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vulnerabilities-workflow-1.md

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Here is the combined list of vulnerabilities, formatted as markdown and with duplicates removed:

Combined Vulnerability List

  • Vulnerability Name: Excessive Data Exposure via Include Parameter

    • Description: An attacker can use the include query parameter to request inclusion of related resources. If the application does not properly validate or limit the depth and breadth of included resources, or if the serializers for included resources expose more data than intended for the context of the primary resource, it can lead to excessive data exposure. An attacker could potentially retrieve sensitive information from related models that they are not authorized to access directly, simply by crafting a specific include query.

      • Step-by-step trigger:
        1. An attacker identifies an API endpoint that uses Django REST framework JSON:API and supports the include parameter.
        2. The attacker crafts a GET request to this endpoint with an include parameter specifying related resources, potentially including nested relationships (e.g., include=relation1.relation2).
        3. The application processes the request and, due to insufficient validation, includes the requested related resources in the response.
        4. If the serializers for the included resources expose sensitive data and/or there are no authorization checks on included resources, the attacker gains access to data they should not be able to see in the context of the primary resource.

    • Impact: Exposure of sensitive data from related resources. This could include personal information, business secrets, or other confidential data, depending on the models and relationships configured in the application.

    • Vulnerability Rank: High

    • Currently implemented mitigations:

      • Validation of include paths against included_serializers in IncludedResourcesValidationMixin in /code/rest_framework_json_api/serializers.py. This validation ensures that only paths defined in included_serializers are allowed. However, it does not limit depth, breadth, or perform authorization checks on included resources.

    • Missing mitigations:

      • Implement validation and sanitization of the include parameter to ensure only allowed relationships are included. (Partially Implemented - path validation exists, but not sufficient)
      • Implement a configuration to limit the depth and breadth of allowed includes to prevent excessive data retrieval.
      • Review and potentially create specialized serializers for included resources that expose only the necessary data when included in a compound document, rather than reusing serializers intended for detailed views of those resources.
      • Consider implementing access control checks within the extract_included function to ensure the current user is authorized to access the included resources in the context of the primary resource.

    • Preconditions:

      • Application uses Django REST framework JSON:API and enables the include feature.
      • Application does not have sufficient validation or limitations on the include parameter.
      • Serializers for included resources might expose more data than intended when included in the context of the primary resource.

    • Source code analysis:

      • File: /code/rest_framework_json_api/renderers.py

      • Function: JSONRenderer.extract_included

      • Step-by-step analysis:

        1. The extract_included function is called during rendering to process the include query parameter.
        2. It retrieves the included_resources from the request and included_serializers from the serializer.
        3. It iterates through the requested included_resources.
        4. For each resource, it determines the related instance and serializer.
        5. It recursively calls extract_included for nested resources based on dot notation in the include parameter (e.g., include=relation1.relation2).
        6. Vulnerability: There are no explicit checks within JSONRenderer.extract_included function to validate if the user is authorized to access the requested included resources. While IncludedResourcesValidationMixin validates if the include path is defined in the serializer, it does not check authorization. The function blindly follows the include parameter and the defined included_serializers, fetching and including data. This allows an attacker to potentially request inclusion of any related resource defined in included_serializers, regardless of whether it's appropriate in the current context or if the user is authorized to access it in this manner.

      • File: /code/rest_framework_json_api/serializers.py

      • Class: IncludedResourcesValidationMixin

      • Function: __init__

      • Step-by-step analysis:

        1. The __init__ method of IncludedResourcesValidationMixin is called when a serializer using this mixin is initialized.
        2. It retrieves the include query parameter from the request using get_included_resources(request).
        3. It iterates through each included resource path.
        4. For each path, it splits the path by dots to handle nested includes (e.g., relation1.relation2).
        5. It recursively validates each segment of the path against the included_serializers defined in the serializer and its nested serializers.
        6. Mitigation (Partial): This mixin does provide a level of validation by ensuring that only include paths that are explicitly defined in included_serializers are allowed. If an attacker tries to include a relationship that is not defined in included_serializers, a ParseError is raised, and the request is rejected.
        7. Still Vulnerable: However, this validation is insufficient because it only checks if the path is defined, not if the user is authorized to access the related resources. If a relationship is included in included_serializers, it is considered valid for inclusion, even if the user should not have access to the related data in the context of the primary resource. This validation also does not limit the depth or breadth of the include, potentially leading to performance issues and excessive data retrieval if complex include paths are defined.

