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Attack Tree Analysis for github/markup

Objective: Execute Arbitrary Code, Leak Sensitive Info, or Cause DoS via github/markup

Attack Tree Visualization

Attacker Goal: Execute Arbitrary Code, Leak Sensitive Info, or Cause DoS via github/markup ├── 1. Exploit Vulnerabilities in Specific Markup Renderers │ ├── 1.1 Markdown Renderer (github.com/github/markup uses github/cmark-gfm) [HIGH-RISK] │ │ ├── 1.1.1 Regular Expression Denial of Service (ReDoS) in cmark-gfm [HIGH-RISK] │ │ │ └── 1.1.1.1 Craft input with deeply nested structures (e.g., many [ or *) to trigger exponential backtracking. [CRITICAL] │ │ ├── 1.1.2 HTML Injection via Markdown (if raw HTML is allowed) [HIGH-RISK] [CRITICAL] │ │ │ ├── 1.1.2.1 Inject malicious <script> tags. [CRITICAL] │ │ │ └── 1.1.2.2 Inject malicious attributes (e.g., onload, onerror) in allowed HTML tags. [CRITICAL] ├── 2. Exploit Logic Errors in github/markup Itself │ ├── 2.2 Vulnerabilities in the command-line interface (if used). │ │ └── 2.2.1 Command injection if user input is passed unsanitized to shell commands. [CRITICAL]

Attack Tree Path: 1.1.1.1: Craft input with deeply nested structures (ReDoS)

  • Description: The attacker crafts malicious input containing deeply nested Markdown structures (e.g., many opening square brackets [[[[[..., or asterisks ******...). This exploits vulnerabilities in the regular expressions used by cmark-gfm (the Markdown processor) to cause exponential backtracking, consuming excessive CPU resources and leading to a denial-of-service.
  • Likelihood: Medium (Known issue, but requires specific input)
  • Impact: High (DoS can disrupt service)
  • Effort: Low (Simple crafted input)
  • Skill Level: Low (Basic understanding of ReDoS)
  • Detection Difficulty: Medium (Requires monitoring CPU usage or analyzing logs for slow requests)
  • Mitigation:
    • Limit input length.
    • Use a ReDoS-resistant regex engine (if possible, and if you have control over the underlying engine).
    • Implement input sanitization/validation to remove or limit nested structures.
    • Monitor CPU usage to detect potential ReDoS attacks.

Attack Tree Path: 1.1.2.1: Inject malicious <script> tags (HTML Injection)

  • Description: If the application allows raw HTML input within Markdown, the attacker can inject malicious <script> tags containing JavaScript code. This code will be executed in the context of the victim's browser, leading to a Cross-Site Scripting (XSS) vulnerability.
  • Likelihood: High (If raw HTML is enabled)
  • Impact: Very High (Client-side XSS, potential for session hijacking, data theft, defacement)
  • Effort: Low (Simple HTML injection)
  • Skill Level: Low (Basic HTML and JavaScript knowledge)
  • Detection Difficulty: Low (Client-side effects may be visible, server-side detection requires input/output analysis)
  • Mitigation:
    • Preferred: Disable raw HTML input entirely.
    • If raw HTML is required: Use a robust, well-maintained HTML sanitizer (e.g., OWASP Java HTML Sanitizer, Bleach in Python) after github/markup processing. Never rely on github/markup to sanitize HTML. The sanitizer should whitelist safe tags and attributes and remove or escape dangerous ones.

Attack Tree Path: 1.1.2.2: Inject malicious attributes (HTML Injection)

  • Description: Even if <script> tags are blocked, an attacker can inject malicious JavaScript code within allowed HTML tag attributes like onload, onerror, onmouseover, etc. This achieves the same result as injecting <script> tags – client-side XSS.
  • Likelihood: High (If raw HTML is enabled and sanitization is weak)
  • Impact: Very High (Similar to 1.1.2.1 - Client-side XSS)
  • Effort: Low (Simple HTML injection)
  • Skill Level: Low (Basic HTML and JavaScript knowledge)
  • Detection Difficulty: Low (Similar to 1.1.2.1)
  • Mitigation: Same as 1.1.2.1 – use a robust HTML sanitizer after github/markup processing. The sanitizer must handle attributes correctly, either by whitelisting safe attributes or by properly escaping dangerous ones.

Attack Tree Path: 2.2.1: Command injection (CLI)

  • Description: If the application uses the github/markup command-line interface and passes user-supplied input directly to shell commands without proper sanitization or escaping, an attacker can inject arbitrary shell commands. This leads to Remote Code Execution (RCE) on the server.
  • Likelihood: Very Low (If best practices are followed)
  • Impact: Very High (RCE on the server – complete system compromise)
  • Effort: Low (If vulnerable, exploitation is easy)
  • Skill Level: Medium (Requires understanding of command injection)
  • Detection Difficulty: Low (If vulnerable, exploitation attempts may be visible in logs)
  • Mitigation:
    • Never directly construct shell commands using user input.
    • Use parameterized commands or a library that handles escaping properly (e.g., subprocess.run with shell=False in Python, or prepared statements in other languages).
    • Avoid using the shell entirely if possible.