Skip to content

Latest commit

 

History

History
66 lines (55 loc) · 7.42 KB

attack-surface.md

File metadata and controls

66 lines (55 loc) · 7.42 KB

Attack Surface Analysis for cube-js/cube

Attack Surface: Data Source Credential Compromise (Cube.js Storage/Handling)

  • Description: Unauthorized access to database credentials because of how Cube.js stores or handles them. This is distinct from general credential mismanagement; it focuses on vulnerabilities introduced by Cube.js's configuration.
  • How Cube.js Contributes: Cube.js requires and uses these credentials. If its configuration files, environment variable handling, or internal mechanisms for accessing secrets are flawed, this creates a direct vulnerability.
  • Example: Cube.js is configured to read credentials from a file with overly permissive access, or a vulnerability in Cube.js's environment variable parsing allows an attacker to inject their own credentials.
  • Impact: Complete database compromise, bypassing all Cube.js security.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Secrets Management Integration: Use Cube.js's documented integration with secure secrets management solutions (Vault, AWS Secrets Manager, etc.). Ensure Cube.js is correctly configured to use these.
    • Secure Configuration Practices: Follow Cube.js's documentation precisely regarding secure configuration of database connections. Avoid any undocumented or "workaround" methods.
    • Code Review (Cube.js Configuration): Thoroughly review the Cube.js configuration files and any code related to credential handling for potential vulnerabilities.
    • Principle of Least Privilege (Database User): Ensure the database user configured within Cube.js has only the absolute minimum necessary permissions.

Attack Surface: Schema-Driven Data Exposure (Flawed Schema Design)

  • Description: Unintentional exposure of sensitive data due to errors or omissions within the Cube.js schema definition itself.
  • How Cube.js Contributes: The Cube.js schema is the definition of how data is exposed. Flaws in the schema directly translate to data exposure vulnerabilities.
  • Example: A users cube includes a password_hash dimension that is not marked as shown: false, making it accessible via the API. Or, a join is incorrectly defined, leading to unintended data leakage across tables.
  • Impact: Exposure of sensitive data defined within the schema.
  • Risk Severity: High
  • Mitigation Strategies:
    • Schema Design Best Practices: Follow Cube.js's schema design best practices meticulously. Use shown: false appropriately. Carefully consider the implications of each dimension, measure, and join.
    • Security Context (Cube.js Feature): Must implement Cube.js's security context feature to enforce row-level and column-level security. This is not optional for sensitive data.
    • Schema Validation (Automated): Implement automated schema validation to check for common errors and enforce security policies before deployment.
    • Regular Schema Audits: Conduct regular, thorough audits of the Cube.js schema, specifically looking for potential data exposure vulnerabilities.

Attack Surface: Denial of Service (DoS) via Query Complexity (Cube.js Query Translation)

  • Description: Attackers craft complex queries that, when translated by Cube.js into SQL, overwhelm the database or Cube.js server.
  • How Cube.js Contributes: Cube.js performs the translation from its query language to SQL. The complexity of this translation, and the potential for generating inefficient SQL, is a direct factor.
  • Example: An attacker crafts a Cube.js query with many joins and filters that, when translated, results in a highly inefficient SQL query that consumes all database resources.
  • Impact: Service unavailability due to resource exhaustion.
  • Risk Severity: High
  • Mitigation Strategies:
    • Query Cost Analysis (within Cube.js): Implement a mechanism within Cube.js (potentially using a custom extension) to analyze the estimated cost of a query before sending it to the database.
    • Cube.js Query Timeouts: Configure appropriate timeouts within Cube.js to limit the execution time of queries.
    • Pre-Aggregations (Cube.js Feature): Heavily utilize Cube.js's pre-aggregation feature to pre-compute common aggregations, reducing the complexity of on-demand queries.
    • Rate Limiting (Cube.js API): Implement rate limiting on the Cube.js API to prevent attackers from submitting a large number of complex queries.

Attack Surface: Unauthorized API Access (Cube.js API Security)

  • Description: Attackers directly access the Cube.js API without proper authentication or authorization, exploiting weaknesses in Cube.js's API security configuration.
  • How Cube.js Contributes: Cube.js provides the API and is responsible for its security. Misconfiguration or vulnerabilities in its API security mechanisms are direct attack vectors.
  • Example: The Cube.js API is deployed without any authentication configured, or the JWT secret used for authentication is weak or exposed.
  • Impact: Unauthorized data access and potential server compromise.
  • Risk Severity: High
  • Mitigation Strategies:
    • Authentication (Cube.js Configuration): Must configure strong authentication for the Cube.js API, following Cube.js's documentation precisely (JWTs, API keys, etc.).
    • Authorization (Cube.js Security Context): Use Cube.js's security context to enforce fine-grained authorization rules, controlling which users/roles can access which data.
    • CORS (Cube.js Configuration): Correctly configure CORS within Cube.js to restrict API access to trusted origins.
    • Regular Security Audits (Cube.js API): Regularly audit the Cube.js API configuration and security settings.

Attack Surface: Node.js and Dependency Vulnerabilities (Impacting Cube.js)

  • Description: Vulnerabilities in Node.js or dependencies specifically used by Cube.js that allow attackers to compromise the Cube.js server. This focuses on vulnerabilities that directly impact the running Cube.js instance.
  • How Cube.js Contributes: Cube.js is a Node.js application and depends on specific packages. Vulnerabilities in these directly affect Cube.js.
  • Example: A vulnerability in a Cube.js dependency used for query parsing allows an attacker to inject malicious code.
  • Impact: Remote code execution (RCE), server compromise, data theft.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Dependency Scanning (Targeted): Regularly scan Cube.js's specific dependencies for known vulnerabilities. Focus on packages used by Cube.js itself, not just general project dependencies.
    • Prompt Updates (Cube.js and Dependencies): Keep Cube.js and its dependencies up to date. Apply security patches immediately when released.
    • Vulnerability Monitoring (Cube.js Specific): Monitor security advisories and vulnerability databases specifically for issues related to Cube.js and its core dependencies.