CVE-2024-0102 in CUDA Toolkit
Summary
by MITRE • 08/08/2024
NVIDIA CUDA Toolkit for all platforms contains a vulnerability in nvdisasm, where an attacker can cause an out-of-bounds read issue by deceiving a user into reading a malformed ELF file. A successful exploit of this vulnerability might lead to denial of service.
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Analysis
by VulDB Data Team • 09/17/2024
The vulnerability identified as CVE-2024-0102 affects the NVIDIA CUDA Toolkit across all supported platforms and specifically targets the nvdisasm component. This tool serves as a disassembler for NVIDIA CUDA binaries and is commonly used by developers and security researchers for analyzing compiled CUDA code. The flaw resides in how nvdisasm processes ELF (Executable and Linkable Format) files, which are the standard binary format used by Unix-like operating systems and many embedded systems. When an attacker crafts a malformed ELF file and convinces a user to process it through nvdisasm, the tool fails to properly validate the file structure before attempting to read memory regions beyond the intended boundaries.
This out-of-bounds read vulnerability stems from inadequate input validation within the nvdisasm utility's ELF parsing routines. The flaw allows an attacker to manipulate the parsing logic by providing specially crafted ELF headers or sections that cause the disassembler to attempt memory accesses outside of the allocated buffer boundaries. Such memory access violations typically result in segmentation faults or access violations that terminate the application process, leading to a denial of service condition. The vulnerability is particularly concerning because it requires minimal privileges to exploit and can be triggered through simple user interaction with a malicious file. The attack vector relies on social engineering techniques where users are deceived into opening or processing a crafted ELF file through the nvdisasm tool, making it difficult to defend against through traditional network-based security controls.
The operational impact of CVE-2024-0102 extends beyond simple denial of service scenarios as it represents a potential gateway for more sophisticated attacks. While the immediate effect is system availability disruption, the vulnerability could serve as a stepping stone for attackers seeking to establish persistent access or escalate privileges within systems running affected CUDA toolkits. The vulnerability maps to CWE-125, which describes out-of-bounds read conditions in software, and aligns with ATT&CK technique T1059.007 for command and scripting interpreter, as attackers might leverage this vulnerability to disrupt legitimate development workflows. Organizations using NVIDIA CUDA toolkits for scientific computing, machine learning development, or graphics processing are particularly at risk since these environments often involve extensive use of disassembly tools and binary analysis. The vulnerability affects all platforms supported by NVIDIA CUDA Toolkit including Windows, Linux, and macOS systems, making it a cross-platform threat that requires comprehensive remediation across entire development ecosystems.
Mitigation strategies for CVE-2024-0102 should focus on immediate patch application from NVIDIA, which typically addresses the root cause through improved input validation and bounds checking in the nvdisasm component. System administrators should implement strict file validation policies for any ELF files processed through CUDA toolchains and consider sandboxing execution environments for binary analysis activities. Network segmentation and access controls should be enforced to limit exposure of systems running affected toolkits to untrusted file processing scenarios. Additionally, security monitoring should be enhanced to detect abnormal process termination patterns or memory access violations associated with nvdisasm usage, as these could indicate exploitation attempts. Organizations should also consider implementing automated vulnerability scanning tools that can detect and alert on potentially malicious ELF files before they are processed by development tools, thereby reducing the attack surface and protecting against both current and future exploitation attempts targeting similar parsing vulnerabilities in similar software components.