attack-surface.md

Attack Surface Analysis for perwendel/spark

Attack Surface: Path Traversal via Wildcards and Parameters

• Description: Exploiting insufficient input validation of URL parameters, captured by Spark's routing, when used in file system operations, leading to access outside intended directories.
• Spark Contribution: Spark's routing features like wildcards (*) and parameters (:param) enable easy URL parameter capture. If these parameters are used to construct file paths without proper sanitization, Spark's routing directly contributes to this attack surface.
• Example: A Spark route /files/:filename uses the :filename parameter directly to serve files. Without validation, a request like /files/../../etc/passwd could bypass intended directory restrictions and expose sensitive system files.
• Impact: Unauthorized access to sensitive files, including configuration files, application source code, and potentially system files. This can lead to data breaches, information disclosure, and in severe cases, system compromise.
• Risk Severity: Critical
• Mitigation Strategies:
  • Strict Input Validation: Implement rigorous validation and sanitization of all URL parameters used in file path construction.
  • Secure Path Resolution: Utilize secure path manipulation functions that prevent directory traversal by resolving paths against a safe, restricted base directory.
  • Principle of Least Privilege: Ensure the application's process has minimal file system permissions, limiting the scope of potential path traversal exploits.
  • Avoid Direct File Path Construction from User Input: Refrain from directly using user-provided input to build file paths. Employ indirect methods like using validated identifiers to look up file paths internally.

Attack Surface: Insecure Route Definitions and Overly Permissive Routing

• Description: Misconfiguration of Spark routes, leading to overly broad or permissive routing rules that unintentionally expose sensitive functionalities or bypass intended access controls.
• Spark Contribution: Spark's flexible routing system, while powerful, can become an attack surface if not configured carefully. Overly broad routes defined using wildcards can inadvertently match and expose unintended endpoints.
• Example: Defining a route /* intended for serving static files, but failing to restrict it properly. This could unintentionally expose administrative endpoints located under paths like /admin/* if they are not explicitly defined with more specific routes, allowing unauthorized access.
• Impact: Unauthorized access to administrative functionalities, sensitive data, or internal application logic. This can lead to privilege escalation, data breaches, and system compromise depending on the exposed functionalities.
• Risk Severity: High
• Mitigation Strategies:
  • Principle of Least Privilege in Routing: Define routes with the narrowest possible scope, avoiding overly broad wildcards unless absolutely necessary and meticulously controlled.
  • Regular Route Audits: Conduct periodic reviews of route definitions to ensure they align with intended access control policies and do not expose unintended or sensitive endpoints.
  • Explicit Route Definitions: Define specific routes for all intended functionalities instead of relying on broad, catch-all routes that might inadvertently expose sensitive areas.
  • Access Control Middleware: Implement authentication and authorization middleware to enforce access controls on sensitive routes, regardless of the route definition's specificity, adding an extra layer of security.

Attack Surface: Lack of Built-in Input Validation Leading to Injection Vulnerabilities

• Description: Spark framework's design choice to not include built-in input validation mechanisms places the entire burden of secure input handling on the developer. This omission, if not addressed, directly leads to injection vulnerabilities.
• Spark Contribution: Spark, as a lightweight framework, intentionally avoids imposing specific input validation. It provides access to raw request data, making secure input handling solely the developer's responsibility. This design, while offering flexibility, directly contributes to the potential attack surface if developers fail to implement robust validation.
• Example: A Spark route handler takes a query parameter and directly uses it in a system command: Runtime.getRuntime().exec("process_data.sh " + request.queryParams("query")). Due to the lack of built-in input validation in Spark, this code is vulnerable to command injection if an attacker provides a malicious query like ; malicious_command.
• Impact: Command injection, SQL injection (if parameters are used in database queries within the application), and other injection-based attacks. These vulnerabilities can lead to complete system compromise, data breaches, and denial of service.
• Risk Severity: Critical
• Mitigation Strategies:
  • Mandatory Input Validation: Implement robust input validation for all request parameters, headers, and request body data within the application code. Validate data type, format, length, and allowed character sets.
  • Input Sanitization and Encoding: Sanitize or encode user inputs before using them in any sensitive context, such as when constructing system commands, database queries, or generating HTML output. Use context-appropriate encoding (e.g., HTML encoding for web output, escaping for shell commands, parameterized queries for databases).
  • Utilize Validation Libraries: Integrate and use established input validation libraries suitable for Java to streamline and standardize input validation processes within the Spark application.
  • Principle of Least Privilege (Execution): Avoid directly using user input in system commands or database queries whenever possible. Employ safer alternatives like parameterized queries for database interactions and pre-defined command structures with validated parameters for system commands.