CON02-J. Facilitate thread reuse by using Thread Pools

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

On the other hand, there can be several disadvantages of this design such as thread creation overhead in case of frequent or recurring requests, significant processing overhead, resource exhaustion of threads (leading to OutOfMemoryError), thread scheduling and context switching overhead [[Lea 00]].

Thread Pools overcome these disadvantages as the maximum number of worker threads that can be initiated and executed simultaneously can be suitably controlled. Every worker accepts a Runnable object from a request and stores it in a temporary Channel like a buffer or a queue until resources become available. Because threads are reused and can be efficiently added to the Channel, most of the thread creation overhead is eliminated.

Noncompliant Code Example

This noncompliant code example demonstrates the Thread-Per-Message design that fails to provide graceful degradation of service.

class Helper {
  public void handle(String request) {
    //... 		
  }	
}

class GetRequest {
  protected final Helper h = new Helper();
  String request;

  public synchronized String accept() {
    String data = "Read data from pipe";
    // Read the request data, else block
    return data;
  }

  public void request() {
    while(true) {
      request = accept();
      new Thread(new Runnable() {
        public void run() {
          h.handle(request);
        }
      }).start();
    }
  }
}

Compliant Solution

This compliant solution uses a Fixed Thread Pool that places an upper bound on the number of simultaneously executing threads. Tasks submitted to the pool are stored in an internal queue. This prevents the system from getting 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]]

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

[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.

class GetRequest {
  protected final Helper h = new Helper();
  String request;

  public synchronized String accept() {
    String data = "Read data from pipe";
    // Read the request data, else block
    return data;
  }

  public void request() {
    int NoOfThreads = 200;
    Executor exec = (Executor) Executors.newFixedThreadPool(NoOfThreads);
    while(true) {
      request = accept();
      exec.execute(new Runnable() {
        public void run() {
          h.handle(request);
        }
      });
    }
  }
}

Noncompliant Code Example

In reality, there are some problems associated with the use of the Executor interface. For one, tasks that depend on other tasks should not execute in the same Thread Pool. A task that submits another task to a single threaded Executor remains blocked until the results are received whereas the second task waits until the first one has concluded. This constitutes a deadlock.

This noncompliant code example shows a thread starvation deadlock. This situation not only occurs in single threaded Executors, but also in those with large Thread Pools. This can happen when all the threads executing in the pool are blocked on tasks that are waiting on the queue. A blocking operation within a subtask can also lead to unbounded queue growth. [[Goetz 06]]

class NetworkServer extends InitialHandshake implements Runnable {
  private final ServerSocket serverSocket;
  private final ExecutorService pool;

  public NetworkServer(int port, int poolSize) throws IOException {
    serverSocket = new ServerSocket(port);
    pool = Executors.newFixedThreadPool(poolSize);
  }
 
  public void run() {
    try { 
      // Interdependent tasks
      pool.submit(new SanitizeInput(password));  // Password is defined in class InitialHandshake
      pool.submit(new CustomHandshake(password));  // for e.g. client puzzles 
      pool.execute(new Handle(serverSocket.accept()));  // Handle connection
    } catch (IOException ex) { 
      pool.shutdown();
    }	 
  }
}

Compliant Solution

Always try to submit independent tasks to the Executor. Choosing a large pool size can also help reduce thread starvation problems. Note that any operation that has further constraints, such as the total number of database connections or total ResultSets open at a particular time, impose an upper bound on the Thread Pool size as each thread continues to block until the resource becomes available. The other rules of fair concurrency, such as not running response sensitive tasks, also apply.

Sometimes, a private static ThreadLocal variable is used per thread to maintain local state. With Thread Pools, these should be employed only if their lifetime is shorter than that of the corresponding task [[Goetz 06]]. Moreover, such variables should not be used as a communication mechanism between tasks. Finally, the choice of the unbounded newFixedThreadPool may not always be the best. Refer to the API documentation for choosing between the former, newCachedThreadPool, newSingleThreadExecutor and newScheduledThreadPool to suit the design requirements.

This compliant solution recommends executing the interdependent tasks as a single task within the Executor. In other cases, where the subtasks do not require concurrency safeguards, the subtasks can be moved outside the threaded region that is going to be executed by the Executor.

class NetworkServer extends InitialHandshake implements Runnable {
  private final ServerSocket serverSocket;
  private final ExecutorService pool;

  public NetworkServer(int port, int poolSize) throws IOException {
    serverSocket = new ServerSocket(port);
    pool = Executors.newFixedThreadPool(poolSize);
  }
 
  public void run() {
    try {
      // Execute interdependent subtasks as a single combined task within this block
      pool.execute(new Handle(serverSocket.accept())); // Handle connection
    } catch (IOException ex) { 
      pool.shutdown();
    }	 
  }
}

Risk Assessment

Using simplistic concurrency primitives (often incorrectly too) may lead to severe performance degradation, deadlocks and starvation, or exhaustion of system resources. This results in a denial-of-service attack.

Automated Detection

TODO

Related Vulnerabilities

Search for vulnerabilities resulting from the violation of this rule on the CERT website.

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"

CON01-J. Avoid using ThreadGroup APIs      11. Concurrency (CON)      CON03-J. Do not assume that elements of an array declared volatile are volatile