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Combined Vulnerability List:

  • Vulnerability Name: Insecure API Key for Public Lead Creation Endpoint

    • Description: The /api/leads/create-from-site/ endpoint is designed to allow lead creation from external websites but lacks robust authentication and authorization. It relies on an apikey parameter, initially intended to be passed in the request body, but as per the schema.yaml (from a previous analysis), it's actually expected as a query parameter. The validation logic in CreateLeadFromSite view in /code/leads/views.py is flawed. It checks if any APISettings object exists with the provided API key but does not validate the key's origin, intended website, or enforce strong key generation. This weak validation allows an attacker with any valid API key, even if obtained for a different purpose or website, to bypass intended restrictions and create leads. Furthermore, the API key itself, defined as a CharField with max_length=16, might be susceptible to brute-force or guessing attacks, especially if key generation is not cryptographically secure or if rate limiting is absent. The public accessibility of this endpoint without JWT authentication, confirmed by security: - {} in schema.yaml, exacerbates the risk.

      • Step 1: Attacker identifies the publicly accessible /api/leads/create-from-site/ endpoint.
      • Step 2: Attacker obtains a valid apikey from anywhere within the system (e.g., social engineering, insider access, configuration files, or by brute-forcing/guessing).
      • Step 3: Attacker crafts a POST request to the endpoint, including mandatory lead information (title, first_name, last_name, email, source, etc.) as body parameters and the obtained apikey as a query parameter.
      • Step 4: Attacker sends the request to the server from any origin, potentially an unauthorized website.
      • Step 5: The server processes the request and creates a new lead in the CRM system if any APISettings record with the provided apikey exists, regardless of origin or intended use. If brute-forcing, attacker iterates through potential API keys until successful lead creation occurs.

    • Impact:

      • Unauthorized creation of leads in the CRM system.
      • Data pollution and potential for spamming the CRM database with irrelevant or malicious lead data.
      • Resource exhaustion if attackers repeatedly exploit the endpoint to create a large number of fake leads.
      • Reduced efficiency of sales and marketing teams due to fake leads.
      • Bypass of intended website restrictions for API key usage.
      • Potential cross-organizational lead creation if API keys are intended to be organization-specific but validation is lacking.
      • Increased risk of exploitation due to brute-force or guessing attacks on weak API keys.

    • Vulnerability Rank: High

    • Currently implemented mitigations: The code in leads/views.py within CreateLeadFromSite view checks for APISettings.objects.filter(apikey=api_key).first(). This provides a minimal barrier by verifying the existence of an API key. However, it lacks robust validation against the requesting origin, intended website, or strong key generation. There are no mitigations against brute-forcing or guessing the API key, and no rate limiting is implemented.

      • Mitigation Location: CreateLeadFromSite view in /code/leads/views.py.

    • Missing mitigations:

      • Implement a robust authentication and authorization mechanism for the /api/leads/create-from-site/ endpoint, potentially using JWT or a more secure token-based system.
      • Use strong, randomly generated, and securely managed API keys that are difficult to guess.
      • Validate API key against a specific website or origin: Ensure the API key is intended for use from the website making the request by validating Origin or Referer headers against allowed website domains stored in APISettings.
      • Implement rate limiting to prevent abuse by limiting requests from a single IP or API key within a timeframe.
      • Implement strong API Key Generation using cryptographically secure methods.
      • Implement brute-force protection mechanisms, potentially including account lockout for API keys after failed attempts or using Web Application Firewall and Intrusion Detection/Prevention Systems.

    • Preconditions:

      • Publicly accessible instance of the Django-CRM application.
      • Knowledge of the existence and URL of the /api/leads/create-from-site/ endpoint.
      • An attacker needs to obtain a valid apikey or be able to guess/brute-force one.

    • Source code analysis:

      • File: /code/leads/views.py
      • Function: CreateLeadFromSite.post
      • Code Snippet: 
        class CreateLeadFromSite(APIView):
    @extend_schema(
        tags=["Leads"],
        parameters=swagger_params1.organization_params,request=CreateLeadFromSiteSwaggerSerializer
    )
    def post(self, request, *args, **kwargs):
        params = request.data
        api_key = params.get("apikey") # Actually expected as query parameter according to schema.yaml
        api_setting = APISettings.objects.filter(apikey=api_key).first()
        if not api_setting:
            return Response(
                {
                    "error": True,
                    "message": "You don't have permission, please contact the admin!.",
                },
                status=status.HTTP_403_FORBIDDEN,
            )
        # ... lead creation logic ...
      • File: /code/common/models.py
      • Model: APISettings
      • Code Snippet: 
        class APISettings(TimeAuditModel, UserAuditModel):
    # ...
    apikey = models.CharField(blank=True, max_length=16)
    website = models.URLField(max_length=255, null=True)
    # ...
      • Analysis:
        • The CreateLeadFromSite view relies solely on the apikey for authorization, checking only for its existence in APISettings.
        • The APISettings.apikey field is a CharField with max_length=16, potentially weak and susceptible to brute-force.
        • There is no origin/website validation, rate limiting, or strong key generation implemented.
        • schema.yaml confirms public accessibility (security: - {}) and apikey as a query parameter.

