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Attack Tree Analysis for doctrine/orm

Objective: Unauthorized Data Access/Modification/Exfiltration or Disruption via Doctrine ORM

Attack Tree Visualization

Goal: Unauthorized Data Access/Modification/Exfiltration or Disruption via Doctrine ORM

├── 1. SQL Injection (Despite ORM) [HIGH-RISK PATH] │ ├── 1.1 Improper Use of Native Queries [HIGH-RISK PATH] │ │ ├── 1.1.1 Direct User Input Concatenation in EntityManager::createNativeQuery() [CRITICAL NODE] │ │ ├── 1.1.2 Insufficient Validation of User Input Before Native Query Construction [CRITICAL NODE] │ ├── 1.2 Abuse of DQL (Doctrine Query Language) │ │ ├── 1.2.1 Dynamic DQL Construction with Unvalidated User Input [CRITICAL NODE] │ └── 1.3 Second-Order SQL Injection │ ├── 1.3.1 Storing Malicious Data that is Later Used in a Query [CRITICAL NODE] ├── 2. Data Leakage / Information Disclosure │ ├── 2.1 Improper Error Handling │ │ ├── 2.1.1 Revealing Database Structure or Query Details in Error Messages [CRITICAL NODE] │ │ └── 2.1.2 Leaking Sensitive Data Through Debugging Features (e.g., Debug::dump()) in Production [CRITICAL NODE] │ └── 2.3 Profiling and Logging │ ├── 2.3.1 Logging Raw Queries with Sensitive Data [CRITICAL NODE] │ └── 2.3.2 Exposing Profiler Information in Production [CRITICAL NODE] ├── 3. Denial of Service (DoS) │ ├── 3.1 Resource Exhaustion │ │ ├── 3.1.1 Uncontrolled Query Execution (e.g., fetching too many entities) [CRITICAL NODE] │ │ ├── 3.1.2 Complex Queries with Inefficient Joins or Filtering [CRITICAL NODE] └── 5. Configuration Issues ├── 5.1 Using Default/Weak Credentials for Database Connection [CRITICAL NODE] └── 5.3 Leaving Debug Mode Enabled in Production [CRITICAL NODE]

Attack Tree Path: 1. SQL Injection (Despite ORM) [HIGH-RISK PATH]

  • 1.1 Improper Use of Native Queries [HIGH-RISK PATH]

    • 1.1.1 Direct User Input Concatenation in EntityManager::createNativeQuery() [CRITICAL NODE]

      • Description: The attacker directly injects malicious SQL code into a native query by manipulating user input that is concatenated directly into the query string. This bypasses the ORM's protection mechanisms.
      • Example: 
        $userInput = $_GET['id']; // Untrusted input
$query = $entityManager->createNativeQuery('SELECT * FROM users WHERE id = ' . $userInput, $rsm);
// If $userInput is  "1; DROP TABLE users;"  the entire users table is dropped.
      • Likelihood: Medium
      • Impact: High
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Medium
      • Mitigation: Use parameterized queries with setParameter() or setParameters(). Never concatenate user input directly.

    • 1.1.2 Insufficient Validation of User Input Before Native Query Construction [CRITICAL NODE]

      • Description: Even if parameters are used, insufficient validation of the input before it's used as a parameter can still lead to vulnerabilities. For example, if the input is expected to be an integer, but no type checking is performed, an attacker might be able to inject SQL code.
      • Example: An attacker might try to inject a subquery or other SQL constructs even if the input is eventually passed as a parameter.
      • Likelihood: Medium
      • Impact: High
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Medium
      • Mitigation: Implement strict input validation and sanitization before using the input in any query, even parameterized ones. Whitelist allowed values whenever possible.

  • 1.2 Abuse of DQL (Doctrine Query Language)

    • 1.2.1 Dynamic DQL Construction with Unvalidated User Input [CRITICAL NODE]
      • Description: Similar to native SQL injection, but using Doctrine's Query Language (DQL). If DQL queries are built dynamically using unvalidated user input, attackers can inject malicious DQL code.
      • Example: 
        $userInput = $_GET['orderBy']; // Untrusted input
$dql = "SELECT u FROM MyProject\Model\User u ORDER BY " . $userInput;
$query = $entityManager->createQuery($dql);
// If $userInput is  "u.id; DROP TABLE users;" (although DQL syntax might make this specific example harder, the principle remains)
      • Likelihood: Low
      • Impact: High
      • Effort: Low
      • Skill Level: Medium
      • Detection Difficulty: Medium
      • Mitigation: Avoid dynamic DQL construction with user input. Use the QueryBuilder and its methods (where(), setParameter()) to safely build queries.

