Skip to content

Latest commit

 

History

History
110 lines (95 loc) · 8.31 KB

attack-tree.md

File metadata and controls

110 lines (95 loc) · 8.31 KB

Attack Tree Analysis for apollographql/apollo-android

Objective: Exfiltrate Sensitive Data or Manipulate Application Data via Apollo Android

Attack Tree Visualization

└── Goal: Exfiltrate Sensitive Data or Manipulate Application Data via Apollo Android

├── [HIGH-RISK PATH] 1. Exploit GraphQL Query/Mutation Manipulation
│   └── [HIGH-RISK PATH] 1.1. GraphQL Injection (Client-Side) [CRITICAL NODE]
│       └── [HIGH-RISK PATH] 1.1.a. Unsanitized User Input in Query Construction [CRITICAL NODE]
│
├── 2. Exploit GraphQL Response Handling Vulnerabilities
│   └── [CRITICAL NODE] 2.1.b. Client-Side Parsing Vulnerabilities (Less Likely)
│       └── [CRITICAL NODE] 2.1.b.ii. Apollo Android's response parsing logic has vulnerabilities (e.g., buffer overflows, format string bugs - unlikely but theoretically possible).
│
├── [CRITICAL NODE] 4.2. Build Dependency Vulnerabilities (Indirect)
│   └── [CRITICAL NODE] 4.2.a. Vulnerable Dependencies
│
├── [HIGH-RISK PATH] 5. Misconfiguration and Misuse of Apollo Android
│   └── [CRITICAL NODE] 5.1. Insecure HTTP Usage (General Web Security Issue, Less Apollo Specific)
│       └── [HIGH-RISK PATH] 5.1.a. HTTP instead of HTTPS [CRITICAL NODE]
│   └── [HIGH-RISK PATH] 5.2. Insufficient Input Validation in Application Logic (Application Logic Flaw) [CRITICAL NODE]
│       └── [HIGH-RISK PATH] 5.2.a. Lack of Validation on GraphQL Data [CRITICAL NODE]
│       └── [HIGH-RISK PATH] 5.2.b. Improper Query Construction Logic [CRITICAL NODE]

Attack Tree Path: 1. Exploit GraphQL Query/Mutation Manipulation - High-Risk Path

  • 1.1. GraphQL Injection (Client-Side) - Critical Node
    • 1.1.a. Unsanitized User Input in Query Construction - Critical Node
      • Attack Vector: Application dynamically builds GraphQL queries using user input without proper escaping or validation. An attacker can inject malicious GraphQL syntax into the user input to alter the query's logic.
      • Likelihood: Medium
      • Impact: High (Data exfiltration, manipulation, unauthorized access)
      • Effort: Low
      • Skill Level: Medium
      • Detection Difficulty: Medium
      • Mitigation Strategies:
        • Avoid dynamic query construction with user input.
        • Use parameterized queries if dynamic construction is necessary.
        • Implement robust server-side input validation and sanitization.

Attack Tree Path: 2. Exploit GraphQL Response Handling Vulnerabilities - Critical Node (Specific Sub-Node)

  • 2.1.b. Client-Side Parsing Vulnerabilities (Less Likely) - Critical Node
    • 2.1.b.ii. Apollo Android's response parsing logic has vulnerabilities (e.g., buffer overflows, format string bugs - unlikely but theoretically possible) - Critical Node
      • Attack Vector: A compromised GraphQL server sends malformed or specifically crafted malicious GraphQL responses designed to exploit potential vulnerabilities in Apollo Android's response parsing logic. This could potentially lead to buffer overflows, format string bugs, or other parsing-related vulnerabilities on the client side.
      • Likelihood: Very Low
      • Impact: Critical (Code execution, full compromise of the application and potentially the device)
      • Effort: Very High
      • Skill Level: Expert
      • Detection Difficulty: Very High
      • Mitigation Strategies:
        • Keep Apollo Android library updated to the latest version.
        • Implement robust error handling in the application to handle unexpected responses gracefully.
        • Conduct thorough security testing and consider static/dynamic analysis tools on the application and its dependencies.

Attack Tree Path: 3. Build Dependency Vulnerabilities (Indirect) - Critical Node

  • 4.2. Build Dependency Vulnerabilities (Indirect) - Critical Node
    • 4.2.a. Vulnerable Dependencies - Critical Node
      • Attack Vector: Apollo Android or its plugins rely on vulnerable third-party dependencies (e.g., Gradle plugins, Kotlin libraries). Exploiting known vulnerabilities in these dependencies can indirectly compromise the application.
      • Likelihood: Medium
      • Impact: Medium to High (Depends on the nature of the dependency vulnerability, could range from Denial of Service to code execution)
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Low
      • Mitigation Strategies:
        • Implement a robust dependency management process.
        • Regularly scan dependencies for known vulnerabilities using automated tools.
        • Keep dependencies updated to the latest secure versions.
        • Monitor security advisories related to dependencies.

Attack Tree Path: 4. Misconfiguration and Misuse of Apollo Android - High-Risk Path

  • 5.1. Insecure HTTP Usage (General Web Security Issue, Less Apollo Specific) - Critical Node

    • 5.1.a. HTTP instead of HTTPS - Critical Node
      • Attack Vector: The application is configured to use HTTP instead of HTTPS for communication with the GraphQL server. This makes the application vulnerable to Man-in-the-Middle (MitM) attacks, allowing attackers to intercept and modify data in transit.
      • Likelihood: Low (Due to best practices, but misconfiguration is possible)
      • Impact: Critical (Man-in-the-Middle attacks, complete data interception and manipulation, session hijacking)
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Low
      • Mitigation Strategies:
        • Always enforce HTTPS for all GraphQL communication.
        • Regularly review application configuration to ensure HTTPS is enabled and correctly implemented.

  • 5.2. Insufficient Input Validation in Application Logic (Application Logic Flaw) - Critical Node

    • 5.2.a. Lack of Validation on GraphQL Data - Critical Node

      • Attack Vector: The application does not properly validate or sanitize data received from GraphQL queries before using it in application logic or displaying it to the user. This can lead to various vulnerabilities like Cross-Site Scripting (XSS), logic errors, or data corruption.
      • Likelihood: Medium
      • Impact: Medium to High (Depends on how mishandled data is used, could lead to XSS, logic errors, data corruption, etc.)
      • Effort: Low
      • Skill Level: Low to Medium
      • Detection Difficulty: Medium
      • Mitigation Strategies:
        • Implement robust input validation and sanitization for all data received from GraphQL queries.
        • Apply context-appropriate output encoding when displaying data to users or using it in UI components.

    • 5.2.b. Improper Query Construction Logic - Critical Node

      • Attack Vector: The application's logic for constructing GraphQL queries based on user actions or application state is flawed. This can lead to unintended GraphQL queries being executed, potentially exposing sensitive data or performing unauthorized actions.
      • Likelihood: Medium
      • Impact: Medium to High (Unauthorized data access, unintended actions, business logic bypass)
      • Effort: Low
      • Skill Level: Medium
      • Detection Difficulty: Medium
      • Mitigation Strategies:
        • Carefully design and test the application's query construction logic.
        • Implement thorough functional testing and penetration testing to identify logic flaws.
        • Apply the principle of least privilege in GraphQL schema design and server-side authorization to limit the impact of unintended queries.