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attack-surface.md

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Attack Surface Analysis for seldaek/monolog

Attack Surface: Log Injection/Forging (Due to Unsanitized Input)

  • Description: Attackers inject malicious content or control characters into log messages, or forge entirely fake log entries, by exploiting Monolog's handling of unsanitized input.
  • Monolog Contribution: Monolog processes and formats log messages. If the application passes unsanitized user input directly to Monolog's formatting functions (e.g., Logger::info($userInput) without prior sanitization), Monolog will include that input in the output, including any malicious content. This is the direct involvement.
  • Example: An attacker uses a username like eviluser\n[ERROR] Fake error message and the application logs this directly using $logger->info("User logged in: " . $userInput);. Monolog formats and outputs the injected newline and fake error.
  • Impact:
    • Misleading investigations.
    • Triggering false alerts.
    • Covering up malicious activity.
    • Potential XSS vulnerabilities in log viewers (if the viewer doesn't properly escape output).
    • Log file corruption.
  • Risk Severity: High (Potentially Critical if logs are used for security monitoring or automated actions).
  • Mitigation Strategies:
    • Strict Input Sanitization: Always sanitize and encode all user-supplied data before passing it to any Monolog function. Use a dedicated sanitization library or function. This is the primary mitigation.
    • Use Monolog Formatters: Leverage Monolog's built-in formatters (e.g., LineFormatter, JsonFormatter) to automatically escape special characters as part of the formatting process. This provides a second layer of defense.
    • Contextual Escaping (Log Viewers): If displaying logs in a web interface, ensure the viewer uses appropriate HTML escaping (this is not Monolog's direct responsibility, but is related).

Attack Surface: Path Traversal (File Handlers - Direct Misconfiguration)

  • Description: Attackers manipulate the log file path to write logs to arbitrary locations on the file system, due to a direct misconfiguration of Monolog's file handler.
  • Monolog Contribution: Monolog's file-based handlers (e.g., StreamHandler, RotatingFileHandler) write logs to the file path specified in their configuration. If this configuration is vulnerable (e.g., allows user input to influence the path), Monolog will write to the attacker-controlled location. This is the direct involvement.
  • Example: The Monolog configuration is set up to use a file path that is directly constructed from user input, such as new StreamHandler('/var/log/myapp/' . $_GET['log_file'] . '.log');. An attacker can then control the log_file parameter.
  • Impact:
    • Overwriting critical system files.
    • Gaining unauthorized access to sensitive data.
    • Denial of service.
  • Risk Severity: Critical.
  • Mitigation Strategies:
    • Never Use User Input for Paths: The Monolog configuration must not use user input, environment variables that can be manipulated by the user, or any other externally controllable data to determine the log file path.
    • Hardcoded Paths: Use hardcoded, absolute paths in the Monolog configuration, or paths relative to a strictly controlled base directory that is not user-configurable.
    • Least Privilege: Run the application with the minimum necessary file system permissions. The application should only have write access to the pre-defined log directory specified in the Monolog configuration.
    • Configuration Validation (Defense in Depth): Implement validation checks within the application to ensure that the configured log path (even if hardcoded) is within expected boundaries. This is a defense-in-depth measure, as the primary mitigation is to avoid dynamic paths entirely.

Attack Surface: Denial of Service (DoS) via Log Flooding (Handler-Specific Resource Exhaustion)

  • Description: An attacker causes excessive log generation, leading to resource exhaustion specifically within a Monolog handler.
  • Monolog Contribution: While the trigger for excessive logging is usually application logic, Monolog's handlers are responsible for the output of the logs. If a handler is overwhelmed (e.g., a network handler cannot keep up with the volume), this is a direct Monolog-related issue.
  • Example: An attacker triggers rapid, repeated errors that are logged via a SocketHandler. The network connection or the receiving server becomes saturated, preventing legitimate logs from being processed. This is distinct from simply filling up disk space (which is often an application-level issue).
  • Impact:
    • Log server unavailability.
    • Loss of log data (specifically, logs that cannot be processed by the overwhelmed handler).
    • Potential application instability if the handler's failure impacts the application.
  • Risk Severity: High
  • Mitigation Strategies:
    • Rate Limiting (Application Level): The primary mitigation is to implement rate limiting within the application logic to prevent excessive log generation in the first place. This is the most effective approach.
    • Handler-Specific Buffering/Queuing (with Caution): Some Monolog handlers might offer buffering or queuing mechanisms. Use these with caution, as they can introduce complexity and potential data loss if the buffer/queue is overwhelmed. They are not a substitute for application-level rate limiting.
    • Network Throttling/Firewalling (Network Handlers): For network-based handlers, implement network-level throttling or firewall rules to limit incoming log traffic to the logging server. This protects the server, not the application itself.
    • Handler Selection: Choose handlers that are appropriate for the expected log volume and network conditions. For example, if high-volume logging is anticipated, a more robust handler (or a dedicated logging infrastructure) might be necessary.