CWE 362 - Race Condition

Disclaimer

• The code provided is for **educational purposes** only and should not be used in a **production environment** without proper review and testing.

• The provided code should be regarded as **best practice**. There are also several ways to remediate the Vulnerabilities.

• The code provided **may contain vulnerabilities** that could be exploited by attackers, and is intended to be used as a learning tool to help improve security awareness and best practices.

• The mitigations provided are intended to address **specific vulnerabilities** in the code, but may not be effective against all potential attack vectors or scenarios.

• The code provided is not **guaranteed to be secure or free** from all vulnerabilities, and should be reviewed and tested thoroughly before being used in a production environment.

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About CWE ID 362

Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')

This Vulnerability occurs when there is a lack of proper synchronization in concurrent software execution that leads to race conditions. Race conditions can occur in multi-threaded or multi-processenvironments where multiple threads or processes access shared resources simultaneously without adequate coordination.

Impact

• Data Corruption

• Unauthorized Access

• Denial of Service (DoS)

• Security Vulnerabilities

• Inconsistent Program Behavior

• Crashes and Stability Issues

• Difficulty in Detection

Example with Code Explanation

Let us consider an example case and understand the CWE 362 with context of Vulnerable code and Mitigated code.

C

Vulnerable Code

#include <stdio.h>
#include <pthread.h>
#include <unistd.h> // For sleep

#define NUM_THREADS 2
#define ITERATIONS 1000000

int balance = 1000; // Initial balance

void *transferMoney(void *threadID) {
    long tid;
    tid = (long)threadID;

    for (int i = 0; i < ITERATIONS; i++) {
        int temp = balance; // Read the shared resource
        temp = temp - 100; // Modify the local copy (transfer 100 units)
        sleep(1); // Simulate some delay
        balance = temp; // Write back to the shared resource
    }

    pthread_exit(NULL);
}

int main() {
    pthread_t threads[NUM_THREADS];
    int rc;
    long t;

    for (t = 0; t < NUM_THREADS; t++) {
        rc = pthread_create(&threads[t], NULL, transferMoney, (void *)t);
        if (rc) {
            printf("Error: Unable to create thread %ld\n", t);
            return 1;
        }
    }

    for (t = 0; t < NUM_THREADS; t++) {
        pthread_join(threads[t], NULL);
    }

    printf("Final balance: %d\n", balance);

    return 0;
}

The above code is vulnerable because it lacks proper synchronization mechanisms, such as mutex locks, to protect the critical section where the balance variable is read and modified. As a result, it is susceptible to race conditions, which can lead to several issues:

1. Data Corruption: Multiple threads can access and modify the balance variable concurrently without synchronization. This concurrent access can result in data corruption because there is no guarantee that each thread will read and modify the variable in a consistent and orderly manner.

2. Unpredictable Results: Race conditions can lead to unpredictable and non-deterministic outcomes. The final value of the balance variable depends on the timing and order of thread execution, making it difficult to predict the actual balance after multiple threads have completed their operations.

3. Inconsistent State: The lack of synchronization can leave the program in an inconsistent state. For example, if one thread reads the balance variable while another is in the process of modifying it, the read value may not reflect the actual balance, leading to incorrect financial transactions.

• Some of the ways the Vulnerable code can be mitigated is:

  • Mutex Locks: Use mutex locks to protect the critical section where the balance variable is accessed and modified. Mutex locks ensure that only one thread can execute the critical section at a time.

  • Synchronization: Employ proper synchronization mechanisms, such as mutexes, to coordinate access to shared resources and ensure that multiple threads do not simultaneously access or modify them.

  • Atomic Operations: Utilize atomic operations or atomic data types (if available in your programming language) for operations that involve reading and modifying shared variables. Atomic operations ensure that these operations are performed atomically and are not interrupted by other threads.

  • Critical Section Isolation: Isolate the critical section of code, so it is the only part of the code where the balance variable is accessed and modified. This minimizes the potential for race conditions.

  • Thread-Safe Data Structures: Consider using thread-safe data structures or containers when dealing with shared data to eliminate the need for manual synchronization in some cases.

