Skip to content

Latest commit

 

History

History
285 lines (243 loc) · 25.4 KB

attack-tree.md

File metadata and controls

285 lines (243 loc) · 25.4 KB

Attack Tree Analysis for jetbrains/compose-jb

Objective: Compromise a Compose-jb application by exploiting vulnerabilities within the Compose-jb framework or its usage.

Attack Tree Visualization

Compromise Compose-jb Application **[CRITICAL NODE]**
*   Exploit Compose-jb Framework Vulnerabilities **[CRITICAL NODE]**
    *   Memory Corruption Vulnerabilities **[CRITICAL NODE]**
        *   Buffer Overflows in Rendering Engine **[CRITICAL NODE]**
        *   Use-After-Free or Double-Free Errors in UI Component Lifecycle **[CRITICAL NODE]**
    *   Dependency Vulnerabilities in Compose-jb Libraries **[CRITICAL NODE]**
        *   Exploiting Known Vulnerabilities in Transitive Dependencies **[CRITICAL NODE]**
*   Exploit Misuse of Compose-jb Features in Application Code **[CRITICAL NODE]**
    *   Insecure Data Handling due to Compose-jb State Management **[CRITICAL NODE]**
        *   Storing Sensitive Data in Unencrypted Application State **[CRITICAL NODE]**
        *   Leaking Sensitive Data through UI Components (e.g., in logs, debug outputs) **[CRITICAL NODE]**
    *   Platform API Misuse via Compose-jb Interop **[CRITICAL NODE]**
        *   Unsafe System Calls initiated from Compose-jb UI Events **[CRITICAL NODE]**
*   Social Engineering & Supply Chain Attacks (Indirectly related to Compose-jb, but relevant) **[CRITICAL NODE]**
    *   Compromised Development Environment for Compose-jb Application **[CRITICAL NODE]**
        *   Injecting Malicious Code during Development or Build Process **[CRITICAL NODE]**
    *   Malicious Third-Party Compose-jb Libraries or Components **[CRITICAL NODE]**
        *   Using Unverified or Compromised Compose-jb Extensions/Libraries **[CRITICAL NODE]**

Attack Tree Path: 1. Compromise Compose-jb Application [CRITICAL NODE]

  • Description: The ultimate goal of the attacker. Successful compromise means achieving unauthorized access, control, or information from the application or the system it runs on.
  • Likelihood: Varies depending on specific vulnerabilities exploited.
  • Impact: High - Full application and potentially system compromise.
  • Effort: Varies depending on the attack path.
  • Skill Level: Varies depending on the attack path.
  • Detection Difficulty: Varies depending on the attack path.

Attack Tree Path: 2. Exploit Compose-jb Framework Vulnerabilities [CRITICAL NODE]

  • Description: Targeting vulnerabilities directly within the Compose-jb framework code. This is a high-impact attack vector as it can affect multiple applications using the framework.
  • Likelihood: Medium - Frameworks are complex and can have vulnerabilities, though JetBrains likely invests in security.
  • Impact: High - Widespread impact, potentially affecting many applications.
  • Effort: Medium-High - Requires reverse engineering, deep understanding of the framework.
  • Skill Level: High - Expert level security skills, reverse engineering, exploit development.
  • Detection Difficulty: Medium - Vulnerabilities can be subtle and require deep code analysis.
  • Mitigation Strategies:
    • Thorough security audits and penetration testing of the Compose-jb framework.
    • Fuzz testing of critical components like the rendering engine.
    • Static and dynamic analysis tools during framework development.
    • Memory sanitizers and address space layout randomization (ASLR).
    • Prompt patching of identified vulnerabilities.

