attack-surface.md

Attack Surface Analysis for touchlab/kermit

Attack Surface: Information Disclosure through Verbose Logging

• Description: Sensitive application or user data is unintentionally exposed in logs due to overly verbose logging configurations (e.g., Debug, Verbose levels left enabled in production).
  • Kermit Contribution: Kermit's simple API and configuration make it easy for developers to enable detailed logging. If developers fail to restrict logging levels in production, Kermit will faithfully log all messages at the configured level, including potentially sensitive information.
  • Example: A developer uses Kermit.d { "User logged in", userDetails } at Debug level, which includes the user's full profile with email and address. If production logging level is mistakenly set to Debug and logs are accessible, this PII is exposed.
  • Impact: Data breach, privacy violation, potential identity theft, regulatory non-compliance, reputational damage.
  • Risk Severity: High
  • Mitigation Strategies:
    • Enforce strict logging level control in production: Ensure production environments are configured with minimal logging levels (e.g., Info, Warn, Error) and prevent accidental enabling of verbose levels.
    • Regularly review logging configurations: Periodically audit logging configurations to verify they are appropriate for the production environment and minimize verbosity.
    • Implement automated checks for sensitive data in logs (post-logging): Consider using log analysis tools to automatically scan logs for patterns resembling sensitive data and trigger alerts or redaction processes.

Attack Surface: Resource Exhaustion through Uncontrolled Logging

• Description: Attackers can trigger application behavior that generates an excessive volume of log messages via Kermit, leading to resource exhaustion and Denial of Service (DoS).
  • Kermit Contribution: Kermit efficiently logs messages as instructed. If logging is not strategically implemented and controlled within the application logic, especially in error handling paths or loops, attackers can exploit this to flood the logging system. Kermit itself doesn't inherently limit the rate or volume of logs it processes.
  • Example: An attacker repeatedly sends malformed requests to an API endpoint. The error handling logic, using Kermit, logs detailed error information for each invalid request at Error level. A large volume of these requests can quickly overwhelm disk space, I/O, and potentially the logging infrastructure, leading to application slowdown or unavailability for legitimate users.
  • Impact: Denial of Service (DoS), application unavailability, performance degradation, operational disruption, increased infrastructure costs due to log storage and processing.
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement rate limiting for logging: Introduce mechanisms to limit the rate at which logs are generated, especially for specific log categories or sources prone to abuse (e.g., error logs for invalid requests).
    • Strategic logging in error paths: Avoid excessively verbose logging in error handling paths. Log essential error information but prevent logging excessive details for every single error occurrence, especially in high-volume scenarios.
    • Monitor log volume and system resources: Actively monitor log volume, disk space usage, and system resource consumption related to logging to detect and respond to unusual spikes or potential DoS attempts.
    • Implement robust log rotation and retention policies: Ensure efficient log rotation and archiving to prevent disk space exhaustion. Consider using compressed log formats.