  • Lock-Free Data Structures: If applicable and supported by your platform, explore the use of lock-free data structures and algorithms, which can reduce contention and improve performance in multi-threaded scenarios.

Mitigated Code

#include <stdio.h>
#include <pthread.h>
#include <unistd.h> // For sleep

#define NUM_THREADS 2
#define ITERATIONS 1000000

int balance = 1000; // Initial balance
pthread_mutex_t balance_mutex; // Mutex for protecting the balance variable

void *transferMoney(void *threadID) {
    long tid;
    tid = (long)threadID;

    for (int i = 0; i < ITERATIONS; i++) {
        if (pthread_mutex_lock(&balance_mutex) != 0) {
            // Handle error when locking the mutex
            perror("pthread_mutex_lock");
            return NULL;
        }
        int temp = balance; // Read the shared resource
        temp = temp - 100; // Modify the local copy (transfer 100 units)
        sleep(1); // Simulate some delay
        balance = temp; // Write back to the shared resource
        if (pthread_mutex_unlock(&balance_mutex) != 0) {
            // Handle error when unlocking the mutex
            perror("pthread_mutex_unlock");
            return NULL;
        }
    }

    pthread_exit(NULL);
}

int main() {
    pthread_t threads[NUM_THREADS];
    int rc;
    long t;

    // Initialize the mutex
    if (pthread_mutex_init(&balance_mutex, NULL) != 0) {
        printf("Error: Mutex initialization failed\n");
        return 1;
    }

    for (t = 0; t < NUM_THREADS; t++) {
        rc = pthread_create(&threads[t], NULL, transferMoney, (void *)t);
        if (rc) {
            printf("Error: Unable to create thread %ld\n", t);
            return 1;
        }
    }

    for (t = 0; t < NUM_THREADS; t++) {
        pthread_join(threads[t], NULL);
    }

    // Destroy the mutex
    pthread_mutex_destroy(&balance_mutex);

    printf("Final balance: %d\n", balance);

    return 0;
}

• The Mitigated code does the following:

  • Mutex Initialization:

    • The code initializes a mutex using pthread_mutex_init(&balance_mutex, NULL) in the main function before any threads are created. This initialization sets up the mutex for proper synchronization.

  • Mutex Locking:

    • Inside the transferMoney function, each thread attempts to acquire the mutex using pthread_mutex_lock(&balance_mutex) before accessing and modifying the shared balance variable. This locking ensures that only one thread can access the balance variable at any given time.

  • Mutex Unlocking:

    • After each thread has finished its critical section (the part of the code where it accesses and modifies the balance variable), it releases the mutex using pthread_mutex_unlock(&balance_mutex). This ensures that other threads can acquire the mutex and proceed with their critical sections.

  • Exclusive Access:

    • Because of the mutex locking and unlocking, only one thread can access the critical section at any given time. This prevents data races and ensures that the shared balance variable is updated safely in a mutually exclusive manner.

  • Thread Joining:

    • The main function waits for all threads to complete their work using pthread_join. This ensures that the program does not exit until all threads have finished, preventing premature destruction of the mutex.

  • Mutex Destruction:

    • After all threads have completed, the code destroys the mutex using pthread_mutex_destroy(&balance_mutex). This step is important for proper resource cleanup.

C++

Vulnerable Code

#include <iostream>
#include <thread>

class SharedResource {
public:
    SharedResource() : counter(0) {}

    void Increment() {
        counter++; // Vulnerable operation, not properly synchronized
    }

    int GetCounter() {
        return counter;
    }

private:
    int counter;
};

void ThreadFunction(SharedResource& resource, int threadId) {
    for (int i = 0; i < 10000; ++i) {
        resource.Increment(); // Vulnerable access to shared resource
    }
    std::cout << "Thread " << threadId << " finished." << std::endl;
}

int main() {
    SharedResource resource;

    std::thread t1(ThreadFunction, std::ref(resource), 1);
    std::thread t2(ThreadFunction, std::ref(resource), 2);

    t1.join();
    t2.join();

    std::cout << "Counter: " << resource.GetCounter() << std::endl;

    return 0;
}

In this example, we have a SharedResource class representing a shared resource (an integer counter). Two threads (t1 and t2) concurrently call the Increment method to increment the counter by 1. However, this code is vulnerable to a data race because it lacks proper synchronization.