Attack Tree Path: 3. Memory Corruption Vulnerabilities [CRITICAL NODE]

  • Description: Exploiting memory corruption bugs like buffer overflows, use-after-free, and double-free errors within Compose-jb's C++/Native components (rendering engine, UI component lifecycle).
  • Likelihood: Medium - Complex C++/Native code is prone to memory errors.
  • Impact: High - Code execution, system compromise, denial of service.
  • Effort: Medium-High - Requires reverse engineering, exploit development for specific memory bugs.
  • Skill Level: High - Expert in memory corruption vulnerabilities and exploit techniques.
  • Detection Difficulty: Medium - Can be subtle, requires memory monitoring, crash analysis, and specialized debugging tools.
  • Mitigation Strategies:
    • Secure coding practices in C++/Native code.
    • Robust bounds checking and input validation in rendering engine and critical paths.
    • Memory sanitizers (AddressSanitizer, MemorySanitizer) during development and testing.
    • Regular code audits and penetration testing focused on memory safety.

Attack Tree Path: 4. Buffer Overflows in Rendering Engine [CRITICAL NODE]

  • Description: Triggering buffer overflows in the rendering engine by providing oversized or malformed input data (images, fonts, UI element descriptions) that exceed allocated buffer sizes.
  • Likelihood: Medium - Rendering engines are complex and process external data, increasing the risk of buffer overflows.
  • Impact: High - Code execution, system compromise.
  • Effort: Medium-High - Requires understanding rendering engine input formats and crafting specific overflow payloads.
  • Skill Level: High - Expertise in buffer overflow exploitation and rendering engine internals.
  • Detection Difficulty: Medium - Fuzzing and memory monitoring are needed for detection.
  • Mitigation Strategies:
    • Thorough fuzz testing of rendering engine components with various input types and sizes.
    • Implement robust bounds checking in critical rendering paths.
    • Use safe memory management practices in rendering engine code.

Attack Tree Path: 5. Use-After-Free or Double-Free Errors in UI Component Lifecycle [CRITICAL NODE]

  • Description: Exploiting use-after-free or double-free errors in the lifecycle management of UI components within Compose-jb. This can occur due to incorrect object lifetime management, race conditions, or errors in component disposal logic.
  • Likelihood: Medium - Complex UI component lifecycles and asynchronous operations can lead to memory management errors.
  • Impact: High - Code execution, system compromise.
  • Effort: Medium - Requires understanding of component lifecycle and debugging memory management issues.
  • Skill Level: Medium-High - Proficient in debugging and understanding memory management in complex systems.
  • Detection Difficulty: Medium - Memory sanitizers can detect these errors during testing, but runtime exploitation can be harder to trace.
  • Mitigation Strategies:
    • Employ static analysis tools and memory sanitizers (e.g., AddressSanitizer) during development and testing.
    • Rigorous testing of UI component lifecycle management, especially in concurrent scenarios.
    • Careful code reviews focusing on object lifetime and memory management.

Attack Tree Path: 6. Dependency Vulnerabilities in Compose-jb Libraries [CRITICAL NODE]

  • Description: Exploiting known vulnerabilities in third-party libraries that Compose-jb depends on, including transitive dependencies.
  • Likelihood: Medium - Dependencies often have vulnerabilities, and transitive dependencies are harder to track and manage.
  • Impact: High - Depends on the vulnerability in the dependency - could be code execution, data breach, denial of service.
  • Effort: Low-Medium - Using vulnerability scanners, exploiting known vulnerabilities is often easier as exploits might be publicly available.
  • Skill Level: Low-Medium - Using vulnerability scanners and readily available exploit code requires less expertise.
  • Detection Difficulty: Low - Vulnerability scanners easily detect known vulnerabilities.
  • Mitigation Strategies:
    • Regularly scan Compose-jb project dependencies (including transitive ones) for known vulnerabilities using dependency scanning tools (e.g., OWASP Dependency-Check, Snyk).
    • Implement a process for promptly patching or updating vulnerable dependencies.
    • Monitor security advisories for Compose-jb dependencies.

Attack Tree Path: 7. Exploiting Known Vulnerabilities in Transitive Dependencies [CRITICAL NODE]

  • Description: Specifically targeting vulnerabilities in libraries that are not directly used by Compose-jb but are dependencies of Compose-jb's direct dependencies (transitive dependencies).
  • Likelihood: Medium - Transitive dependencies are often overlooked in security assessments, making them a potential attack vector.
  • Impact: High - Same as dependency vulnerabilities in general.
  • Effort: Low-Medium - Similar to exploiting direct dependency vulnerabilities.
  • Skill Level: Low-Medium - Similar to exploiting direct dependency vulnerabilities.
  • Detection Difficulty: Low - Dependency scanners can identify transitive vulnerabilities.
  • Mitigation Strategies:
    • Use dependency scanning tools that analyze transitive dependencies.
    • Maintain an up-to-date dependency tree and track transitive dependencies.
    • Prioritize patching vulnerabilities in transitive dependencies as well.

