attack-tree.md

Attack Tree Analysis for ljharb/qs

Objective: Compromise Application Security and Availability by Exploiting qs Library Weaknesses.

Attack Tree Visualization

• Compromise Application Security and Availability
  • Exploit Parsing Logic Vulnerabilities in qs
    • Prototype Pollution [CRITICAL NODE, POTENTIALLY HIGH-RISK]
      • Manipulate Object Prototype via __proto__, constructor.prototype, or similar properties (if vulnerable version used) [POTENTIALLY HIGH-RISK]
  • Exploit Application's Misuse of qs Parsed Data [CRITICAL NODE]
    • Injection Vulnerabilities due to Unsafe Handling of Parsed Data [CRITICAL NODE, HIGH-RISK]
      • Application fails to sanitize or validate data parsed by qs before using it in sensitive operations. [HIGH-RISK]
        • SQL Injection [CRITICAL NODE, HIGH-RISK PATH]
        • Command Injection [CRITICAL NODE, HIGH-RISK PATH]
        • Path Traversal [CRITICAL NODE, HIGH-RISK PATH]
        • Logic Bugs and Application-Specific Vulnerabilities [CRITICAL NODE, HIGH-RISK PATH]

Attack Tree Path: Prototype Pollution [CRITICAL NODE, POTENTIALLY HIGH-RISK]

• Attack Vector: Manipulate Object Prototype via __proto__, constructor.prototype, or similar properties (if vulnerable version used) [POTENTIALLY HIGH-RISK]
  • Mechanism: Craft query string parameters that attempt to modify the prototype of Object or other built-in objects through __proto__ or constructor.prototype properties.
  • Impact: Pollution of JavaScript object prototypes, potentially leading to:
    • Unexpected application behavior.
    • Security vulnerabilities if application logic relies on default object properties or behaviors.
    • In some scenarios, potentially lead to Cross-Site Scripting (XSS) or other attacks if polluted properties are later accessed in a vulnerable context.
  • Mitigation:
    • Use a patched and up-to-date version of qs library. Modern versions of qs have mitigations against prototype pollution.
    • Sanitize or validate data parsed by qs before using it in sensitive operations.
    • Implement Content Security Policy (CSP) to mitigate potential XSS if prototype pollution leads to script injection.
  • Example Query String: ?__proto__[isAdmin]=true or ?constructor.prototype.polluted=true (These are examples, actual exploitability depends on qs version and application context)
  • Risk Estimations:
    • Likelihood: Low (for recent qs versions) to Medium (for older, unpatched versions)
    • Impact: Medium to High
    • Effort: Low to Medium
    • Skill Level: Medium
    • Detection Difficulty: High

Attack Tree Path: Injection Vulnerabilities due to Unsafe Handling of Parsed Data [CRITICAL NODE, HIGH-RISK]

• Attack Vector: Application fails to sanitize or validate data parsed by qs before using it in sensitive operations. [HIGH-RISK]

  • 2.1. SQL Injection [CRITICAL NODE, HIGH-RISK PATH]

    • Mechanism: Attacker crafts query string parameters that, when parsed by qs and used in SQL queries without proper sanitization, lead to SQL injection.
    • Impact: Data breach, data manipulation, unauthorized access to database.
    • Mitigation:
      • Parameterized queries or prepared statements: Use these to prevent SQL injection.
      • Input validation and sanitization: Validate and sanitize all data received from qs before using it in SQL queries.
    • Example Query String: ?search='; DROP TABLE users; -- (classic SQL injection example)
    • Risk Estimations:
      • Likelihood: High
      • Impact: High
      • Effort: Low to Medium
      • Skill Level: Medium
      • Detection Difficulty: Medium

  • 2.2. Command Injection [CRITICAL NODE, HIGH-RISK PATH]

    • Mechanism: Attacker crafts query string parameters that, when parsed by qs and used in system commands without proper sanitization, lead to command injection.
    • Impact: Remote code execution on the server.
    • Mitigation:
      • Avoid executing system commands based on user input whenever possible.
      • If system commands are necessary, use safe APIs and libraries that avoid shell execution.
      • Input validation and sanitization: Strictly validate and sanitize any data from qs used in system commands.
    • Example Query String: ?file=; rm -rf / (dangerous command injection example)
    • Risk Estimations:
      • Likelihood: Medium
      • Impact: High
      • Effort: Medium
      • Skill Level: Medium
      • Detection Difficulty: Medium to High

  • 2.3. Path Traversal [CRITICAL NODE, HIGH-RISK PATH]

    • Mechanism: Attacker crafts query string parameters that, when parsed by qs and used to construct file paths without proper validation, lead to path traversal.
    • Impact: Unauthorized access to files on the server, potential information disclosure.
    • Mitigation:
      • Validate and sanitize file paths: Ensure that paths constructed from qs data are properly validated to prevent traversal outside of allowed directories.
      • Use secure file handling APIs that restrict access to specific directories.
    • Example Query String: ?file=../../../../etc/passwd (path traversal example)
    • Risk Estimations:
      • Likelihood: Medium
      • Impact: Medium to High
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Low to Medium

  • 2.4. Logic Bugs and Application-Specific Vulnerabilities [CRITICAL NODE, HIGH-RISK PATH]

    • Mechanism: Attacker exploits application logic flaws that arise from how the application processes and uses the data parsed by qs. This is highly application-specific.
    • Impact: Varies depending on the application logic, could range from data manipulation to privilege escalation or other security breaches.
    • Mitigation:
      • Thoroughly review application logic that uses qs parsed data.
      • Implement robust input validation and business logic checks.
      • Perform security testing specific to the application's functionality.
    • Example: Application uses a parsed parameter to determine user role without proper authorization checks.
    • Risk Estimations:
      • Likelihood: Medium
      • Impact: Medium to High
      • Effort: Medium to High
      • Skill Level: Medium to High
      • Detection Difficulty: High