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Attack Tree Analysis for reactivex/rxswift

Objective: To compromise the application by exploiting vulnerabilities arising from the implementation, usage, or inherent characteristics of RxSwift, leading to unauthorized data access, manipulation, denial of service, or control over application behavior.

Attack Tree Visualization

Root Goal: Compromise Application via RxSwift Exploitation
├── [CRITICAL NODE] 1. Exploit Data Stream Manipulation [HIGH RISK PATH]
│   ├── [CRITICAL NODE] 1.1. Data Injection into Observables/Subjects [HIGH RISK PATH]
│   │   └── [HIGH RISK PATH] 1.1.1. Inject Malicious Data into Subject (e.g., `PublishSubject`, `BehaviorSubject`)
│   └── [HIGH RISK PATH] 1.3. Denial of Service (DoS) via Stream Overload [CRITICAL NODE]
│       ├── [HIGH RISK PATH] 1.3.1. Flood Observable with Excessive Events
│       ├── [HIGH RISK PATH] 1.3.2. Create Infinite or Long-Running Observables without Proper Disposal
│       └── [HIGH RISK PATH] 1.3.3. Trigger computationally expensive operations within Rx chains repeatedly
├── [CRITICAL NODE] 2. Exploit Scheduler Misconfiguration or Abuse [HIGH RISK PATH]
│   ├── [HIGH RISK PATH] 2.1.2. Blocking Operations on Main Thread Scheduler
│   └── [HIGH RISK PATH] 2.2. Race Conditions due to Incorrect Scheduler Usage [CRITICAL NODE]
│       └── [HIGH RISK PATH] 2.2.1. Shared Mutable State Accessed Concurrently in Rx Streams
└── [CRITICAL NODE] 3. Exploit Operator Misuse or Logic Flaws in Rx Chains [HIGH RISK PATH]
    ├── [CRITICAL NODE] 3.1. Logic Errors in Operator Chains Leading to Vulnerable States [HIGH RISK PATH]
    │   ├── [HIGH RISK PATH] 3.1.1. Incorrect Filtering or Mapping Exposing Sensitive Data
    │   └── [HIGH RISK PATH] 3.1.2. Improper Error Handling in Operators Leading to Unhandled Exceptions or Crashes
    └── [HIGH RISK PATH] 3.2. Resource Leaks due to Improper Operator Usage [CRITICAL NODE]
        └── [HIGH RISK PATH] 3.2.1. Retain Cycles in Rx Chains Leading to Memory Leaks

Attack Tree Path: 1. Exploit Data Stream Manipulation (Critical Node & High-Risk Path)

  • 1.1. Data Injection into Observables/Subjects (Critical Node & High-Risk Path):

    • 1.1.1. Inject Malicious Data into Subject (High-Risk Path):
      • Attack Vector: Attacker injects malicious data into Subject instances (like PublishSubject, BehaviorSubject) if input validation is weak or missing before data is pushed into the Subject.
      • Consequences:
        • Data corruption within the application's reactive streams.
        • Bypassing application logic or security checks.
        • Potential Cross-Site Scripting (XSS) if injected data is displayed in UI without sanitization.
        • Exploiting vulnerabilities in downstream operators or application logic that process the injected data.

  • 1.3. Denial of Service (DoS) via Stream Overload (Critical Node & High-Risk Path):

    • 1.3.1. Flood Observable with Excessive Events (High-Risk Path):

      • Attack Vector: Attacker floods an Observable with a massive number of events, especially if the application lacks backpressure or rate limiting mechanisms.
      • Consequences:
        • Resource exhaustion (CPU, memory) on the application server or client device.
        • Application slowdown and unresponsiveness for legitimate users.
        • Temporary or complete service unavailability (DoS).

    • 1.3.2. Create Infinite or Long-Running Observables without Proper Disposal (High-Risk Path):

      • Attack Vector: Often due to coding errors, but attacker might trigger application flows that create infinite or long-running Observable chains without proper disposal of subscriptions.
      • Consequences:
        • Memory leaks as resources are not released.
        • Resource exhaustion over time.
        • Application instability and eventual crashes.

    • 1.3.3. Trigger computationally expensive operations within Rx chains repeatedly (High-Risk Path):

      • Attack Vector: Attacker repeatedly triggers Rx chains that perform computationally intensive operations synchronously within the stream processing.
      • Consequences:
        • CPU starvation and application slowdown.
        • Resource exhaustion.
        • DoS by overloading application resources.

Attack Tree Path: 1.1. Data Injection into Observables/Subjects (Critical Node & High-Risk Path)

  • 1.1.1. Inject Malicious Data into Subject (High-Risk Path): * Attack Vector: Attacker injects malicious data into Subject instances (like PublishSubject, BehaviorSubject) if input validation is weak or missing before data is pushed into the Subject. * Consequences: * Data corruption within the application's reactive streams. * Bypassing application logic or security checks. * Potential Cross-Site Scripting (XSS) if injected data is displayed in UI without sanitization. * Exploiting vulnerabilities in downstream operators or application logic that process the injected data.