Attack Tree Path: 8. Exploit Misuse of Compose-jb Features in Application Code [CRITICAL NODE]

  • Description: Exploiting vulnerabilities introduced by developers' insecure usage of Compose-jb features, even if the framework itself is secure.
  • Likelihood: High - Developer errors are a common source of vulnerabilities.
  • Impact: Medium-High - Depends on the specific misuse, can lead to data breaches, logic bypasses, or system compromise.
  • Effort: Low-Medium - Often easier to exploit than framework vulnerabilities as it targets application-level logic.
  • Skill Level: Low-Medium - Basic security knowledge and application understanding are often sufficient.
  • Detection Difficulty: Low-Medium - Code review, static analysis, and penetration testing of the application can detect these issues.
  • Mitigation Strategies:
    • Secure coding training for developers focusing on Compose-jb specific security considerations.
    • Code review processes to identify insecure usage patterns.
    • Static and dynamic application security testing (SAST/DAST).
    • Security guidelines and best practices for developing Compose-jb applications.

Attack Tree Path: 9. Insecure Data Handling due to Compose-jb State Management [CRITICAL NODE]

  • Description: Vulnerabilities arising from improper handling of sensitive data within Compose-jb's state management mechanisms. This includes storing sensitive data unencrypted in application state or leaking it through UI components or logs.
  • Likelihood: High - Common developer mistake, easy to overlook secure data handling practices in UI applications.
  • Impact: Medium-High - Data breach, privacy violations, reputational damage.
  • Effort: Low - Requires access to application's memory, storage, logs, or UI.
  • Skill Level: Low - Basic debugging skills or access to system tools are often enough.
  • Detection Difficulty: Low-Medium - Code review, static analysis, data leakage detection tools can identify these issues.
  • Mitigation Strategies:
    • Educate developers on secure data handling practices within Compose-jb applications.
    • Provide guidelines and examples for encrypting sensitive data at rest and in memory, even within application state.
    • Implement secure logging practices and prevent logging of sensitive data.
    • Review UI components for potential data leakage vulnerabilities.

Attack Tree Path: 10. Storing Sensitive Data in Unencrypted Application State [CRITICAL NODE]

  • Description: Developers directly storing sensitive information (passwords, API keys, personal data) in Compose-jb application state without encryption.
  • Likelihood: High - Easy mistake for developers to make, especially if not security-conscious.
  • Impact: Medium-High - Data breach if application state is accessed (memory dump, storage access).
  • Effort: Low - Requires access to the application's memory or storage.
  • Skill Level: Low - Basic debugging or system access skills.
  • Detection Difficulty: Low-Medium - Code review, static analysis, memory inspection tools.
  • Mitigation Strategies:
    • Never store sensitive data in plain text.
    • Use encryption for sensitive data at rest and in memory.
    • Utilize secure storage mechanisms provided by the platform.
    • Implement data masking or redaction in UI and logs.

Attack Tree Path: 11. Leaking Sensitive Data through UI Components (e.g., in logs, debug outputs) [CRITICAL NODE]

  • Description: Sensitive data being inadvertently displayed in UI components (e.g., debug information, error messages) or logged in application logs, making it accessible to attackers.
  • Likelihood: Medium-High - Logging and debug outputs often contain sensitive information and are easily overlooked.
  • Impact: Medium - Data breach, privacy violation.
  • Effort: Low - Requires access to logs, debug builds, or sometimes even production UI.
  • Skill Level: Low - Basic access to system logs or application UI.
  • Detection Difficulty: Low-Medium - Log analysis, code review, penetration testing.
  • Mitigation Strategies:
    • Implement secure logging practices.
    • Ensure sensitive data is not logged or exposed through UI components in debug or production builds.
    • Review UI components for potential data leakage vulnerabilities.
    • Disable debug outputs in production builds.

