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Mitigation Strategies Analysis for cube-js/cube

Mitigation Strategy: Implement Row-Level Security (RLS) within Cube.js

1. Implement Row-Level Security (RLS) within Cube.js

  • Mitigation Strategy: Row-Level Security (RLS) Implementation in Cube.js

  • Description:

    1. Identify User Roles and Data Access Needs: Define different user roles and their corresponding data access requirements within your application.
    2. Utilize securityContext in Cube.js Schema: Within your Cube.js schema files (.cube files), define the securityContext property. This allows you to implement functions that control data access based on the current user's context within Cube.js queries.
    3. Implement Access Control Logic in securityContext: Inside the securityContext function, access user information (e.g., from JWT claims or session data passed through the Cube.js API context). Write conditional logic to filter data based on user roles or attributes. For example, filter data based on organization_id so users only see data relevant to their organization.
    4. Test RLS Thoroughly: Write tests to verify that RLS rules are correctly applied and that users can only access authorized data. Test different user roles and access scenarios to ensure comprehensive coverage.
    5. Regularly Review and Update RLS Rules: Periodically review and update RLS rules in the Cube.js schema to adapt to evolving business needs and security requirements, ensuring continued effectiveness of access controls.

  • Threats Mitigated:

    • Unauthorized Data Access (High Severity): Prevents users from accessing data beyond their authorized permissions, even if they bypass UI restrictions or directly query the Cube.js API.
    • Data Breaches due to Insider Threats (Medium Severity): Reduces the risk of data breaches caused by internal users attempting to access sensitive data outside their authorized scope.
    • Data Leakage through API Exploitation (Medium Severity): Protects against attackers exploiting API vulnerabilities to gain access to sensitive data by bypassing UI-level security, as RLS is enforced at the query level.

  • Impact:

    • Unauthorized Data Access: High Risk Reduction. RLS directly and significantly reduces the risk of unauthorized data access at the core data query level within Cube.js.
    • Data Breaches due to Insider Threats: Medium Risk Reduction. RLS provides a crucial layer of defense against insider threats by enforcing granular access control within the data layer.
    • Data Leakage through API Exploitation: Medium Risk Reduction. RLS limits the data accessible even if API vulnerabilities are exploited, minimizing potential damage and data exposure.

  • Currently Implemented:

    • Partially implemented in schema/Orders.cube. securityContext is defined, but currently only checks for admin role and lacks granular filtering based on organization or other attributes.

  • Missing Implementation:

    • Granular filtering based on attributes like organization_id needs to be implemented within securityContext for all relevant cubes (e.g., Orders, Customers, Products, etc.).
    • RLS needs to be implemented across all cubes containing sensitive data, not just Orders.
    • Comprehensive testing of RLS rules for all defined user roles and various access scenarios is currently lacking.

Mitigation Strategy: Minimize Data Exposure in Cube.js Schemas

2. Minimize Data Exposure in Cube.js Schemas

  • Mitigation Strategy: Cube.js Schema Data Exposure Minimization

  • Description:

    1. Review Cube.js Schemas for Sensitive Data: Carefully examine all .cube schema files to identify measures, dimensions, and segments that expose sensitive or personally identifiable information (PII).
    2. Remove Unnecessary Data Fields: Eliminate any measures, dimensions, or segments from the schema that are not strictly required for reporting and analytics. Only expose data that is actively used and essential for business purposes.
    3. Aggregate and Anonymize Data within Schemas: Where possible, instead of exposing raw, granular sensitive data, consider aggregating data at higher levels (e.g., daily summaries instead of individual transactions). Implement data anonymization or masking techniques directly within Cube.js schema definitions for sensitive fields when full data access is not necessary. Utilize Cube.js's data transformation capabilities within measures and dimensions to achieve this.
    4. Implement Data Type Restrictions in Schemas: Use specific and restrictive data types in your schema definitions to limit the range and format of data exposed. Avoid overly permissive data types that might inadvertently expose more information than intended.
    5. Regular Schema Audits for Data Exposure: Establish a process for periodic reviews of your Cube.js schemas to ensure they continuously adhere to the principle of least privilege and minimize data exposure as application requirements evolve.