Attack Tree Path: 1.1.1. Inject Malicious Data into Subject (High-Risk Path)

  • Attack Vector: Attacker injects malicious data into Subject instances (like PublishSubject, BehaviorSubject) if input validation is weak or missing before data is pushed into the Subject. * Consequences: * Data corruption within the application's reactive streams. * Bypassing application logic or security checks. * Potential Cross-Site Scripting (XSS) if injected data is displayed in UI without sanitization. * Exploiting vulnerabilities in downstream operators or application logic that process the injected data.

Attack Tree Path: 1.3. Denial of Service (DoS) via Stream Overload (Critical Node & High-Risk Path)

  • 1.3.1. Flood Observable with Excessive Events (High-Risk Path): * Attack Vector: Attacker floods an Observable with a massive number of events, especially if the application lacks backpressure or rate limiting mechanisms. * Consequences: * Resource exhaustion (CPU, memory) on the application server or client device. * Application slowdown and unresponsiveness for legitimate users. * Temporary or complete service unavailability (DoS).

    • 1.3.2. Create Infinite or Long-Running Observables without Proper Disposal (High-Risk Path):

      • Attack Vector: Often due to coding errors, but attacker might trigger application flows that create infinite or long-running Observable chains without proper disposal of subscriptions.
      • Consequences:
        • Memory leaks as resources are not released.
        • Resource exhaustion over time.
        • Application instability and eventual crashes.

    • 1.3.3. Trigger computationally expensive operations within Rx chains repeatedly (High-Risk Path):

      • Attack Vector: Attacker repeatedly triggers Rx chains that perform computationally intensive operations synchronously within the stream processing.
      • Consequences:
        • CPU starvation and application slowdown.
        • Resource exhaustion.
        • DoS by overloading application resources.

Attack Tree Path: 1.3.1. Flood Observable with Excessive Events (High-Risk Path)

  • Attack Vector: Attacker floods an Observable with a massive number of events, especially if the application lacks backpressure or rate limiting mechanisms. * Consequences: * Resource exhaustion (CPU, memory) on the application server or client device. * Application slowdown and unresponsiveness for legitimate users. * Temporary or complete service unavailability (DoS).

Attack Tree Path: 1.3.2. Create Infinite or Long-Running Observables without Proper Disposal (High-Risk Path)

  • Attack Vector: Often due to coding errors, but attacker might trigger application flows that create infinite or long-running Observable chains without proper disposal of subscriptions. * Consequences: * Memory leaks as resources are not released. * Resource exhaustion over time. * Application instability and eventual crashes.

Attack Tree Path: 1.3.3. Trigger computationally expensive operations within Rx chains repeatedly (High-Risk Path)

  • Attack Vector: Attacker repeatedly triggers Rx chains that perform computationally intensive operations synchronously within the stream processing. * Consequences: * CPU starvation and application slowdown. * Resource exhaustion. * DoS by overloading application resources.

Attack Tree Path: 2. Exploit Scheduler Misconfiguration or Abuse (Critical Node & High-Risk Path)

  • 2.1.2. Blocking Operations on Main Thread Scheduler (High-Risk Path): * Attack Vector: Developers mistakenly perform blocking operations (e.g., network requests, file I/O) on the main thread scheduler, often implicitly used for UI-related Rx streams. * Consequences: * User interface freezes and unresponsiveness. * Application hangs or becomes unusable. * Application Not Responding (ANR) errors on mobile platforms.

  • 2.2. Race Conditions due to Incorrect Scheduler Usage (Critical Node & High-Risk Path):

    • 2.2.1. Shared Mutable State Accessed Concurrently in Rx Streams (High-Risk Path):
      • Attack Vector: In concurrent Rx streams (using observeOn, subscribeOn), developers access and modify shared mutable state without proper synchronization.
      • Consequences:
        • Race conditions leading to unpredictable application behavior.
        • Data corruption and inconsistent application state.
        • Logic errors and potential security vulnerabilities due to unexpected data states.

Attack Tree Path: 2.1.2. Blocking Operations on Main Thread Scheduler (High-Risk Path)

  • Attack Vector: Developers mistakenly perform blocking operations (e.g., network requests, file I/O) on the main thread scheduler, often implicitly used for UI-related Rx streams. * Consequences: * User interface freezes and unresponsiveness. * Application hangs or becomes unusable. * Application Not Responding (ANR) errors on mobile platforms.