  • 1.3 Second-Order SQL Injection

    • 1.3.1 Storing Malicious Data that is Later Used in a Query [CRITICAL NODE]
      • Description: The attacker injects malicious data into the database (e.g., through a seemingly harmless form field). This data is not immediately dangerous. However, later, when this stored data is retrieved and used in a different query (without proper sanitization), the SQL injection payload is triggered.
      • Example: An attacker injects a malicious string into a "comments" field. Later, when displaying comments, the application uses this data in a query without proper escaping.
      • Likelihood: Medium
      • Impact: High
      • Effort: Medium
      • Skill Level: Medium
      • Detection Difficulty: High
      • Mitigation: Validate and sanitize data before storing it in the database, and validate and sanitize it again before using it in any query.

Attack Tree Path: 2. Data Leakage / Information Disclosure

  • 2.1 Improper Error Handling

    • 2.1.1 Revealing Database Structure or Query Details in Error Messages [CRITICAL NODE]

      • Description: When a database error occurs, the application displays the raw error message to the user. This message can reveal sensitive information about the database schema, table names, column names, and even the query itself.
      • Example: A database error message might reveal the table structure or the SQL query that caused the error.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Very Low
      • Skill Level: Very Low
      • Detection Difficulty: Low
      • Mitigation: Implement custom error handling that displays generic error messages to users. Log detailed error information separately for debugging.

    • 2.1.2 Leaking Sensitive Data Through Debugging Features (e.g., Debug::dump()) in Production [CRITICAL NODE]

      • Description: Debugging tools, like Doctrine's Debug::dump(), are left enabled in the production environment. These tools can expose sensitive data, including entity details, database queries, and configuration information.
      • Example: Debug::dump($user) might expose the user's password hash or other sensitive attributes.
      • Likelihood: Low
      • Impact: High
      • Effort: Very Low
      • Skill Level: Very Low
      • Detection Difficulty: Low
      • Mitigation: Disable all debugging features in production environments. Use environment variables to control debugging settings.

  • 2.3 Profiling and Logging

    • 2.3.1 Logging Raw Queries with Sensitive Data [CRITICAL NODE]

      • Description: The application logs raw SQL queries, including parameters, which may contain sensitive data like passwords, API keys, or personal information.
      • Example: A log file might contain a query like SELECT * FROM users WHERE username = 'admin' AND password = 'plaintext_password'.
      • Likelihood: Low
      • Impact: Medium
      • Effort: Very Low
      • Skill Level: Very Low
      • Detection Difficulty: Low
      • Mitigation: Configure logging to avoid logging raw queries or sensitive parameters. Use parameterized query logging or redact sensitive information.

    • 2.3.2 Exposing Profiler Information in Production [CRITICAL NODE]

      • Description: The Doctrine profiler, which provides detailed information about database queries and performance, is left enabled in the production environment. This can expose sensitive information to attackers.
      • Example: The profiler might reveal the database schema, query execution times, and other details that could be used to craft attacks.
      • Likelihood: Low
      • Impact: Medium
      • Effort: Very Low
      • Skill Level: Very Low
      • Detection Difficulty: Low
      • Mitigation: Disable the Doctrine profiler in production environments.

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

  • 3.1 Resource Exhaustion

    • 3.1.1 Uncontrolled Query Execution (e.g., fetching too many entities) [CRITICAL NODE]

      • Description: The application allows users to trigger queries that fetch a large number of entities without any limits. This can consume excessive server resources (memory, CPU, database connections), leading to a denial of service.
      • Example: A user could request to display all records from a table with millions of rows.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Medium
      • Mitigation: Implement pagination or limits on the number of entities that can be fetched in a single query. Use setMaxResults() and setFirstResult() on the QueryBuilder.

    • 3.1.2 Complex Queries with Inefficient Joins or Filtering [CRITICAL NODE]

      • Description: The application executes complex queries with inefficient joins, filtering, or sorting operations. These queries can consume excessive database resources, leading to a denial of service.
      • Example: A query with multiple joins and complex WHERE clauses that is not optimized.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Medium
      • Mitigation: Optimize database queries for performance. Use appropriate indexes. Avoid unnecessary joins or complex filtering conditions. Profile queries to identify performance bottlenecks.

Attack Tree Path: 5. Configuration Issues

  • 5.1 Using Default/Weak Credentials for Database Connection [CRITICAL NODE] * Description: The application uses default or easily guessable credentials for the database connection. * Example: Using "root" with an empty password, or a common password like "password123". * Likelihood: Low * Impact: Very High * Effort: Very Low * Skill Level: Very Low * Detection Difficulty: Low * Mitigation: Always use strong, unique passwords for database connections. Store credentials securely (e.g., using environment variables or a secure configuration management system).

  • 5.3 Leaving Debug Mode Enabled in Production [CRITICAL NODE] * Description: Debug mode is left enabled in the production environment, exposing sensitive information and potentially enabling other vulnerabilities. * Example: Symfony's debug mode, if enabled, can expose detailed error messages, configuration details, and other sensitive information. * Likelihood: Low * Impact: High * Effort: Very Low * Skill Level: Very Low * Detection Difficulty: Low * Mitigation: Disable debug mode in production environments.