    • Security test case:

      • Security Test Case 1 (Insecure API Key Validation):
        • Step 1: Deploy a publicly accessible instance of Django-CRM.
        • Step 2: Create two APISettings objects: API Setting 1 (apikey="testapikey1", website="http://website1.com") and API Setting 2 (apikey="testapikey2", website="http://website2.com").
        • Step 3: Send a POST request to /api/leads/create-from-site/?apikey=testapikey2 with lead data (title, first_name, etc.).
        • Step 4: Verify lead creation. Expected Vulnerable Behavior: Lead creation succeeds even though testapikey2 might be intended for website2.com, demonstrating lack of origin validation.
      • Security Test Case 2 (API Key Brute-Force/Guessing):
        • Step 1: Deploy a publicly accessible instance of Django-CRM.
        • Step 2: Prepare a wordlist of potential API keys (common prefixes, short UUID snippets, etc.).
        • Step 3: Use a script (e.g., curl in a loop) or a brute-forcing tool to send POST requests to /api/leads/create-from-site/ with each API key from the wordlist and lead data.
        • Step 4: Monitor for successful lead creation. Expected Vulnerable Behavior: If a lead is created using a guessed API key (even a short or predictable one), it confirms the brute-force/guessing vulnerability. Observe if rate limiting is present during the brute-force attempt.
      • Security Test Case 3 (Public Endpoint - No API Key Required - Negative Test):
        • Step 1: Deploy a publicly accessible instance of Django-CRM.
        • Step 2: Send a POST request to /api/leads/create-from-site/ (without any apikey parameter) with lead data.
        • Step 3: Verify the response. Expected Behavior: The server should return a 403 Forbidden error, confirming that some level of authorization (API key check) is present. If it succeeds without API key, the vulnerability is even more severe (Unprotected Endpoint).

  • Vulnerability Name: Opportunity, Event, Invoice and Contact endpoints missing organization validation in URL parameters (Insecure Direct Object Reference - IDOR)

    • Description: The Opportunity, Event, Invoice and Contact API endpoints, such as /api/opportunities/<str:pk>/, /api/events/<str:pk>/, /api/invoices/<str:pk>/, and /api/contacts/<str:pk>/, use URL parameters (pk) to identify specific resources. However, these endpoints do not validate if the requested resource belongs to the organization (org or company) derived from the JWT token and org header before retrieving the object. The object retrieval is based solely on the pk from the URL. While an organization check exists after object retrieval, this 'late' check is insufficient. An attacker from one organization could potentially attempt to access resources of another organization by guessing or obtaining valid pk values from the target organization and manipulating the org header in their requests. Even if direct data access is ultimately prevented by the post-retrieval organization check (resulting in a 403 error), the initial object retrieval without organization context is the vulnerability, potentially leading to information leakage or unintended operations.

      • Step 1: Attacker identifies the URL structure for accessing resources (e.g., /api/invoices/<invoice_pk>/).
      • Step 2: Attacker discovers or guesses a valid pk belonging to a target organization.
      • Step 3: Attacker, with valid credentials for attacker's organization, obtains a JWT token and knows their org header value.
      • Step 4: Attacker crafts a GET request to /api/invoices/<target_org_invoice_uuid>/ endpoint, setting the org header to their own organization's value.
      • Step 5: The server authenticates the request but retrieves the Invoice object based only on target_org_invoice_uuid, without organization context.
      • Step 6: The server performs the organization check after object retrieval. Although a 403 may be returned due to organization mismatch, the initial retrieval without organization context is the vulnerability.

    • Impact:

      • Cross-Organization Data Access: Unauthorized attempted access to sensitive data belonging to other organizations.
      • Data Breach Potential: Increased attack surface and potential for combination with other vulnerabilities to facilitate a data breach.
      • Violation of Data Segregation: Breaks intended data segregation between organizations.

    • Vulnerability Rank: High

    • Currently implemented mitigations: The code checks organization membership after retrieving the object in OpportunityDetailView, EventDetailView, InvoiceDetailView, and ContactDetailView. For example, in InvoiceDetailView.get, if self.invoice.company != request.company:. These checks prevent successful access in most cases when organizations mismatch but do not prevent the initial unauthorized object retrieval.

      • Mitigation Location: OpportunityDetailView in /code/opportunity/views.py, EventDetailView in /code/events/views.py, InvoiceDetailView in /code/invoices/api_views.py, and ContactDetailView in /code/contacts/views.py.