Attack Tree Path: 12. Platform API Misuse via Compose-jb Interop [CRITICAL NODE]

  • Description: Vulnerabilities arising from insecure or improper use of platform-specific APIs (system calls, OS features) through Compose-jb's interop mechanisms.
  • Likelihood: Medium - Developers might directly call system APIs from UI events without proper security checks.
  • Impact: High - System compromise, privilege escalation, arbitrary code execution.
  • Effort: Medium - Requires identifying system call points and crafting malicious UI interactions.
  • Skill Level: Medium - Understanding system APIs and security implications of system calls.
  • Detection Difficulty: Medium - System call monitoring, security auditing of API usage.
  • Mitigation Strategies:
    • Restrict and carefully audit any system calls or platform API interactions initiated from UI events.
    • Implement proper input validation and sanitization before making system calls.
    • Follow the principle of least privilege when granting permissions to the application.
    • Use secure platform API wrappers or libraries where available.

Attack Tree Path: 13. Unsafe System Calls initiated from Compose-jb UI Events [CRITICAL NODE]

  • Description: Directly initiating system calls (e.g., file system access, process execution) from UI event handlers in Compose-jb without proper authorization or input validation.
  • Likelihood: Medium - Developers might directly call system APIs for convenience without considering security implications.
  • Impact: High - System compromise, arbitrary code execution, privilege escalation.
  • Effort: Medium - Requires identifying system call points in the code and crafting malicious UI interactions to trigger them with malicious parameters.
  • Skill Level: Medium - Understanding system APIs and security implications of direct system calls.
  • Detection Difficulty: Medium - System call monitoring, security auditing of API usage in the application.
  • Mitigation Strategies:
    • Avoid direct system calls from UI event handlers if possible.
    • If system calls are necessary, implement strict input validation and sanitization of all parameters.
    • Enforce least privilege principles and minimize permissions required for system calls.
    • Use secure platform API wrappers or libraries that provide built-in security checks.

Attack Tree Path: 14. Exploiting Native Libraries or JNI Bridges used by Compose-jb Application [CRITICAL NODE]

  • Description: Exploiting vulnerabilities in native libraries or JNI bridges that are used by a Compose-jb application to interact with platform-specific functionality.
  • Likelihood: Low-Medium - Native libraries can have vulnerabilities, and JNI bridges introduce complexity and potential security risks in inter-language communication.
  • Impact: High - Code execution, system compromise if the native library is vulnerable.
  • Effort: Medium-High - Requires reverse engineering native libraries and developing exploits for native code vulnerabilities.
  • Skill Level: High - Native code security expertise, reverse engineering, and exploit development for native platforms.
  • Detection Difficulty: Medium-High - Native code analysis and vulnerability scanning of native libraries are more complex.
  • Mitigation Strategies:
    • Ensure native libraries are securely developed and maintained.
    • Scan native libraries for known vulnerabilities using specialized tools.
    • Follow secure coding practices for JNI interactions to prevent vulnerabilities in the bridge itself.
    • Regularly update native libraries to patch security vulnerabilities.

Attack Tree Path: 15. Social Engineering & Supply Chain Attacks (Indirectly related to Compose-jb, but relevant) [CRITICAL NODE]

  • Description: Attacks that target the software development lifecycle and supply chain, indirectly impacting Compose-jb applications. This includes compromising the development environment or using malicious third-party libraries.
  • Likelihood: Low-Medium - Targeted attacks and supply chain compromises are increasing, but still less common than direct application vulnerabilities.
  • Impact: High - Complete application compromise, widespread distribution of malware, significant reputational damage.
  • Effort: High - Requires significant planning, access to development infrastructure, social engineering, or advanced persistent threat techniques.
  • Skill Level: High - Advanced attacker, supply chain attack expertise, system administration, social engineering skills.
  • Detection Difficulty: High - Requires robust security monitoring of development infrastructure, code integrity checks, and supply chain security measures.
  • Mitigation Strategies:
    • Secure development environments and build pipelines.
    • Implement code review processes and verify the integrity of development tools and dependencies.
    • Carefully vet and verify the integrity of any third-party Compose-jb libraries or components.
    • Use reputable sources for libraries and perform security audits of external dependencies.
    • Implement supply chain security measures and monitor for anomalies.