      • File: /code/rest_framework_json_api/utils.py

      • Function: get_included_resources

      • Step-by-step analysis:

        1. The get_included_resources function simply retrieves the include query parameter from the request.
        2. If the parameter is present, it splits the comma-separated values into a list of included resources.
        3. If the parameter is not present, it attempts to get default included resources from the serializer's JSONAPIMeta.included_resources.
        4. No Mitigation: This function does not perform any validation or sanitization of the include parameter itself. It only extracts the values from the query parameter.

    • Security test case:

      1. Step 1: Set up a Django REST framework JSON:API application with two models, e.g., Article and Author. Article has a ForeignKey relationship to Author.
      2. Step 2: Create serializers for Article and Author. In ArticleSerializer, define included_serializers = {'author': AuthorSerializer} and include 'author' in JSONAPIMeta.included_resources. In AuthorSerializer, include a field that is considered sensitive, e.g., email. Assume that in a normal /authors/{id} endpoint, the email field is protected or not always exposed.
      3. Step 3: Create a viewset for Article that uses ArticleSerializer.
      4. Step 4: Send a GET request to the /articles/ endpoint with the include=author query parameter: GET /articles/?include=author.
      5. Step 5: Examine the JSON response. Check if the included author resources in the included section contain the sensitive email field.
      6. Step 6: If the email field is present in the included author resources, it confirms the excessive data exposure vulnerability. An attacker can use the include parameter to bypass intended data access restrictions and retrieve sensitive information through related resources.

  • Vulnerability Name: Misconfigured ReadOnlyModelViewSet Allows Write Operations

    • Description: The custom “read‑only” viewset class is derived from DRF’s ReadOnlyModelViewSet but overrides its default allowed HTTP methods to include POST, PATCH, and DELETE. An attacker may send write‑oriented requests (such as POST, PATCH, or DELETE) to an endpoint implemented using this class when the developer intended it to be read‑only.

      • Step‑by-step trigger:
        1. An attacker identifies an endpoint built with ReadOnlyModelViewSet.
        2. The attacker sends HTTP POST, PATCH, or DELETE requests containing valid JSON:API payloads.
        3. Due to the permissive method list and lack of strict permission checks, the endpoint processes the request and modifies or deletes data.

    • Impact: Unauthorized modifications or deletions occur on data that should be immutable, compromising data integrity and violating the principle of least privilege.

    • Vulnerability Rank: High

    • Currently Implemented Mitigations:

      • The base class currently lists “get”, “post”, “patch”, “delete”, “head”, and “options” as allowed HTTP methods.
      • Custom actions using the @action decorator may override behavior, but endpoints built with this base class remain at risk if they assume read‑only behavior.

    • Missing Mitigations:

      • Use a stricter default that limits http_method_names to only “get”, “head”, and “options” for read‑only endpoints.
      • Apply additional default permission enforcement on endpoints intended to be read‑only.

    • Preconditions:

      • An API endpoint is implemented using the provided ReadOnlyModelViewSet without any additional restrictions on HTTP methods or permissions.
      • The endpoint is publicly accessible.

    • Source Code Analysis:

      • In /code/rest_framework_json_api/views.py (and corroborated by tests in /code/tests/views.py), the custom ReadOnlyModelViewSet shows that non‑safe methods are allowed by default.
      • The design allows developer‑override through custom actions; however, the default behavior is too permissive for endpoints intended only for data retrieval.

    • Security Test Case:

      1. Deploy an endpoint using ReadOnlyModelViewSet without additional method or permission restrictions.
      2. Send an HTTP DELETE request (e.g. DELETE /some_resource/1/) with a valid JSON:API payload.
      3. Confirm that the resource is removed.
      4. Repeat with POST and PATCH requests to verify that write operations are accepted without explicit permission checks.

  • Vulnerability Name: Unrestricted CRUD Operations due to Lack of Access Controls

    • Description: Multiple endpoints—including those for blogs, entries, comments, companies, and projects—inherit directly from ModelViewSet without specifying any permission classes or access control measures.

