attack-tree.md

Attack Tree Analysis for reactivex/rxjava

Objective: Compromise Application Using RxJava

Attack Tree Visualization

Compromise Application Using RxJava Weaknesses [CRITICAL]
├───[AND]─► Exploit Logic Flaws in Operator Usage [CRITICAL]
│   ├───► [Leaf Node] Cause unexpected behavior by providing crafted input that exploits the internal logic of RxJava operators when combined in a stream.
│   └───► [Leaf Node] Trigger resource exhaustion by manipulating operator behavior (e.g., unbounded buffering due to incorrect operator chaining leading to memory exhaustion).
├───[AND]─► Exploit Asynchronous and Concurrency Issues [CRITICAL]
│   ├───[OR]─► Induce Race Conditions [CRITICAL]
│   │   └───► [Leaf Node] Manipulate timing or input rates to create race conditions in shared state accessed by RxJava streams, leading to data corruption or inconsistent application state.
│   ├───[OR]─► [Leaf Node] Starve critical RxJava streams by overwhelming schedulers with malicious or resource-intensive operations, causing denial of service.
│   └───[OR]─► Exploit Backpressure Mismanagement [CRITICAL]
│       └───► [Leaf Node] Overwhelm the application with data exceeding backpressure handling capabilities, leading to resource exhaustion, dropped events, or application instability.
├───[AND]─► Bypass Security Checks via Error Handling
│   └───► [Leaf Node] Manipulate input to trigger specific RxJava errors that bypass intended security checks or validation logic within the application's reactive streams.
└───[AND]─► Exploit Misconfiguration or Misuse of RxJava [CRITICAL]
    ├───[OR]─► Insecure Scheduler Configuration
    │   └───► [Leaf Node] Exploit applications using insecure or default schedulers that might not provide adequate isolation or resource management, leading to performance degradation or vulnerabilities. (e.g., using `Schedulers.immediate()` in production where concurrency is expected).
    ├───[OR]─► Unbounded Buffers and Memory Exhaustion
    │   └───► [Leaf Node] Exploit applications that create unbounded buffers in RxJava streams (e.g., using operators like `replay()` or `cache()` without limits) leading to memory exhaustion and denial of service.
    └───[OR]─► Incorrect Disposal Handling
        └───► [Leaf Node] Exploit applications with improper disposal of RxJava subscriptions, leading to resource leaks (memory, threads) over time, eventually causing instability or denial of service.

Attack Tree Path: Exploit Logic Flaws in Operator Usage [CRITICAL]

• Attack Vector: Cause unexpected behavior by providing crafted input that exploits the internal logic of RxJava operators when combined in a stream.

  • Description: Attackers craft specific inputs designed to trigger unintended behavior in the application's RxJava streams. This leverages a deep understanding of RxJava operator logic and how they interact when chained together. Examples include exploiting integer overflows in buffer sizes, unexpected side effects in operators when given specific data types, or manipulating state within operators in unforeseen ways.
  • Potential Impact: Data corruption, unexpected application behavior, denial of service, or potentially security vulnerabilities depending on the application logic.
  • Mitigation: Thoroughly test RxJava streams with diverse and potentially malicious inputs. Conduct code reviews focusing on operator combinations and their potential side effects. Implement input validation and sanitization before data enters RxJava streams.

• Attack Vector: Trigger resource exhaustion by manipulating operator behavior (e.g., unbounded buffering due to incorrect operator chaining leading to memory exhaustion).

  • Description: Attackers exploit misconfigurations or incorrect chaining of RxJava operators that lead to excessive resource consumption. A common example is creating unbounded buffers through operators like replay() or cache() without limits. By sending a large volume of data, attackers can fill these buffers, leading to memory exhaustion and denial of service.
  • Potential Impact: Denial of service due to memory exhaustion, application instability, performance degradation.
  • Mitigation: Carefully review operator usage, especially operators that buffer data. Implement backpressure strategies to control data flow. Set limits on buffer sizes for operators like replay() and cache(). Monitor resource usage (memory, CPU) to detect anomalies.

Attack Tree Path: Exploit Asynchronous and Concurrency Issues [CRITICAL]

• 2.1. Induce Race Conditions [CRITICAL]:

  • Attack Vector: Manipulate timing or input rates to create race conditions in shared state accessed by RxJava streams, leading to data corruption or inconsistent application state.
    • Description: RxJava operates asynchronously and concurrently. If application logic within RxJava streams accesses shared mutable state without proper synchronization, attackers can manipulate the timing or rate of input events to trigger race conditions. This can result in data corruption, inconsistent application state, security bypasses, or unpredictable behavior.
    • Potential Impact: Data corruption, security bypass, inconsistent application state, unpredictable behavior, potential for further exploitation.
    • Mitigation: Minimize shared mutable state within reactive streams. If shared state is necessary, use appropriate concurrency control mechanisms like thread-safe data structures or reactive concurrency primitives (if available in RxJava extensions). Thoroughly test concurrent scenarios and edge cases. Conduct code reviews to identify potential race conditions.

