mitigations.md

Mitigation Strategies Analysis for gabime/spdlog

Mitigation Strategy: Implement Strict Data Sanitization and Filtering using spdlog Formatting

• Description:
  • Step 1: Conduct a code review to identify potential logging of sensitive data using spdlog.
  • Step 2: For necessary sensitive data logging, implement sanitization before passing data to spdlog.
  • Step 3: Utilize spdlog's formatting capabilities within log messages to further mask or redact sensitive information. For example, use format specifiers to truncate strings or replace parts with placeholders directly in the log message format string.
  • Step 4: Configure different spdlog loggers with varying formatters for different log levels or modules. Use more restrictive formatters (with sanitization) for loggers that might handle sensitive data, especially at lower log levels like debug or trace.
  • Step 5: Regularly review and update spdlog formatters and sanitization logic as the application evolves.
• Threats Mitigated:
  • Information Disclosure (High Severity) - Unintentional logging of sensitive data can expose confidential information.
  • Compliance Violations (Medium Severity) - Logging PII or regulated data without safeguards can violate privacy regulations.
• Impact:
  • Information Disclosure: Significantly Reduces - spdlog formatting combined with pre-logging sanitization minimizes sensitive data exposure in logs.
  • Compliance Violations: Significantly Reduces - Reduces the risk of logging regulated data in violation of compliance requirements.
• Currently Implemented: Partially implemented. spdlog formatters are used for basic log structuring, but not extensively for data sanitization within log messages.
• Missing Implementation: Need to expand the use of spdlog formatters to actively sanitize or mask sensitive data within log messages, especially for loggers handling user inputs or sensitive operations.

Mitigation Strategy: Utilize Structured Logging and Contextual Information with spdlog Formatters and Context

• Description:
  • Step 1: Configure spdlog to use structured logging formats (like JSON, if a suitable formatter is available or custom-built) using spdlog::set_formatter.
  • Step 2: Leverage spdlog's contextual logging features (using logger->with(...)) to add structured context (key-value pairs) to log messages.
  • Step 3: Design log messages to use structured context for relevant data instead of embedding everything in the main message string. This makes filtering and analysis easier.
  • Step 4: When using structured logging, carefully consider what data is included in the structured context and ensure sensitive data is either excluded or appropriately sanitized before being added to the context.
• Threats Mitigated:
  • Information Disclosure (Medium Severity) - Structured logging facilitates easier filtering and processing to remove sensitive information during analysis.
  • Inefficient Log Analysis (Low Severity) - Plain text logs are harder to parse; structured logs improve analysis efficiency.
• Impact:
  • Information Disclosure: Moderately Reduces - spdlog's structured logging aids in post-processing and filtering, reducing exposure risk.
  • Inefficient Log Analysis: Significantly Reduces - spdlog's structured logging makes analysis and management more efficient.
• Currently Implemented: Partially implemented. Structured logging (JSON format for some loggers) and contextual logging are used in some modules, leveraging spdlog features, but not consistently across all loggers.
• Missing Implementation: Consistent adoption of structured logging and contextual logging across all spdlog loggers. Explore or develop JSON or other structured formatters for broader use within spdlog.

Mitigation Strategy: Parameterize Log Messages using spdlog Formatting

• Description:
  • Step 1: Identify all instances where user input or external data is included in spdlog log messages.
  • Step 2: Replace string concatenation or direct embedding of user input in log messages with spdlog's parameterized logging functions (e.g., logger->info("User {}", username);).
  • Step 3: Ensure all dynamic data is passed as separate arguments to spdlog logging functions, utilizing spdlog's formatting capabilities.
  • Step 4: Enforce parameterization in code reviews specifically for spdlog logging statements.
• Threats Mitigated:
  • Log Injection (High Severity) - Attackers can inject malicious commands via user input directly logged without parameterization.
• Impact:
  • Log Injection: Significantly Reduces - spdlog parameterization prevents log injection by separating message structure from user data.
• Currently Implemented: Partially implemented. Parameterization with spdlog is used in newer code and critical logging, but legacy code still uses concatenation in some places.
• Missing Implementation: Full codebase-wide implementation of spdlog parameterization, especially in older modules and error handling paths. Refactor legacy logging to use spdlog parameterization.

