mitigations.md

Mitigation Strategies Analysis for sirupsen/logrus

Mitigation Strategy: Sanitize and Filter Sensitive Data Before Logging with Logrus

• Description:

  1. Identify Sensitive Data in Application Context: Pinpoint all sensitive data points within your application code that might be passed to logrus for logging.
  2. Implement Sanitization Functions (External to Logrus): Create dedicated functions outside of your logrus configuration to sanitize identified sensitive data. These functions should redact, mask, filter, or use allow-lists to process data.
  3. Apply Sanitization Before Logrus Calls: Before calling any logrus logging function (logrus.Info, logrus.Error, etc.), apply the sanitization functions to the sensitive data you intend to log. Ensure this happens before the data enters logrus.
  4. Use Logrus Structured Logging for Sanitized Data: Pass the sanitized data to logrus using structured logging features like logrus.WithField or logrus.WithFields. This ensures you are logging the safe, processed version.
  5. Code Reviews Focused on Pre-Logrus Sanitization: During code reviews, specifically check that sanitization is consistently applied before any sensitive data is handed to logrus for logging.

• List of Threats Mitigated:

  • Information Disclosure (High Severity): Logging sensitive data directly through logrus exposes it in logs, potentially leading to breaches.
  • Compliance Violations (High Severity): Logging PII or regulated data via logrus without sanitization can violate privacy regulations.

• Impact:

  • Information Disclosure (High Reduction): Prevents sensitive data from being logged by logrus in the first place, significantly reducing exposure risk.
  • Compliance Violations (High Reduction): Helps meet compliance requirements by ensuring logrus only logs sanitized, non-sensitive representations of data.

• Currently Implemented:

  • Partially implemented. Basic password redaction occurs before logging with logrus in user authentication modules.

• Missing Implementation:

  • Lack of comprehensive sanitization before logrus calls for API keys, session tokens, and PII across all application modules.
  • No automated checks to ensure sanitization happens before data reaches logrus.

Mitigation Strategy: Control Log Levels Configured in Logrus for Production

• Description:

  1. Define Log Level Policy for Logrus: Establish a clear policy for which logrus log levels are appropriate for different environments (development, staging, production).
  2. Configure Logrus Levels Dynamically (External Configuration): Implement a mechanism to set logrus log levels via external configuration (environment variables, config files) outside of the application code itself. This allows changing logrus verbosity without code changes.
  3. Set Production Logrus Level to Appropriate Verbosity: Configure logrus in production to use Info, Warning, Error, or Fatal levels by default. Avoid Debug or Trace in production logrus configurations unless temporarily needed for specific debugging and then promptly reverted.
  4. Monitor and Adjust Logrus Levels (Configuration Changes): Monitor production logs. If logrus is logging too much debug information, adjust the external configuration to reduce the logrus log level. If more detail is needed, temporarily increase the logrus level via configuration changes.

• List of Threats Mitigated:

  • Information Disclosure (Medium Severity): Overly verbose logrus logging (Debug/Trace levels) in production can expose internal details through logrus outputs.
  • Performance Degradation (Medium Severity): Excessive logrus logging, especially at verbose levels, consumes resources, impacting performance.

• Impact:

  • Information Disclosure (Medium Reduction): Limits the amount of potentially sensitive information logrus outputs in production by controlling verbosity.
  • Performance Degradation (Medium Reduction): Reduces logrus logging overhead, improving application performance.

• Currently Implemented:

  • Partially implemented. logrus log levels are configurable via environment variables. Production default for logrus is set to Info.

• Missing Implementation:

  • No formal policy document specifically for logrus log levels in different environments.
  • No monitoring or alerts for unexpectedly verbose logrus logging in production.

Mitigation Strategy: Utilize Logrus Structured Logging (Fields) to Prevent Injection

• Description:

  1. Adopt Logrus Structured Logging (Fields) Consistently: Mandate and enforce the use of logrus.WithField and logrus.WithFields throughout the codebase for logging dynamic data.
  2. Avoid String Concatenation in Logrus Messages: Prohibit string concatenation or formatting directly within logrus logging calls when including user-supplied or dynamic data.
  3. Train Developers on Logrus Fields for Security: Train developers specifically on how logrus.Fields prevents log injection and why it's crucial for secure logging with logrus.
  4. Code Review Enforcement of Logrus Fields: During code reviews, strictly enforce the use of logrus.Fields and reject code that uses string concatenation within logrus logging for dynamic data.

• List of Threats Mitigated:

  • Log Injection Vulnerabilities (Medium Severity): String concatenation in logrus messages can be exploited for log injection attacks.

• Impact:

  • Log Injection Vulnerabilities (High Reduction): logrus.Fields effectively eliminates the primary log injection vector by separating log messages from dynamic data within logrus itself.

• Currently Implemented:

  • Partially implemented. Structured logging with logrus.Fields is used in some modules, but older code still uses string concatenation in logrus calls.

• Missing Implementation:

  • Inconsistent usage of logrus.Fields across all modules.
  • No coding guidelines specifically prohibiting string concatenation within logrus calls for dynamic data.
  • No automated checks to detect string concatenation within logrus logging.

Mitigation Strategy: Sanitize User Inputs Before Logging with Logrus Fields (Defense in Depth)

• Description:

  1. Identify Input Points Logged via Logrus Fields: Locate all places where user inputs or external data are logged using logrus.Fields.
  2. Implement Input Sanitization (Pre-Logrus Fields): Develop sanitization functions to process user inputs before they are added as fields to logrus.WithField or logrus.WithFields. Focus on escaping or removing characters that could be misinterpreted by systems processing logrus outputs.
  3. Apply Sanitization Before Logrus Field Assignment: Apply these sanitization functions to user input data immediately before assigning it as a value in logrus.WithField or logrus.WithFields.
  4. Context-Aware Sanitization for Logrus Fields: Consider the context where logrus outputs will be processed when designing sanitization rules for data logged via logrus.Fields.

