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VulnerabilityPublished

CVE-2025-23273: NVIDIA CUDA Toolkit · Divide By Zero

Affects NVIDIA CUDA ToolkitSource CVE Database V5

0

Not known to be exploited · CVSS 2.5 Low : upgrade to 13.0 when convenient.

Data as of 26 Oct 2026, 14:05 UTC

CVSS 3.1 base score
2.5Low
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.1% chance of exploitation in 30 days – higher than 2% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 13.0
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 24 Sep 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Upgrade NVIDIA CUDA Toolkit to 13.0.

Affected software

ProductAffectedFixed in
NVIDIA NVIDIA CUDA ToolkitAffected
  • <13.0
Fixed in
  • 13.0

AI-suggested

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.

Description

NVIDIA CUDA Toolkit for all platforms contains a vulnerability in nvJPEG where a local authenticated user may cause a divide by zero error by submitting a specially crafted JPEG file. A successful exploit of this vulnerability may lead to denial of service.

References

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