  • Threats Mitigated:

    • Data Breaches due to Schema Over-Exposure (Medium Severity): Reduces the potential impact of data breaches by limiting the amount of sensitive data readily accessible through the Cube.js API if the application is compromised.
    • Compliance Violations (e.g., GDPR, CCPA) (Medium Severity): Aids in meeting data privacy regulations by minimizing the unnecessary exposure of PII and sensitive data within the analytics layer.
    • Accidental Data Leakage (Low Severity): Reduces the risk of unintentional data leakage through reports or dashboards if schemas are designed to be minimally permissive in terms of sensitive data exposure.

  • Impact:

    • Data Breaches due to Schema Over-Exposure: Medium Risk Reduction. Limits the scope and severity of potential data breaches by reducing the amount of sensitive data readily available through Cube.js.
    • Compliance Violations: Medium Risk Reduction. Contributes to data privacy compliance efforts by minimizing PII exposure, although it's not a complete compliance solution on its own.
    • Accidental Data Leakage: Low Risk Reduction. Makes accidental data leakage less likely by reducing the amount of sensitive data exposed in standard reporting and analytics contexts.

  • Currently Implemented:

    • Basic schema design is implemented for functionality, but there has been no specific focus on minimizing data exposure as a primary design principle. Schemas are designed to provide necessary data, but not necessarily with minimal exposure in mind.

  • Missing Implementation:

    • A systematic and security-focused review of all .cube schema files to identify and remove potentially unnecessary or overly granular sensitive data fields is needed.
    • Implementation of data aggregation or anonymization techniques within schemas for sensitive fields is currently absent.
    • No established process for regular, security-oriented schema audits to ensure ongoing minimal data exposure is in place.

Mitigation Strategy: Implement Robust Authentication and Authorization for Cube.js APIs using checkAuth

3. Implement Robust Authentication and Authorization for Cube.js APIs using checkAuth

  • Mitigation Strategy: Cube.js API Authentication and Authorization via checkAuth

  • Description:

    1. Choose Authentication Mechanism (External to Cube.js): Select an appropriate authentication mechanism for your application (e.g., JWT, OAuth 2.0). This is typically handled outside of Cube.js itself, often in your application's API gateway or authentication service.
    2. Configure Cube.js checkAuth Hook: Utilize Cube.js's checkAuth hook within your Cube.js configuration file (cube.js or similar). This hook is the primary mechanism within Cube.js to enforce authentication and authorization for all incoming API requests.
    3. Verify User Identity in checkAuth: Inside the checkAuth hook function, verify the user's identity based on the chosen authentication mechanism. For JWT, this involves validating the token signature and ensuring it's not expired. Access user information from the validated token or session.
    4. Implement Authorization Logic in checkAuth: Within the checkAuth hook, implement authorization checks based on user roles, permissions, or attributes. Determine if the authenticated user is authorized to access the requested Cube.js data or perform the requested operation. This logic should align with your application's access control policies.
    5. Enforce checkAuth for All API Requests: Ensure that the checkAuth hook is properly configured and active for all Cube.js API endpoints (GraphQL and REST). No API request should bypass the checkAuth hook and access data without proper authentication and authorization checks.
    6. Return false or Throw Error in checkAuth for Unauthorized Access: If authentication or authorization fails within the checkAuth hook, ensure it returns false or throws an error to prevent the request from proceeding and accessing data.

  • Threats Mitigated:

    • Unauthorized API Access (High Severity): Prevents unauthorized users from accessing Cube.js APIs and retrieving data or performing operations they are not permitted to, by enforcing authentication and authorization at the Cube.js API level.
    • Data Breaches through API Exploitation (High Severity): Significantly reduces the risk of data breaches caused by attackers exploiting API vulnerabilities to gain unauthorized access to data, as checkAuth acts as a gatekeeper for all data access.
    • Circumvention of UI Security (Medium Severity): Prevents users from bypassing UI-level security controls and directly accessing sensitive data through the Cube.js API without proper authorization checks enforced by checkAuth.

  • Impact:

    • Unauthorized API Access: High Risk Reduction. checkAuth is the primary Cube.js mechanism for directly preventing unauthorized API access, making it a highly impactful mitigation.
    • Data Breaches through API Exploitation: High Risk Reduction. Strongly mitigates the risk of data breaches by ensuring only authenticated and authorized requests are processed by Cube.js, acting as a critical security control point.
    • Circumvention of UI Security: Medium Risk Reduction. Prevents a common attack vector where users might attempt to bypass UI restrictions and directly interact with the API to access unauthorized data.

  • Currently Implemented:

    • Basic authentication using JWT is implemented. The checkAuth hook in cube.js verifies JWT tokens sent in the Authorization header to ensure a valid token is present.

