Skip to content

Latest commit

 

History

History
64 lines (55 loc) · 6.63 KB

attack-surface.md

File metadata and controls

64 lines (55 loc) · 6.63 KB

Attack Surface Analysis for gatsbyjs/gatsby

Attack Surface: Vulnerable Third-Party Plugins

  • Description: Exploitation of security flaws in Gatsby plugins installed from the plugin ecosystem.
  • How Gatsby Contributes: Gatsby's core functionality is extended through a large, third-party plugin ecosystem. This reliance on external code directly introduces the risk of vulnerable plugins. The plugin API, while powerful, can be misused to create insecure functionality.
  • Example: A plugin designed to handle form submissions has a vulnerability allowing cross-site scripting (XSS). An attacker injects malicious JavaScript into a form field, which is then executed in the browsers of other users visiting the site.
  • Impact: Complete site compromise, data breaches, defacement, malware distribution.
  • Risk Severity: Critical (if the plugin has high privileges or handles sensitive data) / High (for most plugins).
  • Mitigation Strategies:
    • Plugin Selection: Choose well-maintained, reputable plugins with a good security track record. Favor plugins from known developers.
    • Dependency Auditing: Regularly use tools like npm audit, yarn audit, Snyk, or Dependabot to identify and update vulnerable plugins and their dependencies. Automate this.
    • Updates: Keep all plugins updated to the latest versions. Subscribe to update notifications.
    • Least Privilege: Configure plugins with the minimum necessary permissions.
    • Code Review (Optional): For critical plugins, consider reviewing the source code.
    • Content Security Policy (CSP): Implement a strict CSP to limit the resources a plugin can access.
    • Minimize Plugin Usage: Use only essential plugins.

Attack Surface: GraphQL Misconfiguration and Exploitation

  • Description: Attackers exploiting weaknesses in the GraphQL data layer, often due to misconfiguration or lack of proper access controls.
  • How Gatsby Contributes: Gatsby uses GraphQL as its core data layer. This is a fundamental architectural choice that directly introduces the GraphQL attack surface. Gatsby's automatic schema generation, while convenient, can lead to unintended data exposure if not carefully managed.
  • Example: An attacker uses an introspection query to discover the entire GraphQL schema, including fields related to user authentication tokens. They then craft queries to retrieve these tokens, gaining unauthorized access.
  • Impact: Data breaches, denial of service, unauthorized access to sensitive information.
  • Risk Severity: Critical (if sensitive data is exposed) / High (for DoS).
  • Mitigation Strategies:
    • Disable Introspection: Disable GraphQL introspection in production environments using Gatsby's configuration.
    • Query Complexity Limits: Implement query complexity analysis and depth limiting. Use libraries like graphql-validation-complexity.
    • Authorization: Implement robust authorization and access control at the GraphQL layer. Use Gatsby's createPages API and context.
    • Rate Limiting: Implement rate limiting on GraphQL API requests.
    • Input Validation: Sanitize and validate all user input used in GraphQL queries.
    • Schema Validation: Use a GraphQL schema validation library.

Attack Surface: Exposed API Keys and Secrets (within Gatsby context)

  • Description: Accidental exposure of API keys, secrets, or other sensitive credentials used by Gatsby plugins or within the Gatsby build process.
  • How Gatsby Contributes: Gatsby's build process, and the frequent use of plugins that interact with external services, directly increases the risk of exposing secrets if not handled carefully. The client-side nature of the final output means build-time secrets must be handled with extreme care.
  • Example: A developer accidentally includes a build-time environment variable containing an API key in a client-side JavaScript bundle, exposing the key to anyone who views the site's source code.
  • Impact: Data breaches, financial loss, unauthorized access to third-party services, account compromise.
  • Risk Severity: Critical / High (depending on the sensitivity of the exposed credentials).
  • Mitigation Strategies:
    • Environment Variables: Use environment variables correctly. Understand the difference between build-time and runtime variables in Gatsby.
    • .gitignore: Ensure .env files (and any files with secrets) are in .gitignore.
    • .env.example: Provide a .env.example file.
    • Secret Management Tools: Consider using secret management tools (e.g., AWS Secrets Manager, HashiCorp Vault) for production deployments.
    • Code Scanning: Use tools to scan for accidentally committed secrets before pushing to the repository.
    • Build-time vs. Runtime: Carefully distinguish between build-time and runtime environment variables. Never expose build-time secrets in client-side code.

Attack Surface: Gatsby Functions Vulnerabilities

  • Description: Exploitation of vulnerabilities in serverless functions used with Gatsby Functions.
  • How Gatsby Contributes: Gatsby Functions directly introduce server-side code execution into the Gatsby environment, creating a new attack surface that wouldn't exist in a purely static site.
  • Example: A Gatsby Function that interacts with a database is vulnerable to SQL injection. An attacker crafts a malicious input that modifies the SQL query, allowing them to access or modify data in the database.
  • Impact: Server compromise, data breaches, denial of service, unauthorized access.
  • Risk Severity: High / Critical (depending on the function's purpose and data).
  • Mitigation Strategies:
    • Secure Coding Practices: Follow secure coding practices for serverless functions rigorously.
    • Least Privilege: Configure functions with the minimum necessary permissions.
    • Dependency Management: Keep function dependencies updated; use a vulnerability scanner.
    • Input Validation: Thoroughly validate and sanitize all user input.
    • Authentication and Authorization: Implement strong authentication and authorization where needed.
    • Monitoring and Logging: Monitor function execution logs.
    • Rate Limiting: Implement rate limiting.