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Attack Tree Analysis for mikepenz/materialdrawer

Objective: Manipulate UI/Behavior or Gain Unauthorized Access via MaterialDrawer Exploitation

Attack Tree Visualization

                                      Attacker's Goal:
                                      Manipulate UI/Behavior or Gain Unauthorized Access
                                      via MaterialDrawer Exploitation
                                                  |
          -------------------------------------------------------------------------
          |
  1. Inject Malicious Drawer Items [HIGH RISK]                        3. Leverage Configuration Errors
          |
  -------------------------
  |
1a. XSS via Item Text                                               3b. Misconfigured Event Listeners
   (if input not sanitized) [CRITICAL]                                 (e.g., exposing sensitive data
                                                                        in callbacks) [CRITICAL]
          |
          |
          ---------------------------------
          |
          2ai. Manipulate DOM via Event Handler (from 2. Exploit Event Handling)
          (if vulnerable) [CRITICAL]

  • Overall Description: This attack path focuses on the attacker's ability to insert malicious content into the drawer itself. Since the MaterialDrawer is a UI component, controlling its content is a direct way to influence the application. The primary vulnerability here is Cross-Site Scripting (XSS).
  • Description: If the application using MaterialDrawer doesn't properly sanitize user-supplied input before passing it to the library to create drawer items (e.g., item names, descriptions), an attacker can inject JavaScript code. This injected code will then be executed in the context of the victim's browser. * Likelihood: High (if input is not sanitized; Low if sanitized). This is a very common web vulnerability. * Impact: High. XSS can lead to: * Account takeover * Data theft (including cookies and session tokens) * Session hijacking * Website defacement * Redirection to malicious websites * Malware distribution * Effort: Low. Injecting a basic XSS payload is often trivial. * Skill Level: Low. Basic knowledge of HTML and JavaScript is sufficient. * Detection Difficulty: Medium. Detectable through code reviews, penetration testing, and Web Application Firewalls (WAFs), but sophisticated XSS can be obfuscated. * Mitigation: Thoroughly sanitize all user-supplied input before passing it to the MaterialDrawer library. Use a reputable HTML sanitization library.
  • Description: If the application uses custom event handlers for drawer item interactions (clicks, selections, etc.), and these handlers directly manipulate the Document Object Model (DOM) based on unsanitized event data, this can lead to DOM-based Cross-Site Scripting (XSS). The attacker crafts malicious input that, when processed by the event handler, injects malicious script into the DOM. * Likelihood: Medium. Depends on the presence of vulnerabilities in the application's custom event handlers. * Impact: High. DOM-based XSS has the same potential impact as traditional XSS (see 1a). * Effort: Medium. Requires finding and exploiting vulnerabilities in the DOM manipulation logic within the event handlers. * Skill Level: Medium. Requires understanding of DOM manipulation and XSS techniques. * Detection Difficulty: Medium. Similar to other XSS attacks, detectable through code reviews, penetration testing, and WAFs. * Mitigation: * Carefully review all event handlers associated with the drawer. * Ensure event data is properly validated and sanitized before being used to modify the DOM. * Avoid using eval() or similar functions with event data. * Use safe DOM manipulation methods.
  • Overall Description: This attack path focuses on mistakes made by the developers using the MaterialDrawer library, rather than inherent vulnerabilities in the library itself.
  • Description: If the application developer configures event listeners incorrectly, they might inadvertently expose sensitive data or allow unauthorized actions. For example, a callback function might: * Log sensitive data (like API keys, user tokens, or personal information) to the browser's console. * Perform an action (like making an API call) without proper authorization checks, allowing an attacker to bypass security controls. * Incorrectly handle user input within the callback, leading to other vulnerabilities (like XSS, if the callback updates the UI). * Likelihood: Medium. This is a common type of developer error. * Impact: Variable (Low to High). Depends on the sensitivity of the data exposed or the actions allowed without proper authorization. * Effort: Low to Medium. Depends on the specific misconfiguration. Finding an exposed API key in the console is low effort; exploiting a missing authorization check might require more effort. * Skill Level: Low to Medium. Requires understanding of the application's logic and the potential consequences of misconfiguration. * Detection Difficulty: Medium. Detectable through: * Code reviews (looking for insecure callback logic). * Penetration testing (trying to trigger unauthorized actions). * Monitoring application logs (for exposed sensitive data). * Mitigation: * Thoroughly review all event listener configurations. * Ensure that callbacks do not expose sensitive data. * Implement proper authorization checks within callbacks that perform actions. * Follow the principle of least privilege: callbacks should only have the minimum necessary permissions. * Use a linter to identify potential security issues in the code.