      • Step‑by-step trigger:
        1. An attacker sends a POST request (for example, to /blogs/) with a well‑formed JSON:API payload to create a new resource.
        2. Similarly, the attacker sends PATCH or DELETE requests to endpoints such as /comments/1/ or /companies/1/ to update or remove records.
        3. With no authentication or authorization checks in place, the operations succeed, allowing unauthorized modifications.

    • Impact: Any unauthorized user can create, modify, or delete resources, leading to potential data integrity, confidentiality, and availability issues.

    • Vulnerability Rank: Critical

    • Currently Implemented Mitigations:

      • The project relies on DRF’s default permission model (“AllowAny”) when no explicit permission classes are set on endpoints.

    • Missing Mitigations:

      • Implement robust permission classes (e.g. IsAuthenticated or custom logic) on all endpoints that allow data modification.
      • Enforce strict authentication and authorization checks on all modifying endpoints.

    • Preconditions:

      • The application’s endpoints built on ModelViewSet (or JsonApiViewSet without overrides) are deployed publicly without any access control layers.

    • Source Code Analysis:

      • In /code/example/views.py (and the corresponding URL registrations in /code/example/urls.py), viewsets such as BlogViewSet, EntryViewSet, CommentViewSet, and CompanyViewSet expose full CRUD operations without additional restrictions.

    • Security Test Case:

      1. On a publicly deployed instance, identify an endpoint (e.g. /blogs/).
      2. Send a POST request with a valid JSON:API payload to create a new blog resource.
      3. Verify that the resource is created successfully without requiring authentication.
      4. Similarly, send PATCH and DELETE requests to other endpoints and confirm that write operations are accepted.

  • Vulnerability Name: Insecure Object Selection in Featured Entry Endpoints

    • Description: The “featured” entry endpoints in EntryViewSet and DRFEntryViewSet override the standard get_object() method incorrectly. Instead of fetching the record matching the provided primary key, the method uses the URL parameter (named “entry_pk”) to exclude that record and returns the first entry that does not match the given ID.

      • Step‑by-step trigger:
        1. An API client sends a GET request to an endpoint such as /entries/{entry_pk}/ expecting the entry with that specific ID.
        2. The overridden get_object() method executes code that excludes the provided entry_pk and returns the first available entry with a different ID.
        3. The client receives a resource that does not correspond to the requested identifier.

    • Impact: This mis‑selection can lead to unintended data exposure and confusion in API response behavior. If business logic relies on a reliable primary key–based lookup, unauthorized data may be disclosed or object‑specific restrictions bypassed.

    • Vulnerability Rank: High

    • Currently Implemented Mitigations:

      • A comment in the code (“# Handle featured”) suggests that the override was intended for a “featured” use case but is applied unconditionally whenever the “entry_pk” URL parameter is supplied.

    • Missing Mitigations:

      • Correct the object retrieval logic so that when a primary key is specified, the endpoint returns the matching resource.
      • If “featured” entries are needed, serve them via a dedicated endpoint with clear and unambiguous logic.

    • Preconditions:

      • The endpoint is implemented using EntryViewSet or DRFEntryViewSet and the URL includes an “entry_pk” parameter.
      • The endpoint is publicly accessible and no custom logic exists to enforce correct object lookup.

    • Source Code Analysis:

      • In /code/example/views.py, the get_object() method checks for “entry_pk” in self.kwargs and, if present, calls: 
        entry_pk = self.kwargs.get("entry_pk", None)
if entry_pk is not None:
    return Entry.objects.exclude(pk=entry_pk).first()
        This deviates from the standard lookup using Entry.objects.get(pk=entry_pk), inadvertently returning an unrelated resource.

    • Security Test Case:

      1. Deploy an endpoint using EntryViewSet (or DRFEntryViewSet) with a URL pattern that includes an “entry_pk” parameter.
      2. Choose a valid primary key (for example, “5”) and send a GET request to /entries/5/.
      3. Observe that the returned entry does not have ID 5 but is instead the first entry with a different ID.
      4. This confirms the retrieval logic is flawed and does not adhere to the expected RESTful behavior.

  • Vulnerability Name: DEBUG Mode Enabled in Production Exposes Sensitive Debug Information

    • Description: The application’s configuration (in /code/example/settings/dev.py) sets DEBUG = True and is imported by default via /code/example/settings/__init__.py. In production, causing an exception (for example, by requesting an undefined URL) will trigger a detailed Django debug page that displays stack traces, environment variables, and configuration settings—including sensitive information.

