threat-modeling.md

Threat Model Analysis for encode/django-rest-framework

Threat: Mass Assignment Vulnerability

• Description: An attacker crafts an API request with unexpected fields. Due to misconfigured serializers, these fields are processed, leading to unintended data modifications, potentially escalating privileges or compromising sensitive information. The attacker exploits overly permissive serializers to directly manipulate data.
• Impact: Data integrity compromise, unauthorized privilege escalation, potential account takeover.
• DRF Component Affected: Serializers (field definitions, fields/exclude attributes).
• Risk Severity: High
• Mitigation Strategies:
  • Explicitly define fields or exclude in serializers to strictly control writable fields.
  • Utilize read_only_fields for fields that should not be modified via API requests.
  • Implement custom validation within serializers to enforce stricter input data constraints.
  • Regularly audit serializer definitions to ensure they align with intended data access and modification policies.

Threat: Incorrect Data Type Handling

• Description: An attacker sends API requests with unexpected data types that are not strictly validated by serializers or view logic. This can lead to application errors, security bypasses, or data corruption if the application logic incorrectly handles or assumes specific data types. The attacker leverages loose data type validation to inject unexpected data, potentially leading to critical vulnerabilities depending on application logic.
• Impact: Application errors, potential security bypasses, data corruption, in critical scenarios, privilege escalation or remote code execution if type confusion vulnerabilities exist in application logic.
• DRF Component Affected: Serializers (field type definitions and validation), Views (data processing logic).
• Risk Severity: High
• Mitigation Strategies:
  • Utilize DRF's serializer field types effectively for built-in type validation.
  • Implement robust custom validation in serializers to enforce specific data type requirements and formats beyond basic types.
  • Sanitize and rigorously validate deserialized data within view functions before any further processing or database interaction.
  • Employ type hinting and static analysis tools to proactively identify potential type-related vulnerabilities.

Threat: Deserialization of Untrusted Data Formats

• Description: An attacker sends API requests in data formats like XML or YAML, processed by DRF using deserialization libraries. Vulnerabilities in these libraries can be exploited by malicious payloads, potentially leading to remote code execution (RCE) or denial of service (DoS). The attacker leverages vulnerabilities in data format parsing libraries used by DRF.
• Impact: Remote code execution, denial of service, information disclosure, complete system compromise in RCE scenarios.
• DRF Component Affected: Parsers (format handling), underlying deserialization libraries (e.g., PyYAML, defusedxml).
• Risk Severity: Critical
• Mitigation Strategies:
  • Minimize the number of supported data formats. Only enable parsers for formats absolutely necessary.
  • Ensure deserialization libraries used by DRF and custom parsers are consistently updated to the latest versions, patched against known vulnerabilities.
  • Consider safer, less complex data formats if possible.
  • Implement robust input validation after deserialization to detect and neutralize malicious payloads that might bypass initial parsing.

Threat: Insecure Default Authentication Schemes

• Description: Developers rely on DRF's default authentication schemes like SessionAuthentication over HTTP or BasicAuthentication in production. Attackers can intercept credentials or session cookies transmitted over insecure channels (HTTP), gaining unauthorized access to accounts and sensitive data. The attacker exploits weak or unencrypted authentication methods to steal credentials.
• Impact: Account compromise, unauthorized access to sensitive data and functionality, potential data breaches, full account takeover.
• DRF Component Affected: Authentication (default authentication classes).
• Risk Severity: High
• Mitigation Strategies:
  • Mandatory use of HTTPS in production to encrypt all communication and protect credentials in transit.
  • Choose and enforce secure authentication schemes appropriate for the application's security requirements, such as TokenAuthentication, OAuth 2.0, or JWT.
  • Avoid using BasicAuthentication in production unless absolutely necessary and strictly over HTTPS.
  • Configure DRF to strictly enforce HTTPS for all API endpoints.

Threat: Insufficient Permission Checks in Views

• Description: Developers neglect to apply or incorrectly implement permission classes in DRF views. Attackers can bypass intended access controls, accessing API endpoints and performing actions they are not authorized to, potentially leading to data breaches or unauthorized modifications. The attacker exploits missing or weak authorization checks to gain unauthorized access.
• Impact: Unauthorized access to data and functionality, data breaches, privilege escalation, unauthorized data modification or deletion.
• DRF Component Affected: Views (permission classes and application).
• Risk Severity: High
• Mitigation Strategies:
  • Always explicitly define and apply appropriate permission_classes in every DRF view.
  • Utilize built-in DRF permission classes or develop robust custom permission classes to strictly enforce access control policies.
  • Conduct thorough testing of permission configurations to guarantee they function as intended and prevent unauthorized access.
  • Implement regular security audits to proactively identify and rectify any missing or misconfigured permission checks across all API endpoints.

