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Wiki MarkupMany programs must address the problem of handling a series of incoming requests. The One simple concurrency strategy is the Thread-Per-Message design pattern (described in \[[Lea 00|AA. Java References#Lea 00]\]) is the simplest concurrency strategy wherein a new thread is created for each request. This design pattern is generally recommended over sequential executions of time consuming, I/O bound, session based or isolated tasks. Wiki MarkupHowever, this design pattern also has several pitfalls, including overheads of thread-creation and scheduling, task processing, resource allocation and deallocation, and frequent context switching \[[Lea 00|AA. Java References#Lea 00]\]. 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 a denial of service. From the safety point of view, one component can potentially exhaust all resources because of some pattern, which uses a new thread for each request [Lea 2000a]. This pattern is generally preferred over sequential executions of time-consuming, I/O-bound, session-based, or isolated tasks.

However, the pattern also introduces overheads not seen in sequential execution, including the time and resources required for thread creation and scheduling, for task processing, for resource allocation and deallocation, and for frequent context switching [Lea 2000a]. Furthermore, an attacker can cause a denial of service (DoS) by overwhelming the system with too many requests at once, causing the system to become unresponsive rather than degrading gracefully. From a safety perspective, one component can exhaust all resources because of an intermittent error, consequently starving all other intermittent error, starving all other components.

Thread pools allow a system to service as many requests as limit the maximum number of simultaneous requests that it processes to a number that it can comfortably sustain, serve rather than terminating all services when presented with a deluge of requests. Thread pools overcome these issues because by controlling the maximum number of worker threads that can be initialized and executed concurrently can be suitably controlled. Every execute concurrently. Each object that supports thread pools accepts a Runnable or Callable<T> task and stores it in a temporary queue until resources become available. Because Additionally, thread life-cycle management overhead is minimized because the threads in a thread pool can be reused and can be efficiently added to or removed from the pool, thread life-cycle management related overhead is minimized.

Programs that use multiple threads to service requests should—and programs that may be subjected to DoS attacks must—ensure graceful degradation of service during traffic bursts. Use of thread pools is one acceptable approach to meeting this requirement.

Noncompliant Code Example (Thread-Per-Message)

This noncompliant code example demonstrates the Thread-Per-Message design pattern. The RequestHandler class RequestHandler provides a public static factory method so that callers can obtain its a RequestHandler instance. Subsequently, the The handleRequest() method is used subsequently invoked 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 shutting down the thread pool and task cancellation ...
}

The Threadthread-Perper-Message message strategy fails to provide graceful degradation of service. As the number of concurrent threads increasesthreads are created, processing continues normally until some scarce resource is exhausted. The resource to be exhausted first depends on the tasks being performed, and could be available file descriptors, available threads provided by the system, available memory, or any number of other resources. When a critical resource, such as memory, gets exhausted, the system will fail hard, refusing to service any more requests.

Compliant Solution

For example, a system may allow only a limited number of open file descriptors even though additional threads can be created to serve requests. When the scarce resource is memory, the system may fail abruptly, resulting in a DoS.

Compliant Solution (Thread Pool)

This compliant solution uses a fixed thread pool that places a strict limit on the number of concurrently executing threads. Tasks submitted to the pool are stored in an internal queue. Storing tasks in a queue prevents the system from being overwhelmed when attempting to respond to all incoming requests and allows it to degrade gracefully by serving a fixed maximum number of simultaneous clients [Java Tutorials]. Wiki MarkupThis 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. \[[Tutorials 08|AA. Java References#Tutorials 08]\]

// 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						
          }
        }
    });
  }
  // ... Other methods such as shutting down the thread pool 
  // and task cancellation ...
}

...

According to the Java API documentation for the {{Executor}} interface \ [[API 06|AA. Java References#API 06]\API 2014]:

Wiki Markup\[The Interface {{Executor}} is\] 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 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 ExecutorService interface used in this compliant solution derives from the java.util.concurrent.Executor interface. The ExecutorService.submit() method allows callers to obtain a Future<?> Future<V> object. This object encapuslates both encapsulates the as-yet - unknown result of an asynchronous computation , and enables callers to perform additional functions such as task cancellation.

The choice of the unbounded newFixedThreadPool may is not always be the bestappropriate. Refer to the Java API documentation for choosing between documentation [API 2014] for guidance on choosing among the following methods to meet specific design requirements:

• newFixedThreadPool()

...

• newCachedThreadPool()

...

• newSingleThreadExecutor()

...

• newScheduledThreadPool()

...

Risk Assessment

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

Automated Detection

...

TODO

Related Vulnerabilities

Apache Geronimo 3838

References

Sound automated detection is infeasible; heuristic checks could be useful.

Tool	Version	Checker	Description
Parasoft Jtest	Include Page Parasoft_V Parasoft_V	CERT.TPS00.ISTART	Do not call the 'start()' method directly on Thread class instances

Related Guidelines

Bibliography

...

Image Added Image Added Image Added

\[[API 06|AA. Java References#API 06]\] [Interface Executor|http://java.sun.com/j2se/1.5.0/docs/api/java/util/concurrent/Executor.html]
\[[Lea 00|AA. Java References#Lea 00]\] Section 4.1.3 Thread-Per-Message and 4.1.4 Worker Threads
\[[Tutorials 08|AA. Java References#Tutorials 08]\] [Thread Pools|http://java.sun.com/docs/books/tutorial/essential/concurrency/pools.html]
\[[Goetz 06|AA. Java References#Goetz 06]\] Chapter 8, Applying Thread Pools
\[[MITRE 09|AA. Java References#MITRE 09]\] [CWE ID 405|http://cwe.mitre.org/data/definitions/405.html] "Asymmetric Resource Consumption (Amplification)", [CWE ID 410|http://cwe.mitre.org/data/definitions/410.html] "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