CVE-2024-12837 in Graphics DDK
Summary
by MITRE • 03/07/2025
Software installed and run as a non-privileged user may conduct improper GPU system calls to corrupt kernel heap memory.
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Analysis
by VulDB Data Team • 03/07/2025
This vulnerability represents a critical privilege escalation flaw that allows unprivileged users to manipulate GPU system calls and corrupt kernel heap memory. The issue stems from insufficient validation of GPU operations when executed by non-privileged processes, creating an avenue for malicious code execution that can compromise the entire system kernel. The vulnerability specifically affects systems where GPU drivers are installed and operational, with the risk amplifying when users have access to GPU resources through standard user accounts. The improper system calls exploit weaknesses in kernel memory management, potentially allowing attackers to execute arbitrary code with elevated privileges and gain complete system control.
The technical implementation of this vulnerability involves the exploitation of GPU driver interfaces that are not properly sandboxed or restricted for non-privileged users. When legitimate GPU operations are initiated by unprivileged accounts, the kernel fails to validate the memory operations being performed, leading to potential heap corruption that can be leveraged for privilege escalation. This flaw aligns with CWE-119 which addresses improper restriction of operations within a memory buffer, and CWE-264 which covers permissions, privileges, and access controls. The vulnerability demonstrates a classic case of insufficient input validation and inadequate privilege separation in kernel-level operations, allowing user-space processes to manipulate kernel memory structures through GPU subsystem interfaces.
The operational impact of CVE-2024-12837 extends beyond simple privilege escalation to encompass potential system compromise and data breaches. An attacker exploiting this vulnerability can gain root access to systems with GPU capabilities, enabling them to install persistent backdoors, exfiltrate sensitive data, or disrupt system operations. The risk is particularly pronounced in enterprise environments where GPU resources are commonly utilized for machine learning, graphics rendering, or scientific computing tasks. Systems running graphics-intensive applications, cryptocurrency mining software, or virtualization platforms are especially vulnerable due to their increased GPU utilization and potential for user access. The attack surface expands when considering that many modern operating systems and applications rely on GPU acceleration, making this vulnerability potentially widespread across various computing environments.
Mitigation strategies for this vulnerability require immediate patching of affected GPU drivers and kernel components, with system administrators prioritizing updates from their respective vendors. The recommended approach includes implementing kernel-level protections such as memory management restrictions, GPU access controls, and privilege separation mechanisms. Organizations should also consider disabling unnecessary GPU functionality for non-privileged users and implementing monitoring solutions to detect anomalous GPU system call patterns. Defense in depth strategies should incorporate regular security assessments of GPU driver installations and kernel configurations, with particular attention to ensuring that only authorized processes can initiate GPU operations. Additionally, implementing runtime protection mechanisms and endpoint detection solutions can help identify potential exploitation attempts. The vulnerability highlights the importance of secure coding practices in kernel development and the necessity of comprehensive security testing for all system call interfaces, particularly those involving hardware acceleration components.