  • Missing Implementation:

    • Authorization logic within the checkAuth hook is currently very rudimentary. It needs to be expanded to implement proper role-based access control (RBAC) or attribute-based access control (ABAC) based on user roles and permissions. Currently, it primarily validates the token's existence, not user permissions.
    • Detailed user permission management and integration with checkAuth are missing. The application lacks a robust system to define and enforce user-specific permissions within the Cube.js context.
    • Error handling and logging within checkAuth could be improved to provide more informative security logs and better handle authentication/authorization failures.

Mitigation Strategy: Secure Cube Store (Caching) Configuration

4. Secure Cube Store (Caching) Configuration

  • Mitigation Strategy: Secure Cube Store Configuration and Management

  • Description:

    1. Restrict Access to Cube Store Instance: If using Cube Store for caching, ensure that access to the Cube Store instance (e.g., Redis, database) is strictly limited to only authorized Cube.js server processes. Use network firewalls and access control lists (ACLs) to restrict network access.
    2. Implement Authentication for Cube Store: Configure authentication mechanisms for your Cube Store instance (e.g., Redis AUTH, database authentication). Ensure that Cube.js server is configured to authenticate when connecting to Cube Store using strong credentials.
    3. Encrypt Data in Transit to Cube Store: Enable encryption for communication between the Cube.js server and the Cube Store instance (e.g., TLS/SSL for Redis). This protects cached data during transmission from eavesdropping.
    4. Encrypt Data at Rest in Cube Store (if sensitive): If caching sensitive data in Cube Store, consider enabling data-at-rest encryption provided by your Cube Store solution (e.g., Redis Enterprise encryption, database encryption). This protects cached data if the Cube Store storage is compromised.
    5. Regularly Review Cube Store Security Configuration: Periodically review the security configuration of your Cube Store instance and Cube.js Cube Store integration to ensure that access controls, authentication, and encryption settings remain secure and aligned with security best practices.
    6. Implement Cache Invalidation Strategies: Implement robust cache invalidation strategies to prevent serving stale or outdated data, especially if caching sensitive or time-sensitive information. Ensure cache invalidation mechanisms are triggered appropriately when underlying data changes to maintain data integrity and prevent serving potentially incorrect or outdated information.

  • Threats Mitigated:

    • Unauthorized Access to Cached Data (Medium Severity): Prevents unauthorized access to sensitive data cached in Cube Store if access controls are not properly configured.
    • Data Breaches through Cube Store Compromise (Medium Severity): Reduces the risk of data breaches if the Cube Store instance is compromised by securing access and potentially encrypting cached data.
    • Data Leakage due to Unencrypted Cache Communication (Low Severity): Protects against data leakage during communication between Cube.js and Cube Store by encrypting data in transit.
    • Serving Stale or Outdated Data (Low Severity - Data Integrity): While not directly a security threat in terms of confidentiality, serving stale data can lead to incorrect decisions and undermine data integrity, which can have indirect security implications in some contexts.

  • Impact:

    • Unauthorized Access to Cached Data: Medium Risk Reduction. Restricting access and implementing authentication directly reduces the risk of unauthorized access to the cache.
    • Data Breaches through Cube Store Compromise: Medium Risk Reduction. Securing Cube Store reduces the potential impact of a compromise by limiting access and potentially protecting data at rest.
    • Data Leakage due to Unencrypted Cache Communication: Low Risk Reduction. Encrypting communication protects against eavesdropping during data transfer to and from the cache.
    • Serving Stale or Outdated Data: Low Risk Reduction (Data Integrity). Implementing cache invalidation improves data integrity and reduces the risk of decisions based on outdated information.

  • Currently Implemented:

    • Cube Store (Redis) is used for caching in production. Basic network access restrictions are in place via firewall rules to limit access to the Redis instance.

  • Missing Implementation:

    • Authentication for Redis (Cube Store) is not currently implemented. Redis is accessible without authentication from within the allowed network.
    • Encryption for data in transit between Cube.js and Redis (TLS/SSL) is not configured.
    • Data at rest encryption in Redis is not implemented.
    • Formal, regularly scheduled reviews of Cube Store security configuration are not in place.
    • While basic cache invalidation is likely happening through Cube.js mechanisms, a clearly defined and robust cache invalidation strategy, especially for sensitive data, is not explicitly documented or implemented.