CVE-2023-4211 is a security vulnerability found in the processing of GPU (Graphics Processing Unit) memory where a local non-privileged user can gain access to already freed memory. This can lead to unintended information disclosure, manipulation of data, and potentially result in privilege escalation. In this post, we will dive into the technical details of this vulnerability and demonstrate how it can be exploited.

Understanding the vulnerability

The issue lies within the GPU memory processing, where specific operations are performed for rendering graphics and compute tasks. When allocating and deallocating memory, an error in the handling of these operations allows the affected user to access the memory even after it has been freed. The improper handling occurs when calling specific system APIs that interact with the GPU.

Here's a code snippet demonstrating the vulnerability

// Allocating GPU memory
void *gpu_mem_ptr;
cudaError_t cuda_err = cudaMalloc(&gpu_mem_ptr, size);

// Processing the allocated memory
processGPUmemory(gpu_mem_ptr);

// Freeing the GPU memory
cuda_err = cudaFree(gpu_mem_ptr);

// Trying to access freed memory (vulnerable operation)
processGPUmemory(gpu_mem_ptr);

Exploiting the vulnerability

Suppose an attacker manages to inject malicious code into a running application on the victim's system. By exploiting this vulnerability, the attacker can access and manipulate previously freed GPU memory, gaining access to sensitive information and potentially using this information for further privilege escalation.

Here's an example of how this exploit can be executed

// Attacker's malicious code
void processGPUmemory(void *gpu_mem_ptr) {
    // Accessing freed GPU memory
    dst_data = accessFreedMemory(gpu_mem_ptr);

    // Using the captured data for further exploitation
    escalatePrivileges(dst_data);
}

Possible attack scenarios include gaining user credentials stored in GPU memory, accessing confidential data from other applications, and even taking control of the affected system by executing arbitrary code.

Mitigation and recommendations

To prevent this vulnerability, it's essential to ensure proper handling of the GPU memory during allocation and deallocation. Developers should utilize the proper GPU programming interfaces, such as CUDA, OpenCL, or Vulkan, and follow the best practices of resource management. Additionally, introducing memory sanitization techniques to erase the contents of the freed memory blocks can also mitigate the risk of information disclosure.

For more information about CVE-2023-4211, please refer to the following resources

1. "NVD - CVE-2023-4211"
2. "Security Advisory for GPU Memory Processing Vulnerability"

Conclusion

CVE-2023-4211 highlights the potential risks associated with GPU memory handling and the importance of implementing proper security measures during all stages of code execution. Developers should be vigilant in following best practices and ensuring their applications are secure against vulnerabilities like CVE-2023-4211.

Timeline

Published on: 10/01/2023 18:15:00 UTC
Last modified on: 10/04/2023 20:51:00 UTC