attack-surface.md

Attack Surface Analysis for badoo/reaktive

Attack Surface: 1. Uncontrolled Data Streams

• Description: Processing data from untrusted sources within Reaktive pipelines without proper validation and sanitization, allowing malicious data to propagate and cause harm.
• Reaktive Contribution: Reaktive's reactive nature and operator chaining can obscure the data flow, making it easy to overlook input validation within the pipeline. If validation is missed at the pipeline's entry point, malicious data is seamlessly processed by subsequent Reaktive operators.
• Example: An application uses Reaktive to process user-provided search queries from a web interface. The query string is directly passed into a reactive pipeline and used to construct a database query via string concatenation within a map operator. A malicious user inputs a crafted query like '; DROP TABLE users; -- which, when processed by the pipeline and executed, results in SQL injection and data loss.
• Impact: Data breaches, unauthorized data access, data manipulation, complete compromise of backend systems due to injection vulnerabilities, denial of service.
• Risk Severity: Critical
• Mitigation Strategies:
  • Reactive Input Validation: Implement input validation and sanitization as the absolute first step within the Reaktive pipeline, immediately after the data source is introduced as an Observable. Use operators like map and filter for validation and sanitization reactively.
  • Schema Enforcement: If data is structured (e.g., JSON, XML), enforce schema validation at the pipeline's entry point using Reaktive operators to ensure data conforms to expected formats before further processing.
  • Immutable Data Flow: Design reactive pipelines to treat data as immutable as it flows through operators. This helps in tracking data transformations and ensuring validation steps are consistently applied.
  • Security Audits of Pipelines: Conduct regular security audits specifically focusing on reactive pipelines that handle untrusted data, verifying that input validation is robust and correctly placed within the Reaktive flow.

Attack Surface: 2. Error Handling Failures Leading to Information Disclosure or Bypass

• Description: Insufficient or incorrect error handling within Reaktive pipelines that can lead to the exposure of sensitive information through error messages or stack traces, or potentially bypass critical security checks due to unhandled exceptions.
• Reaktive Contribution: Reaktive's error handling relies on explicit operators like onErrorReturn and onErrorResumeNext. If these are not correctly implemented or are missed in critical parts of the pipeline, exceptions can propagate uncontrolled, potentially revealing internal application details or disrupting security logic.
• Example: A reactive pipeline handles user authentication. If an unexpected error occurs during a database lookup within the authentication pipeline and is not handled with onErrorReturn, the raw exception (including database connection strings or internal paths) might be logged verbosely or even propagated to the user in a development environment. In a more critical scenario, an unhandled exception in a security check within the pipeline could cause the check to be skipped entirely, leading to unauthorized access.
• Impact: Information disclosure of sensitive application details, potential bypass of security controls, application instability leading to exploitable states.
• Risk Severity: High
• Mitigation Strategies:
  • Comprehensive Reactive Error Handling: Implement robust error handling in every Reaktive pipeline, especially those dealing with sensitive operations or data. Use onErrorReturn, onErrorResumeNext, or onErrorStop operators to gracefully manage errors and prevent uncontrolled propagation.
  • Secure Error Transformation: When using onErrorReturn or similar operators, ensure that the fallback value or alternative Observable does not inadvertently bypass security checks or expose sensitive information. Transform errors into generic, safe error representations before propagating them further.
  • Centralized Error Logging for Pipelines: Implement a centralized and secure logging mechanism specifically for errors occurring within Reaktive pipelines. Ensure logs are reviewed regularly and do not contain sensitive data. Configure logging to avoid verbose error details in production environments.
  • Testing Error Scenarios in Pipelines: Thoroughly test error scenarios within reactive pipelines, including simulating failures in dependencies and invalid data inputs, to verify that error handling is effective and secure.

Attack Surface: 3. Vulnerabilities in Custom Reaktive Operators

• Description: Security vulnerabilities introduced through poorly designed or implemented custom Reaktive operators, which can be exploited if these operators handle sensitive data or are part of critical reactive pipelines.
• Reaktive Contribution: Reaktive's extensibility allows developers to create custom operators. If developers lack security expertise or fail to apply secure coding practices when creating these operators, they can become a direct source of vulnerabilities within the Reaktive application.
• Example: A custom operator is created to decrypt data within a reactive pipeline. If this operator is implemented with a flawed decryption algorithm or insecure key management practices, it can introduce a cryptographic vulnerability. An attacker could potentially bypass the decryption or compromise the encryption keys by exploiting weaknesses in the custom operator's implementation.
• Impact: Introduction of new vulnerability types specific to the custom operator's logic (e.g., cryptographic flaws, injection vulnerabilities, buffer overflows), potential compromise of sensitive data processed by the operator, application instability.
• Risk Severity: High to Critical (depending on the nature of the vulnerability and the operator's role in the application).
• Mitigation Strategies:
  • Minimize Custom Operators: Prioritize using built-in Reaktive operators whenever possible. Only create custom operators when absolutely necessary and when no suitable built-in operator exists.
  • Secure Development Lifecycle for Custom Operators: Apply a secure development lifecycle to the creation of custom Reaktive operators, including threat modeling, secure coding practices, and rigorous security testing.
  • Security Reviews of Custom Operators: Subject all custom Reaktive operators to thorough security reviews by experienced security professionals before deployment. Focus on code logic, data handling, and potential vulnerabilities specific to the operator's functionality.
  • Sandboxing or Isolation for Custom Operators: If possible, consider sandboxing or isolating custom operators to limit the impact of potential vulnerabilities. This might involve running custom operators in separate processes or with restricted permissions.