Securing GraphQL APIs - A Guide to OWASP GraphQL Security Cheat Sheet

Securing GraphQL APIs - A Guide to OWASP GraphQL Security Cheat Sheet

Dive into the essentials of GraphQL security with our comprehensive guide, exploring common attacks and best practices as outlined in the OWASP GraphQL Security
TABLE OF CONTENTS

The Open Web Application Security Project (OWASP) has developed a comprehensive guide for securing GraphQL APIs, the GraphQL Security Cheat Sheet. This blog post will delve into the key aspects of this cheat sheet, providing a detailed understanding of how to secure your GraphQL APIs.

Introduction to GraphQL and Its Security Concerns

GraphQL, an open-source query language originally developed by Facebook, is an alternative to REST and SOAP for building APIs. Its flexibility in constructing and invoking APIs has led to its widespread adoption. However, like any technology, it comes with its security challenges. The OWASP GraphQL Security Cheat Sheet guides various areas that need attention when working with GraphQL. These areas include input validation, query limiting, access control, and secure configurations.

Understanding the Common Attacks on GraphQL

Several common attacks can be launched against GraphQL. These include:

  • Injection Attacks: These attacks typically involve SQL and NoSQL injection, OS command injection, Server-Side Request Forgery (SSRF), and Carriage Return Line Feed (CRLF) injection/request smuggling.
  • Denial of Service (DoS): Attackers can exploit expensive queries to cause a DoS condition.
  • Abuse of Broken Authorization: involves improper or excessive access, including Insecure Direct Object References (IDOR).
  • Batching Attacks: A GraphQL-specific method of brute force attack.
  • Abuse of Insecure Default Configurations: Attackers can exploit insecure default settings to launch attacks.

Best Practices and Recommendations for Securing GraphQL

Input Validation

Implementing strict input validation can help prevent injection and DoS attacks. This involves validating all incoming data only to allow valid values, using specific GraphQL data types such as scalars or enums, defining schemas for mutations input, and rejecting invalid input gracefully.

Preventing Injection Attacks

When handling input to be passed to another interpreter (e.g., SQL/NoSQL/ORM, OS, LDAP, XML), choosing libraries/modules/packages that offer safe APIs, such as parameterized statements, is crucial. Always escape/encode input data according to the best practices of the target interpreter to prevent injection attacks.

Preventing DoS Attacks

To limit the potential for DoS attacks, consider implementing depth and amount limiting to incoming queries, adding pagination, setting reasonable timeouts at the application layer, infrastructure layer, or both, performing query cost analysis and enforcing a maximum allowed cost per query, enforcing rate limiting on incoming requests per IP or user, and implementing server-side batching and caching.

here's an example of implementing a depth limit in a GraphQL server using JavaScript. This example uses the graphql-depth-limit package along with Apollo Server:


const express = require('express');
const { ApolloServer } = require('apollo-server-express');
const rateLimit = require('express-rate-limit');
const typeDefs = require('./schema');
const resolvers = require('./resolvers');

// Create a new express application
const app = express();

// Create a new rate limiter middleware
const limiter = rateLimit({
  windowMs: 15 * 60 * 1000, // 15 minutes
  max: 100 // limit each IP to 100 requests per windowMs
});

// Apply the rate limiter to the path for your GraphQL endpoint
app.use('/graphql', limiter);

const server = new ApolloServer({
  typeDefs,
  resolvers
});

server.applyMiddleware({ app });

app.listen({ port: 4000 }, () =>
  console.log(`Server ready at http://localhost:4000${server.graphqlPath}`)
);

In this example, the depthLimit function from the graphql-depth-limit package is used as a validation rule for the Apollo Server. The argument to depthLimit is the maximum depth you want to allow for your queries. In this case, the maximum depth is set to 5.

This means the server will reject any query with a depth greater than 5. This can be useful to prevent overly complex queries that could cause performance issues for your server.

Implementing Access Control

Always validate that the requester is authorized to view or mutate/modify the data they are requesting. This can be done with Role-Based Access Control (RBAC) or other access control mechanisms. Enforce authorization checks on edges and nodes, use Interfaces and Unions to create structured, hierarchical data types, and disable introspection queries system-wide in production or publicly accessible environments.

It's crucial to implement granular authentication at the application logic level. This practice ensures that a user is authenticated to access a certain function and authorized to perform actions on specific items. Here's an example of how you might implement access control in a GraphQL resolver using JavaScript. This example assumes you're using a JWT (JSON Web Token) for authentication and that the user's role is included in the JWT.


const { AuthenticationError } = require('apollo-server');

const resolvers = {
  Query: {
    getSecretData: async (parent, args, context) => {
      // Check if the user is authenticated
      if (!context.user) {
        throw new AuthenticationError('You must be logged in');
      }

      // Check if the user has the correct role
      if (context.user.role !== 'admin') {
        throw new AuthenticationError('You are not authorized');
      }

      // If the user is authenticated and authorized, return the secret data
      const secretData = await getSecretDataFromDatabase();
      return secretData;
    },
  },
};

In this example, the getSecretData resolver first checks if the user is authenticated by checking if context.user exists. This context.user would be set earlier in your code, typically in the context function of your Apollo Server setup, where you would decode the JWT and attach the user data to the context.

