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attack-surface.md

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Attack Surface Analysis for reactivex/rxswift

Attack Surface: 1. Uncontrolled Event Stream DoS

  • Description: An attacker can flood the application with a high volume of events through an exposed Observable, overwhelming the system and leading to a denial of service.
    • RxSwift Contribution: RxSwift's core functionality is building reactive streams. Without proper controls, these streams are vulnerable to being exploited to process an excessive number of events, far beyond what the application can handle. The asynchronous nature can make detection and mitigation more complex.
    • Example: An attacker repeatedly triggers a network request that is observed by an RxSwift stream. Without rate limiting, the application becomes unresponsive. Another example: a UI element (like a text field) bound to an Observable is flooded with rapid input, overwhelming the UI thread.
    • Impact: Application unresponsiveness, crashes, resource exhaustion (CPU, memory), potential data corruption (if processing involves state updates).
    • Risk Severity: High to Critical (depending on exposed functionality and ease of triggering).
    • Mitigation Strategies:
      • Rate Limiting: Crucially, use operators like throttle, debounce, sample, or buffer to control the event emission rate. Choose the operator based on the desired behavior (discarding, delaying, or batching events).
      • Input Validation: Validate all inputs feeding into Observables. Reject malformed or excessive inputs before they enter the reactive stream.
      • Backpressure (if possible): If the underlying data source supports it, implement backpressure. RxSwift doesn't have universal backpressure, so this may require custom solutions.
      • Resource Monitoring: Monitor CPU, memory, and network usage. Implement alerts for unusual activity.
      • Circuit Breakers: Consider a circuit breaker pattern to temporarily stop processing events from an overwhelmed source.

Attack Surface: 2. Race Conditions and Threading Errors

  • Description: Incorrect handling of threading within Observable chains can lead to race conditions, data corruption, and UI freezes.
    • RxSwift Contribution: RxSwift provides threading operators (observeOn, subscribeOn), but incorrect usage easily introduces concurrency issues. The asynchronous nature of Observables requires careful understanding of threading.
    • Example: Two Observables on different threads modify a shared mutable variable without synchronization, leading to unpredictable results. Another example: long-running operations on the main thread within an Observable chain freeze the UI.
    • Impact: Data corruption, UI freezes, unpredictable behavior, crashes.
    • Risk Severity: High to Critical (depending on the shared data and frequency of concurrent access).
    • Mitigation Strategies:
      • observeOn(MainScheduler.instance): Always use this for UI updates.
      • Immutability: Strongly prefer immutable data structures to minimize synchronization needs.
      • Synchronization: If mutability is required, use appropriate synchronization (locks, mutexes, serial dispatch queues) for shared state access, even within Observable chains.
      • subscribeOn Carefully: Understand its implications (affects subscription and Observable work). Often, only observeOn is needed.
      • Avoid Blocking on Main Thread: Offload long-running operations to background threads using subscribeOn or other asynchronous methods.
      • Thread Sanitizer: Use tools like the Thread Sanitizer (Xcode) to detect data races during development.