attack-surface.md

Attack Surface Analysis for ruby-concurrency/concurrent-ruby

Attack Surface: Race Conditions and Data Corruption

• Description: Unintended and unpredictable behavior arising from multiple threads or fibers accessing and modifying shared data concurrently without proper synchronization. This can lead to data corruption, inconsistent application state, and logic errors.
• How concurrent-ruby contributes: concurrent-ruby provides tools for concurrency, increasing the likelihood of race conditions if developers don't correctly use thread-safe data structures and synchronization mechanisms. Improper use of Concurrent::Map, Concurrent::Array, or atomic operations can still lead to races.
• Example: Imagine a counter incremented by multiple threads using a non-atomic operation. Two threads might read the same initial value, increment it, and write back, resulting in only one increment instead of two, leading to an incorrect count. In a more critical scenario, this could corrupt financial transactions or user data.
• Impact: Data corruption, application instability, incorrect business logic execution, potential security breaches due to flawed state management.
• Risk Severity: High to Critical
• Mitigation Strategies:
  • Use Atomic Operations: Leverage concurrent-ruby's atomic operations (e.g., Concurrent::AtomicInteger, Concurrent::AtomicReference) for simple updates to shared variables.
  • Employ Thread-Safe Data Structures Correctly: Utilize Concurrent::Map, Concurrent::Array, and other thread-safe collections provided by concurrent-ruby, understanding their specific guarantees and limitations.
  • Implement Proper Synchronization: Use mutexes, semaphores, or other synchronization primitives (provided by Ruby or concurrent-ruby) to protect critical sections of code accessing shared resources.
  • Thorough Testing: Conduct rigorous concurrency testing, including stress testing and race condition detection tools, to identify and fix potential race conditions.
  • Code Reviews: Perform code reviews specifically focused on concurrency aspects to ensure correct synchronization and data access patterns.

Attack Surface: Deadlocks and Livelocks

• Description: Deadlock occurs when two or more threads are blocked indefinitely, each waiting for a resource held by another. Livelock is similar, but threads continuously change state in response to each other without making progress. Both lead to application freeze or severe performance degradation.
• How concurrent-ruby contributes: Incorrect use of mutexes, semaphores, or condition variables (even if provided by underlying Ruby mechanisms and used in conjunction with concurrent-ruby's concurrency constructs) within concurrent code can easily lead to deadlocks or livelocks. Complex synchronization logic increases the risk.
• Example: Thread A acquires lock L1, then tries to acquire lock L2. Thread B acquires lock L2, then tries to acquire lock L1. Both threads are now blocked indefinitely, waiting for each other to release the lock they need, resulting in a deadlock.
• Impact: Denial of Service (application freeze), severe performance degradation, application unresponsiveness.
• Risk Severity: High
• Mitigation Strategies:
  • Minimize Lock Usage: Reduce the number of locks and the duration for which locks are held. Favor lock-free or wait-free algorithms where possible.
  • Establish Lock Ordering: Define a consistent order for acquiring locks to prevent circular dependencies that lead to deadlocks.
  • Use Timeouts: Implement timeouts when acquiring locks to prevent indefinite blocking. If a timeout occurs, release any held locks and retry or handle the error gracefully.
  • Deadlock Detection and Prevention: Employ deadlock detection mechanisms (if available in the environment) and design concurrency logic to avoid common deadlock scenarios.
  • Careful Design and Review: Thoroughly design and review concurrent logic to identify and eliminate potential deadlock or livelock situations.

Attack Surface: Resource Exhaustion (Thread Pool Saturation)

• Description: An attacker overwhelms the application by submitting a large number of tasks, exhausting available resources like threads in a thread pool. This leads to denial of service as the application becomes unable to process legitimate requests.
• How concurrent-ruby contributes: concurrent-ruby's thread pools (Concurrent::ThreadPoolExecutor) are central to its concurrency model. If not properly configured and protected, they can become a target for resource exhaustion attacks.
• Example: An attacker floods the application with numerous requests that trigger asynchronous tasks executed by a concurrent-ruby thread pool. If the thread pool's maximum size is reached and the task queue fills up, the application will become unresponsive to new requests, effectively causing a denial of service.
• Impact: Denial of Service, application unresponsiveness, performance degradation.
• Risk Severity: High
• Mitigation Strategies:
  • Rate Limiting: Implement rate limiting to restrict the number of requests or tasks from a single source within a given time frame.
  • Input Validation and Sanitization: Validate and sanitize input to prevent malicious or excessively resource-intensive tasks from being submitted.
  • Appropriate Thread Pool Configuration: Configure thread pool parameters (maximum pool size, queue size, rejection policy) based on application needs and resource constraints. Avoid excessively large thread pools that can consume too many resources.
  • Queue Management: Implement queue management strategies to handle task overflow gracefully (e.g., task rejection, backpressure).
  • Monitoring and Alerting: Monitor thread pool utilization and set up alerts to detect and respond to thread pool saturation or performance issues.

