mitigations.md

Mitigation Strategies Analysis for go-gorm/gorm

Mitigation Strategy: Use Parameterized Queries Consistently

• Description:
  1. Identify GORM Query Points: Review your codebase and locate all places where GORM interacts with the database using query builders and raw SQL execution (db.Where(), db.First(), db.Find(), db.Exec(), db.Raw()).
  2. Utilize GORM Query Builders: For standard queries, consistently use GORM's query builder methods (Where, First, Find, Create, Updates, Delete). These methods inherently use parameterized queries, protecting against SQL injection.
  3. Parameterize Raw SQL in GORM: If db.Exec() or db.Raw() are necessary for complex queries:
     • Employ placeholder syntax (? for positional, @var for named parameters) within your SQL query strings.
     • Pass user-supplied inputs as separate arguments to Exec() or Raw(). GORM will handle parameterization of these inputs before executing the query.
  4. Code Reviews for Parameterization: Conduct code reviews specifically to verify that developers are consistently using parameterized queries throughout the application's GORM interactions.
• Threats Mitigated:
  • SQL Injection (Severity: High) - Prevents attackers from injecting malicious SQL code through user inputs processed by GORM, potentially leading to unauthorized data access, modification, or deletion.
• Impact:
  • SQL Injection: High Risk Reduction - Effectively eliminates the primary SQL injection vector arising from GORM usage when consistently applied.
• Currently Implemented: Partial - Parameterized queries are generally used in new feature development leveraging GORM's query builders.
• Missing Implementation: Legacy modules or specific instances using db.Exec or db.Raw might lack proper parameterization and require review and refactoring to ensure consistent parameterized query usage.

Mitigation Strategy: Use Select and Omit for Mass Assignment Control in GORM

• Description:
  1. Review GORM Update Operations: Identify all code sections where GORM's Updates or UpdateColumns methods are used to modify database records based on user-provided data.
  2. Implement Select for Field Whitelisting in GORM: When using Updates or UpdateColumns, consistently use the .Select() method to explicitly define the fields that are permitted to be updated by user input. List only the intended updateable fields.
  3. Implement Omit for Field Blacklisting in GORM (Alternative): As an alternative to Select, use the .Omit() method to explicitly exclude sensitive or non-updateable fields from being modified during GORM update operations. This is useful when most fields are updateable except a few.
  4. Avoid Direct Struct Binding for GORM Updates: Discourage directly binding entire request bodies to GORM model structs followed by Updates without using Select or Omit. This practice can inadvertently enable mass assignment vulnerabilities.
• Threats Mitigated:
  • Mass Assignment Vulnerability (Severity: High) - Prevents attackers from manipulating request parameters to modify unintended database fields through GORM's update mechanisms, potentially leading to privilege escalation or data corruption.
• Impact:
  • Mass Assignment Vulnerability: High Risk Reduction - Effectively prevents mass assignment vulnerabilities within GORM update operations by enforcing explicit control over modifiable fields.
• Currently Implemented: Partial - Select is used in some GORM update operations, particularly for critical entities. However, consistent application of Select or Omit across all update operations is needed.
• Missing Implementation: A systematic code review of all Updates and UpdateColumns calls is necessary to ensure Select or Omit is consistently applied. Development guidelines should be updated to mandate this practice for all future GORM update operations.