Mitigation Strategy: Implement Log Level Controls within spdlog Configuration

• Description:
  • Step 1: Define appropriate log levels (trace, debug, info, etc.) for different environments.
  • Step 2: Configure spdlog to use different log levels based on the environment (e.g., using spdlog::set_level(spdlog::level::info)). Production should use higher levels (less verbose).
  • Step 3: Implement mechanisms to dynamically adjust spdlog log levels if needed, potentially through configuration reloading or programmatic changes to spdlog::set_level.
  • Step 4: Utilize spdlog's level filtering capabilities to control the verbosity of different loggers or sinks independently.
• Threats Mitigated:
  • Denial of Service (DoS) via Excessive Logging (Medium Severity) - Excessive logging can consume resources and disrupt service.
  • Performance Degradation (Medium Severity) - Verbose logging impacts performance, especially under load.
• Impact:
  • Denial of Service (DoS) via Excessive Logging: Moderately Reduces - spdlog log level controls limit log volume, reducing DoS risk.
  • Performance Degradation: Moderately Reduces - spdlog log levels and filtering mitigate performance impact.
• Currently Implemented: Partially implemented. spdlog log levels are configured differently for environments, but dynamic adjustment is not fully implemented.
• Missing Implementation: Add dynamic spdlog log level adjustment. Explore fine-grained level control for different spdlog loggers or sinks.

Mitigation Strategy: Utilize spdlog's Log Rotation Features

• Description:
  • Step 1: Configure spdlog's rotating file sinks (spdlog::sinks::rotating_file_sink_mt) to automatically rotate log files.
  • Step 2: Define rotation policies within spdlog sink configuration (e.g., rotate daily, by size, number of files to keep).
  • Step 3: Ensure spdlog rotation policies are appropriate for storage capacity and logging volume.
  • Step 4: Regularly review and adjust spdlog rotation policies as needed.
• Threats Mitigated:
  • Denial of Service (DoS) via Disk Exhaustion (Medium Severity) - Uncontrolled log growth can fill disk space.
  • Compliance Violations (Low Severity) - Some regulations may require log retention management.
• Impact:
  • Denial of Service (DoS) via Disk Exhaustion: Significantly Reduces - spdlog rotation prevents uncontrolled log growth and disk exhaustion.
  • Compliance Violations: Moderately Reduces - spdlog rotation helps manage log lifecycle for retention requirements.
• Currently Implemented: Yes, spdlog's rotating file sink is used with daily rotation and file limits.
• Missing Implementation: No major missing implementation related to spdlog rotation itself, but consider automating archiving of rotated logs for long-term retention if needed, outside of spdlog's direct features.

Mitigation Strategy: Regularly Review and Update spdlog Library

• Description:
  • Step 1: Regularly monitor for updates and security advisories for the spdlog library.
  • Step 2: Establish a process to promptly update spdlog to the latest stable version.
  • Step 3: Test spdlog updates in a staging environment before production deployment.
  • Step 4: Include spdlog updates in regular dependency update cycles and security patching processes.
• Threats Mitigated:
  • Exploitation of Known Vulnerabilities (High Severity) - Outdated spdlog versions may contain exploitable vulnerabilities.
• Impact:
  • Exploitation of Known Vulnerabilities: Significantly Reduces - Keeping spdlog updated patches known vulnerabilities, reducing the attack surface.
• Currently Implemented: Partially implemented. Dependency updates are done periodically, but proactive monitoring for spdlog-specific security advisories could be improved.
• Missing Implementation: Implement proactive monitoring for spdlog security advisories and integrate spdlog updates more tightly into security patching processes.