Threat: Logic Flaws in Custom Permission Classes

• Description: Custom permission classes, designed for complex authorization logic, contain implementation errors. Attackers can exploit these flaws to bypass intended access controls, gaining unauthorized access or overly permissive access to resources. The attacker finds and exploits vulnerabilities in custom authorization logic to bypass access controls.
• Impact: Unauthorized access, privilege escalation, data breaches, potential for complete bypass of intended security model.
• DRF Component Affected: Permissions (custom permission classes).
• Risk Severity: High
• Mitigation Strategies:
  • Develop comprehensive unit tests for all custom permission classes to rigorously verify their logic and ensure correct authorization behavior under various conditions.
  • Conduct thorough code reviews of custom permission classes, involving multiple developers, to identify potential logic flaws and edge cases.
  • Strive to keep custom permission logic as simple, clear, and auditable as possible to minimize the risk of introducing errors.
  • Where feasible, leverage existing, well-tested permission libraries or established authorization patterns to reduce the complexity and potential for vulnerabilities in custom implementations.

Threat: Overly Permissive Default Permissions

• Description: Developers set overly permissive default permission classes globally or in specific views, unintentionally granting broader access than intended. Attackers can exploit these overly permissive defaults to access resources they should not be able to, potentially leading to information disclosure or unauthorized actions. The attacker benefits from misconfigured default access controls granting wider access than intended.
• Impact: Unauthorized access, information disclosure, data breaches, potential for widespread unauthorized access across the API.
• DRF Component Affected: Settings (default permission classes), Views (permission class inheritance).
• Risk Severity: High
• Mitigation Strategies:
  • Carefully review and configure default permission classes, ensuring they are appropriately restrictive and aligned with the principle of least privilege.
  • Prefer explicit permission class definitions in individual views over relying solely on potentially overly broad defaults.
  • Regularly audit and review default permission settings to ensure they remain appropriate as the application evolves and access requirements change.
  • Adopt a "deny by default" approach, where default permissions are highly restrictive, and access is explicitly granted where needed, rather than relying on permissive defaults.

Threat: Misconfigured DRF Settings

• Description: Incorrectly configured DRF settings can introduce significant vulnerabilities or weaken security measures. Attackers can exploit these misconfigurations to bypass security controls, gain unauthorized access, or cause other security breaches. The attacker benefits from exploitable weaknesses introduced by misconfigured security settings within DRF.
• Impact: Various security vulnerabilities depending on the specific misconfiguration, including unauthorized access, information disclosure, weakened authentication or authorization, and potential for broader system compromise.
• DRF Component Affected: Settings (DRF settings configuration).
• Risk Severity: High
• Mitigation Strategies:
  • Thoroughly review and understand all DRF settings and their potential security implications before deployment.
  • Adhere to security best practices and security hardening guidelines when configuring DRF settings, particularly in production environments.
  • Utilize configuration management tools to enforce consistent and secure settings across all deployment environments, minimizing configuration drift and errors.
  • Implement regular security audits of DRF settings to proactively identify and rectify any misconfigurations that could introduce vulnerabilities.

Threat: Unintentional Exposure of Sensitive Data in Serializers

• Description: Serializers inadvertently include sensitive data fields (e.g., password hashes, API keys, internal identifiers) that should not be exposed in API responses. Attackers can access these API responses and obtain sensitive information, potentially leading to further attacks or direct misuse of the exposed data. The attacker gains access to sensitive data through overly verbose API responses due to serializer misconfiguration.
• Impact: Information disclosure, privacy violations, potential misuse of sensitive data for further attacks, compliance violations related to data privacy.
• DRF Component Affected: Serializers (field definitions, fields/exclude attributes).
• Risk Severity: High
• Mitigation Strategies:
  • Carefully and meticulously define fields or exclude in serializers to strictly control which data is included in API responses, ensuring sensitive data is never exposed unintentionally.
  • Utilize read_only_fields for fields that should not be included in write operations but might be exposed in read operations, and critically evaluate if even read exposure is necessary for sensitive fields.
  • Implement regular reviews of serializer definitions to proactively identify and rectify any unintentional exposure of sensitive data fields.
  • Apply data masking, redaction, or secure data handling techniques within serializers for sensitive fields when exposure is absolutely necessary, minimizing the risk of direct sensitive data leakage.