      • Step‑by-step trigger:
        1. An attacker accesses a non‑existent endpoint or deliberately triggers an application error.
        2. The application, running with DEBUG = True, returns a detailed error page with stack trace and configuration details.
        3. The attacker examines the response and extracts sensitive internal information.

    • Impact: Exposure of internal state, file paths, configuration details, and potentially sensitive data (such as the SECRET_KEY) may help an attacker map the internal structure of the application and plan further attacks.

    • Vulnerability Rank: Critical

    • Currently Implemented Mitigations:

      • No mitigation is in place—the settings file explicitly sets DEBUG = True.

    • Missing Mitigations:

      • Disable debug mode in production by setting DEBUG = False.
      • Configure a custom exception handler that does not expose detailed debug information.

    • Preconditions:

      • The publicly accessible instance is deployed using the development configuration of settings (i.e. using /code/example/settings/dev.py).

    • Source Code Analysis:

      • In /code/example/settings/dev.py, the line DEBUG = True is explicitly set.
      • Since /code/example/settings/__init__.py imports the development settings, no production‑specific override exists, leaving the application in debug mode even if deployed publicly.

    • Security Test Case:

      1. Deploy the application using the provided settings.
      2. Access a non‑existent or error‑producing endpoint (for example, /nonexistent).
      3. Confirm that the response contains a Django debug page with a full stack trace and internal configuration details such as file paths and environment variables.
      4. Verify that sensitive data (e.g. SECRET_KEY and database configuration) are exposed on the error page.

  • Vulnerability Name: Hardcoded SECRET_KEY in Configuration Allows Forged Signatures

    • Description: The application’s configuration file (/code/example/settings/dev.py) contains a hardcoded secret key value ("abc123"). If an attacker gains knowledge of this secret key—either through accidental code disclosure or via debug error pages—they may use it to forge session cookies or other signed data.

      • Step‑by-step trigger:
        1. An attacker discovers the hardcoded SECRET_KEY by viewing publicly accessible source code or via a debug page triggered by an error.
        2. Using the known SECRET_KEY, the attacker crafts forged session cookies or tampered signed data (such as JSON Web Tokens).
        3. The server, relying on the compromised key for cryptographic signing, accepts the forged data and may allow the attacker to impersonate users or escalate privileges.

    • Impact: The integrity and authenticity of signed data is compromised, which could lead to session hijacking, unauthorized access to user accounts, and bypass of security controls.

    • Vulnerability Rank: Critical

    • Currently Implemented Mitigations:

      • No mitigations are implemented—the SECRET_KEY is statically defined in the development settings.

    • Missing Mitigations:

      • Remove hardcoded secret values from the source code and instead load the SECRET_KEY securely from environment variables or a dedicated secrets management service.

    • Preconditions:

      • The development settings—which include a hardcoded SECRET_KEY—are deployed in the production environment, and the source configuration is either directly accessible or inadvertently exposed (for example, via debug error pages).

    • Source Code Analysis:

      • In /code/example/settings/dev.py, the line SECRET_KEY = "abc123" is hardcoded.
      • Since /code/example/settings/__init__.py imports dev.py by default, this insecure secret key is used in the deployed application.

    • Security Test Case:

      1. Examine the deployed application (or trigger an error page via the DEBUG mode vulnerability) to retrieve the SECRET_KEY value.
      2. Using the known key "abc123", craft a signed session cookie or token that mimics a valid user session.
      3. Send the forged token to any endpoint that requires authenticated access.
      4. Verify that the server accepts the forged token, thereby confirming that the signature can be recreated due to the hardcoded secret.