The vulnerability occurs because multiple threads are accessing and modifying the counter variable without any locks or synchronization mechanisms like mutexes. This can lead to unpredictable and erroneous behavior, where the final value of the counter may not be what is expected due to the interleaved execution of threads.

• Some of the ways the Vulnerable code can be mitigated is:

  • Mutex (Mutual Exclusion):

  Use std::mutex (or other synchronization primitives) to protect the critical section of code where the shared resource is accessed. This ensures that only one thread can access the shared resource at a time.

  • Read-Write Locks:

  If the shared resource allows concurrent reads but requires exclusive access for writes, you can use read-write locks (std::shared_mutex in C++17) to allow multiple threads to read concurrently and ensure exclusive access during writes.

  • Atomic Operations:

  If the shared resource is a simple variable and you only need to perform simple operations like increments, you can use atomic operations (e.g., std::atomic) to ensure that the operations are atomic and thread-safe without the need for explicit locks.

  • Thread-Safe Data Structures:

  Use thread-safe data structures (e.g., std::queue, std::map, etc.) from the C++ Standard Library or third-party libraries that are designed for concurrent access. These data structures internally handle synchronization.

Mitigated Code

#include <iostream>
#include <thread>
#include <atomic>

class SharedResource {
public:
    SharedResource() : counter(0) {}

    void Increment() {
        counter++; // Atomically increment the counter
    }

    int GetCounter() {
        return counter; // Atomically read the counter
    }

private:
    std::atomic<int> counter; // Atomic variable to store the counter
};

void ThreadFunction(SharedResource& resource, int threadId) {
    for (int i = 0; i < 10000; ++i) {
        resource.Increment(); // Safely increment the shared counter
    }
    std::cout << "Thread " << threadId << " finished." << std::endl;
}

int main() {
    SharedResource resource;

    std::thread t1(ThreadFunction, std::ref(resource), 1);
    std::thread t2(ThreadFunction, std::ref(resource), 2);

    t1.join();
    t2.join();

    std::cout << "Counter: " << resource.GetCounter() << std::endl;

    return 0;
}

• The Mitigated code does the following:

  • Atomic Operations: The counter variable is declared as std::atomic<int>, which means that operations on this variable are atomic. Atomic operations ensure that the variable can be safely accessed and modified by multiple threads concurrently without data races. In this code, the Increment and GetCounter methods use atomic operations (counter++ and return counter) to access the shared resource.

  • Synchronized Access: When multiple threads call the Increment or GetCounter methods simultaneously, the atomic operations guarantee that only one thread will access the counter variable at a given time. This prevents data races and ensures that the shared resource is accessed safely.

JAVA

Vulnerable Code

public class SharedResource {
    private int counter = 0;

    public void increment() {
        counter++; // Vulnerable operation, not properly synchronized
    }

    public int getCounter() {
        return counter;
    }
}

public class Main {
    public static void main(String[] args) {
        SharedResource resource = new SharedResource();

        Thread t1 = new Thread(() -> {
            for (int i = 0; i < 10000; i++) {
                resource.increment(); // Vulnerable access to shared resource
            }
        });

        Thread t2 = new Thread(() -> {
            for (int i = 0; i < 10000; i++) {
                resource.increment(); // Vulnerable access to shared resource
            }
        });

        t1.start();
        t2.start();

        try {
            t1.join();
            t2.join();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        System.out.println("Counter: " + resource.getCounter());
    }
}

In this code, we have a SharedResource class representing a shared resource (an integer counter). Two threads (t1 and t2) concurrently call the increment method to increment the counter by 1. However, this code is vulnerable to a data race because it lacks proper synchronization.

The vulnerability occurs because multiple threads are accessing and modifying the counter variable without any synchronization mechanisms like synchronized blocks or the use of java.util.concurrent classes. This can lead to unpredictable and erroneous behavior, where the final value of the counter may not be what is expected due to the interleaved execution of threads.

• Some of the ways the Vulnerable code can be mitigated is:

  • Use Synchronization Mechanisms:

    • Apply synchronization mechanisms to control access to shared resources in a multi-threaded environment.

