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Mitigation Strategies Analysis for google/ksp

Mitigation Strategy: Strict Dependency Management and Vetting (of KSP Processors)

Description:

  1. Identify all KSP Processors: List all KSP processors, their sources, and versions.
  2. Research Each Processor: Investigate reputation, maintainer, activity, and security issues.
  3. Pin Dependencies: In build.gradle.kts (or equivalent), specify the exact version of each KSP processor. Use implementation("com.example:my-processor:1.2.3"), not implementation("com.example:my-processor:+").
  4. Calculate Checksums: Calculate SHA-256 checksums (or similar) for each processor JAR.
  5. Configure Dependency Verification: Configure your build system (Gradle, Maven) to verify dependencies using checksums.
  6. Regular Audits: Schedule regular audits of all KSP processor dependencies. Use tools like OWASP Dependency-Check or Snyk.
  7. Private Repository (Optional): Consider a private repository manager (Nexus, Artifactory) for pre-vetted KSP processors.

  • Threats Mitigated:

    • Malicious KSP Processor (Supply Chain Attack): Severity: Critical.
    • Vulnerable KSP Processor (Known Vulnerabilities): Severity: High to Critical.

  • Impact:

    • Malicious KSP Processor: Significantly reduces risk. Pinning and checksums make substitution difficult.
    • Vulnerable KSP Processor: Reduces risk by ensuring a known, (hopefully) patched version. Audits catch new vulnerabilities.

  • Currently Implemented:

    • Dependency pinning in build.gradle.kts.
    • Monthly dependency audits with OWASP Dependency-Check.

  • Missing Implementation:

    • Checksum verification is not implemented.
    • No private repository manager.

Mitigation Strategy: Code Review of Processor Source (If Available)

Description:

  1. Obtain Source Code: Get the source code (e.g., from GitHub) if the processor is open-source.
  2. Initial Assessment: Review project structure, build process, and main entry points.
  3. Focus Areas: Concentrate on code that:
    • Handles user input (annotations, configuration).
    • Performs file I/O.
    • Interacts with the network.
    • Executes external commands.
    • Generates code interacting with sensitive data or external systems.
  4. Detailed Review: Line-by-line review of focus areas, looking for vulnerabilities.
  5. Document Findings: Record potential issues.
  6. Report Issues (If Necessary): Responsibly disclose vulnerabilities to maintainers.

  • Threats Mitigated:

    • Malicious KSP Processor (Supply Chain Attack): Severity: Critical.
    • Vulnerable KSP Processor (Unknown Vulnerabilities): Severity: High to Critical.

  • Impact:

    • Malicious KSP Processor: High impact (but effort-intensive). Best for sophisticated attacks.
    • Vulnerable KSP Processor: Moderate to high impact.

  • Currently Implemented:

    • Initial source code review for the primary KSP processor (MyProcessor).

  • Missing Implementation:

    • No ongoing code reviews on processor updates.
    • Not all KSP processors have undergone source code review.

Mitigation Strategy: Code Review of Generated Code

Description:

  1. Locate Generated Code: Find the output directory (e.g., build/generated/ksp/...).
  2. IDE Integration: Configure your IDE to include this directory in the project view.
  3. Review Schedule: Integrate generated code review into your regular code review process.
  4. Focus Areas: Pay attention to:
    • Code handling user input or external data.
    • Code interacting with databases, networks, etc.
    • Code performing security-sensitive operations.
  5. Document Findings: Record potential vulnerabilities.

  • Threats Mitigated:

    • Vulnerabilities in Generated Code: Severity: High to Critical.

  • Impact:

    • Vulnerabilities in Generated Code: High impact. Primary defense against processor output vulnerabilities.

  • Currently Implemented:

    • Generated code is in the IDE project view.

  • Missing Implementation:

    • Generated code is not consistently reviewed.

Mitigation Strategy: Static Analysis of Generated Code

Description:

  1. Choose Static Analysis Tools: Select tools supporting Kotlin and generated code (SonarQube, Detekt, Ktlint, SpotBugs/FindBugs).
  2. Configure Tools: Include the KSP generated code directory in the analysis scope.
  3. Customize Rules (Optional): Create custom rules for specific KSP processor concerns.
  4. Integrate into Build: Run static analysis automatically on every build.
  5. Review Results: Regularly review reports and address issues.

