expose metadata about your data model, such as attribute names and types, which may aid an attacker in crafting enumeration or injection attacks.

In FeathersJS, services are defined with a configuration object that specifies the model name and the DynamoDB table used for storage. If introspection is enabled without access restrictions, an attacker can send a standard introspection query and receive a response that includes type definitions and possible queries. Because DynamoDB does not enforce field-level permissions at the schema layer, the introspection response might hint at the presence of sensitive attributes (e.g., userId, email, or role) that are validated only at the application level. This can lead to information disclosure similar to issues described in the OWASP API Top 10 category on Security Misconfiguration.

The risk is amplified when the FeathersJS application does not implement proper authentication on introspection operations. Since DynamoDB stores data in a schemaless manner, the GraphQL layer often defines the schema explicitly, and introspection provides a direct view into that schema. An attacker could use this information to probe for BOLA/IDOR vulnerabilities by testing known identifiers in combination with the discovered field names. Additionally, if the service exposes queries that return items with sensitive properties, introspection can clarify which fields are available for extraction, increasing the impact of data exposure findings identified by middleBrick scans.

To illustrate, consider a FeathersJS service configured for a DynamoDB table named UserProfiles. An introspection query might return fields such as id, username, and preferences, revealing the attribute names stored in DynamoDB. If the service lacks proper authorization checks on these fields, an attacker could leverage this knowledge to test Property Authorization flaws or unsafe consumption patterns. middleBrick’s checks for GraphQL introspection and Property Authorization highlight this risk by correlating schema exposure with runtime behavior.

Disabling introspection in production is a common mitigation, but it must be done carefully to avoid breaking developer tooling. In FeathersJS, this can be achieved by conditionally enabling introspection based on the environment and ensuring that the GraphQL server is not exposed to unauthenticated requests. Combining this with DynamoDB fine-grained access patterns reduces the chance that exposed schema information leads to successful exploitation.

Remediation focuses on disabling introspection in production and enforcing strict access patterns for DynamoDB-backed FeathersJS services. You should ensure that the GraphQL server does not expose schema details to unauthenticated clients and that DynamoDB operations follow the principle of least privilege.

Below is a concrete example of a FeathersJS service definition that integrates with DynamoDB using the feathers-dynamodb adapter. The service is configured without exposing sensitive runtime details through introspection.

const feathers = require('@feathersjs/feathers');
const express = require('@feathersjs/express');
const dynamodb = require('feathers-dynamodb');
const { GraphQLServer } = require('graphql-yoga');

const app = express(feathers());

// Configure DynamoDB service without exposing introspection in production
app.configure(dynamodb({
  table: 'UserProfiles',
  partitionKey: 'userId',
  // Ensure endpoint and credentials are provided via environment variables
  endpoint: process.env.AWS_DYNAMODB_ENDPOINT,
  accessKeyId: process.env.AWS_ACCESS_KEY_ID,
  secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY
}));

// Example of a safe service setup that limits GraphQL introspection
const server = new GraphQLServer({
  typeDefs: `
    type UserProfile {
      userId: ID!
      username: String!
      preferences: JSON
    }

    type Query {
      userProfile(userId: ID!): UserProfile
    }
  `,
  resolvers: {
    Query: {
      userProfile: async (_, { userId }, context) => {
        // Authorization check should be implemented here
        return context.app.service('userprofiles').get(userId);
      }
    }
  },
  context: () => ({
    app,
    // Do not pass introspection flag in production
    introspection: process.env.NODE_ENV !== 'production'
  })
});

// Disable introspection explicitly in production
if (process.env.NODE_ENV === 'production') {
  server.expressApp.use((req, res, next) => {
    if (req.body && req.body.query && req.body.query.includes('__schema')) {
      res.status(403).send('Introspection disabled');
      return;
    }
    next();
  });
}

app.use('/graphql', server.express);

app.listen(3000).then(() => {
  console.log('GraphQL server running on port 3000');
});

In this example, the introspection context flag is controlled by the environment, ensuring that production deployments do not expose schema details. The middleware check provides an additional layer of protection by rejecting queries containing __schema or __type operations when introspection is disabled.
For DynamoDB specifically, ensure that the IAM role associated with the service has only the necessary permissions (e.g., dynamodb:GetItem, dynamodb:Query) and does not allow broad scanning or describe actions that could amplify information disclosure. Combine this with row-level security in your application logic to prevent BOLA/IDOR, and validate all input to avoid injection risks mapped by middleBrick’s Input Validation and Property Authorization checks.