• 2.2. Attack Vector: Starve critical RxJava streams by overwhelming schedulers with malicious or resource-intensive operations, causing denial of service.

  • Description: Attackers can flood the application with requests or data designed to consume excessive resources on the schedulers used by RxJava. By overwhelming the schedulers, they can starve critical RxJava streams of processing time, leading to denial of service for essential application functionalities.
  • Potential Impact: Denial of service for specific application features or the entire application, performance degradation.
  • Mitigation: Properly configure and limit scheduler resources. Implement rate limiting and request throttling at the application level. Monitor scheduler performance and resource utilization. Isolate critical streams to dedicated schedulers if necessary.

• 2.3. Exploit Backpressure Mismanagement [CRITICAL]:

  • Attack Vector: Overwhelm the application with data exceeding backpressure handling capabilities, leading to resource exhaustion, dropped events, or application instability.
    • Description: If backpressure is not correctly implemented or handled in the application's RxJava streams, attackers can send data at a rate faster than the application can process it. This overwhelms the system, leading to resource exhaustion (memory, CPU), dropped events, application instability, and potentially denial of service.
    • Potential Impact: Denial of service, application instability, data loss, performance degradation.
    • Mitigation: Implement robust backpressure strategies throughout the reactive streams. Use appropriate backpressure operators (e.g., onBackpressureBuffer, onBackpressureDrop, onBackpressureLatest). Configure buffer sizes and overflow strategies according to application needs and capacity. Monitor resource usage and dropped events.

Attack Tree Path: Bypass Security Checks via Error Handling

• Attack Vector: Manipulate input to trigger specific RxJava errors that bypass intended security checks or validation logic within the application's reactive streams.
  • Description: Attackers craft inputs designed to trigger specific error conditions within RxJava streams that are not properly handled. If security checks or validation logic are implemented within these streams, and error handling is flawed, attackers might be able to bypass these checks by inducing errors that prematurely terminate the stream processing before security measures are applied.
  • Potential Impact: Security bypass, unauthorized access, data manipulation, or other security breaches depending on the bypassed security checks.
  • Mitigation: Ensure security checks are robust and cannot be bypassed through error conditions. Implement comprehensive error handling that does not weaken security. Thoroughly test error handling paths to confirm they do not inadvertently bypass security measures. Design security checks to be resilient to error conditions and handle errors securely.

Attack Tree Path: Exploit Misconfiguration or Misuse of RxJava [CRITICAL]

• 4.1. Insecure Scheduler Configuration:

  • Attack Vector: Exploit applications using insecure or default schedulers that might not provide adequate isolation or resource management, leading to performance degradation or vulnerabilities. (e.g., using Schedulers.immediate() in production where concurrency is expected).
    • Description: Using inappropriate or default RxJava schedulers can lead to performance issues and potential vulnerabilities. For example, using Schedulers.immediate() in production where concurrency is expected can cause blocking and performance bottlenecks. Using default schedulers without resource limits can allow attackers to consume excessive resources.
    • Potential Impact: Performance degradation, resource exhaustion, potential for denial of service, and in some cases, vulnerabilities due to lack of isolation.
    • Mitigation: Carefully choose and configure schedulers based on the application's concurrency requirements and resource constraints. Avoid using Schedulers.immediate() in production unless specifically intended for synchronous operations. Configure thread pools and resource limits for schedulers. Regularly review scheduler configurations.

• 4.2. Unbounded Buffers and Memory Exhaustion (Reiteration from 1.2, but important in Misconfiguration context):

  • Attack Vector: Exploit applications that create unbounded buffers in RxJava streams (e.g., using operators like replay() or cache() without limits) leading to memory exhaustion and denial of service.
    • Description: (Same as 1.2) Attackers exploit misconfigurations or incorrect chaining of RxJava operators that lead to excessive resource consumption, specifically unbounded buffers.
    • Potential Impact: (Same as 1.2) Denial of service due to memory exhaustion, application instability, performance degradation.
    • Mitigation: (Same as 1.2) Carefully review operator usage, especially operators that buffer data. Implement backpressure strategies to control data flow. Set limits on buffer sizes for operators like replay() and cache(). Monitor resource usage (memory, CPU) to detect anomalies.

• 4.3. Incorrect Disposal Handling:

  • Attack Vector: Exploit applications with improper disposal of RxJava subscriptions, leading to resource leaks (memory, threads) over time, eventually causing instability or denial of service.
    • Description: Failing to properly dispose of RxJava subscriptions results in resource leaks (memory, threads). Over time, these leaks accumulate, degrading performance and eventually leading to application instability or denial of service. While not a direct exploit, it weakens the application's resilience and makes it more vulnerable to other attacks or resource exhaustion.
    • Potential Impact: Denial of service (gradual), application instability, performance degradation, increased vulnerability to other attacks.
    • Mitigation: Implement proper disposal mechanisms for all RxJava subscriptions. Use CompositeDisposable to manage multiple subscriptions. Utilize takeUntil or similar operators to control subscription lifecycles. Employ try-with-resources for resources within streams. Regularly review and test subscription lifecycle management. Monitor resource usage over time to detect leaks.