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Attack Tree Analysis for mongodb/mongo

Objective: To gain unauthorized access to, modify, or exfiltrate data stored in the MongoDB database, or to disrupt the availability of the application relying on the database, by exploiting vulnerabilities or misconfigurations related to the MongoDB driver and its interaction with the database.

Attack Tree Visualization

                                     Compromise Application via MongoDB Driver
                                                    |
        -------------------------------------------------------------------------
        |						|
  1. Data Exfiltration/Modification			  2. Denial of Service (DoS)
        |						|
  -------------------------			   -------------------------
  |					   |				   |
1.1 Injection Attacks	   1.2 Auth Bypass		  2.1 Resource Exhaustion
  |					   |				   |
  -----					   -----				   -----
  |					   |				   |
***1.1.1***				 ***1.2.1***				 ***2.1.2***
***NoSQL***				  ***Weak***				  ***Slow***
***Inj.*** [CRITICAL]		     ***Creds.*** [CRITICAL]		 ***Queries*** [CRITICAL]
        |
        |
  3. Code Execution
        |
  -------------------------
        |
    3.1 Driver-Level Vulnerabilities
        |
      -----
        |
      3.1.1
      Zero-Day
      in Driver [CRITICAL]

Attack Tree Path: 1. Data Exfiltration/Modification

  • 1.1 Injection Attacks

    • 1.1.1 NoSQL Injection [CRITICAL]

      • Description: The attacker injects malicious MongoDB operators or commands into application queries by manipulating user input that is not properly validated or sanitized. This allows the attacker to bypass intended access controls and retrieve, modify, or delete arbitrary data.
      • Likelihood: High (if input validation is weak or absent) / Medium (if some validation exists, but is flawed).
      • Impact: High (complete data compromise, modification, or deletion).
      • Effort: Low to Medium (depending on the complexity of the application and the vulnerability).
      • Skill Level: Medium (requires understanding of MongoDB query language and injection techniques).
      • Detection Difficulty: Medium to High (can be difficult to detect without proper logging, intrusion detection, and query analysis). Anomalous query patterns might be a clue.
      • Mitigation:
        • Strict Input Validation: Implement rigorous input validation and sanitization before constructing any MongoDB queries. Use a whitelist approach.
        • Parameterized Queries: Use parameterized queries if supported by the driver or ORM. Verify that the ORM truly parameterizes.
        • Least Privilege: Ensure the database user account has the minimum necessary permissions.
        • Regular Expression Caution: Carefully craft and test regular expressions used in queries.

    • 1.2 Authentication Bypass

      • 1.2.1 Weak Credentials [CRITICAL]
        • Description: The attacker gains access to the MongoDB database by using default, easily guessable, or compromised credentials.
        • Likelihood: Medium (depends on password policies and user awareness).
        • Impact: High (complete database access).
        • Effort: Low (brute-force or dictionary attacks).
        • Skill Level: Low (basic scripting skills).
        • Detection Difficulty: Medium (failed login attempts can be logged, but sophisticated attackers might use slow, distributed attacks).
        • Mitigation:
          • Strong, Unique Passwords: Use strong, randomly generated passwords.
          • Password Management: Store credentials securely (environment variables, secrets management system). Never hardcode.
          • Multi-Factor Authentication (MFA): Enable MFA if supported.

Attack Tree Path: 2. Denial of Service (DoS)

  • 2.1 Resource Exhaustion * 2.1.2 Slow Queries [CRITICAL] * Description: The attacker submits intentionally complex or inefficient queries that consume excessive database resources (CPU, memory, I/O), slowing down or crashing the database server, thus denying service to legitimate users. * Likelihood: Medium (depends on query complexity and database indexing). * Impact: Medium to High (application slowdown or unavailability). * Effort: Low to Medium (crafting a slow query might require some understanding of MongoDB's query optimizer). * Skill Level: Medium (requires knowledge of MongoDB query performance). * Detection Difficulty: Medium (database profiling and monitoring can identify slow queries). * Mitigation: * Query Optimization: Analyze and optimize all application queries. Use indexes appropriately. * Query Timeouts: Set reasonable timeouts for all database operations. * Rate Limiting: Implement rate limiting to prevent query flooding. * Profiling: Use MongoDB's profiling tools.

Attack Tree Path: 3. Code Execution

  • 3.1 Driver-Level Vulnerabilities * 3.1.1 Zero-Day in Driver [CRITICAL]: * Description: A previously unknown and unpatched vulnerability in the MongoDB driver itself is exploited by the attacker, potentially leading to remote code execution on the application server. * Likelihood: Very Low. * Impact: Very High (potential for complete system compromise). * Effort: Very High. * Skill Level: Very High. * Detection Difficulty: Very High. * Mitigation: * Keep Driver Updated: The primary defense is to apply updates as soon as they are available. * Security Monitoring: Monitor security advisories and vulnerability databases. * Defense in Depth: Implement other security measures (network segmentation, intrusion detection) to limit the impact.