Skip to content

Latest commit

 

History

History
49 lines (40 loc) · 7.53 KB

attack-surface.md

File metadata and controls

49 lines (40 loc) · 7.53 KB

Attack Surface Analysis for 99designs/gqlgen

Attack Surface: 1. Schema Complexity and Denial of Service (DoS)

  • Description: Overly complex GraphQL schemas, facilitated by gqlgen's schema-first approach, can lead to computationally expensive queries that exhaust server resources and cause denial of service.
  • gqlgen Contribution: gqlgen generates the GraphQL server directly from the schema. While it doesn't force complex schemas, its ease of schema definition can inadvertently lead to schemas lacking complexity controls if developers are not careful.
  • Example: A schema with deeply nested object types and numerous relationships is defined using gqlgen's SDL. An attacker crafts a GraphQL query that exploits this complexity by requesting deeply nested fields, causing the gqlgen server to perform excessive computations and potentially crash or become unresponsive.
  • Impact: Denial of Service (DoS) - The API becomes unavailable or severely degraded for legitimate users due to resource exhaustion.
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement Query Complexity Analysis and Limits: Utilize or develop middleware that analyzes incoming GraphQL queries processed by gqlgen and calculates their complexity. Reject queries exceeding predefined complexity thresholds.
    • Schema Design Review with Complexity in Mind: During schema design (using gqlgen's SDL), consciously limit schema complexity. Avoid excessive nesting and consider the performance implications of complex relationships.

Attack Surface: 2. Injection Vulnerabilities in Resolvers

  • Description: Resolvers, which are Go functions wired to the GraphQL schema by gqlgen, are susceptible to injection vulnerabilities if developers don't sanitize inputs properly. This is a common vulnerability in any application interacting with databases or external systems, but directly relevant to resolver implementation in gqlgen.
  • gqlgen Contribution: gqlgen framework relies on developers to implement resolvers. It provides the structure for resolvers but does not enforce or automatically provide protection against injection vulnerabilities within resolver logic.
  • Example: A resolver, generated and wired by gqlgen, constructs a SQL query by directly concatenating user-provided arguments without sanitization. An attacker injects malicious SQL code through a GraphQL query argument, leading to unauthorized database access or data manipulation.
  • Impact: Data Breach, Data Manipulation, Unauthorized Access, Privilege Escalation - Injection vulnerabilities in resolvers can have severe consequences.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Input Validation and Sanitization within Resolvers: Within resolver functions (written in Go and integrated with gqlgen), rigorously validate and sanitize all input data received from GraphQL queries before using it in database queries, system commands, or any external interactions.
    • Utilize Parameterized Queries or ORM/ODM: Employ parameterized queries or use ORM/ODM libraries within resolvers to interact with databases securely. These methods automatically handle input escaping and prevent SQL/NoSQL injection.

Attack Surface: 3. Business Logic Flaws in Resolvers Leading to Authorization Bypass

  • Description: Flaws in the business logic implemented within gqlgen resolvers can lead to authorization bypasses, allowing users to access or manipulate data they should not be permitted to.
  • gqlgen Contribution: gqlgen's architecture relies on resolvers to handle business logic and authorization. The framework itself doesn't enforce specific authorization models; it's up to developers to implement these checks within resolvers connected to the schema by gqlgen.
  • Example: A mutation resolver, wired by gqlgen to update user profiles, fails to correctly verify if the requesting user is authorized to modify the target user's profile. An attacker exploits this flaw to update profiles of other users, bypassing intended authorization controls.
  • Impact: Unauthorized Access, Data Manipulation, Data Integrity Issues, Privilege Escalation.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Implement Robust Authorization Checks in Resolvers: Within each resolver function (especially mutation resolvers), implement explicit and thorough authorization checks to ensure users are permitted to perform the requested action on the specific data.
    • Centralize and Reuse Authorization Logic: Create reusable authorization functions or middleware that can be consistently applied across resolvers to enforce authorization rules and prevent inconsistencies or omissions.
    • Thorough Testing of Resolver Authorization Logic: Specifically test authorization logic within resolvers with various scenarios, including authorized and unauthorized access attempts, to ensure it functions as intended and prevents bypasses.

Attack Surface: 4. Insecure Authentication/Authorization Implementation via gqlgen's Context

  • Description: While gqlgen provides context and middleware for handling authentication and authorization, insecure or flawed implementations within these mechanisms can lead to complete bypass of security controls.
  • gqlgen Contribution: gqlgen's context and middleware features are designed to facilitate authentication and authorization. However, the security of these mechanisms is entirely dependent on how developers implement and configure them within the gqlgen application. gqlgen itself doesn't provide secure defaults or enforce secure practices.
  • Example: A developer uses gqlgen's middleware to implement JWT-based authentication, but fails to properly validate the JWT signature or expiration, or incorrectly extracts user information from the token. An attacker can forge or manipulate JWTs to gain unauthorized access, bypassing the intended authentication. Or, authorization logic in middleware is flawed, allowing unauthorized requests to proceed.
  • Impact: Unauthorized Access, Data Breach, Data Manipulation, Privilege Escalation - Failures in authentication and authorization are critical.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Use Established and Secure Authentication Protocols: Implement authentication using well-vetted and secure protocols like OAuth 2.0 or JWT. Leverage established libraries for JWT handling and validation within gqlgen middleware and resolvers.
    • Thoroughly Validate Authentication Tokens: Within gqlgen middleware, rigorously validate authentication tokens (e.g., JWTs) including signature verification, expiration checks, and issuer validation.
    • Implement Fine-Grained Authorization based on Context: Utilize gqlgen's context to pass authentication and authorization information to resolvers. Implement fine-grained authorization checks within resolvers based on user roles and permissions derived from the context.
    • Regular Security Audits and Penetration Testing: Conduct security audits and penetration testing specifically focusing on the authentication and authorization mechanisms implemented within the gqlgen application to identify and remediate vulnerabilities.