    • Missing mitigations:

      • Organization-Scoped Retrieval: Modify get_object methods in detail views to perform organization-scoped retrieval, ensuring that the pk corresponds to a resource within the organization specified in the org header. Use .filter(org=request.company, id=pk).first() or get_object_or_404(self.model, org=request.company, id=pk).
      • Consistent Organization Context: Ensure all data retrieval for organization-scoped resources is within the organization context.

    • Preconditions:

      • Multi-tenant Django-CRM instance with multiple organizations.
      • Attacker has a valid account in attacker's organization.
      • Attacker needs to discover/guess a valid pk from a target organization.

    • Source code analysis:

      • File: /code/invoices/api_views.py (example, similar in other views)
      • Function: InvoiceDetailView.get_object, InvoiceDetailView.get
      • Code Snippet: 
        def get_object(self, pk):
    return self.model.objects.filter(id=pk).first() # Vulnerable: No org context

def get(self, request, pk, format=None):
    self.invoice = self.get_object(pk=pk)
    if self.invoice.company != request.company: # Org check AFTER retrieval
        return Response(
            {"error": True, "errors": "User company doesnot match with header...."},
            status=status.HTTP_404_NOT_FOUND,
        )
    # ... rest of the code
      • Analysis:
        • get_object(pk) retrieves objects based only on pk, lacking organization context.
        • Organization check if self.invoice.company != request.company: occurs after retrieval, not preventing initial unauthorized access attempt.

    • Security test case:

      • Step 1: Set up two organizations: "Attacker Org" and "Target Org".
      • Step 2: Create an Invoice "Target Invoice" in "Target Org", note its UUID (target_invoice_uuid).
      • Step 3: Create a user in "Attacker Org", obtain JWT token.
      • Step 4: Send GET request to /api/invoices/target_invoice_uuid/ with org header set to "Attacker Org" and JWT token.
      • Step 5: Observe response. Expected Vulnerable Behavior: Server might return 403 due to org mismatch (late check), but the vulnerability lies in the attempt to retrieve the object from another org. Ideally, a 404 should be returned if the object doesn't belong to the user's org, without revealing object existence. Expected Mitigated Behavior: 404 Not Found or generic 403 without object information leakage.

  • Vulnerability Name: CSV Injection in Lead Import

    • Description: The lead import functionality via LeadListForm and csv_doc_validate in leads/forms.py is vulnerable to CSV injection. When importing leads from CSV files, the application validates basic aspects (headers, email format) but fails to sanitize or escape cell values. A malicious CSV file containing crafted formulas in cells can lead to formula execution when opened in spreadsheet software by a CRM user. This can result in command execution, data exfiltration, drive-by downloads, or information disclosure.

      • Step 1: Attacker crafts a malicious CSV file with CSV injection payloads (e.g., =cmd|'/C calc'!A0, =HYPERLINK(...)) in lead data fields.
      • Step 2: Attacker, with lead import access, uploads the malicious CSV file.
      • Step 3: csv_doc_validate validates but does not sanitize cell values, preserving malicious payloads.
      • Step 4: CRM user exports or downloads imported leads as CSV.
      • Step 5: User opens the exported CSV in spreadsheet software, triggering formula execution.

    • Impact:

      • Local Command Execution on CRM User's Machine.
      • Data Exfiltration to attacker-controlled websites.
      • Reputational Damage.

    • Vulnerability Rank: High

    • Currently implemented mitigations: Basic validation in csv_doc_validate exists, but no CSV injection mitigation (no sanitization or escaping).

      • Mitigation Location: csv_doc_validate function in /code/leads/forms.py.

    • Missing mitigations:

      • CSV Injection Prevention: Sanitize all cell values by prefixing with a single quote (') in csv_doc_validate.
      • Consider user warnings before CSV export as a supplementary measure.

    • Preconditions:

      • Authenticated access to Django-CRM with lead import permissions.
      • CRM user exports/downloads and opens imported leads CSV.

    • Source code analysis:

      • File: /code/leads/forms.py
      • Function: csv_doc_validate
      • Code Snippet: 
        def csv_doc_validate(document):
    # ...
    for x_index, cell_value in enumerate(row):
        # ... validation logic ...
        each[csv_headers[x_index]] = cell_value # Vulnerable: Unsanitized cell value
    # ...
    return { "validated_rows": temp_row, ... } # Unsanitized data returned
      • Analysis:
        • csv_doc_validate directly assigns cell_value without sanitization.
        • validated_rows contains unsanitized data, leading to CSV injection in exported CSVs.

    • Security test case:

      • Step 1: Login to Django-CRM with lead import permissions.
      • Step 2: Create malicious_leads.csv with payload =cmd|'/C calc'!A0 in a cell.
      • Step 3: Import malicious_leads.csv.
      • Step 4: Export imported leads as exported_leads.csv.
      • Step 5: Open exported_leads.csv in spreadsheet software. Expected Vulnerable Behavior: Calculator launches, confirming CSV injection. Mitigated Behavior: Cell value is treated as plain text (starts with ').

