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threat-modeling.md

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Threat Model Analysis for php-fig/log

Threat: Logging Sensitive Data

  • Description: An attacker might gain unauthorized access to log files and read highly sensitive information like passwords, API keys, personally identifiable information (PII), financial data, or critical system credentials that were unintentionally logged. Access could be gained through web server vulnerabilities, file system exploits, or breaches of centralized logging systems.
    • Impact: Critical Information Disclosure leading to severe consequences such as complete account compromise, large-scale data breaches, significant financial loss, identity theft, and catastrophic reputational damage.
    • Affected Log Component: Log Handlers (file, database, stream, etc.), Log Storage (file system, database, centralized logging).
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Mandatory Data Sanitization: Implement and enforce rigorous data sanitization and filtering processes before any data is logged. Treat all potentially sensitive data with extreme caution.
      • Strict Context-Aware Logging Policies: Establish and enforce clear policies defining what data is permissible to log in different contexts. Minimize logging of user inputs and request details in production.
      • Robust Secure Log Storage: Implement the strongest possible access controls on log storage locations. Utilize encryption at rest for log files and databases. Regularly audit access logs to log storage.
      • Aggressive Log Rotation and Minimal Retention: Implement short log retention periods and frequent rotation to minimize the window of exposure for sensitive data.
      • Automated Log Auditing and Alerting: Implement automated systems to continuously scan logs for patterns of sensitive data exposure and trigger immediate alerts for security teams.
      • Structured Logging with Mandatory Data Masking: Enforce structured logging formats (like JSON) and implement mandatory data masking or redaction for fields that could potentially contain sensitive information at the logging handler level.

Threat: Log File Access Vulnerability

  • Description: An attacker might exploit critical vulnerabilities in the web server, operating system, or application to gain direct, unauthorized read access to log files stored on the server's file system. This could be achieved through directory traversal exploits, local file inclusion vulnerabilities, or gaining shell access.
    • Impact: High Information Disclosure, allowing attackers to read sensitive data within logs, potentially leading to further compromise of the application and infrastructure.
    • Affected Log Component: Log Storage (file system), Operating System, Web Server Configuration.
    • Risk Severity: High
    • Mitigation Strategies:
      • Principle of Least Privilege for Web Server: Configure the web server to operate with the absolute minimum necessary privileges, limiting access to log files.
      • Hardened File System Permissions: Implement strict file system permissions on log files and directories, restricting read access to only essential system accounts and processes.
      • Log Storage Outside Web Document Root and System Partition: Store logs on a separate partition and outside of the web server's document root to isolate them from web-accessible areas and potential system drive compromises.
      • Regular Vulnerability Scanning and Patching: Implement regular vulnerability scanning and promptly apply security patches to the operating system and web server to eliminate potential access vectors.
      • Intrusion Detection/Prevention Systems (IDS/IPS): Deploy IDS/IPS to detect and block attempts to access sensitive files, including log files.

Threat: Exposure through Insecure Log Aggregation/Shipping

  • Description: An attacker might intercept or compromise log data during transmission to a centralized logging system if insecure protocols (like unencrypted HTTP) are used. Alternatively, attackers could breach a poorly secured centralized logging system to access a vast repository of logs from multiple applications.
    • Impact: High Information Disclosure on a potentially massive scale, as a compromised central logging system can expose logs from numerous applications and systems.
    • Affected Log Component: Log Handlers (remote shipping handlers), Network Communication, Log Aggregation System.
    • Risk Severity: High
    • Mitigation Strategies:
      • Mandatory Encrypted Log Shipping: Enforce the use of strong encryption (HTTPS, TLS) for all log transmission to centralized systems. Disable unencrypted protocols entirely.
      • Secure Centralized Logging Infrastructure: Implement robust security measures for the centralized logging system itself, including strong access controls, multi-factor authentication, encryption at rest and in transit within the system, and regular security audits.
      • VPN or Private Network for Log Shipping: Consider using a VPN or private network for log shipping to further isolate log traffic from public networks.
      • End-to-End Encryption for Logs: Implement end-to-end encryption for log data, ensuring that logs are encrypted from the point of origin to the final storage location in the centralized system.

Threat: Log Deletion or Modification for Audit Trail Tampering

  • Description: A sophisticated attacker who gains elevated privileges on the logging system or underlying infrastructure might attempt to delete or modify log files to erase evidence of their malicious activities, effectively tampering with audit trails and hindering incident response and forensic investigations.
    • Impact: High Tampering with critical audit logs, severely compromising incident response capabilities, hindering forensic analysis, and potentially allowing attackers to operate undetected for extended periods.
    • Affected Log Component: Log Storage (file system, database, centralized system), Access Control mechanisms, Log Integrity mechanisms.
    • Risk Severity: High
    • Mitigation Strategies:
      • Immutable Log Storage: Implement immutable log storage solutions (e.g., WORM storage, blockchain-based logging) where logs cannot be altered or deleted after creation, even by administrators.
      • Strong Separation of Duties for Log Management: Enforce strict separation of duties, ensuring that application administrators do not have write access to log storage and that log management is handled by dedicated security or operations teams.
      • Log Integrity Monitoring with Cryptographic Verification: Implement log integrity monitoring using cryptographic hashing or digital signatures to detect any unauthorized modifications or deletions. Alert security teams immediately upon detection of tampering.
      • Centralized Security Information and Event Management (SIEM): Utilize a SIEM system to collect, analyze, and monitor logs in real-time, providing an independent and centralized audit trail that is harder for attackers to tamper with completely.
      • Write-Only Log Storage with Append-Only Access: Configure log storage to be write-only and append-only for the application, preventing modification or deletion while still allowing new logs to be added.

Threat: Log Flooding leading to Denial of Service

  • Description: A malicious actor might intentionally generate a massive volume of log events, such as repeated invalid requests, application errors, or security alerts, to overwhelm the logging system and consume excessive resources (disk space, CPU, I/O). This can lead to disk space exhaustion, performance degradation of the application and logging infrastructure, and ultimately a Denial of Service for legitimate users and monitoring capabilities.
    • Impact: High Denial of Service, causing application downtime, performance degradation, and failure of critical logging and monitoring systems, potentially masking other attacks and hindering incident detection.
    • Affected Log Component: Log Handlers, Log Storage, Logging Infrastructure, Resource Management, Application Error Handling.
    • Risk Severity: High
    • Mitigation Strategies:
      • Aggressive Rate Limiting for Logging: Implement strict rate limiting on logging, particularly for specific event types or log sources that are susceptible to flooding. Dynamically adjust rate limits based on system load and detected anomalies.
      • Dynamic Log Level Management and Adaptive Sampling: Implement dynamic log level adjustment based on system health and detected attack patterns. Employ adaptive sampling techniques to reduce logging volume during periods of high load or suspected attacks while still capturing representative data.
      • Dedicated Logging Infrastructure with Resource Quotas: Deploy dedicated infrastructure for logging with sufficient resources to handle expected peak loads and implement resource quotas to prevent log flooding from impacting other systems.
      • Real-time Resource Monitoring and Automated Alerting for Logging Systems: Implement comprehensive monitoring of disk space usage, logging system performance, and application performance related to logging. Set up automated alerts to trigger immediate responses to potential log flooding attacks.
      • Input Validation and Robust Error Handling to Minimize Error Logs: Implement rigorous input validation and robust error handling in the application to minimize the generation of unnecessary error logs caused by invalid user input or predictable application errors.