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Threat Model Analysis for alibaba/druid

Threat: Sensitive Data Exposure through Druid Monitoring Console

  • Description: An attacker gains unauthorized access to Druid's monitoring console due to weak authentication or authorization vulnerabilities within Druid itself. Upon successful access, the attacker can view sensitive information exposed by Druid, such as SQL queries (potentially containing sensitive data), database connection details, performance metrics, and internal application details displayed through Druid's monitoring dashboards.
    • Impact: Information disclosure, privacy violation, potential exposure of database credentials, reputational damage, potential further attacks based on exposed information.
    • Druid Component Affected: Monitoring Console, Web UI, API Endpoints for monitoring data, Authentication Module.
    • Risk Severity: High
    • Mitigation Strategies:
      • Implement strong authentication and authorization mechanisms specifically for Druid's monitoring console.
      • Restrict access to the monitoring console to only strictly authorized personnel.
      • Deploy Druid's monitoring console within a secured, isolated network segment, not directly accessible from public networks.
      • Configure Druid to mask or redact sensitive data within SQL queries and monitoring logs displayed in the console.
      • Regularly review and harden Druid's monitoring configuration, ensuring default settings are changed and secure practices are enforced.

Threat: Authentication Bypass in Druid Monitoring Console

  • Description: An attacker exploits vulnerabilities directly within Druid's authentication implementation for its monitoring console. This allows the attacker to bypass intended login procedures and gain unauthorized access to the monitoring console without providing valid credentials. This grants access to sensitive monitoring data and potentially any administrative functionalities exposed through the console if such vulnerabilities exist in Druid.
    • Impact: Unauthorized access to sensitive monitoring data, potential unauthorized administrative actions within Druid if available, information disclosure, system compromise, potential for further exploitation.
    • Druid Component Affected: Monitoring Console, Authentication Module, potentially Authorization Module if bypass leads to privilege escalation.
    • Risk Severity: High
    • Mitigation Strategies:
      • Ensure Druid's monitoring console is configured with the strongest available authentication methods.
      • Consider integrating Druid's authentication with a robust, established application authentication system if possible to leverage proven security mechanisms.
      • Conduct regular security audits and penetration testing specifically targeting Druid's monitoring console and its authentication implementation to identify and remediate any vulnerabilities.
      • Apply security updates for Druid promptly, prioritizing patches that address authentication or authorization related vulnerabilities.

Threat: SQL Injection Vulnerabilities due to Application's Misuse of Druid's SQL Parsing Features

  • Description: While Druid's SQL parser itself is designed for analysis and not direct query execution, vulnerabilities can arise if application code incorrectly relies on and trusts Druid's SQL parsing output without proper sanitization or validation. An attacker could craft malicious SQL queries that, when processed by Druid and subsequently used by vulnerable application logic, lead to unintended SQL execution against the underlying database. This is not a vulnerability in Druid's parser causing direct SQL injection, but rather a vulnerability in how the application uses Druid's parsing results insecurely.
    • Impact: Data breach, unauthorized data modification, unauthorized access to database resources, complete application compromise, potential for persistent attacks.
    • Druid Component Affected: SQL Parser (indirectly), primarily affects application logic that integrates with and utilizes Druid's SQL parsing capabilities.
    • Risk Severity: High
    • Mitigation Strategies:
      • Never directly use or trust Druid's SQL parsing output in security-sensitive application logic without thorough validation and sanitization.
      • Implement robust input validation and sanitization for all user inputs before they are processed by Druid or incorporated into SQL queries in any way.
      • Adhere to secure coding practices, especially when building dynamic SQL queries or logic based on external input or parsed data.
      • Conduct rigorous security code reviews, specifically focusing on areas where application code interacts with Druid's SQL parsing features and database interactions.
      • Apply the principle of least privilege to database user accounts used by the application and Druid, limiting the potential damage from any successful SQL injection.