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Mitigation Strategies Analysis for encode/django-rest-framework

Mitigation Strategy: Implement Robust Authentication and Authorization using DRF Features

Description:

  • Step 1: Configure DEFAULT_AUTHENTICATION_CLASSES in DRF settings. Specify authentication schemes like JWT or Token Authentication globally in your settings.py file within the REST_FRAMEWORK dictionary. This ensures all API endpoints by default require authentication based on the chosen schemes.
  • Step 2: Utilize DRF's Permission Classes in views and viewsets. Apply permission classes such as IsAuthenticated, IsAdminUser, or custom permission classes to individual views or viewsets. This is done by setting the permission_classes attribute within the view class, controlling access to specific API endpoints based on user authentication and authorization.
  • Step 3: Develop Custom Permission Classes for fine-grained control. Create custom permission classes inheriting from rest_framework.permissions.BasePermission to implement specific authorization logic. Override has_permission and has_object_permission methods to define rules based on user roles, object ownership, or application-specific logic, enhancing access control beyond built-in classes.

Threats Mitigated:

  • Unauthorized Access: - Severity: High
  • Data Breaches: - Severity: High
  • Account Takeover: - Severity: High
  • Privilege Escalation: - Severity: High

Impact:

  • Unauthorized Access: High risk reduction - Prevents access to API endpoints by unauthenticated or unauthorized users through DRF's access control mechanisms.
  • Data Breaches: High risk reduction - Limits data exposure by ensuring only authorized users can access sensitive information exposed through the API, enforced by DRF permissions.
  • Account Takeover: High risk reduction - Makes it harder for attackers to exploit API vulnerabilities to gain control of user accounts due to enforced authentication and authorization by DRF.
  • Privilege Escalation: High risk reduction - Prevents users from accessing functionalities or data beyond their intended roles by leveraging DRF's permission system for granular access control.

Currently Implemented:

  • JWTAuthentication is configured as a DEFAULT_AUTHENTICATION_CLASS in settings.py.
  • IsAuthenticated permission class is used in many API views.

Missing Implementation:

  • Custom permission classes are needed for more complex authorization scenarios beyond simple authentication checks, especially for resource-level permissions.

Mitigation Strategy: Secure Serializers and Data Handling using DRF Serializer Features

Description:

  • Step 1: Explicitly define serializer fields using fields or exclude. In your DRF serializers, explicitly list the fields to be included or excluded. Avoid using fields = '__all__' in production to prevent accidental exposure of sensitive model fields through the API.
  • Step 2: Utilize read_only_fields and write_only_fields in serializers. Mark fields that should only be present in API responses as read_only_fields and fields only for input as write_only_fields. This controls data flow and prevents unintended modifications via the API.
  • Step 3: Implement Custom Field Validation within DRF Serializers. Use built-in validators or define custom validators within serializer fields to enforce data integrity. Validate data types, formats, ranges, and business rules directly within the serializer field definitions.
  • Step 4: Implement validate_<field_name> methods in serializers for complex validation. Create methods like validate_email(self, value) within serializers to perform more intricate validation logic specific to individual fields, going beyond basic field-level validators.

Threats Mitigated:

  • Mass Assignment Vulnerabilities: - Severity: Medium
  • Data Injection Attacks (indirectly by data validation): - Severity: Medium
  • Exposure of Sensitive Data: - Severity: Medium
  • Data Integrity Issues: - Severity: Medium

Impact:

  • Mass Assignment Vulnerabilities: Medium risk reduction - Prevents unintended modification of model fields by explicitly controlling serialized fields in DRF serializers.
  • Data Injection Attacks: Medium risk reduction - Reduces the risk of injection by validating input data formats and types within DRF serializers, although direct sanitization is still needed for certain contexts.
  • Exposure of Sensitive Data: Medium risk reduction - Prevents accidental exposure of sensitive data by explicitly defining serializer fields and using read_only_fields in DRF serializers.
  • Data Integrity Issues: Medium risk reduction - Ensures data consistency and validity by enforcing data type and format constraints through DRF serializer validation.

Currently Implemented:

  • Serializers generally use explicit fields definitions.
  • Basic field validation (data types, required=True) is used in serializers.
  • read_only_fields are used for fields like id and created_at.

Missing Implementation:

  • Comprehensive custom field validation is missing for many serializers, especially for complex business rules and data format constraints.
  • write_only_fields are not consistently used for sensitive input fields.
  • Validation within nested serializers needs review and improvement.

Mitigation Strategy: Implement Rate Limiting and Throttling using DRF Throttling

Description:

  • Step 1: Configure DEFAULT_THROTTLE_CLASSES and DEFAULT_THROTTLE_RATES in DRF settings. Set global throttling for your API by specifying DRF's throttling classes like UserRateThrottle and AnonRateThrottle in DEFAULT_THROTTLE_CLASSES and defining rate limits in DEFAULT_THROTTLE_RATES within the REST_FRAMEWORK settings in settings.py.
  • Step 2: Apply throttling classes to specific DRF views or viewsets. Override global throttling settings for particular endpoints by setting the throttle_classes attribute directly within a view or viewset. This allows for endpoint-specific rate limiting using DRF's throttling mechanism.
  • Step 3: Customize throttling rates in DEFAULT_THROTTLE_RATES or custom classes. Adjust the rate limits defined in DEFAULT_THROTTLE_RATES or within custom throttling classes to match the sensitivity and expected usage of different API endpoints, leveraging DRF's rate configuration.

