mitigations.md

Mitigation Strategies Analysis for sirupsen/logrus

Mitigation Strategy: Data Scrubbing/Masking Hooks

Mitigation Strategy: Implement Data Scrubbing/Masking Hooks

• Description:
  1. Identify Sensitive Data: List all types of sensitive data your application might log.
  2. Create a Custom Logrus Hook: Develop a Go struct that implements the logrus.Hook interface.
  3. Implement Scrubbing Logic in Hook: Within the Fire method of your hook, iterate through logrus.Fields, identify sensitive fields by name or value patterns, and redact or remove them.
  4. Register the Hook with Logrus: Add your custom hook to logrus using logrus.AddHook(&YourCustomHook{}).
  5. Test Thoroughly: Verify the hook correctly scrubs sensitive data in development/staging.
• Threats Mitigated:
  • Sensitive Data Exposure in Logs (High Severity)
• Impact:
  • Sensitive Data Exposure in Logs (High Reduction)
• Currently Implemented: Yes, implemented in production logging pipeline with a custom hook redacting specific fields and patterns.
• Missing Implementation: Needs full implementation in development and staging environments. Regular review and update of sensitive field lists and patterns are required across all environments.

Mitigation Strategy: Structured Logging with Field-Level Control

Mitigation Strategy: Employ Structured Logging with Field-Level Control

• Description:
  1. Use logrus.WithFields() Consistently: Train developers to use logrus.WithFields(logrus.Fields{...}) for logging events with dynamic data.
  2. Log Only Necessary Fields: Select and log only essential fields from complex objects, avoiding logging entire objects directly.
  3. Sanitize Field Values (logrus context): Sanitize field values before adding them to logrus.WithFields() if needed for consistency or basic cleaning within the logging context.
  4. Avoid String Formatting for Dynamic Data in Log Messages: Discourage fmt.Sprintf or similar for log messages with dynamic data to prevent log injection risks within logrus usage.
• Threats Mitigated:
  • Sensitive Data Exposure in Logs (Medium Severity)
  • Log Injection Vulnerabilities (Medium Severity)
• Impact:
  • Sensitive Data Exposure in Logs (Medium Reduction)
  • Log Injection Vulnerabilities (Medium Reduction)
• Currently Implemented: Partially implemented. Developers are generally aware of logrus.WithFields(), but consistent enforcement is lacking.
• Missing Implementation: Enforce logrus.WithFields() usage via code review guidelines and linters. Developer training on secure logrus practices is needed.

Mitigation Strategy: Control Log Levels in Production

Mitigation Strategy: Control Log Levels in Production

• Description:
  1. Set Production Log Level: Configure logrus log level in production to INFO, WARN, ERROR, or FATAL. Avoid DEBUG or TRACE in production unless temporarily needed for specific debugging.
  2. Externalize Log Level Configuration (logrus context): Use environment variables or configuration files to set the logrus log level, allowing adjustments without code changes.
  3. Monitor Production Log Volume (logrus context): Monitor log volume and adjust logrus log levels or logging logic if volume is unexpectedly high.
  4. Document Log Level Policy (logrus context): Create and document a policy for logrus log levels in different environments.
• Threats Mitigated:
  • Sensitive Data Exposure in Logs (Medium Severity)
  • Excessive Logging and Resource Exhaustion (Medium Severity)
• Impact:
  • Sensitive Data Exposure in Logs (Medium Reduction)
  • Excessive Logging and Resource Exhaustion (Medium Reduction)
• Currently Implemented: Yes, implemented in production. Log level is set to INFO via environment variable for logrus in production.
• Missing Implementation: Ensure consistent logrus log level configuration across all services. Educate developers on the implications of DEBUG/TRACE levels in production within the logrus context.

Mitigation Strategy: Parameterize Log Messages with Structured Logging (logrus specific)

Mitigation Strategy: Parameterize Log Messages with Structured Logging (logrus specific)

• Description:
  1. Always Use logrus.WithFields() (logrus context): Reinforce using logrus.WithFields() for all log messages with dynamic data.
  2. Separate Message Template from Data (logrus context): Ensure the core log message string is static, and dynamic data is passed as fields to logrus.WithFields().
  3. Prohibit String Concatenation in Log Messages (logrus context): Explicitly prohibit string concatenation or formatting functions directly within logrus log message strings when including dynamic data.
• Threats Mitigated:
  • Log Injection Vulnerabilities (High Severity)
• Impact:
  • Log Injection Vulnerabilities (High Reduction)
• Currently Implemented: Partially implemented. Developers are generally aware of logrus.WithFields(), but consistent enforcement within logrus usage is lacking.
• Missing Implementation: Stricter code reviews, linters to detect insecure logrus logging patterns (string concatenation in logrus messages), and developer training focused on log injection prevention within logrus usage.

Mitigation Strategy: Configure Appropriate Log Levels (Resource Exhaustion - logrus specific)

Mitigation Strategy: Configure Appropriate Log Levels (Resource Exhaustion - logrus specific)

• Description:
  1. Environment-Specific Log Levels (logrus context): Define different logrus log levels for development, staging, and production. Use more verbose levels in development and less verbose in production.
  2. Application Component Log Levels (logrus context): If possible, configure logrus log levels at a granular level, per application component, to fine-tune verbosity.
  3. Regular Review and Adjustment (logrus context): Periodically review logrus log levels and adjust based on monitoring, performance, and debugging needs related to logrus logging volume.
• Threats Mitigated:
  • Excessive Logging and Resource Exhaustion (Medium Severity) - specifically related to logrus output volume
• Impact:
  • Excessive Logging and Resource Exhaustion (Medium Reduction) - specifically related to logrus output volume
• Currently Implemented: Partially implemented. Environment-specific logrus log levels are used for production and staging, but development environments are less consistent.
• Missing Implementation: Standardize logrus log level configurations across all environments. Explore granular component-level logrus log level settings. Monitor log volume and resource usage related to logrus to proactively address excessive logging.

Mitigation Strategy: Externalize Log Configuration (logrus specific)

Mitigation Strategy: Externalize Log Configuration (logrus specific)

• Description:
  1. Use Environment Variables or Configuration Files (logrus context): Configure logrus settings (log level, formatter, output destination, hooks) using environment variables, configuration files, or a configuration management system.
  2. Avoid Hardcoding Configuration (logrus context): Remove hardcoded logrus configuration from the application code.
  3. Centralized Configuration Management (Optional - logrus context): For larger deployments, consider centralized configuration management to manage logrus configuration across services.
• Threats Mitigated:
  • Configuration Management Issues (Low Severity) - specifically related to logrus configuration
  • Inconsistent Logging (Low Severity) - specifically related to logrus configuration across environments
• Impact:
  • Configuration Management Issues (Low Reduction) - specifically related to logrus configuration
  • Inconsistent Logging (Low Reduction) - specifically related to logrus configuration
• Currently Implemented: Yes, implemented for log level in production and staging using environment variables for logrus.
• Missing Implementation: More comprehensive externalization is needed for logrus. Currently, only log level is fully externalized for logrus. Externalize formatter, output destination, and hook configurations for logrus for greater flexibility and consistency.