CON21-J. Use thread pools to enable graceful degradation of service during traffic bursts

The Thread-Per-Message design pattern is the simplest concurrency strategy wherein a thread is created for each incoming request. This design pattern is only productive when the benefits of creating a new thread outweigh the corresponding thread creation overheads. This design strategy is generally recommended over sequential executions of time consuming, I/O bound, session based or isolated tasks.

At the same time, this design pattern has several pitfalls, including overheads of thread-creation and scheduling, task processing, resource allocation and deallocation, and frequent context switching [[Lea 00]]. Furthermore, an attacker can cause a denial of service by overwhelming the system with too many requests, all at once. Instead of degrading gracefully, the system becomes unresponsive, resulting in an availability issue. From the safety point of view, one component can potentially exhaust all resources because of some intermittent error, starving all other components.

Thread pools allow the system to service as many requests as it can comfortably sustain, instead of terminating all services when faced with a deluge of requests. They overcome these issues because the maximum number of worker threads that can be initiated and executed concurrently can be suitably controlled. Every worker accepts a Runnable or Callable<T> task and stores it in a temporary Channel such as a buffer or a queue until resources become available. Because threads in a thread pool can be reused, and efficiently added or removed from the Channel, thread life-cycle management related overhead is minimized.

Noncompliant Code Example

This noncompliant code example demonstrates the Thread-Per-Message design pattern which fails to provide graceful degradation of service. The class RequestHandler provides a public static factory method so that callers can obtain its instance. Subsequently, the handleRequest() method is used to handle each request in its own thread.

class Helper {
  public void handle(Socket socket) {
    //... 		
  }	
}

final class RequestHandler {
  private final Helper helper = new Helper();
  private final ServerSocket server;

  private RequestHandler(int port) throws IOException {
    server = new ServerSocket(port);
  }
  
  public static RequestHandler newInstance() throws IOException {
    return new RequestHandler(0); // Selects next available port
  }
  
  public void handleRequest() {
    new Thread(new Runnable() {
      public void run() {
        try {
          helper.handle(server.accept());
	} catch (IOException e) {
 	  // Forward to handler   
        }
      }
    }).start();
  }
  // Other methods such as for shutting down the thread pool and task cancellation ...
}

Compliant Solution

This compliant solution uses a Fixed Thread Pool that places an upper bound on the number of concurrently executing threads. Tasks submitted to the pool are stored in an internal queue. This prevents the system from being overwhelmed when trying to respond to all incoming requests and allows it to degrade gracefully by serving a fixed number of clients at a particular time. [[Tutorials 08]]

// class Helper remains unchanged

final class RequestHandler {
  private final Helper helper = new Helper();
  private final ServerSocket server;
  private final ExecutorService exec;
	 
  private RequestHandler(int port, int poolSize) throws IOException {
    server = new ServerSocket(port);
    exec = Executors.newFixedThreadPool(poolSize);
  }
	  
  public static RequestHandler newInstance(int poolSize) throws IOException {
    return new RequestHandler(0, poolSize); 
  }
	  
  public void handleRequest() {	
    Future<?> future = exec.submit(new Runnable() {
      @Override public void run() {
	try {
  	  helper.handle(server.accept());
	} catch (IOException e) {
          // Forward to handler						
        }
      }
    });
  }
}

According to the Java API documentation for the Executor interface [[API 06]]:

[The Interface Executor is] An object that executes submitted Runnable tasks. This interface provides a way of decoupling task submission from the mechanics of how each task will be run, including details of thread use, scheduling, etc. An Executor is normally used instead of explicitly creating threads.

The interface ExecutorService used in this compliant solution derives from the java.util.concurrent.Executor interface. The ExecutorService.submit() method allows callers to obtain a "future" (result of an asynchronous computation) that enables them to perform additional functions such as task cancellation.

The choice of the unbounded newFixedThreadPool may not always be the best. Refer to the API documentation for choosing between newFixedThreadPool, newCachedThreadPool, newSingleThreadExecutor and newScheduledThreadPool to meet specific design requirements.

Risk Assessment

Using simplistic concurrency primitives to process an unbounded number of requests may result in severe performance degradation, deadlocks and starvation, or exhaustion of system resources (denial-of-service).

Automated Detection

TODO

Related Vulnerabilities

Apache Geronimo 3838

References

[[API 06]] Interface Executor
[[Lea 00]] Section 4.1.3 Thread-Per-Message and 4.1.4 Worker Threads
[[Tutorials 08]] Thread Pools
[[Goetz 06]] Chapter 8, Applying Thread Pools
[[MITRE 09]] CWE ID 405 "Asymmetric Resource Consumption (Amplification)", CWE ID 410 "Insufficient Resource Pool"

CON20-J. Do not perform operations that may block while holding a lock      11. Concurrency (CON)      CON22-J. Do not use incorrect forms of the double-checked locking idiom