Mitigation Strategy: Carefully Review Eager Loading Logic in GORM

• Description:
  1. Identify GORM Eager Loading Points: Locate all instances in your code where GORM's Preload or Joins are used to eagerly load related data.
  2. Analyze GORM Loaded Relationships: For each instance of eager loading, carefully examine which relationships are being loaded and the sensitivity of the data they contain.
  3. Minimize GORM Eager Loading: Only eagerly load relationships that are strictly necessary for the current operation. Avoid over-eager loading of data that is not immediately required to minimize potential information exposure.
  4. Implement Authorization Checks for GORM Relationships: Even with eager loading, ensure that authorization checks are implemented to verify if the current user is authorized to access the related data being loaded by GORM. Do not rely on eager loading itself as a form of authorization.
  5. Consider Lazy Loading in GORM: Where appropriate, consider using lazy loading instead of eager loading for GORM relationships. This can reduce the amount of data retrieved and potentially exposed, improving both security and performance.
• Threats Mitigated:
  • Information Disclosure (Severity: Medium) - Prevents accidental exposure of sensitive related data through GORM's eager loading features when users should not have access to it.
  • Performance Issues (Severity: Medium) - Reduces unnecessary database queries and data transfer associated with GORM's eager loading, improving application performance.
• Impact:
  • Information Disclosure: Medium Risk Reduction - Reduces the risk of accidental information disclosure through GORM by limiting the scope of data retrieval via eager loading.
  • Performance Issues: Medium Risk Reduction - Improves application performance by optimizing data loading strategies within GORM.
• Currently Implemented: Partial - Eager loading is used in some areas for performance optimization, but thorough review of loaded relationships and implementation of authorization checks on related data loaded by GORM are not consistently performed.
• Missing Implementation: A comprehensive review of all Preload and Joins usage in GORM queries is needed to optimize eager loading and implement authorization checks for related data. Establish guidelines for appropriate and secure use of GORM's eager loading features.

Mitigation Strategy: Configure GORM Logging for Production Security

• Description:
  1. Separate GORM Logging Configurations: Implement distinct logging configurations for development and production environments specifically for GORM.
  2. Reduce GORM Logging Verbosity in Production: In production, configure GORM logging to a minimal level, logging only errors or critical events. Significantly reduce or disable the logging of SQL queries generated by GORM.
  3. Disable GORM Query Logging in Production (Ideal): If query logging is not essential for production debugging, disable it entirely within GORM's configuration to prevent accidental logging of sensitive data within the queries.
  4. Sanitize GORM Logs (If Query Logging is Necessary): If GORM query logging is required in production for specific debugging needs, implement log sanitization to remove or mask sensitive data (e.g., user inputs, passwords, API keys) from logged SQL queries before they are written to log files.
• Threats Mitigated:
  • Information Disclosure (Severity: Medium) - Prevents accidental logging of sensitive data within SQL queries generated by GORM, which could be exposed through production log files.
  • Compliance Violations (Severity: Medium) - Helps comply with data privacy regulations by avoiding logging of sensitive personal data in GORM logs.
• Impact:
  • Information Disclosure: Medium Risk Reduction - Reduces the risk of sensitive data exposure through GORM logs.
  • Compliance Violations: Medium Risk Reduction - Improves compliance posture regarding data privacy by controlling GORM logging practices.
• Currently Implemented: Partial - Logging levels are configured differently for development and production environments. However, GORM query logging might still be enabled in production for some services, and log sanitization for GORM logs is not implemented.
• Missing Implementation: Disable GORM query logging in production environments where feasible. Implement log sanitization specifically for GORM logs in services where query logging is deemed necessary. Review and adjust GORM logging configurations across all services to minimize verbosity in production.

Mitigation Strategy: Keep GORM Updated for Security Patches

• Description:
  1. Dependency Management for GORM: Use a dependency management tool (e.g., Go modules) to manage project dependencies, including GORM.
  2. Monitor GORM Security Releases: Regularly monitor GORM's GitHub repository and release notes for new versions, bug fixes, and security advisories specifically related to GORM.
  3. Update GORM Regularly for Security: Update GORM to the latest stable version as part of a regular maintenance cycle, prioritizing security updates.
  4. Test Application After GORM Updates: After updating GORM, thoroughly test the application to ensure compatibility and that no regressions have been introduced due to the GORM update.
• Threats Mitigated:
  • Exploitation of Known GORM Vulnerabilities (Severity: High to Medium, depending on vulnerability) - Prevents attackers from exploiting known security vulnerabilities present in older versions of GORM.
• Impact:
  • Exploitation of Known GORM Vulnerabilities: High Risk Reduction - Directly addresses and mitigates the risk of exploiting known vulnerabilities within GORM itself.
• Currently Implemented: Partial - GORM updates are performed periodically, but not on a strict schedule driven by security releases. Monitoring of GORM releases for security advisories is not fully automated.
• Missing Implementation: Implement automated monitoring for GORM security releases and advisories. Establish a regular schedule for reviewing and updating GORM, prioritizing security updates. Integrate GORM updates into the CI/CD pipeline with automated testing to ensure smooth and secure updates.