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Attack Tree Analysis for go-gorm/gorm

Objective: Gain Unauthorized Access to or Control over Data Managed by GORM

Attack Tree Visualization

                                     Gain Unauthorized Access to or Control over Data Managed by GORM
                                                        |
          ---------------------------------------------------------------------------------
          |												|
  1. SQL Injection (GORM Specific)					    3. Denial of Service (GORM Specific)
          |												|
  -------------------------								---------------------------------
  |														|
1.1														3.1
Raw SQL with String Concatenation [CRITICAL]						Resource Exhaustion (e.g., large queries) [CRITICAL]

Attack Tree Path: 1. SQL Injection (GORM Specific)

  • Overall Description:
    • This attack path focuses on exploiting vulnerabilities that allow an attacker to inject malicious SQL code into queries executed by GORM. Even though GORM is designed to prevent SQL injection, improper usage can still create vulnerabilities.
    • Successful SQL injection can lead to data breaches, data modification, privilege escalation, and potentially even remote code execution (depending on the database and its configuration).

Attack Tree Path: 1.1 Raw SQL with String Concatenation [CRITICAL]

  • Description: This is the most dangerous and direct form of SQL injection within the context of GORM. It occurs when developers use db.Exec() or db.Raw() and directly concatenate user-supplied data into the SQL query string without using parameterized queries. GORM's built-in protection mechanisms are bypassed in this scenario.
    • Example: 
      userInput := "'; DROP TABLE users; --"
db.Raw("SELECT * FROM users WHERE name = '" + userInput + "'").Scan(&users)
    • Likelihood: Medium (if developers are not properly trained or if code reviews are lax)
    • Impact: Very High (complete data compromise, potential code execution)
    • Effort: Low (simple string manipulation)
    • Skill Level: Intermediate (understanding of SQL injection basics)
    • Detection Difficulty: Medium (can be detected with static analysis and code review, but might be missed if not explicitly looked for)
    • Mitigation:
      • Strictly prohibit the use of db.Raw() and db.Exec() with direct string concatenation.
      • Enforce the use of parameterized queries: db.Raw("SELECT * FROM users WHERE name = ?", userInput).Scan(&users). GORM handles escaping correctly with placeholders.
      • Use static analysis tools (e.g., go vet, gosec) to automatically detect string concatenation in SQL queries.
      • Conduct thorough code reviews with a focus on identifying potential SQL injection vulnerabilities.
      • Educate developers on the dangers of SQL injection and the proper use of GORM's API.

Attack Tree Path: 3. Denial of Service (GORM Specific)

  • Overall Description:
    • This attack path focuses on exploiting vulnerabilities that allow an attacker to disrupt the availability of the application by overwhelming the database or application resources.
    • Successful DoS attacks can make the application unusable for legitimate users.

Attack Tree Path: 3.1 Resource Exhaustion (e.g., large queries) [CRITICAL]

  • Description: This vulnerability occurs when an attacker can craft queries that retrieve an excessive amount of data from the database, consuming significant resources (memory, CPU, database connections). This can lead to the database server becoming unresponsive or the application crashing.
    • Example: An endpoint that retrieves all users without pagination: 
      func GetAllUsers(w http.ResponseWriter, r *http.Request) {
    var users []User
    db.Find(&users) // No Limit or Offset
    // ...
}
      An attacker could repeatedly call this endpoint, eventually exhausting database resources.
    • Likelihood: Medium (common if pagination and limits are not implemented)
    • Impact: High (application unavailability)
    • Effort: Low (simple query manipulation)
    • Skill Level: Intermediate (understanding of database performance)
    • Detection Difficulty: Medium (can be detected through performance monitoring and database logs)
    • Mitigation:
      • Implement pagination for all queries that could potentially return a large number of results. Use GORM's Limit and Offset methods: db.Limit(10).Offset(0).Find(&users).
      • Set reasonable limits on the maximum number of records that can be retrieved in a single query, even with pagination.
      • Validate user input to prevent excessively large offset or limit values.
      • Monitor database resource usage (CPU, memory, connections) and set alerts for unusual activity.
      • Implement rate limiting to prevent attackers from making too many requests in a short period.
      • Use database-specific features (e.g., query timeouts) to prevent long-running queries from monopolizing resources.