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Threat Model Analysis for pinterest/ktlint

Threat: Malicious Custom Rule Execution

  • Threat: Malicious Custom Rule Execution

    • Description: An attacker crafts a malicious ktlint rule set (JAR file) and distributes it through a compromised repository, social engineering, or a compromised dependency. A developer unknowingly downloads and integrates this rule set. When ktlint runs, the malicious rule executes arbitrary code on the developer's machine or within the CI/CD pipeline. The attacker could steal credentials, modify source code, install malware, or pivot to other systems. This is a classic supply chain attack.

    • Impact:

      • Complete system compromise (developer machine or CI/CD server).
      • Data exfiltration (source code, credentials, sensitive data).
      • Code modification (introduction of backdoors, vulnerabilities, or malicious logic).
      • Lateral movement within the network.

    • Affected ktlint Component: Custom rule loading mechanism (RuleSetProvider, class loading, and the ServiceLoader mechanism). The core vulnerability is ktlint's ability to load and execute arbitrary code from external JAR files provided as rule sets.

    • Risk Severity: Critical

    • Mitigation Strategies:

      • Source Verification: Strictly obtain rule sets only from trusted, official sources (e.g., the official ktlint GitHub repository, extremely well-known and vetted community providers with a strong security track record). Avoid any unknown or unverified sources.
      • Code Review: Mandate thorough, manual code review of the source code of any custom rule set before integration. Treat it as a high-risk third-party dependency. Do not rely solely on automated scanning.
      • Checksum Verification: Always verify the SHA-256 (or other strong cryptographic hash) checksum of the downloaded rule set JAR against a known good value published by the trusted source. Automate this verification in build scripts.
      • Sandboxing: Run ktlint within a strictly sandboxed environment (e.g., a Docker container with minimal privileges and network access) to contain the potential impact of malicious code execution. This is essential for CI/CD pipelines.
      • Dependency Management: Use a dependency management system (e.g., Gradle, Maven) that supports and enforces checksum verification for external JAR dependencies. Configure it to fail the build if checksums do not match.
      • Least Privilege: Run ktlint with the absolute minimum necessary privileges. Never run it as root or with administrator access.
      • Network Restrictions: If possible, restrict network access for the environment where ktlint is executed, especially during CI/CD, to limit the attacker's ability to exfiltrate data or communicate with command-and-control servers.

Threat: Exploitation of ktlint Vulnerability (Leading to Code Execution)

  • Threat: Exploitation of ktlint Vulnerability (Leading to Code Execution)

    • Description: An attacker discovers a zero-day vulnerability in ktlint itself (e.g., in the parsing logic, rule engine, or a specific built-in rule) that allows for arbitrary code execution. They craft a specially designed Kotlin file that, when processed by ktlint, triggers the vulnerability and executes malicious code. This is less likely than the malicious rule scenario but still a significant risk.

    • Impact:

      • Remote code execution on the developer's machine or CI/CD server.
      • Data exfiltration.
      • Code modification.
      • System compromise.

    • Affected ktlint Component: Potentially any part of ktlint, depending on the specific vulnerability. Likely areas include:

      • KtLint.kt (main entry point and processing logic)
      • com.pinterest.ktlint.core.ast (Abstract Syntax Tree parsing)
      • Specific rule implementations within com.pinterest.ktlint.ruleset.standard or com.pinterest.ktlint.ruleset.experimental

    • Risk Severity: High (Potentially Critical if a readily exploitable RCE is found)

    • Mitigation Strategies:

      • Keep Updated: Maintain a strict policy of updating to the latest version of ktlint immediately upon release. Automate this process in CI/CD.
      • Monitor Advisories: Actively monitor ktlint's security advisories, release announcements, and any relevant security mailing lists for vulnerability disclosures.
      • Sandboxing: As with malicious rules, running ktlint in a sandboxed environment (e.g., Docker) significantly reduces the impact of a potential code execution vulnerability.
      • Fuzzing (Advanced): For organizations with high security requirements, consider implementing fuzz testing of ktlint to proactively discover vulnerabilities before attackers do. This is a specialized security testing technique.
      • Vulnerability Scanning (Advanced): Integrate static analysis tools that can scan ktlint's codebase itself for potential vulnerabilities.