  • Vulnerability Name: Inadequate validation of sparse fieldset parameters leading to potential information disclosure

    • Description:

      1. An attacker crafts a request to a JSON:API endpoint that supports sparse fieldsets.
      2. The attacker includes the fields[resource_name] query parameter with a value that contains special characters or unexpected field names, potentially not corresponding to actual serializer fields.
      3. The JSONRenderer._filter_sparse_fields method in rest_framework_json_api/renderers.py retrieves this value from request.query_params and splits it by commas without proper validation or sanitization of individual field names.
      4. While the current code iterates through serializer fields and checks for inclusion based on the split sparse_fields, inadequate validation of sparse_fields values could lead to unexpected behavior if a crafted value bypasses intended filtering, potentially exposing more data than intended or causing backend errors.
      5. Although direct injection into field names seems limited by the serializer's field definitions, the lack of validation on the input sparse_fieldset_value itself is a potential vulnerability. It could be exploited if future code changes or specific serializer configurations introduce weaknesses when handling these unfiltered field names.
      • Step-by-step trigger:
        1. An attacker identifies a JSON:API endpoint supporting sparse fieldsets.
        2. The attacker crafts a GET request with the fields[resource_name] query parameter.
        3. The value of this parameter includes invalid field names or special characters.
        4. The server processes the request without validating the fields[resource_name] value.
        5. Although current filtering might prevent immediate data exposure, the lack of validation is a vulnerability that could be exploited in the future.

    • Impact: Potential information disclosure. While the immediate risk might be low due to the current field filtering logic, inadequate validation opens the door for future vulnerabilities or unexpected behavior that could lead to exposing sensitive data if field filtering is bypassed or if backend errors expose information.

    • Vulnerability Rank: High

    • Currently Implemented Mitigations:

      • None: The code retrieves and processes the fields[resource_name] query parameter without any explicit validation of the field names provided.

    • Missing Mitigations:

      • Input validation: Implement robust validation for the fields[resource_name] query parameter to ensure that only valid field names for the given resource are accepted. This validation should occur in JSONRenderer._filter_sparse_fields before splitting and using the field names.
      • Sanitization: Sanitize the input field names to remove any potentially malicious characters or unexpected input.

    • Preconditions:

      • The API endpoint must be using rest_framework_json_api.renderers.JSONRenderer.
      • The API endpoint must support sparse fieldsets.
      • The application must be deployed publicly and accessible to external attackers.

    • Source Code Analysis:

      File: /code/rest_framework_json_api/renderers.py
      @classmethod
def _filter_sparse_fields(cls, serializer, fields, resource_name):
    request = serializer.context.get("request")
    if request:
        sparse_fieldset_query_param = f"fields[{resource_name}]"
        sparse_fieldset_value = request.query_params.get(
            sparse_fieldset_query_param
        )
        if sparse_fieldset_value is not None: # <-- Input from query parameter is used without validation
            sparse_fields = sparse_fieldset_value.split(",") # <-- Input is split by comma without validation
            return {
                field_name: field
                for field_name, field, in fields.items()
                if field.field_name in sparse_fields # <-- Filtering logic based on unvalidated input
                # URL field is not considered a field in JSON:API spec
                # but a link so need to keep it
                or (
                    field.field_name == api_settings.URL_FIELD_NAME
                    and isinstance(field, relations.HyperlinkedIdentityField)
                )
            }

    return fields
      • The _filter_sparse_fields method retrieves the fields[resource_name] query parameter value directly from request.query_params without validation.
      • It then splits this value by commas to create a list of sparse_fields.
      • The code iterates through the serializer's fields and includes a field in the output only if its field.field_name is present in the sparse_fields list or if it's the URL field.
      • The vulnerability lies in the lack of validation of sparse_fieldset_value. An attacker could potentially inject crafted values here. While the current filtering logic might limit immediate exploitation, it's a risky pattern.

    • Security Test Case:

      1. Send a GET request to a JSON:API endpoint that supports sparse fieldsets (e.g., /blogs/).
      2. Include the fields[Blog] query parameter with an invalid or unexpected value, for example: fields[Blog]=name,invalid-field,name.
      3. Observe the response. While in the current implementation it might not directly expose extra data due to the field check against serializer fields, a lack of validation is present.
      4. To enhance the test case for future potential vulnerabilities, try injecting special characters or very long strings in fields[Blog] to observe if it causes any backend errors or unexpected behavior that might indicate a deeper issue related to how unvalidated input is handled. For example: fields[Blog]=name,very-long-field-name-AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.
      5. Examine the server-side logs for any errors or warnings related to processing the crafted fields[Blog] parameter. While a successful exploit might not be immediately apparent due to current filtering, the lack of validation is a vulnerability that should be addressed to prevent future exploits or unexpected behavior arising from input injection.