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attack-surface.md

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Attack Surface Analysis for reactivex/rxkotlin

Attack Surface: 1. Uncontrolled Stream Emission (DoS)

  • Description: Attackers trigger excessive event emissions in an RxKotlin stream, overwhelming the application.
  • RxKotlin Contribution: RxKotlin's core functionality is built around event streams, making it easy to create sources that can emit rapidly. The library provides the mechanisms for this attack, even if the attacker's input is external.
  • Example: An attacker manipulates a web form input that controls the frequency of an Observable.interval used to fetch data. They set the interval to a very small value, flooding the application.
  • Impact: Denial of Service (DoS), application unavailability, resource exhaustion.
  • Risk Severity: High
  • Mitigation Strategies:
    • Input Validation: Rigorously validate and sanitize all inputs that affect Observable emission rates (e.g., timer intervals, retry counts). Use whitelisting.
    • Rate Limiting: Employ operators like throttleFirst, throttleLast, debounce, sample to control the rate of event processing, regardless of the source emission rate.
    • Backpressure Handling: Use Flowable and appropriate BackpressureStrategy (e.g., BUFFER, DROP, LATEST) to manage situations where the subscriber cannot keep up. Choose the strategy carefully, as ERROR can itself be a DoS vector.
    • Resource Monitoring: Monitor CPU, memory, and network usage related to Observable processing. Set alerts for anomalies.

Attack Surface: 2. Unbounded Buffers/Memory Leaks (DoS)

  • Description: Attackers exploit operators that buffer data internally, causing unbounded memory growth and eventual application crash.
  • RxKotlin Contribution: Operators like buffer, window, replay, and cache inherently accumulate data. Their misuse, combined with attacker-controlled input, directly leads to the vulnerability.
  • Example: An attacker sends a continuous stream of data to an Observable.window without ever triggering the window closing condition (which might be based on attacker-controlled data), leading to an ever-growing buffer.
  • Impact: Denial of Service (DoS), application crash, memory exhaustion.
  • Risk Severity: High
  • Mitigation Strategies:
    • Bounded Buffers: Always use operators with built-in size or time limits (e.g., buffer(count), buffer(timespan), window(timespan)). Avoid unbounded variants unless absolutely necessary and tightly controlled by trusted logic.
    • Subscription Management: Ensure all subscriptions are properly disposed of using CompositeDisposable or similar to prevent memory leaks. Leaked subscriptions are a direct cause of unbounded buffer growth.
    • Memory Profiling: Regularly profile the application's memory usage to detect leaks related to RxKotlin operators.

Attack Surface: 3. Concurrency/Threading Issues (Logic Errors)

  • Description: Incorrect use of RxKotlin's concurrency features leads to race conditions, deadlocks, or data corruption, potentially exploitable.
  • RxKotlin Contribution: RxKotlin provides subscribeOn and observeOn for managing concurrency. Misuse of these operators is the direct cause of the vulnerability. The threading model is a core RxKotlin feature.
  • Example: A security check is performed on one thread (subscribeOn), and the action is taken on another (observeOn), without proper synchronization. An attacker exploits the timing window.
  • Impact: Data corruption, security bypass, unpredictable application behavior.
  • Risk Severity: High
  • Mitigation Strategies:
    • Threading Model Understanding: Thoroughly understand RxKotlin's threading model and the use of Schedulers (e.g., Schedulers.io(), Schedulers.computation()). Incorrect Scheduler choice is a direct misuse.
    • Avoid Shared Mutable State: Minimize shared mutable state between threads. If unavoidable, use synchronization mechanisms (locks, atomic variables) provided by the underlying platform, not RxKotlin itself.
    • Immutability: Prefer immutable data structures to inherently avoid many concurrency issues.
    • Concurrency Testing: Test concurrent code rigorously to identify race conditions and deadlocks.

Attack Surface: 4. Error Handling Bypass

  • Description: Unhandled errors in RxKotlin streams are silently ignored, potentially bypassing security checks.
  • RxKotlin Contribution: RxKotlin streams require explicit error handling via onError. The absence or incorrect implementation of onError is a direct misuse of the RxKotlin error handling mechanism.
  • Example: An exception during a security check within an Observable is not caught by an onError handler, allowing the attacker to proceed.
  • Impact: Security bypass, inconsistent application state, data corruption.
  • Risk Severity: High
  • Mitigation Strategies:
    • Comprehensive Error Handling: Implement onError handlers for all Observables, especially those in security-critical paths. This is a direct RxKotlin requirement.
    • Fail Fast: Design error handling to fail fast and prevent the application from continuing in an invalid state.
    • Logging and Auditing: Log all errors, even handled ones, for auditing and debugging.