threat-modeling.md

Threat Model Analysis for 99designs/gqlgen

Threat: GraphQL Injection Attacks

• Threat: GraphQL Injection Attacks
  • Description: Attackers exploit GraphQL query language features, potentially amplified by the schema complexity facilitated by gqlgen, to bypass security controls or access unauthorized data. gqlgen's schema-first approach, while powerful, can inadvertently create complex schemas that, if resolvers are not carefully implemented, become vulnerable to injection when attackers manipulate query structure, aliases, or directives.
  • Impact: Data breaches, unauthorized access to sensitive information, data manipulation, potential server-side code execution if resolvers are vulnerable.
  • gqlgen Component Affected: Schema Definition, Resolvers (interface generated by gqlgen), GraphQL Engine (query parsing/execution within gqlgen framework).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Strict input validation and sanitization within resolver implementations (developer responsibility when implementing gqlgen resolvers).
    • Careful schema design to minimize complexity and potential injection points (schema defined when using gqlgen).
    • Implementation of query complexity analysis and limits to restrict potentially malicious query structures.
    • Consider using GraphQL security libraries or middlewares designed to detect and prevent injection attempts in gqlgen applications.

Threat: Denial of Service (DoS) via Complex Queries

• Threat: Denial of Service (DoS) via Complex Queries
  • Description: Attackers craft excessively complex or deeply nested GraphQL queries, leveraging the flexibility gqlgen provides in schema design, to exhaust server resources (CPU, memory, database connections). gqlgen's efficient code generation can inadvertently enable the execution of resource-intensive queries if complexity limits are not enforced, leading to service disruption.
  • Impact: Service unavailability, degraded performance, potential system crashes, financial loss due to downtime.
  • gqlgen Component Affected: GraphQL Engine (query execution within gqlgen), Server infrastructure (impacted by resource exhaustion).
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement and enforce robust query complexity analysis and limits within the gqlgen application.
    • Utilize rate limiting mechanisms at the API gateway or application level to control request frequency.
    • Establish resource monitoring and alerting to detect and respond to unusual resource consumption patterns indicative of DoS attacks.
    • Employ pagination and limits for list queries to prevent retrieval of excessively large datasets in single requests, especially relevant when designing schemas with gqlgen.

Threat: Information Exposure via GraphQL Introspection

• Threat: Information Exposure via GraphQL Introspection
  • Description: gqlgen enables GraphQL introspection by default, allowing attackers to query the schema and discover the API's structure, including types, fields, and directives. This reveals valuable information about the backend, potentially exposing sensitive data structures and business logic that attackers can use for reconnaissance and targeted attacks.
  • Impact: Information leakage about the API's internal structure, increased attack surface, easier reconnaissance for attackers, potential exposure of sensitive data structures or business logic.
  • gqlgen Component Affected: GraphQL Engine (introspection functionality provided by gqlgen), Schema Definition (exposed through introspection).
  • Risk Severity: High
  • Mitigation Strategies:
    • Disable GraphQL introspection in production environments using gqlgen configuration options.
    • If introspection is necessary for specific purposes (e.g., monitoring), implement schema access control to restrict introspection access to authorized entities.
    • Carefully design the schema to avoid exposing overly sensitive internal details, even if introspection is enabled in development environments using gqlgen.

Threat: Over-fetching Misconfigurations

• Threat: Over-fetching Misconfigurations
  • Description: Due to schema design choices made when using gqlgen, the API might return more data than the client actually requests (over-fetching). This can unintentionally expose sensitive information through fields that clients should not necessarily have access to in every context. gqlgen's schema-first approach requires careful consideration of data exposure during schema design.
  • Impact: Unintended exposure of sensitive data through over-fetched fields, potential data leakage, increased risk of unauthorized access to information.
  • gqlgen Component Affected: Schema Definition (design choices made when using gqlgen), Resolvers (if resolvers are not optimized to fetch only necessary data).
  • Risk Severity: High
  • Mitigation Strategies:
    • Thorough schema design review with a focus on data minimization and least privilege principles when defining schemas in gqlgen.
    • Optimize resolvers to fetch and return only the data explicitly requested by the client in the GraphQL query (developer responsibility when implementing gqlgen resolvers).
    • Implement field-level authorization to control access to specific fields based on user roles or permissions, ensuring that over-fetching does not lead to unauthorized data access.

Threat: Misconfigured gqlgen Server or Middleware

• Threat: Misconfigured gqlgen Server or Middleware
  • Description: Incorrect configuration of the gqlgen server or associated middleware (e.g., CORS, authentication, authorization) can introduce significant vulnerabilities. For example, overly permissive CORS configurations enabled when setting up the gqlgen server can allow cross-origin attacks. Weak or improperly configured authentication middleware used with gqlgen can lead to authorization bypass.
  • Impact: Cross-site scripting (XSS) vulnerabilities (via CORS misconfiguration), authorization bypass (via weak authentication middleware), information leakage (if debug endpoints are unintentionally exposed in production), and other vulnerabilities depending on the specific misconfiguration.
  • gqlgen Component Affected: gqlgen Server Configuration, Middleware Integration (how middleware is configured and used with gqlgen).
  • Risk Severity: High
  • Mitigation Strategies:
    • Adhere to secure configuration practices when setting up the gqlgen server and integrating middleware.
    • Implement least privilege CORS policies, restricting access to only authorized origins when configuring CORS for the gqlgen server.
    • Utilize strong and well-tested authentication and authorization middleware, ensuring proper configuration and integration with the gqlgen application.
    • Disable debug endpoints, development-related features, and verbose error logging in production environments when configuring the gqlgen server.

Threat: Information Leakage via Error Handling

• Threat: Information Leakage via Error Handling
  • Description: Insecure error handling within the gqlgen application can lead to the exposure of sensitive information in error responses sent to clients. This might include stack traces, internal system details, or database error messages, which attackers can use to gain insights into the system's inner workings and plan further attacks. gqlgen's error handling mechanisms need to be carefully configured to prevent such leaks.
  • Impact: Information leakage, increased attack surface, easier reconnaissance for attackers, potential exposure of sensitive system details.
  • gqlgen Component Affected: Error Handling within Resolvers (developer implemented), gqlgen Server (default error handling behavior).
  • Risk Severity: High
  • Mitigation Strategies:
    • Configure gqlgen to return generic and non-descriptive error messages to clients in production environments.
    • Implement centralized error logging to capture detailed error information for debugging and monitoring purposes, ensuring this logging is not directly accessible to clients.
    • Implement custom error handling logic within resolvers and the gqlgen server to precisely control the information returned to clients in error responses, preventing exposure of sensitive details.