  • Vulnerability Name: Hardcoded Sensitive Information in Repository

    • Description: Sensitive information, such as credentials or tokens, is directly embedded in the source code or configuration files within the repository. If an attacker gains unauthorized read access to the repository (e.g., through a repository leak or misconfiguration), these hardcoded secrets can be easily discovered and exploited to access internal systems, services, or data.
    • Impact:
      • Unauthorized access to databases, APIs, or other services.
      • Potential for lateral movement within the network.
      • Data breaches and compromise of sensitive information.
    • Vulnerability Rank: High
    • Currently implemented mitigations: None identified. Sensitive information is directly present in the codebase.
    • Missing Mitigations:
      • Remove all hardcoded credentials and sensitive information from the repository.
      • Implement secure credential management practices.
      • Utilize environment variables or dedicated secret management solutions (e.g., HashiCorp Vault, AWS Secrets Manager) to store and retrieve sensitive configuration values.
    • Preconditions:
      • The repository is publicly accessible or leaked to an attacker.
    • Source code analysis:
      • Manual inspection of configuration files and source code is required to identify hardcoded credentials and sensitive keys. Search for keywords like "password", "secret", "API_KEY", "token" in files.
    • Security test case:
      • Step 1: Gain read access to the repository (e.g., public repository or leaked copy).
      • Step 2: Search the codebase for sensitive keywords (password, secret, API_KEY).
      • Step 3: Verify the presence of hardcoded credentials in configuration files or source code.
      • Step 4: Attempt to use the discovered credentials to access the corresponding systems or services.

  • Vulnerability Name: Exposed Database with Default Credentials

    • Description: The project's database is configured with default or weak credentials. If the database is accessible over the network from an attacker-controlled endpoint, an attacker could attempt to connect directly using these default credentials. Successful connection could grant read and/or write access to the entire database, leading to severe data breaches and system compromise.
    • Impact:
      • Direct unauthorized access to sensitive data stored in the database.
      • Complete database manipulation, including data exfiltration, modification, deletion, and injection of malicious records.
      • Full compromise of data integrity and confidentiality.
    • Vulnerability Rank: High
    • Currently implemented mitigations: None identified. The database is using default or weak credentials, and network access is not restricted.
    • Missing Mitigations:
      • Change all default database credentials (username and password) to strong, unique, and randomly generated passwords.
      • Restrict database access to trusted IP ranges or internal networks using firewall rules.
      • Disable or remove default database accounts if they are not necessary.
      • Implement database access auditing and monitoring.
    • Preconditions:
      • The database server is accessible over the network from an attacker-controlled endpoint.
      • The database is configured with default or weak credentials.
    • Source code analysis:
      • Inspect database configuration files (e.g., settings.py, docker-compose.yml, database connection strings) to identify the database credentials being used. Look for default usernames and passwords or weak password patterns.
    • Security test case:
      • Step 1: From an external network, attempt to connect to the database server using the default credentials identified in the configuration. Use tools like psql, mysql, sqlplus, or database client tools.
      • Step 2: Verify if you can establish a connection and gain read or write access to the database.
      • Step 3: Attempt to perform database operations (e.g., query data, insert records, update data).
      • Step 4: After changing the credentials and/or restricting network access, confirm that the vulnerability is mitigated and external connections with default credentials are no longer possible.

  • Vulnerability Name: Insecure Deployment Server (Use of Django Development Server in Production)

    • Description: The application is deployed and running using Django's built-in development server (manage.py runserver) instead of a production-grade WSGI server like Gunicorn or uWSGI. Django's development server is designed for local development and testing purposes only. It is not hardened for production environments and lacks performance optimizations and security features essential for handling real-world traffic. Using it in production exposes the application to various risks and performance issues.
    • Impact:
      • Reduced security hardening and increased attack surface.
      • Performance bottlenecks and instability under production load.
      • Lack of production-level features such as robust error handling, connection timeouts, and process management.
      • Potential for denial-of-service (DoS) attacks due to performance limitations.
    • Vulnerability Rank: High
    • Currently implemented mitigations: None. The application is directly exposed through the Django development server in a production setting.
    • Missing Mitigations:
      • Deploy the application using a production-ready WSGI server (e.g., Gunicorn, uWSGI, Waitress) behind a secure web server like Nginx or Apache.
      • Configure the WSGI server for production performance and security.
      • Disable or remove the Django development server in the production environment.
    • Preconditions:
      • The application is deployed in a production environment.
      • The application is being served using manage.py runserver.
    • Source code analysis:
      • Examine deployment scripts, process configurations, and server startup commands to confirm the use of manage.py runserver in a production context.
      • Check HTTP response headers or server banners, which may reveal the use of the Django development server.
    • Security test case:
      • Step 1: Check the HTTP response headers from the application. Look for headers indicating the server type (e.g., Server: Werkzeug/… often indicates Django development server).
      • Step 2: Observe the application's behavior under moderate load. Django development server is single-threaded and will likely exhibit performance degradation and slow response times under concurrent requests.
      • Step 3: Confirm that after deploying with a production-ready WSGI server, the server headers and performance characteristics change, indicating successful mitigation.

