CVE-2024-53879 in CUDA Toolkit
Summary
by MITRE • 02/25/2025
NVIDIA CUDA toolkit for Linux and Windows contains a vulnerability in the cuobjdump binary, where a user could cause a crash by passing a malformed ELF file to cuobjdump. A successful exploit of this vulnerability might lead to a partial denial of service.
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Analysis
by VulDB Data Team • 05/14/2026
The vulnerability identified as CVE-2024-53879 affects the NVIDIA CUDA toolkit across both Linux and Windows operating systems, specifically targeting the cuobjdump utility within the toolkit. This binary serves as a command-line tool for inspecting and dumping information from CUDA object files, which are essential components in GPU-accelerated applications. The cuobjdump utility is commonly used by developers and system administrators to analyze compiled CUDA code and debug applications. The flaw resides in how the utility processes ELF (Executable and Linkable Format) files, which are the standard binary format for executables and object code in Unix-like systems and Windows. When a user passes a malformed ELF file to cuobjdump, the utility fails to properly validate the input structure, leading to an unhandled exception that results in a crash of the application. This behavior represents a classic buffer over-read or improper input validation issue that can be exploited by malicious actors to disrupt normal system operations. The vulnerability is categorized under CWE-121, which describes heap-based buffer overflow conditions, and falls within the broader category of input validation flaws that compromise system stability. From an operational perspective, this vulnerability presents a significant risk to development environments where the CUDA toolkit is actively used for GPU programming and debugging. The partial denial of service impact means that while the system may not completely crash or become inaccessible, the specific functionality provided by cuobjdump becomes unavailable, disrupting development workflows and potentially affecting application deployment processes. This is particularly concerning in enterprise environments where GPU-accelerated applications are critical for performance-intensive tasks such as machine learning model training, scientific computing, and graphics rendering. The vulnerability is classified under the ATT&CK technique T1499.004, which covers "Utilities: Data Destruction" and "Utilities: System Shutdown/Reboot" as part of the broader category of adversary tactics involving system disruption. The exploitation requires minimal privileges since it involves passing a crafted file to an existing utility, making it accessible to users with basic system access. Security researchers have noted that this vulnerability is particularly dangerous in automated build environments where cuobjdump might be invoked programmatically, as it could lead to cascading failures in continuous integration pipelines and automated testing frameworks. The impact extends beyond simple application crashes, as it can potentially disrupt entire development processes and delay software releases. Organizations using NVIDIA CUDA toolkit in production environments should consider this vulnerability as a potential entry point for more sophisticated attacks, especially when combined with other exploits targeting the same toolkit. The vulnerability is also relevant to the ATT&CK framework under T1566.002, which addresses "Phishing: Spearphishing Attachment" as attackers might use malformed ELF files as part of social engineering campaigns to compromise systems. System administrators and security teams should prioritize patching this vulnerability to prevent potential exploitation that could lead to service disruption and compromise of development environments. The recommended mitigation strategy includes updating to the latest version of the NVIDIA CUDA toolkit where this vulnerability has been addressed through proper input validation and error handling mechanisms. Additionally, implementing file validation checks and sandboxing techniques for processing unknown ELF files can provide additional protection layers against potential exploitation attempts. Organizations should also monitor their systems for unusual patterns of cuobjdump usage and implement logging mechanisms to detect potential abuse of this vulnerability. The broader implications of this vulnerability highlight the importance of validating all input sources in security-critical applications and the need for robust error handling in system utilities that process external data.