CVE-2025-23255 is a security vulnerability identified in the NVIDIA CUDA Toolkit, specifically affecting the cuobjdump binary component across all platforms. The vulnerability is classified as a CWE-125: Out-of-bounds Read. It occurs when an attacker supplies a malformed ELF (Executable and Linkable Format) file to the cuobjdump utility, which is used for dumping CUDA binary objects. This malformed input causes the program to read memory outside the intended buffer boundaries. While this out-of-bounds read does not directly lead to code execution or data leakage, it can cause instability in the cuobjdump process, resulting in a partial denial of service (DoS) condition. The vulnerability affects all versions of the CUDA Toolkit prior to version 13.0. The CVSS v3.1 base score is 3.3, indicating a low severity level. The attack vector is local (AV:L), requiring the attacker to have local access to the system, and user interaction is required (UI:R), meaning the user must run or trigger the malformed ELF file with cuobjdump. No privileges are required (PR:N), and the impact is limited to availability (A:L) with no confidentiality or integrity impact. There are no known exploits in the wild at the time of publication, and no official patches have been linked yet. This vulnerability primarily poses a risk to environments where cuobjdump is used to analyze or debug CUDA binaries, such as development or research settings involving GPU-accelerated computing.

For European organizations, the impact of CVE-2025-23255 is generally limited due to the low severity and local attack vector. However, organizations heavily reliant on GPU-accelerated computing for scientific research, artificial intelligence, machine learning, or high-performance computing (HPC) may experience disruptions if this vulnerability is exploited. A partial denial of service in cuobjdump could interrupt debugging or analysis workflows, potentially delaying development cycles or research outputs. Since the vulnerability requires local access and user interaction, the risk of remote exploitation is minimal, reducing the threat surface for most enterprises. Nonetheless, in environments where multiple users share GPU resources or where untrusted users have local access, there is a risk of intentional disruption. The lack of confidentiality or integrity impact means sensitive data is unlikely to be compromised directly by this vulnerability. Overall, the operational impact is moderate in niche use cases but low for general enterprise environments.

European organizations using NVIDIA CUDA Toolkit should upgrade to version 13.0 or later as soon as it becomes available to remediate this vulnerability. Until an official patch is released, organizations should implement strict access controls to limit local user access to systems running CUDA Toolkit, especially restricting the execution of cuobjdump to trusted users only. Monitoring and auditing usage of cuobjdump can help detect anomalous or unauthorized attempts to process malformed ELF files. Additionally, sandboxing or containerizing the CUDA development environment can contain potential crashes caused by malformed inputs, minimizing disruption to other system components. Educating developers and users about the risks of processing untrusted ELF files with cuobjdump is also advisable. Finally, maintaining up-to-date endpoint protection and system integrity monitoring can help detect and respond to any attempts to exploit this or related vulnerabilities.