Attack Tree Path: 16. Compromised Development Environment for Compose-jb Application [CRITICAL NODE]

  • Description: An attacker compromises the development environment used to build the Compose-jb application, allowing them to inject malicious code directly into the application codebase during development or the build process.
  • Likelihood: Low-Medium - Targeted attacks on development environments are less frequent but highly impactful.
  • Impact: High - Malicious code injected into the application, potentially affecting all users.
  • Effort: High - Requires compromising developer machines, build servers, or code repositories.
  • Skill Level: High - Advanced attacker, system administration, potentially social engineering or APT techniques.
  • Detection Difficulty: High - Requires robust security monitoring of development infrastructure and code integrity checks.
  • Mitigation Strategies:
    • Secure development environments with strong access controls and multi-factor authentication.
    • Implement code review processes to detect malicious code injection.
    • Use secure build pipelines and verify the integrity of build artifacts.
    • Regularly audit and monitor development infrastructure for security breaches.

Attack Tree Path: 17. Injecting Malicious Code during Development or Build Process [CRITICAL NODE]

  • Description: The specific action of injecting malicious code into the application's source code or build artifacts within a compromised development environment.
  • Likelihood: Low-Medium - Dependent on the success of compromising the development environment.
  • Impact: High - Malicious code becomes part of the application, potentially affecting all users.
  • Effort: Medium - Once the development environment is compromised, code injection can be relatively straightforward.
  • Skill Level: Medium - Software development skills to inject code, understanding of the build process.
  • Detection Difficulty: High - Requires thorough code review, build artifact verification, and potentially behavioral analysis of the application.
  • Mitigation Strategies:
    • Implement code signing and verification to ensure code integrity.
    • Use automated code analysis tools to detect suspicious code patterns.
    • Regularly audit and monitor code repositories for unauthorized changes.

Attack Tree Path: 18. Malicious Third-Party Compose-jb Libraries or Components [CRITICAL NODE]

  • Description: Developers unknowingly use malicious or compromised third-party Compose-jb libraries or components in their application, introducing vulnerabilities or malicious functionality.
  • Likelihood: Low-Medium - Developers might use untrusted libraries, especially if not carefully vetted or if attackers compromise legitimate library repositories.
  • Impact: High - Depends on the library's functionality - could be data theft, code execution, backdoors, or other malicious actions.
  • Effort: Low-Medium - Finding or creating malicious libraries and promoting their use can be relatively low effort.
  • Skill Level: Medium - Developing or modifying libraries, potentially social engineering to promote malicious libraries.
  • Detection Difficulty: Medium - Code review of dependencies, dependency scanning for known malicious libraries, behavioral analysis of the application.
  • Mitigation Strategies:
    • Carefully vet and verify the integrity of any third-party Compose-jb libraries or components used in the application.
    • Use reputable sources for libraries and prefer well-established and actively maintained libraries.
    • Perform security audits of external dependencies and their code.
    • Use dependency scanning tools to detect known malicious libraries or components.

Attack Tree Path: 19. Using Unverified or Compromised Compose-jb Extensions/Libraries [CRITICAL NODE]

  • Description: The specific action of incorporating third-party Compose-jb libraries or extensions into the application without proper verification of their security and integrity.
  • Likelihood: Low-Medium - Developers might prioritize functionality over security when choosing libraries, especially from less reputable sources.
  • Impact: High - Malicious code from the library becomes part of the application.
  • Effort: Low-Medium - Finding and incorporating libraries is generally easy.
  • Skill Level: Medium - Basic software development skills to integrate libraries.
  • Detection Difficulty: Medium - Code review of library code, dependency scanning, behavioral analysis of the application.
  • Mitigation Strategies:
    • Establish a process for vetting and approving third-party libraries before use.
    • Check library sources, maintainers, and community reputation.
    • Perform security audits or code reviews of third-party libraries.
    • Use dependency scanning tools to identify known vulnerabilities in libraries.