CVE-2025-23339 identifies a stack-based buffer overflow vulnerability in the cuobjdump utility of the NVIDIA CUDA Toolkit, a widely used platform for GPU-accelerated computing across multiple operating systems. The vulnerability arises when cuobjdump processes a maliciously crafted ELF (Executable and Linkable Format) file, leading to a stack overflow condition. This overflow can corrupt the stack, potentially allowing an attacker to execute arbitrary code with the privileges of the user running cuobjdump. Exploitation requires local access and user interaction, specifically the user running cuobjdump on the malicious file. The vulnerability affects all versions of the CUDA Toolkit prior to 13.0, which means any environment running older versions is susceptible. The CVSS 3.1 base score is 3.3, reflecting low severity primarily because the attack vector is local (AV:L), requires low attack complexity (AC:L), no privileges (PR:N), but does require user interaction (UI:R). The impact is limited to confidentiality, with no direct impact on integrity or availability. No public exploits have been reported, and no patches are linked yet, but upgrading to CUDA Toolkit 13.0 or later is the recommended remediation. Given the specialized nature of cuobjdump, typically used by developers and researchers analyzing CUDA binaries, the threat surface is limited but non-negligible in environments relying on GPU computing.

For European organizations, the impact of this vulnerability is primarily on confidentiality and potentially on the integrity of local systems where the CUDA Toolkit is used. Organizations involved in high-performance computing, AI research, scientific simulations, and other GPU-accelerated workloads may be at risk if users run cuobjdump on untrusted ELF files. Exploitation could lead to arbitrary code execution under the user's privileges, potentially allowing attackers to escalate further if combined with other vulnerabilities. However, since exploitation requires local access and user interaction, the risk of widespread remote compromise is low. Still, in environments with shared workstations or insufficient user training, the vulnerability could be leveraged for lateral movement or privilege escalation. The absence of known exploits in the wild reduces immediate risk but does not eliminate it. The vulnerability may also affect supply chain security if malicious ELF files are introduced via third-party code or libraries.

European organizations should prioritize upgrading all installations of the NVIDIA CUDA Toolkit to version 13.0 or later as soon as it becomes available. Until then, restrict access to the cuobjdump utility to trusted users only, ideally limiting execution permissions to minimize exposure. Implement strict file validation and scanning policies to prevent users from running cuobjdump on untrusted or unknown ELF files. Educate users about the risks of processing untrusted binaries and enforce least privilege principles to reduce the impact of potential exploitation. Network segmentation and endpoint protection solutions can help detect anomalous behavior if exploitation attempts occur. Additionally, monitor for unusual execution of cuobjdump and audit user activities related to GPU development tools. Organizations should also maintain up-to-date vulnerability management processes to quickly apply patches once released.