• List of Threats Mitigated:

  • Log Injection Vulnerabilities (Low to Medium Severity - Residual Risk): While logrus.Fields helps, certain characters in user inputs within logrus.Fields might still cause issues in downstream log processing.
  • Cross-Site Scripting (XSS) in Log Viewers (Low Severity): If logrus outputs are displayed in web viewers, unsanitized inputs in logrus.Fields could lead to XSS.

• Impact:

  • Log Injection Vulnerabilities (Medium Reduction): Further reduces residual log injection risks even when using logrus.Fields.
  • Cross-Site Scripting (XSS) in Log Viewers (Low Reduction): Minimizes XSS risks in log viewers displaying logrus outputs.

• Currently Implemented:

  • Not implemented. User inputs are generally logged as fields in logrus without specific sanitization for log processing contexts before being passed to logrus.Fields.

• Missing Implementation:

  • No input sanitization functions specifically designed for data logged via logrus.Fields.
  • No consideration of downstream log processing when handling data for logrus.Fields.

Mitigation Strategy: Implement Log Rate Limiting or Sampling using Logrus Hooks

• Description:

  1. Identify High-Volume Log Sources Handled by Logrus: Analyze application components that generate high log volumes through logrus.
  2. Develop Logrus Hook for Rate Limiting/Sampling: Create a custom logrus hook that implements rate limiting or sampling logic. This hook will intercept log entries within logrus itself.
     • Rate Limiting Hook: The hook tracks log frequency and discards entries exceeding a threshold within a time window.
     • Sampling Hook: The hook randomly discards a percentage of log entries based on a sampling rate.
  3. Register the Logrus Hook: Register the custom rate limiting or sampling hook with logrus using logrus.AddHook().
  4. Configure Hook Thresholds: Configure the rate limiting thresholds or sampling rates within the logrus hook's settings.
  5. Monitor Log Volume After Hook Implementation: Monitor log volume after deploying the logrus hook to ensure it effectively reduces excessive logging without losing critical information.

• List of Threats Mitigated:

  • Denial of Service (DoS) through Excessive Logging (Medium to High Severity): Attackers or application errors causing log floods through logrus, consuming resources.

• Impact:

  • Denial of Service (DoS) through Excessive Logging (Medium Reduction): Reduces DoS risk by limiting log volume within logrus, preventing resource exhaustion.

• Currently Implemented:

  • Not implemented. No logrus hooks for rate limiting or sampling are in place.

• Missing Implementation:

  • No custom logrus hook developed for rate limiting or sampling.
  • No analysis to identify components suitable for logrus hook-based rate limiting.

Mitigation Strategy: Optimize Logrus Formatter for Performance

• Description:

  1. Benchmark Logrus Formatters: Benchmark different logrus formatters (e.g., TextFormatter, JSONFormatter) in your application's logging context to assess performance.
  2. Choose Efficient Logrus Formatter: Select the most performant logrus formatter suitable for your logging needs. JSONFormatter is often more efficient for machine processing and centralized logging, while TextFormatter might be simpler for human readability in development.
  3. Configure Logrus to Use Optimized Formatter: Configure logrus to use the chosen, optimized formatter using logrus.SetFormatter().
  4. Re-benchmark After Formatter Change: After changing the logrus formatter, re-benchmark logging performance to confirm performance improvements.

• List of Threats Mitigated:

  • Performance Degradation (Medium Severity): Inefficient logrus formatters can contribute to performance slowdowns.
  • Denial of Service (DoS) (Low Severity - Indirect): In extreme cases, very inefficient logrus formatting could contribute to resource exhaustion.

• Impact:

  • Performance Degradation (Medium Reduction): Improves application performance by reducing logrus formatting overhead.
  • Denial of Service (DoS) (Low Reduction): Reduces indirect DoS risk from inefficient logrus logging.

• Currently Implemented:

  • Partially implemented. TextFormatter is currently used as the logrus formatter.

• Missing Implementation:

  • No benchmarking of different logrus formatters.
  • No evaluation of switching to JSONFormatter or other more performant formatters in logrus.

Mitigation Strategy: Thoroughly Review and Test Logrus Configuration

• Description:

  1. Configuration Review of Logrus Setup: Carefully review all aspects of logrus configuration in your application code, including:
     • Formatter selection (logrus.SetFormatter()).
     • Output destination (logrus.SetOutput()).
     • Hooks registration (logrus.AddHook()).
     • Log level setting (logrus.SetLevel()).
  2. Test Logrus Configuration in Non-Production: Test the configured logrus setup in staging or testing environments to verify it behaves as intended and meets security requirements. Check log levels, formatting, output destinations, and hook behavior.
  3. Automated Logrus Configuration Checks (If Possible): If feasible, implement automated checks to validate logrus configuration against security best practices.
  4. Version Control Logrus Configuration Code: Ensure the code that configures logrus is under version control to track changes and enable rollbacks.

• List of Threats Mitigated:

  • Misconfiguration Vulnerabilities (Variable Severity): Incorrect logrus configuration can lead to various security issues (e.g., overly verbose logging, ineffective hooks).

• Impact:

  • Misconfiguration Vulnerabilities (Variable Reduction): Reduces risks arising from misconfigured logrus settings by ensuring proper setup and validation.

• Currently Implemented:

  • Partially implemented. Manual code reviews include basic checks of logrus setup.

• Missing Implementation:

  • No dedicated testing process specifically for logrus configuration.
  • No automated checks to validate logrus configuration.