Attack Surface: Unhandled Promise Rejections/Exceptions

• Description: Errors or exceptions occurring within asynchronous operations (Promises/Futures) are not properly handled, leading to unexpected application states, silent failures, resource leaks, or even crashes.
• How concurrent-ruby contributes: concurrent-ruby's Promise and Future API relies on explicit error handling. If developers fail to attach .rescue or .catch blocks to promise chains, unhandled rejections can propagate unexpectedly or be silently ignored, masking critical errors.
• Example: An asynchronous task within a promise chain fails due to a network error or database issue. If the promise chain lacks proper error handling, the rejection might not be caught, leading to a silent failure of a critical operation, potentially leaving the application in an inconsistent state or failing to notify the user of the error.
• Impact: Application instability, silent failures, data inconsistencies, resource leaks, potential security vulnerabilities due to unexpected application behavior.
• Risk Severity: High
• Mitigation Strategies:
  • Comprehensive Error Handling in Promises: Always attach .rescue or .catch blocks to promise chains to handle rejections and exceptions explicitly.
  • Logging and Monitoring: Log errors and rejections that occur within promise chains for debugging and monitoring purposes.
  • Fallback Mechanisms: Implement fallback mechanisms or default behaviors to handle promise rejections gracefully and prevent application failures.
  • Code Reviews focused on Error Handling: Pay close attention to error handling in promise-based asynchronous code during code reviews.

Attack Surface: Actor System Vulnerabilities (if using concurrent-ruby-actor)

• Description: Vulnerabilities specific to actor-based concurrency models, such as message handling flaws, state corruption within actors, or resource exhaustion within the actor system.
• How concurrent-ruby contributes: If using concurrent-ruby-actor (or similar actor libraries built on concurrent-ruby), the actor model itself introduces new attack surfaces related to message processing and actor lifecycle management.
• Example: An actor receives a maliciously crafted message that exploits a vulnerability in its message handling logic, causing the actor to crash, corrupt its internal state, or perform unintended actions. An attacker might flood an actor with messages, overwhelming its mailbox and causing resource exhaustion within the actor system.
• Impact: Actor failures, state corruption, denial of service within the actor system, potential application instability.
• Risk Severity: High
• Mitigation Strategies:
  • Message Validation and Sanitization: Thoroughly validate and sanitize all incoming messages to actors to prevent injection attacks or exploitation of message handling flaws.
  • Robust Actor Logic: Design actor logic to be resilient to unexpected inputs and errors. Implement proper error handling within actors.
  • Actor Supervision: Utilize actor supervision strategies to handle actor failures gracefully. Supervisors can restart failing actors or escalate errors to higher levels.
  • Resource Limits for Actors: Implement resource limits for actors (e.g., mailbox size, processing rate) to prevent resource exhaustion attacks.
  • Security Audits of Actor System: Conduct security audits specifically focused on the actor system's design and implementation.

Attack Surface: Misuse of Concurrency Primitives leading to Logic Errors

• Description: Developers incorrectly use concurrency primitives or thread-safe data structures, leading to subtle logic errors that are hard to detect but can be exploited by attackers.
• How concurrent-ruby contributes: concurrent-ruby provides powerful concurrency tools, but their misuse due to lack of understanding or programming errors can introduce vulnerabilities.
• Example: A developer might assume that a series of operations on a Concurrent::Map is atomic when it's not, leading to race conditions and incorrect data updates in specific scenarios. This could be exploited to bypass access controls or manipulate data in unintended ways.
• Impact: Logic errors, data inconsistencies, potential security breaches due to flawed application logic.
• Risk Severity: High
• Mitigation Strategies:
  • Concurrency Training: Provide thorough training to development teams on concurrent programming principles and the correct usage of concurrent-ruby's APIs.
  • Rigorous Code Reviews: Conduct in-depth code reviews, specifically focusing on concurrent code paths and potential logic errors arising from concurrency.
  • Static Analysis Tools: Utilize static analysis tools that can detect potential concurrency issues like race conditions or deadlock vulnerabilities.
  • Comprehensive Testing: Implement comprehensive testing, including unit tests, integration tests, and concurrency-specific tests, to uncover logic errors in concurrent code.