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Attack Tree Analysis for jakewharton/butterknife

Objective: Compromise application using Butterknife by exploiting weaknesses or vulnerabilities within Butterknife itself.

Attack Tree Visualization

Compromise Application Using Butterknife
└── [HR][CR] Exploit Supply Chain Vulnerabilities
    └── [HR][CR] Malicious Dependency Injection
        └── [HR][CR] Dependency Confusion Attack
        └── [CR] Compromised Build System/Registry
    └── [CR] Compromised Butterknife Repository (Implicitly High Risk due to impact)
└── [CR] Exploit Butterknife Specific Vulnerabilities (Implicitly High Risk if leading to Sensitive Data Exposure)
    └── [2.1] Bugs in Annotation Processor (Implicitly High Risk if leading to Sensitive Data Exposure)
        └── [2.1.1] Logic Errors in Processing (Implicitly High Risk if leading to Sensitive Data Exposure)
            └── [CR] [2.1.1.2.1] Sensitive Data in Annotations Exposed

Attack Step Description: Targeting the process of obtaining and integrating Butterknife into the application to introduce malicious code or a compromised version.

  • Likelihood: Medium
  • Impact: High
  • Effort: Medium
  • Skill Level: Medium
  • Detection Difficulty: Medium
  • Mitigation Strategies:
    • Implement dependency verification (checksum, signature).
    • Use dependency lock files.
    • Utilize private/internal repositories with access control.
    • Regular dependency audits and vulnerability scanning.

Attack Step Description: Replacing the legitimate Butterknife library with a malicious version during dependency resolution.

  • Likelihood: Medium
  • Impact: High
  • Effort: Medium
  • Skill Level: Medium
  • Detection Difficulty: Medium
  • Mitigation Strategies:
    • Dependency verification.
    • Dependency locking.
    • Secure build system and dependency registry.

Attack Step Description: Uploading a malicious library with the same name to public repositories to trick the build system into downloading it.

  • Likelihood: Medium
  • Impact: High
  • Effort: Low
  • Skill Level: Low
  • Detection Difficulty: Medium
  • Mitigation Strategies:
    • Strictly define dependency sources (prioritize private/internal repositories).
    • Dependency verification.
    • Dependency locking.
    • Regularly review and audit dependency configurations.

Attack Step Description: Compromising the build system or a private dependency registry to inject a malicious Butterknife library directly into the build process.

  • Likelihood: Low
  • Impact: Critical
  • Effort: High
  • Skill Level: High
  • Detection Difficulty: High
  • Mitigation Strategies:
    • Harden build systems and dependency registries with strong access controls.
    • Regular security audits and vulnerability scanning of build infrastructure.
    • Implement integrity checks for dependencies within the build process.
    • Principle of least privilege for build processes and users.

Attack Step Description: Compromising the official Butterknife GitHub repository or its distribution channels to inject malicious code.

  • Likelihood: Very Low
  • Impact: Critical
  • Effort: Very High
  • Skill Level: High
  • Detection Difficulty: Low (Likely to be detected quickly due to widespread impact)
  • Mitigation Strategies:
    • Rely on official and trusted sources for dependencies.
    • Monitor for security advisories related to Butterknife.
    • Verify checksums of downloaded libraries if provided.

Attack Step Description: Developers unintentionally include sensitive data in Butterknife annotations, and a bug in the annotation processor leads to its exposure in generated code or build artifacts.

  • Likelihood: Very Low (Requires developer mistake and processor bug)
  • Impact: High
  • Effort: Low (Developer mistake is the primary factor)
  • Skill Level: Low (Developer mistake)
  • Detection Difficulty: Medium
  • Mitigation Strategies:
    • Avoid storing sensitive data directly in annotations.
    • Use secure configuration management practices (environment variables, configuration files).
    • Regularly review generated code and build artifacts for unintended data exposure.
    • Static analysis tools to detect potential sensitive data in annotations.