Attack Tree Path: 2.2. Race Conditions due to Incorrect Scheduler Usage (Critical Node & High-Risk Path)

  • 2.2.1. Shared Mutable State Accessed Concurrently in Rx Streams (High-Risk Path): * Attack Vector: In concurrent Rx streams (using observeOn, subscribeOn), developers access and modify shared mutable state without proper synchronization. * Consequences: * Race conditions leading to unpredictable application behavior. * Data corruption and inconsistent application state. * Logic errors and potential security vulnerabilities due to unexpected data states.

Attack Tree Path: 2.2.1. Shared Mutable State Accessed Concurrently in Rx Streams (High-Risk Path)

  • Attack Vector: In concurrent Rx streams (using observeOn, subscribeOn), developers access and modify shared mutable state without proper synchronization. * Consequences: * Race conditions leading to unpredictable application behavior. * Data corruption and inconsistent application state. * Logic errors and potential security vulnerabilities due to unexpected data states.

Attack Tree Path: 3. Exploit Operator Misuse or Logic Flaws in Rx Chains (Critical Node & High-Risk Path)

  • 3.1. Logic Errors in Operator Chains Leading to Vulnerable States (Critical Node & High-Risk Path):

    • 3.1.1. Incorrect Filtering or Mapping Exposing Sensitive Data (High-Risk Path):

      • Attack Vector: Errors in filter, map, or similar operators lead to incorrect data transformation or filtering logic.
      • Consequences:
        • Exposure of sensitive data that should be filtered or masked.
        • Privacy breaches due to data leaks.
        • Unauthorized access if filtering logic is intended for access control.

    • 3.1.2. Improper Error Handling in Operators Leading to Unhandled Exceptions or Crashes (High-Risk Path):

      • Attack Vector: Lack of robust error handling in Rx chains or flawed error handling logic.
      • Consequences:
        • Unhandled exceptions causing application crashes.
        • Application instability and DoS.
        • Information leakage through error messages revealing sensitive application details.

  • 3.2. Resource Leaks due to Improper Operator Usage (Critical Node & High-Risk Path):

    • 3.2.1. Retain Cycles in Rx Chains Leading to Memory Leaks (High-Risk Path):
      • Attack Vector: Retain cycles are created in Rx chains, often due to strong references to self within closures in operators, preventing object deallocation.
      • Consequences:
        • Memory leaks and increasing memory consumption over time.
        • Resource exhaustion and application instability.
        • Eventual application crashes due to memory pressure.

Attack Tree Path: 3.1. Logic Errors in Operator Chains Leading to Vulnerable States (Critical Node & High-Risk Path)

  • 3.1.1. Incorrect Filtering or Mapping Exposing Sensitive Data (High-Risk Path): * Attack Vector: Errors in filter, map, or similar operators lead to incorrect data transformation or filtering logic. * Consequences: * Exposure of sensitive data that should be filtered or masked. * Privacy breaches due to data leaks. * Unauthorized access if filtering logic is intended for access control.

    • 3.1.2. Improper Error Handling in Operators Leading to Unhandled Exceptions or Crashes (High-Risk Path):
      • Attack Vector: Lack of robust error handling in Rx chains or flawed error handling logic.
      • Consequences:
        • Unhandled exceptions causing application crashes.
        • Application instability and DoS.
        • Information leakage through error messages revealing sensitive application details.

Attack Tree Path: 3.1.1. Incorrect Filtering or Mapping Exposing Sensitive Data (High-Risk Path)

  • Attack Vector: Errors in filter, map, or similar operators lead to incorrect data transformation or filtering logic. * Consequences: * Exposure of sensitive data that should be filtered or masked. * Privacy breaches due to data leaks. * Unauthorized access if filtering logic is intended for access control.

Attack Tree Path: 3.1.2. Improper Error Handling in Operators Leading to Unhandled Exceptions or Crashes (High-Risk Path)

  • Attack Vector: Lack of robust error handling in Rx chains or flawed error handling logic. * Consequences: * Unhandled exceptions causing application crashes. * Application instability and DoS. * Information leakage through error messages revealing sensitive application details.

Attack Tree Path: 3.2. Resource Leaks due to Improper Operator Usage (Critical Node & High-Risk Path)

  • 3.2.1. Retain Cycles in Rx Chains Leading to Memory Leaks (High-Risk Path): * Attack Vector: Retain cycles are created in Rx chains, often due to strong references to self within closures in operators, preventing object deallocation. * Consequences: * Memory leaks and increasing memory consumption over time. * Resource exhaustion and application instability. * Eventual application crashes due to memory pressure.

Attack Tree Path: 3.2.1. Retain Cycles in Rx Chains Leading to Memory Leaks (High-Risk Path)

  • Attack Vector: Retain cycles are created in Rx chains, often due to strong references to self within closures in operators, preventing object deallocation. * Consequences: * Memory leaks and increasing memory consumption over time. * Resource exhaustion and application instability. * Eventual application crashes due to memory pressure.