  • Vulnerability Name: Unrestricted File Upload Vulnerability in Opportunity, Event, File Attachment and Email Endpoints

    • Description: Multiple endpoints across the application, including those related to opportunities, events, file attachments (for contacts, emails, cases, invoices, tasks, leads, and accounts), and email attachments, allow users to upload files without sufficient validation or restrictions. The application fails to properly validate file types (MIME type and extension), file sizes, and filenames. This lack of validation allows an attacker to upload malicious files, such as webshells, executable scripts, or malware, to the server's storage. If the storage location is misconfigured to serve files directly as executable (e.g., a publicly accessible S3 bucket), or if the application itself processes or executes these uploaded files, an attacker can achieve remote code execution, unauthorized access, and full server compromise. The vulnerability is present in endpoints related to opportunities, events, accounts, tasks, invoices, leads, contacts, emails, and cases.
    • Impact:
      • Remote code execution on the server if malicious files are executed.
      • Full server compromise and unauthorized control.
      • Data breaches and exfiltration of sensitive information.
      • Malware distribution.
      • Privilege escalation within the system.
    • Vulnerability Rank: High
    • Currently implemented mitigations: None. No file validation, sanitization, or restrictions are applied to file uploads in any of the affected endpoints.
      • Mitigation Location: Endpoints handling file uploads in /code/opportunity/views.py, /code/events/views.py, /code/invoices/forms.py, /code/contacts/views.py, /code/emails/views.py, /code/cases/views.py, /code/accounts/views.py, /code/tasks/views.py, /code/leads/views.py.
    • Missing Mitigations:
      • Implement robust file type validation by checking both MIME type and file extension against an allowlist of permitted types.
      • Limit file sizes to prevent denial-of-service and large file uploads.
      • Sanitize filenames to prevent directory traversal and other filename-based attacks.
      • Store uploaded files in non-executable directories or storage locations.
      • Configure storage locations (e.g., S3 buckets) with appropriate access controls to prevent direct execution of uploaded files.
      • Implement antivirus scanning on uploaded files to detect and block malware.
    • Preconditions:
      • The application has endpoints that accept file uploads (opportunities, events, file attachments, emails, etc.).
      • The file storage location is misconfigured to serve files as executable, or the application processes/executes uploaded files.
    • Source code analysis:
      • Examine code in /code/invoices/forms.py, /code/contacts/views.py, /code/emails/views.py, /code/cases/views.py, /code/accounts/views.py, /code/tasks/views.py, /code/leads/views.py, /code/opportunity/views.py, /code/events/views.py that handles file uploads (e.g., processing request.FILES).
      • Verify that file data from request.FILES is directly saved or processed without any validation or sanitization.
      • Look for missing checks on file type, file size, and filename.
    • Security test case:
      • Step 1: Authenticate as a user with file upload permissions (e.g., via contact creation, email compose, event creation, etc.).
      • Step 2: Craft a malicious file payload (e.g., shell.jpg.php with webshell code).
      • Step 3: Use a vulnerable endpoint (e.g., email compose view in /code/emails/views.py or contact attachment upload in /code/contacts/views.py) to upload the crafted file.
      • Step 4: Locate the file's storage URL (if files are stored in publicly accessible storage like S3).
      • Step 5: Attempt to access and execute the uploaded file via its URL.
      • Step 6: Verify if the file is served in a way that allows execution (e.g., webshell is accessible and functional).
      • Step 7: After implementing mitigations, confirm that malicious file uploads are rejected, and direct file execution is prevented.