  • Threats Mitigated:

    • Vulnerabilities in Generated Code: Severity: High to Critical.

  • Impact:

    • Vulnerabilities in Generated Code: Moderate to high impact. Automated detection.

  • Currently Implemented:

    • Detekt runs on all Kotlin source files.

  • Missing Implementation:

    • Detekt is not configured for the KSP generated code directory.
    • No custom Detekt rules for KSP processors.

Mitigation Strategy: Dynamic Analysis and Testing (of Functionality Using Generated Code)

Description:

  1. Comprehensive Testing: Ensure tests (unit, integration, end-to-end) cover all functionality from generated code.
  2. Fuzzing: Use fuzzing to test with unexpected/malicious inputs.
  3. Security-Focused Testing: Use tools like OWASP ZAP to probe for vulnerabilities.
  4. Test Input Validation: Specifically test input validation/sanitization in generated code.

  • Threats Mitigated:

    • Vulnerabilities in Generated Code: Severity: High to Critical.

  • Impact:

    • Vulnerabilities in Generated Code: High impact. Finds runtime vulnerabilities.

  • Currently Implemented:

    • Comprehensive unit and integration tests.

  • Missing Implementation:

    • No fuzzing.
    • No regular security-focused testing (OWASP ZAP).
    • Tests don't specifically target generated code's input validation.

Mitigation Strategy: Processor-Specific Security Guidance

Description:

  1. Consult Documentation: Review official documentation for each KSP processor.
  2. Look for Security Sections: Find sections on security, best practices, or limitations.
  3. Follow Recommendations: Implement any provided security recommendations.
  4. Stay Updated: Subscribe to updates from processor maintainers.

  • Threats Mitigated:

    • Vulnerabilities in Generated Code (Specific to Processor): Severity: Variable.
    • KSP API Misuse (in custom processors): Severity: Medium.

  • Impact:

    • Vulnerabilities in Generated Code: Variable.
    • KSP API Misuse: Moderate.

  • Currently Implemented:

    • Initial documentation review for the primary KSP processor.

  • Missing Implementation:

    • No ongoing documentation review.
    • Not all KSP processor documentation thoroughly reviewed.

Mitigation Strategy: Input Validation and Sanitization (in generated code, influenced by KSP configuration)

Description:

  1. Identify Input Points: Find where user input (annotations, configuration) affects generated code.
  2. Processor-Level Validation (Ideal): Configure the KSP processor to perform validation/sanitization, if possible.
  3. Manual Modification (Less Ideal): If not possible, manually modify generated code (less ideal, can be overwritten).
  4. Contribute to Processor (Best): Contribute validation features to the processor (if open-source).
  5. Validation Rules: Implement strict validation based on expected data type, format, and range.
  6. Sanitization: Sanitize input used in dangerous contexts (SQL, HTML) to prevent injection.

  • Threats Mitigated:

    • Vulnerabilities in Generated Code (Injection Attacks): Severity: High to Critical.

  • Impact:

    • Vulnerabilities in Generated Code: High impact. Crucial defense against injections.

  • Currently Implemented:

    • None. The KSP processor lacks built-in input validation.

  • Missing Implementation:

    • Input validation/sanitization are completely missing.

Mitigation Strategy: Thorough Testing of Custom Processors (If Applicable)

Description: (Only if writing your own KSP processors.)

  1. Testing Framework: Use a framework for testing KSP processors (e.g., compile-testing).
  2. Unit Tests: Test individual processor components.
  3. Integration Tests: Verify interaction with the KSP API and code generation.
  4. Edge Cases: Test edge cases and invalid inputs.
  5. Regression Tests: Ensure changes don't introduce vulnerabilities.

  • Threats Mitigated:

    • KSP API Misuse (in custom processors): Severity: Medium.
    • Vulnerabilities in Generated Code (from custom processors): Severity: High.

  • Impact: * KSP API Misuse: High. * Vulnerabilities in Generated Code: High.

  • Currently Implemented:

    • N/A - No custom KSP processors.

  • Missing Implementation:

    • N/A