Threats Mitigated:

  • Brute-force Attacks: - Severity: Medium
  • Denial-of-Service (DoS) Attacks: - Severity: Medium
  • API Abuse/Resource Exhaustion: - Severity: Medium
  • Credential Stuffing: - Severity: Medium

Impact:

  • Brute-force Attacks: Medium risk reduction - Slows down brute-force attempts by limiting the number of requests per user or IP within a time window using DRF throttling.
  • Denial-of-Service (DoS) Attacks: Medium risk reduction - Mitigates DoS impact by restricting request rates, preventing overwhelming the API server, enforced by DRF throttling.
  • API Abuse/Resource Exhaustion: Medium risk reduction - Prevents excessive API usage that could lead to resource exhaustion by limiting request frequency through DRF throttling.
  • Credential Stuffing: Medium risk reduction - Reduces the effectiveness of credential stuffing by limiting login attempts from the same user or IP address using DRF rate limiting.

Currently Implemented:

  • Global rate limiting is configured in settings.py using UserRateThrottle and AnonRateThrottle with default rates.

Missing Implementation:

  • Throttling rates are not customized for specific endpoints.
  • Scoped throttling is not implemented for endpoints requiring different rate limits based on API scopes.

Mitigation Strategy: Secure API Endpoints and Views using DRF Features

Description:

  • Step 1: Utilize DRF Filtering Backends and filterset_fields or FilterSet. Implement filtering in DRF views using filtering backends like DjangoFilterBackend. Explicitly define allowed filterable fields using filterset_fields or by creating FilterSet classes to control which fields can be filtered via API requests, preventing unintended data exposure.
  • Step 2: Control API Endpoint Exposure using DRF Routers and ViewSets. Carefully manage API endpoint URLs and visibility using DRF's routers and viewsets. Only expose necessary endpoints and structure URLs logically to minimize the attack surface and prevent unintended access to functionalities.
  • Step 3: Implement API Versioning using DRF Versioning Classes. Use DRF's versioning classes like URLPathVersioning or AcceptHeaderVersioning to manage API versions. This allows for controlled API evolution and deprecation, reducing risks associated with breaking changes and maintaining backward compatibility.

Threats Mitigated:

  • Unauthorized Access (through misconfigured endpoints): - Severity: Medium
  • Data Exposure through insecure filtering: - Severity: Medium
  • API Abuse through unintended endpoint exposure: - Severity: Medium
  • Backward Incompatibility Issues (security related to service availability): - Severity: Low

Impact:

  • Unauthorized Access: Medium risk reduction - Reduces risk of unauthorized access by carefully controlling endpoint exposure and structure using DRF routers and viewsets.
  • Data Exposure through insecure filtering: Medium risk reduction - Prevents attackers from extracting excessive data through uncontrolled filtering by explicitly defining filterable fields in DRF.
  • API Abuse through unintended endpoint exposure: Medium risk reduction - Minimizes the attack surface by limiting the number of publicly accessible API endpoints using DRF's endpoint management features.
  • Backward Incompatibility Issues: Low risk reduction (but improves stability) - Manages API changes gracefully, reducing service disruptions related to API updates through DRF versioning.

Currently Implemented:

  • DjangoFilterBackend is used for basic filtering in some viewsets with filterset_fields.
  • Basic API versioning using URL path versioning is implemented.

Missing Implementation:

  • More robust filtering validation and sanitization of ordering parameters are needed.
  • Endpoint exposure review is needed to ensure no unnecessary endpoints are publicly accessible.
  • API versioning strategy needs to be more consistently applied.

Mitigation Strategy: Disable Browsable API in Production via DRF Settings

Description:

  • Step 1: Modify DEFAULT_RENDERER_CLASSES in DRF settings for production. In your settings.py file, within the REST_FRAMEWORK dictionary, ensure that rest_framework.renderers.BrowsableAPIRenderer is removed or commented out from the DEFAULT_RENDERER_CLASSES list specifically for production environments. This disables the browsable API, which is intended for development, in the production deployment.

Threats Mitigated:

  • Information Disclosure (API structure, endpoints, data examples): - Severity: Low to Medium
  • Accidental Modification of Data (through browsable API forms): - Severity: Low

Impact:

  • Information Disclosure: Low to Medium risk reduction - Prevents unauthorized users from easily exploring the API structure and potentially discovering vulnerabilities or sensitive information through the browsable API in production.
  • Accidental Modification of Data: Low risk reduction - Reduces the risk of unintended data modifications by disabling the browsable API's interactive forms in the production environment.

Currently Implemented:

  • Browsable API is enabled in development settings.

Missing Implementation:

  • Browsable API is not explicitly disabled in production settings.

Mitigation Strategy: Secure Error Responses using DRF Exception Handling

Description:

  • Step 1: Implement a custom exception handler using DRF's exception_handler setting. Define a custom function and configure it as exception_handler in the REST_FRAMEWORK settings in settings.py. This custom handler will intercept exceptions raised in DRF views.
  • Step 2: Sanitize error responses within the custom exception handler. Inside your custom exception handler function, modify the error response data before it's returned to the client. Remove sensitive information like internal server paths, database details, or debugging information. Ensure only generic, safe error messages are sent to API clients.

Threats Mitigated:

  • Information Disclosure through Error Messages: - Severity: Medium

Impact:

  • Information Disclosure through Error Messages: Medium risk reduction - Prevents attackers from gaining sensitive information from detailed error responses by sanitizing and providing generic error messages to API clients using DRF's exception handling.

Currently Implemented:

  • Default DRF exception handling is used.

Missing Implementation:

  • Custom DRF exception handler is not implemented to sanitize error responses and prevent information leakage to clients.