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Attack Tree Analysis for cube-js/cube

Objective: Gain Unauthorized Access to Data or Execute Code

Attack Tree Visualization

                                  +-----------------------------------------------------+
                                  | Gain Unauthorized Access to Data or Execute Code  |
                                  +-----------------------------------------------------+
                                                   ^
                                                   |
      +--------------------------------+--------------------------------+--------------------------------+
      |                                |                                |                                |

+---------+---------+ +---------+---------+ +---------+---------+ +---------+---------+ | (Empty) | | Exploit API | | (Empty) | | Exploit Driver | | | | Vulnerabilities| | | | Vulnerabilities| +---------+---------+ +---------+---------+ +---------+---------+ +---------+---------+ ^ | +---------+---------+ +---------+---------+ | Insecure AuthZ| | SQL Injection | | /AuthN Handling| | (via Driver) | | [CRITICAL] | | [CRITICAL] | +---------+---------+ +---------+---------+ [HIGH-RISK] [HIGH-RISK] +--------------------------------+ | +---------+---------+ | Exploit Data | | Schema Leakage | +---------+---------+ ^ | +---------+---------+ | Misconfigured | | Pre-aggregations| +---------+---------+ ^ | +---------+---------+ | Expose Raw Data| | via Pre-aggs | +---------+---------+ ^ | +---------+---------+[HIGH-RISK] | [HIGH-RISK] | +---------+---------+

Attack Tree Path: Exploit API Vulnerabilities -> Insecure AuthZ/AuthN Handling [CRITICAL]

  • Description: This attack vector focuses on exploiting weaknesses in the authentication and authorization mechanisms of the Cube.js API. If an attacker can bypass these controls, they gain unauthorized access to the API and potentially the underlying data.

  • Steps:

    1. Identify API Endpoints: The attacker identifies the exposed API endpoints of the Cube.js application.
    2. Attempt Authentication Bypass: The attacker tries various techniques to bypass authentication, such as:
      • Sending requests without any authentication credentials.
      • Using default or weak credentials.
      • Exploiting vulnerabilities in JWT handling (e.g., weak signing keys, algorithm confusion).
      • Bypassing session management controls.
      • Exploiting custom authentication logic flaws.
    3. Attempt Authorization Bypass: If authentication is bypassed or weak, the attacker attempts to access resources or perform actions they shouldn't be authorized to do. This might involve:
      • Accessing data belonging to other users.
      • Performing administrative actions without proper privileges.
    4. Data Exfiltration or Code Execution: Once unauthorized access is gained, the attacker can exfiltrate sensitive data or, if possible, leverage further vulnerabilities to execute arbitrary code on the server.

  • Likelihood: Medium (Authentication/authorization vulnerabilities are common.)

  • Impact: Very High (Complete compromise of the API and potentially the underlying data.)

  • Effort: Low to Medium (Depends on the specific vulnerability; could be very easy if authentication is completely missing.)

  • Skill Level: Intermediate (Requires understanding of authentication/authorization protocols and common weaknesses.)

  • Detection Difficulty: Medium (Failed login attempts or unauthorized access attempts might be logged, but sophisticated attacks might try to blend in.)

Attack Tree Path: Exploit Driver Vulnerabilities -> SQL Injection (via Driver) [CRITICAL]

  • Description: This attack vector targets vulnerabilities in the database driver used by Cube.js, specifically focusing on SQL injection (or equivalent injection attacks for NoSQL databases).

  • Steps:

    1. Identify Input Points: The attacker identifies input points in the Cube.js API or application that are used to construct database queries.
    2. Craft Injection Payload: The attacker crafts a malicious SQL (or NoSQL) injection payload designed to alter the intended query and execute arbitrary commands.
    3. Submit Payload: The attacker submits the payload through the identified input point.
    4. Exploit Vulnerability: If Cube.js and the driver don't properly sanitize the input, the payload is executed by the database.
    5. Data Exfiltration, Modification, or Code Execution: The attacker can then:
      • Steal sensitive data from the database.
      • Modify or delete data.
      • Potentially gain operating system command execution (depending on the database and its configuration).

  • Likelihood: Medium (SQL injection is a common vulnerability, but depends on input sanitization practices.)

  • Impact: Very High (Arbitrary SQL command execution, leading to complete database compromise.)

  • Effort: Medium (Requires crafting a working SQL injection payload.)

  • Skill Level: Intermediate to Advanced (Requires understanding of SQL injection techniques and the target database.)

  • Detection Difficulty: Medium to Hard (WAFs might detect some attempts, but sophisticated payloads can bypass them. Database auditing is crucial.)

Attack Tree Path: Exploit Data Schema Leakage -> Misconfigured Pre-aggregations -> Expose Raw Data via Pre-aggs

  • Description: This attack vector targets misconfigurations in Cube.js's pre-aggregation feature, which can lead to the exposure of raw, sensitive data that should be protected.

  • Steps:

    1. Identify Pre-aggregation Definitions: The attacker attempts to understand how pre-aggregations are defined within the Cube.js schema. This might involve analyzing the schema itself (if accessible) or observing API responses to infer pre-aggregation behavior.
    2. Craft Queries to Exploit Misconfigurations: The attacker crafts specific queries designed to target potential weaknesses in the pre-aggregation configuration. This might involve:
      • Requesting data at a granularity that is finer than intended.
      • Exploiting edge cases or boundary conditions in the pre-aggregation logic.
      • Combining different dimensions and measures in unexpected ways.
    3. Access Raw Data: If the pre-aggregation is misconfigured, the attacker's queries might return raw data that should have been aggregated or filtered, bypassing intended access controls.
    4. Data Exfiltration: The attacker exfiltrates the exposed raw data.

  • Likelihood: Medium (Requires understanding of Cube.js pre-aggregation and finding a misconfiguration.)

  • Impact: High (Direct access to raw, potentially sensitive data.)

  • Effort: Medium (Requires crafting specific queries to exploit the misconfiguration.)

  • Skill Level: Intermediate (Requires understanding of Cube.js query language and pre-aggregation behavior.)

  • Detection Difficulty: Medium (Unusual query patterns might be detected, but it requires careful monitoring and understanding of expected behavior.)