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Attack Tree Analysis for taosdata/tdengine

Objective: To gain unauthorized access to data stored within TDengine, disrupt the availability of the TDengine service, or escalate privileges within the TDengine system, ultimately compromising the application relying on it.

Attack Tree Visualization

                                     Compromise Application via TDengine
                                                    |
        -------------------------------------------------------------------------
        |																												|
  1. Data Exfiltration [HR]								 2. Denial of Service (DoS) [HR]
        |																												|
  -------------													  ---------------------
  |																												|										|
1.1																											2.1 {CN}						2.2
SQLi																									Resource					 Network
(TDengine																								Exhaustion				 Flooding [HR]
Specific)																							 (TDengine)				 (TDengine)
  |																												|										|
-------																										---------					  ---------
|																												|										|
1.1.1 [HR] {CN}																							2.1.1 [HR]				2.2.1 [HR] {CN}

Attack Tree Path: 1. Data Exfiltration [HR]

  • 1.1 SQL Injection (TDengine Specific)
    • 1.1.1 Exploiting vulnerabilities in TDengine's SQL parser or query execution engine [HR] {CN}:
      • Description: The attacker crafts malicious SQL queries that exploit flaws in how TDengine parses or executes SQL commands. This is specific to TDengine's implementation, targeting potential weaknesses in its custom SQL dialect, functions, or data types.
      • Likelihood: Low to Medium
      • Impact: High to Very High
      • Effort: Medium to High
      • Skill Level: Intermediate to Advanced
      • Detection Difficulty: Medium to Hard
      • Actionable Insights:
        • Implement rigorous input validation and sanitization specifically tailored to TDengine's SQL dialect.
        • Use parameterized queries (prepared statements) consistently.
        • Conduct fuzz testing of the TDengine SQL parser with malformed queries.
        • Regularly review TDengine's security advisories and apply updates promptly.
        • Implement Web Application Firewall (WAF) rules to detect and block SQLi attempts.
        • Monitor TDengine query logs for suspicious patterns.

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

  • 2.1 Resource Exhaustion (TDengine) {CN}

    • 2.1.1 Submitting queries designed to consume excessive resources [HR]:
      • Description: The attacker sends queries to TDengine that are intentionally designed to consume large amounts of CPU, memory, or disk I/O. This could involve complex joins, operations on large datasets, or exploiting known resource-intensive functions within TDengine.
      • Likelihood: Medium to High
      • Impact: Medium to High
      • Effort: Low to Medium
      • Skill Level: Beginner to Intermediate
      • Detection Difficulty: Easy to Medium
      • Actionable Insights:
        • Implement query timeouts and resource limits within TDengine (if supported).
        • Monitor TDengine's resource usage (CPU, memory, disk I/O) and set alerts for unusual spikes.
        • Rate-limit connections and queries from individual clients.
        • Optimize database schema and queries for performance.
        • Use TDengine's built-in monitoring tools to identify and analyze resource-intensive queries.
        • Implement circuit breakers to prevent cascading failures.

  • 2.2 Network Flooding (TDengine) [HR]

    • 2.2.1 Sending a large volume of connection requests [HR] {CN}:
      • Description: The attacker floods TDengine with a high volume of connection requests, exceeding its capacity to handle new connections. This prevents legitimate users from connecting to the database.
      • Likelihood: High
      • Impact: Medium to High
      • Effort: Very Low to Low
      • Skill Level: Script Kiddie to Beginner
      • Detection Difficulty: Very Easy to Easy
      • Actionable Insights:
        • Implement network-level rate limiting and connection limits (e.g., using iptables or similar tools).
        • Use a firewall to restrict access to TDengine to authorized clients only (whitelist known IP addresses).
        • Consider using a load balancer to distribute traffic across multiple TDengine instances.
        • Deploy intrusion detection/prevention systems (IDS/IPS) to detect and block flooding attacks.
        • Monitor network traffic for unusually high connection rates.
        • Configure SYN cookies or other TCP connection protection mechanisms.