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Mitigation Strategies Analysis for php-fig/log

Mitigation Strategy: Data Sanitization and Masking

  • Description:

    1. Identify Sensitive Data: Developers must identify all sensitive data types that might be included in log messages (passwords, API keys, PII, etc.).
    2. Implement Sanitization Functions: Create functions to sanitize or mask sensitive data before logging. Methods include masking (e.g., XXXX for parts of sensitive data), hashing (one-way hash for irreversible anonymization), or removal (if data is not essential in logs).
    3. Integrate into Logging Pipeline: Apply sanitization functions before data reaches the php-fig/log logger. Use log processors or wrapper functions to automatically sanitize log messages.
    4. Regular Log Review and Updates: Periodically review logs to identify and refine sanitization needs. Update sanitization rules as data handling evolves.

  • Threats Mitigated:

    • Information Leakage through Logs (High Severity) - Prevents sensitive data from being exposed in log files.

  • Impact:

    • Information Leakage through Logs (High Impact) - Significantly reduces the risk of sensitive data breaches via logs.

  • Currently Implemented:

    • Partially implemented in the user authentication module for password hashing during login attempts.

  • Missing Implementation:

    • Sanitization is missing in modules handling payments, user profiles, API requests, and general error handling where sensitive data might be logged.

Mitigation Strategy: Log Level Management

  • Description:

    1. Define Log Levels: Use php-fig/log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL, etc.) consistently based on message severity and purpose.
    2. Environment-Specific Configuration: Configure different log levels for development/staging (verbose levels like DEBUG, INFO) and production (higher levels like WARNING, ERROR, CRITICAL). Minimize INFO and DEBUG in production.
    3. Centralized Configuration: Manage log levels centrally (config files, environment variables) for consistency across environments.
    4. Regular Review and Adjustment: Periodically review and adjust log levels based on needs, security, and performance.

  • Threats Mitigated:

    • Information Leakage through Logs (Medium Severity) - Reduces log volume in production, minimizing accidental sensitive data logging.
    • Denial of Service (DoS) through Log Flooding (Medium Severity) - Limits verbose logging in production, reducing risk of log-induced DoS.
    • Exposure of Application Logic and Vulnerabilities through Logs (Low Severity) - Less verbose production logs reveal less application detail.

  • Impact:

    • Information Leakage through Logs (Medium Impact) - Lowers chance of sensitive data in production logs.
    • Denial of Service (DoS) through Log Flooding (Medium Impact) - Mitigates log flooding risk in production.
    • Exposure of Application Logic and Vulnerabilities through Logs (Low Impact) - Slightly reduces application detail in production logs.

  • Currently Implemented:

    • Partially implemented with environment variable-based switching between "development" (DEBUG) and "production" (WARNING) levels.

  • Missing Implementation:

    • Lacks granular control over log levels for specific application parts. Global setting only.
    • No automated checks for correct log level configuration during deployments.

Mitigation Strategy: Input Validation and Escaping for Log Messages

  • Description:

    1. Identify User-Provided Data: Locate all instances where user input or external data is included in log messages.
    2. Input Validation: Validate user input before logging to ensure expected format and prevent malicious payloads.
    3. Output Encoding/Escaping: Escape user input before logging to prevent interpretation as commands by log analysis tools. Use context-specific escaping (JSON, shell, etc.) or parameterized/structured logging.
    4. Code Reviews and Security Testing: Review code for consistent input validation and escaping in logging. Security test for log injection vulnerabilities.

  • Threats Mitigated:

    • Log Injection Vulnerabilities (High Severity) - Prevents injection of malicious data into logs, protecting log analysis tools.

  • Impact:

    • Log Injection Vulnerabilities (High Impact) - Significantly reduces log injection risks, securing logs and analysis systems.

  • Currently Implemented:

    • Not systematically implemented. Some input validation exists, but not specifically for logging.

  • Missing Implementation:

    • Inconsistent input validation and escaping for logged data across the application.
    • No dedicated escaping functions for log messages.
    • Inconsistent use of structured logging, relying on string concatenation which increases injection risk.

Mitigation Strategy: Rate Limiting and Throttling of Logs

  • Description:

    1. Identify High-Volume Logging: Find areas prone to high log volume, especially during errors or attacks (failed logins, API errors, exceptions).
    2. Implement Rate Limiting: Control log generation rate in high-volume scenarios. Implement at application level (limit logs for repeated events), logging framework level (if supported by php-fig/log handlers), or log aggregation system level.
    3. Configure Thresholds and Policies: Define rate limits based on expected volume and resource capacity. Tune to prevent flooding without hindering necessary logging.
    4. Monitoring and Alerting: Monitor log rates and rate limiting effectiveness. Alert on excessive log volumes or frequent rate limiting triggers, indicating issues or attacks.

  • Threats Mitigated:

    • Denial of Service (DoS) through Log Flooding (High Severity) - Prevents log flooding DoS attacks by limiting excessive log generation.

  • Impact:

    • Denial of Service (DoS) through Log Flooding (High Impact) - Significantly reduces DoS risk from log flooding, ensuring application stability.

  • Currently Implemented:

    • Not implemented. No rate limiting for log generation currently exists.

  • Missing Implementation:

    • Rate limiting missing in error handlers, exception handlers, and high-volume areas like authentication and API processing.
    • No dynamic adjustment of log levels or temporary logging disabling during high load.

Mitigation Strategy: Log Integrity Checks

  • Description:

    1. Implement Checksum/Signature Generation: Generate checksums (MD5, SHA-256) or digital signatures for log files or entries.
    2. Regular Integrity Verification: Automate regular verification of log integrity. Recalculate checksums and compare, or verify digital signatures.
    3. Alerting on Integrity Failures: Alert security admins immediately if integrity checks fail, indicating potential tampering.
    4. Secure Storage of Integrity Data: Store checksums/signatures securely and separately from logs to prevent attackers from tampering with both.

  • Threats Mitigated:

    • Log Tampering and Deletion (Medium Severity) - Detects unauthorized log modification, aiding in identifying security breaches.

  • Impact:

    • Log Tampering and Deletion (Medium Impact) - Provides detection of log tampering, improving log reliability for incident response.

  • Currently Implemented:

    • Not implemented. No log integrity checks are in place.

  • Missing Implementation:

    • No checksum/signature generation for logs.
    • No automated log integrity verification processes.
    • No alerting for log integrity failures.