attack-tree.md

Attack Tree Analysis for activerecord-hackery/ransack

Objective: To gain unauthorized access to data, modify data, or cause a denial-of-service (DoS) condition by exploiting vulnerabilities in the Ransack gem or its misuse within the application.

Attack Tree Visualization

[Attacker's Goal: Unauthorized Data Access/Modification/DoS via Ransack]
    |
    ---------------------------------------------------------------------------------
    |                                                 |                               |
[1. Unauthorized Data Access]         [2. Unauthorized Data Modification]       [3. Denial of Service (DoS)]
    |
    -------------------------                  -------------------------       -------------------------       -------------------------       -------------------------
    |                       |                  |                       |       |                       |
[1.1 Attribute Exposure][HR] [1.2 Unsafe Predicate Use] [2.1 Unsafe Predicate Use] [2.2 Mass Assignment][HR] [3.2 Unsafe Predicate DoS][HR] [3.1 Resource Exhaustion]
    |                       |                  |                       |       |
    ---------               |                  |                       |       -------------------------       -------------------------
    |                       |                  |                       |       |                       |       |
[1.1.1 Whitelist Bypass][HR] [1.2.1 SQL Injection][CRITICAL] [2.1.1 SQL Injection][CRITICAL] [2.2.1 Ransackable Attributes] [3.2.1 Regex Predicates][HR] [3.1.2 Large Result Sets][HR]
    |                       |                                                              |                       |
[1.1.2 Association Exposure][HR]                                                                                    [3.2.2 Custom Predicates][HR]

Attack Tree Path: 1. Unauthorized Data Access

• 1.1 Attribute Exposure [HR]

  • Description: Attackers exploit misconfigured or missing attribute whitelists (ransackable_attributes) to access data they shouldn't be able to.
  • Sub-Vectors:
    • 1.1.1 Whitelist Bypass [HR]:
      • Description: The application either doesn't use ransackable_attributes or uses it incorrectly (e.g., a blacklist approach, overly permissive regex). The attacker tries various attribute names in the search parameters to see if any sensitive data is returned.
      • Likelihood: Medium
      • Impact: High
      • Effort: Low to Medium
      • Skill Level: Low to Medium
      • Detection Difficulty: Medium
    • 1.1.2 Association Exposure [HR]:
      • Description: Similar to whitelist bypass, but the attacker exploits poorly configured ransackable_associations to access data from related models. This allows them to traverse relationships and potentially access data they shouldn't have access to.
      • Likelihood: Medium
      • Impact: High
      • Effort: Medium
      • Skill Level: Medium
      • Detection Difficulty: Medium

• 1.2 Unsafe Predicate Use

  • Sub-Vectors:
    • 1.2.1 SQL Injection [CRITICAL]:
      • Description: The attacker injects malicious SQL code through a custom Ransack predicate that doesn't properly sanitize user input. This is the most severe vulnerability, potentially allowing full database access.
      • Likelihood: Low (if Ransack is used correctly, but increases significantly with improper custom predicate usage)
      • Impact: Very High
      • Effort: High
      • Skill Level: High
      • Detection Difficulty: Medium to High

Attack Tree Path: 2. Unauthorized Data Modification

• 2.1 Unsafe Predicate Use

  • Sub-Vectors:
    • 2.1.1 SQL Injection [CRITICAL]:
      • Description: Identical to 1.2.1, but the attacker's goal is to modify or delete data rather than just read it. This leverages the same vulnerability (unsanitized input in custom predicates) for a different, potentially more destructive, purpose.
      • Likelihood: Low (if Ransack is used correctly, but increases significantly with improper custom predicate usage)
      • Impact: Very High
      • Effort: High
      • Skill Level: High
      • Detection Difficulty: Medium to High

• 2.2 Mass Assignment [HR]

  • Sub-Vectors:
    • 2.2.1 ransackable_attributes Misconfiguration:
      • Description: The attacker uses Ransack to set the stage for a mass assignment vulnerability. By controlling the attributes used in a search, they might be able to influence which attributes are later updated in a separate part of the application that is vulnerable to mass assignment. This is an indirect attack using Ransack.
      • Likelihood: Medium
      • Impact: Medium to High
      • Effort: Medium
      • Skill Level: Medium
      • Detection Difficulty: High

Attack Tree Path: 3. Denial of Service (DoS)

• 3.2 Unsafe Predicate DoS [HR]
  • Description: Attackers use specially crafted input to Ransack predicates to cause excessive resource consumption, leading to a denial of service.
  • Sub-Vectors:
    • 3.2.1 Regex Predicates [HR]:
      • Description: The attacker uses a malicious regular expression (ReDoS) in a search parameter (e.g., name_cont_any). The regex is designed to be computationally expensive, causing the server to consume excessive CPU and potentially crash.
      • Likelihood: Medium to High
      • Impact: High
      • Effort: Medium
      • Skill Level: Medium to High
      • Detection Difficulty: Medium
    • 3.2.2 Custom Predicates [HR]:
      • Description: The attacker exploits poorly written custom predicates that contain inefficient database queries or complex logic. By providing specific input, they can trigger the inefficient code, leading to slow response times or a complete denial of service.
      • Likelihood: Medium
      • Impact: Medium to High
      • Effort: Low to Medium
      • Skill Level: Medium
      • Detection Difficulty: High
• 3.1 Resource Exhaustion
  • Sub-Vectors:
    • 3.1.2 Large Result Sets [HR]:
      • Description: The attacker crafts a request that returns a very large number of results, overwhelming the server's resources (memory, database connections, network bandwidth). This is often achieved by bypassing or manipulating pagination parameters.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Medium