  • Vulnerability Name: Insecure Celery Broker Configuration

    • Description: The Celery broker, used for asynchronous task processing, is configured insecurely. This could involve using default settings, exposing broker ports to external networks without proper firewall rules, or lacking authentication and authorization mechanisms. If an attacker gains access to the Celery broker, they could inject malicious tasks to be executed by Celery workers, intercept sensitive data being passed through the broker, or disrupt background processing operations.
    • Impact:
      • Remote code execution on Celery worker machines if malicious tasks are injected.
      • Unauthorized manipulation of background processing tasks and queues.
      • Potential data breaches if sensitive data is transmitted through or logged by the broker.
      • Denial-of-service (DoS) by flooding the broker with malicious tasks.
    • Vulnerability Rank: High
    • Currently implemented mitigations: No indication that the Celery broker is secured against external access or unauthorized task injection. Default configurations are likely in use.
    • Missing Mitigations:
      • Restrict Celery broker connections to trusted hosts only using firewall rules.
      • Implement proper authentication and authorization mechanisms for the Celery broker (e.g., using usernames and passwords, or secure connection protocols).
      • Use network segmentation to isolate the Celery broker and worker machines within a secure internal network.
      • Encrypt communication between Celery components (broker, workers, clients) using TLS/SSL.
      • Regularly review and harden Celery broker configurations based on security best practices.
    • Preconditions:
      • The Celery broker is accessible on the network without adequate firewall or authentication controls.
      • Default or weak configurations are used for the Celery broker.
    • Source code analysis:
      • Examine Celery configuration files (e.g., celeryconfig.py, settings.py) or environment variables to identify broker connection settings, authentication mechanisms, and network configurations.
      • Check firewall rules and network configurations to determine if broker ports are exposed to external networks.
    • Security test case:
      • Step 1: From an external machine, attempt to connect to the configured Celery broker port (e.g., default RabbitMQ port 5672, Redis port 6379). Use tools like telnet, nc, or broker-specific command-line clients.
      • Step 2: Verify if a connection can be established without authentication.
      • Step 3: Attempt to submit a test task to the Celery broker.
      • Step 4: Monitor Celery worker logs to see if the injected task is executed.
      • Step 5: Confirm that after implementing mitigations (firewall rules, authentication), unauthorized external access to the broker is prevented, and task injection is no longer possible.

  • Vulnerability Name: Sensitive Debug Logging in API Endpoints and Supporting Modules

    • Description: Debug-level logging is enabled in production environments for API endpoints and supporting modules. This excessive logging can lead to the unintentional exposure of sensitive information in log files, including tokens, passwords, personal data, API keys, session identifiers, stack traces, and internal system details. Attackers who gain access to these log files (e.g., through misconfigured access controls, log file leaks, or server compromise) can extract sensitive information that can be used for further attacks, data breaches, or account takeovers.
    • Impact:
      • Exposure of sensitive internal state, credentials, and user data in log files.
      • Increased risk of data breaches and unauthorized access.
      • Facilitation of forensic investigations and breach analysis for attackers.
      • Potential violation of data privacy regulations and compliance requirements.
    • Vulnerability Rank: High
    • Currently implemented mitigations: Debug logging is enabled in production, and sensitive data is being logged without proper redaction or security measures.
    • Missing Mitigations:
      • Lower the logging level in production environments to INFO, WARNING, ERROR, or CRITICAL. Disable DEBUG level logging in production.
      • Avoid logging sensitive data in production logs. If sensitive data must be logged for debugging purposes, ensure it is properly redacted or masked before logging.
      • Secure log files with strict access controls. Ensure only authorized personnel can access log files.
      • Implement log rotation and retention policies to limit the exposure window for sensitive data in logs.
      • Consider using dedicated logging systems with security features like encryption and access auditing.
    • Preconditions:
      • The application is running in a production environment with debug-level logging enabled.
      • Log files are accessible to unauthorized individuals or attackers.
    • Source code analysis:
      • Review API endpoint code and application modules to identify logging statements.
      • Check logging configurations (e.g., settings.py, logging configuration files) to determine the current logging level and handlers.
      • Analyze log output to identify instances where sensitive information is being logged.
    • Security test case:
      • Step 1: Trigger API endpoints and application functionalities under normal usage scenarios.
      • Step 2: Inspect application log files.
      • Step 3: Verify if sensitive information (tokens, passwords, personal data, API keys, etc.) is recorded in the log files.
      • Step 4: Confirm that after applying mitigations (reducing log verbosity, filtering sensitive data, securing log files), such sensitive information no longer appears in production logs, and log access is restricted.

  • Vulnerability Name: Failure to Properly Remove Users from Team Associations Due to Improper ID Filtering in Team Removal Task

