CVE-2025-23273 is a vulnerability identified in the NVIDIA CUDA Toolkit, specifically within the nvJPEG component responsible for JPEG image processing. This vulnerability is classified as a CWE-369 Divide By Zero error. It affects all versions of the CUDA Toolkit prior to version 13.0. The flaw arises when a local authenticated user submits a specially crafted JPEG file that triggers a divide by zero operation within the nvJPEG processing code. This results in a denial of service (DoS) condition, causing the affected application or system component to crash or become unresponsive. The vulnerability requires local authentication, meaning the attacker must have some level of access to the system to exploit it. No user interaction beyond submitting the malicious JPEG file is necessary. The CVSS v3.1 base score is 2.5, indicating a low severity primarily due to the limited impact scope (denial of service only), the requirement for local privileges, and the high attack complexity. There are no known exploits in the wild at the time of publication, and no official patches have been linked yet, though upgrading to CUDA Toolkit 13.0 or later is implied as a remediation step. This vulnerability does not impact confidentiality or integrity but affects availability by causing service disruption through a crash or hang triggered by the divide by zero error in image processing.

For European organizations utilizing NVIDIA CUDA Toolkit in their computing environments—particularly those involved in high-performance computing, AI research, scientific simulations, or image processing workflows—this vulnerability poses a risk of local denial of service. While the impact is limited to availability and does not compromise data confidentiality or integrity, disruption of critical GPU-accelerated workloads could affect operational continuity. Organizations relying on automated image processing pipelines or GPU-accelerated applications that handle JPEG files may experience unexpected crashes or service interruptions if an attacker with local access submits malicious JPEG files. This could lead to downtime, loss of productivity, and potential cascading effects in tightly integrated computational environments. However, the requirement for local authentication and the high complexity of exploitation reduce the likelihood of widespread impact. Nonetheless, environments with shared access or multi-user systems where users have local accounts could be more vulnerable to exploitation attempts.

European organizations should implement the following specific mitigation measures: 1) Upgrade to NVIDIA CUDA Toolkit version 13.0 or later as soon as it becomes available, as this version addresses the vulnerability. 2) Restrict local user privileges strictly to minimize the number of users who can execute or submit JPEG files to GPU-accelerated applications using nvJPEG. 3) Implement application-level input validation and sanitization for JPEG files before processing to detect and block malformed or suspicious images that could trigger the divide by zero error. 4) Monitor GPU-accelerated application logs and system stability metrics for signs of crashes or hangs related to image processing. 5) Employ endpoint security solutions that can detect anomalous local user behavior or attempts to exploit local vulnerabilities. 6) In multi-user environments, consider isolating GPU workloads per user or containerizing GPU applications to limit the blast radius of potential DoS attacks. 7) Maintain up-to-date backups and recovery procedures to minimize operational impact in case of service disruption.