    • Use synchronized blocks within methods that access shared resources.

    • This ensures that only one thread can execute the synchronized block at a time.

  • ReentrantLock:

    • Create a ReentrantLock to protect shared resources.

    • Use the lock() and unlock() methods to control access within methods.

    • Ensure that you release the lock in a finally block to handle exceptions.

  • java.util.concurrent Classes:

    • Utilize classes like java.util.concurrent.atomic.AtomicInteger for atomic operations on shared variables.

    • These classes handle synchronization internally, avoiding the need for explicit locks.

  • Consistency in Synchronization:

    • Ensure that all threads access the shared resource using the same synchronization mechanism consistently.

Mitigated Code

import java.util.concurrent.atomic.AtomicInteger;

public class SharedResource {
    private AtomicInteger counter = new AtomicInteger(0);

    public void increment() {
        counter.incrementAndGet(); // Atomically increment the counter
    }

    public int getCounter() {
        return counter.get(); // Atomically get the counter
    }
}

public class Main {
    public static void main(String[] args) {
        SharedResource resource = new SharedResource();

        Thread t1 = new Thread(() -> {
            for (int i = 0; i < 10000; i++) {
                resource.increment(); // Safely increment the shared counter
            }
        });

        Thread t2 = new Thread(() -> {
            for (int i = 0; i < 10000; i++) {
                resource.increment(); // Safely increment the shared counter
            }
        });

        t1.start();
        t2.start();

        try {
            t1.join();
            t2.join();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        System.out.println("Counter: " + resource.getCounter());
    }
}

• The Mitigated code does the following:

  • Atomic Operations: The counter variable is declared as an AtomicInteger. This class provides atomic operations for incrementing and getting the value of the integer, which means that these operations are guaranteed to be executed atomically without the need for explicit locking.

  • Synchronized Access: When multiple threads call the increment or getCounter methods, the atomic operations guarantee that only one thread will access the counter variable at a given time. This prevents data races and ensures the integrity of the shared resource.

  • Efficiency: Using java.util.concurrent.atomic.AtomicInteger is efficient because it avoids the overhead associated with explicit locking (e.g., synchronized blocks or ReentrantLock).

  • Consistent Synchronization: All threads accessing the shared resource consistently use atomic operations from AtomicInteger, ensuring uniform synchronization throughout the code.

Mitigation

• Some common mitigation techniques include:

  • Use Thread-Safe Data Structures:

    • Employ thread-safe data structures and libraries whenever possible. These structures are designed to handle concurrent access safely.

  • Synchronize Access:

    • Use synchronization mechanisms such as mutexes, semaphores, or locks to protect critical sections of code that access shared resources. This ensures that only one thread can access the resource at a time.

  • Atomic Operations:

    • Utilize atomic operations and compare-and-swap (CAS) primitives provided by the programming language or platform. These operations allow for safe updates to shared variables without the need for locks.

  • Thread-Local Storage:

    • When applicable, use thread-local storage (TLS) to create a separate copy of data for each thread, eliminating the need for synchronization in some cases.

  • Avoid Global Variables:

    • Minimize the use of global variables and shared resources whenever possible. Instead, use local variables or pass data explicitly between threads.

  • Immutable Data:

    • If feasible, design data structures to be immutable (unchangeable). Immutable data can be safely shared among threads without the risk of race conditions.

  • Thread-Safety Documentation:

    • Clearly document which functions, data structures, or objects are thread-safe and under what conditions. This helps developers understand how to use shared resources safely.

  • Concurrency Testing:

    • Implement thorough testing that includes concurrency testing, such as race condition detection tools, to identify and fix potential issues before they become security vulnerabilities.

  • Thorough Code Review:

    • Conduct thorough code reviews of your concurrent code to identify synchronization issues, inadequate locking, or potential race conditions.

  • Concurrency Patterns:

    • Familiarize yourself with and follow well-established concurrency design patterns, such as the Singleton pattern, to ensure safe access to shared resources.

References

CWE - CWE-362: Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition') (4.19.1)cwe.mitre.org

Race Condition Vulnerability - GeeksforGeeks

Race Condition