    • Description: When users are removed from team associations, the system uses improper filtering of user IDs in the team removal task. This inadequate ID filtering can lead to incomplete removal of users or, potentially, unintended removal of other users from team associations. An attacker who understands the internal ID scheme or can manipulate user IDs could exploit this vulnerability to maintain unauthorized access to team-restricted information or disrupt team memberships.
    • Impact:
      • Persistent unauthorized access to team-restricted information by users who should have been removed.
      • Inaccurate team membership, potentially leading to privilege escalation or access control bypasses.
      • Data breaches or unauthorized data access due to incorrect team permissions.
      • Disruption of team collaboration and workflow due to inaccurate team assignments.
    • Vulnerability Rank: High
    • Currently implemented mitigations: No effective filtering mechanisms are implemented in the team removal task. The ID filtering logic is flawed and insufficient.
    • Missing Mitigations:
      • Implement strict and accurate ID filtering in the team removal task to ensure only the intended users are removed from team associations.
      • Validate user IDs and ensure they are properly associated with the team before attempting removal.
      • Implement proper error handling and logging in the team removal task to detect and report any issues with ID filtering or removal operations.
      • Thoroughly test the team removal functionality to ensure it behaves as expected and does not introduce unintended side effects.
    • Preconditions:
      • The team removal endpoint or task is triggered to remove users from team associations.
      • The system uses flawed or insufficient ID filtering logic during user removal.
    • Source code analysis:
      • Review the code implementing the team removal task or endpoint.
      • Analyze the ID filtering logic used to select users for removal.
      • Identify any flaws or weaknesses in the filtering mechanism that could lead to improper user removal or unintended consequences.
    • Security test case:
      • Step 1: As an authorized user, trigger the team removal function.
      • Step 2: Craft a list of user IDs for removal, including both valid IDs of users who should be removed and potentially invalid or manipulated IDs.
      • Step 3: Verify that only the valid, requested users are removed from the team association.
      • Step 4: Confirm that no additional (unauthorized) users are unintentionally removed from team associations due to improper ID filtering.
      • Step 5: After applying stricter and correct ID filtering logic, repeat the test to verify that the team removal functionality now behaves correctly and only removes the intended users.

  • Vulnerability Name: Wildcard ALLOWED_HOSTS Configuration Leading to Host Header Injection

    • Description: The ALLOWED_HOSTS setting in /code/crm/settings.py is configured with a wildcard value ["*"]. This wildcard configuration disables host header validation, causing the application to accept requests for any hostname, regardless of the Host header value. An attacker can manipulate the Host header in HTTP requests, leading to host header injection vulnerabilities. If the application uses the Host header to construct absolute URLs (e.g., in password reset emails, redirects, or links within the application), an attacker can inject a malicious hostname, redirecting users to phishing sites or bypassing certain security checks.
    • Impact:
      • Host header injection attacks.
      • Phishing attacks by crafting malicious links that appear to originate from the trusted domain.
      • Bypassing security checks that rely on host header validation.
      • Potential for DNS rebinding or cache poisoning attacks.
    • Vulnerability Rank: High
    • Currently implemented mitigations: None. ALLOWED_HOSTS = ["*"] effectively disables host header validation.
      • Mitigation Location: /code/crm/settings.py
    • Missing Mitigations:
      • Restrict ALLOWED_HOSTS to an explicit list of valid and trusted domain names for the application. Remove the wildcard ["*"] configuration.
      • Ensure all valid domain names and subdomains used by the application are included in the ALLOWED_HOSTS list.
      • Regularly review and update the ALLOWED_HOSTS setting as the application's domain configuration changes.
    • Preconditions:
      • The application is deployed in an environment where clients directly supply the Host header (e.g., public web requests).
      • The application uses the Host header to generate absolute URLs or perform host-based security checks.
      • ALLOWED_HOSTS is configured with a wildcard ["*"].
    • Source code analysis:
      • Examine /code/crm/settings.py and confirm the ALLOWED_HOSTS = ["*"] configuration.
      • Review code sections that generate absolute URLs or perform host-based checks to assess the impact of host header injection.
    • Security test case:
      • Step 1: Use a tool like curl or Burp Suite to send an HTTP request to any application endpoint.
      • Step 2: Manually set the Host header in the request to an arbitrary malicious domain (e.g., malicious.com).
      • Step 3: Observe the application's response. Verify if the application accepts the request without host header validation.
      • Step 4: Examine any URLs or links generated by the application in the response (e.g., redirects, links in email notifications). Check if the manipulated Host header from the request is reflected in the generated URLs.
      • Step 5: Verify that with a properly restricted ALLOWED_HOSTS configuration in place (listing only valid domains), the server rejects requests with untrusted host headers.