After checking if the user is authenticated, the resolver then checks if the user has the correct role to access the secret data. In this case, only users with the 'admin' role are allowed to access the data. If the user does not have the 'admin' role, an error is thrown.

If the user is both authenticated and has the correct role, the resolver then fetches the secret data from the database and returns it.

This is a simple example and real-world applications might require more complex access control logic, but this should give you a good starting point.

Preventing Batching Attacks

GraphQL supports batching requests, which allows for batching attacks, a form of brute force attack specific to GraphQL. To mitigate this attack, add object request rate limiting in code, prevent batching for sensitive objects, and limit the number of queries that can run simultaneously.

Rate limiting at the object level can be a bit more complex because it often involves tracking the number of requests made to specific objects within a certain time frame. However, you can achieve this by using a combination of a rate limiter package like express-rate-limit and a unique identifier for each object.

Here's a simplified example of how you might implement object request rate limiting in a GraphQL resolver:


const express = require('express');
const { ApolloServer } = require('apollo-server-express');
const rateLimit = require('express-rate-limit');
const typeDefs = require('./schema');
const resolvers = require('./resolvers');

// Create a new express application
const app = express();

// Create a new rate limiter middleware
const limiter = rateLimit({
  windowMs: 15 * 60 * 1000, // 15 minutes
  max: 100 // limit each IP to 100 requests per windowMs
});

// Apply the rate limiter to the path for your GraphQL endpoint
app.use('/graphql', limiter);

const server = new ApolloServer({
  typeDefs,
  resolvers
});

server.applyMiddleware({ app });

app.listen({ port: 4000 }, () =>
  console.log(`Server ready at http://localhost:4000${server.graphqlPath}`)
);

In this example, the express-rate-limit middleware is applied to the /graphql path. This means that each IP address will be limited to 100 requests every 15 minutes. If an IP address exceeds this limit, all subsequent requests from that IP will be blocked until the 15-minute window has passed.

This simple form of rate limiting can help mitigate batching attacks by limiting the total number of requests that can be made in a certain time frame. However, it's worth noting that this approach does not limit the number of requests per object but rather the total number of requests per IP address.

For a more advanced form of object request rate limiting, you need to implement a custom solution that tracks the number of requests made to each object and applies rate limits accordingly. This could involve using a database or in-memory data store like Redis to track the number of requests made to each object.

Ensuring Secure Configurations

Most GraphQL implementations have default configurations with some insecurities, which should be changed. Don't return excessive error messages, disable or restrict Introspection and GraphQL based on your needs, and don't return hints of mistyped fields if the introspection is disabled.

Handling Error Messages

In development environments, delivering the full error message and stack trace to the client is handy. However, doing this in production could give a hacker enough understanding of the inner workings of your system to exploit it. Therefore, it's recommended to mask or reformat the error messages in production.

For example, with Apollo Server, you can format error messages as follows:


const server = new ApolloServer({
  typeDefs,
  resolvers,
  formatError: error => {
    return new Error('Internal server error');
  }
});

Implications of OWASP API Top 10 on GraphQL Security

The OWASP API Top 10, a list of the most critical security risks to APIs, presents significant implications for GraphQL. The flexibility of GraphQL can lead to authorization issues, where attackers could potentially access or manipulate data they shouldn't. Additionally, GraphQL's ability to handle complex queries can be exploited to cause resource-intensive operations, potentially leading to Denial of Service attacks. Misconfigurations, improper inventory management, and unsafe consumption of third-party APIs are other areas of concern. Therefore, developers must implement robust security measures to protect their GraphQL APIs against these potential vulnerabilities.

Tools and Resources for Securing GraphQL APIs

Several tools are available to aid in securing GraphQL APIs. These include:

  • GraphiQL: An in-browser IDE for exploring GraphQL. It can be used to understand the structure and data of your GraphQL API.
  • GraphQL Voyager: This tool represents any GraphQL API as an interactive graph, making it a powerful tool for visualizing and understanding your GraphQL schema.

In conclusion, the OWASP GraphQL Security Cheat Sheet provides a comprehensive guide for securing GraphQL APIs. By understanding and implementing these guidelines, developers can ensure their APIs are secure and resilient against threats. As with any technology, staying informed and up-to-date on the latest security best practices is key to maintaining a secure GraphQL API.

Why Product Teams choose Aptori

Searching for an automated API security solution? Aptori is your top choice. It effortlessly discovers and secures your applications and can be implemented in minutes.

Setting up and performing application security scans using Aptori is a breeze. Whether it's you or your security team, it's operational in no time. Benefit from in-depth security insights and expedite the remediation process by integrating security checks seamlessly into your SDLC.

Experience the full potential of Aptori with a free trial before making your final decision.


Interested in a live demo to witness the capabilities of Aptori with your APIs? We'd be delighted to connect and show you firsthand.

Get started with Aptori today!

AI-Driven Testing for Application & API Security

Reduce Risk With Proactive Application Security

Need more info? Contact Sales