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Attack Tree Analysis for hibiken/asynq

Objective: Compromise application using Asynq by exploiting weaknesses or vulnerabilities within Asynq or its interaction with the application.

Attack Tree Visualization

Compromise Application via Asynq [CRITICAL NODE]

  • OR
    • Denial of Service (DoS) against Asynq Server
      • Resource Exhaustion [HIGH RISK PATH - Availability Impact]
        • Send a massive number of tasks
          • Flood the queue with a large volume of tasks exceeding server capacity, leading to performance degradation or server crash.
    • Compromise Redis Instance [CRITICAL NODE]
      • OR
        • Redis Authentication Bypass [HIGH RISK PATH - Critical Impact]
          • If Redis is not properly secured with authentication (no password set or weak password), gain unauthorized access to Redis instance.
    • Inject Malicious Tasks via Asynq Client [CRITICAL NODE]
      • OR
        • Exploit input validation weaknesses in task handlers [HIGH RISK PATH - Code Execution] [CRITICAL NODE]
          • Craft task data to exploit vulnerabilities in the application's task handlers (e.g., command injection, SQL injection, path traversal) when processing task data.
    • Exploit Task Handler Logic [CRITICAL NODE]
      • OR
        • Input Validation Failures in Task Handlers [HIGH RISK PATH - Code Execution] [CRITICAL NODE]
          • Command Injection [HIGH RISK PATH - Code Execution]
            • Task handler executes system commands based on task data without proper sanitization.
          • SQL Injection [HIGH RISK PATH - Data Breach & Code Execution]
            • Task handler constructs SQL queries based on task data without proper parameterization.
          • Path Traversal [HIGH RISK PATH - Information Disclosure & Potential Code Execution]
            • Task handler accesses files based on task data without proper path validation.

Attack Vector: Flooding the Asynq queue with a massive number of tasks or tasks with excessively large payloads.

  • Likelihood: Medium (Relatively easy to execute if application is exposed).
  • Impact: High (Application unavailability, service disruption).
  • Effort: Low (Simple scripting, readily available tools).
  • Skill Level: Low (Script Kiddie).
  • Detection Difficulty: Easy (High task enqueue rate, resource spikes).
  • Actionable Insights:
    • Implement rate limiting on task enqueueing.
    • Set limits on queue sizes.
    • Monitor Asynq server resource usage and set up alerts.
    • Enforce limits on task payload size.

Attack Vector: Exploiting the lack of or weak authentication on the Redis instance used by Asynq.

  • Likelihood: Medium (Common misconfiguration, especially in development/testing).
  • Impact: Critical (Full access to task queue, data manipulation, potential for further application compromise).
  • Effort: Low (Simple network scan, readily available Redis clients).
  • Skill Level: Low (Script Kiddie).
  • Detection Difficulty: Easy to Medium (Unusual Redis connections, command patterns if monitored).
  • Actionable Insights:
    • Strongly recommended: Enable Redis authentication with a strong password.
    • Restrict network access to the Redis instance using firewalls.
    • Apply the principle of least privilege for Asynq server's Redis access.

Attack Vector: Crafting malicious task data when enqueuing tasks through the Asynq client to exploit vulnerabilities in task handlers.

  • Likelihood: High (Common application vulnerability, task handlers are often complex).
  • Impact: High (Code execution in task handler context, data breach, application compromise).
  • Effort: Low to Medium (Standard web application attack techniques, readily available tools).
  • Skill Level: Low to Medium (Script Kiddie to Competent Hacker).
  • Detection Difficulty: Medium (Depends on logging and monitoring of task handler actions).
  • Actionable Insights:
    • Crucial: Implement thorough input validation and sanitization in all task handlers.
    • Treat task data as potentially untrusted input.
    • Apply the principle of least privilege for task handlers.
    • Use secure serialization methods.
  • Attack Vector: Task handler executes system commands based on task data without proper sanitization.
    • Likelihood: Medium (Common coding mistake).
    • Impact: High (Code execution on the server, full application compromise).
    • Effort: Low to Medium (Standard web application attack techniques).
    • Skill Level: Low to Medium (Script Kiddie to Competent Hacker).
    • Detection Difficulty: Medium (Depends on logging of system command execution).
    • Actionable Insights:
      • Avoid executing system commands based on task data if possible.
      • If necessary, use safe command execution libraries and carefully sanitize inputs.
  • Attack Vector: Task handler constructs SQL queries based on task data without proper parameterization.
    • Likelihood: Medium (Common coding mistake in database-driven applications).
    • Impact: High (Data breach, data manipulation, potential for code execution).
    • Effort: Low to Medium (Standard web application attack techniques).
    • Skill Level: Low to Medium (Script Kiddie to Competent Hacker).
    • Detection Difficulty: Medium (Database query logs, anomaly detection in database access patterns).
    • Actionable Insights:
      • Essential: Use parameterized queries or ORM features to prevent SQL injection.
  • Attack Vector: Task handler accesses files based on task data without proper path validation.
    • Likelihood: Medium (Common coding mistake when handling file paths).
    • Impact: Medium to High (Information disclosure, potential for file manipulation or code execution).
    • Effort: Low to Medium (Standard web application attack techniques).
    • Skill Level: Low to Medium (Script Kiddie to Competent Hacker).
    • Detection Difficulty: Medium (File access logs, anomaly detection in file access patterns).
    • Actionable Insights:
      • Implement strict path validation to prevent path traversal vulnerabilities.