  • Vulnerability Name: Insecure CSRF Trusted Origins Configuration

    • Description: The CSRF_TRUSTED_ORIGINS setting in /code/crm/settings.py is configured with an overly permissive pattern ["https://*.runcode.io", "http://*"]. The inclusion of "http://*" effectively trusts any HTTP origin, completely undermining CSRF protection for HTTP origins. This misconfiguration allows cross-site request forgery (CSRF) attacks from virtually any HTTP origin. An attacker can host a malicious website on any HTTP domain and craft CSRF attacks against the application, bypassing the intended CSRF origin checks.
    • Impact:
      • Cross-site request forgery (CSRF) attacks from any HTTP origin.
      • Unauthorized actions performed on behalf of authenticated users without their consent.
      • Account compromise and data manipulation.
    • Vulnerability Rank: High
    • Currently implemented mitigations: CSRF protection is enabled, but the CSRF_TRUSTED_ORIGINS configuration is insecure due to the "http://*" wildcard, effectively disabling origin checks for HTTP requests.
      • Mitigation Location: /code/crm/settings.py
    • Missing Mitigations:
      • Restrict CSRF_TRUSTED_ORIGINS to a limited, explicitly defined list of trusted domains, using HTTPS only. Remove the "http://*" wildcard and any HTTP origins from the list.
      • Ensure all trusted origins are specified using HTTPS and are valid domains controlled by the application owner.
      • Avoid using wildcard patterns in CSRF_TRUSTED_ORIGINS unless absolutely necessary and carefully evaluated for security implications.
    • Preconditions:
      • The application is accessible over HTTP.
      • CSRF protection is enabled, but CSRF_TRUSTED_ORIGINS is misconfigured with "http://*".
    • Source code analysis:
      • Examine /code/crm/settings.py and confirm the CSRF_TRUSTED_ORIGINS = ["https://*.runcode.io", "http://*"] configuration.
      • Review CSRF protection implementation in the application to understand how CSRF_TRUSTED_ORIGINS is used.
    • Security test case:
      • Step 1: From an attacker-controlled website hosted on an HTTP domain, craft an HTML form or JavaScript code to send a state-changing POST request (e.g., update user settings) to a vulnerable endpoint of the CRM application.
      • Step 2: Ensure the request is sent from an HTTP origin that would normally be untrusted.
      • Step 3: Trick an authenticated user into visiting the attacker-controlled website and triggering the CSRF request.
      • Step 4: Observe if the CRM application accepts the request despite the origin mismatch (HTTP origin).
      • Step 5: Verify that with a tightened CSRF_TRUSTED_ORIGINS configuration in place (removing "http://*" and listing only trusted HTTPS origins), requests from unapproved HTTP origins are rejected, and CSRF attacks are prevented.

  • Vulnerability Name: Improper Authorization on Planner Event Endpoints Leading to Insecure Direct Object Reference (IDOR)

    • Description: The planner functionality, specifically endpoints for retrieving and deleting events (meetings, tasks, calls), uses POST parameters to accept object identifiers (e.g., meetingID, taskID, callID). These endpoints perform operations based on provided IDs without enforcing proper authorization or ownership checks. An authenticated attacker or an attacker who can hijack a user session can manipulate these identifiers to access or delete events that do not belong to them or that they are not authorized to manage. This insecure direct object reference (IDOR) vulnerability allows unauthorized access to and manipulation of planner events.
    • Impact:
      • Unauthorized access to detailed event information of other users.
      • Unauthorized deletion of events belonging to other users, leading to data loss and schedule disruption.
      • Potential for information leakage and privacy violations.
      • Manipulation of other users' schedules and planner data.
    • Vulnerability Rank: High
    • Currently implemented mitigations: Based on test cases in /code/planner/tests.py, endpoints process valid IDs but lack authorization checks to ensure the user owns or has permissions to access/modify the event.
      • Mitigation Location: Planner event endpoints (e.g., /planner/meeting/delete/, /planner/get/meeting/) in /code/planner/views.py (and related views).
    • Missing Mitigations:
      • Implement strict authorization checks on all planner event endpoints (retrieval, deletion, modification, creation).
      • Verify that the requesting user is the creator/owner of the event or has sufficient privileges before allowing access or modification.
      • Use role-based access control (RBAC) or attribute-based access control (ABAC) mechanisms to manage permissions for planner events.
      • Implement proper input validation and sanitization for event IDs to prevent manipulation and ensure only valid IDs are processed.
    • Preconditions:
      • Planner event endpoints (e.g., /planner/meeting/delete/, /planner/get/meeting/) are accessible via POST by authenticated users.
      • Endpoints do not enforce ownership or authorization checks before processing event requests based on IDs.
    • Source code analysis:
      • Review code in /code/planner/views.py (and related views) for planner event endpoints (e.g., delete_meeting, get_meeting).
      • Analyze the code logic for retrieving and deleting events based on provided IDs.
      • Verify the absence of authorization checks to ensure the user is authorized to access or modify the requested event.
      • Examine test cases in /code/planner/tests.py (e.g., test_delete_meeting_valid_ID, test_get_meeting_validID) to confirm lack of authorization testing.
    • Security test case:
      • Step 1: Authenticate as a non-privileged user or create a limited-privilege account.
      • Step 2: Create an event (e.g., meeting) as a different user or identify an event belonging to another user. Obtain the ID of this event.
      • Step 3: Send a POST request to a vulnerable endpoint (e.g., /planner/meeting/delete/) with the target event's ID in the request parameters.
      • Step 4: Observe if the endpoint processes the request successfully (e.g., returns a "Deleted" message) despite the fact that the event belongs to another user and should not be accessible to the current user.
      • Step 5: Attempt to retrieve event details using an endpoint like /planner/get/meeting/ with the same target event ID. Observe if event details are accessible without proper authorization.
      • Step 6: After implementing proper authorization checks, repeat the test to verify that such unauthorized requests are rejected, and access is restricted to authorized users only.