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CVE-2025-23272 (GCVE-0-2025-23272)

Vulnerability from cvelistv5 – Published: 2025-09-24 13:11 – Updated: 2025-09-24 18:44
VLAI
Summary
NVIDIA nvJPEG library contains a vulnerability where an attacker can cause an out-of-bounds read by means of a specially crafted JPEG file. A successful exploit of this vulnerability might lead to information disclosure or denial of service.
Severity
5.7 (Medium)
CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-09-24 18:44 UTC
CWE
Assigner
References
Impacted products
Vendor Product Version CPE status
NVIDIA NVIDIA CUDA Toolkit Affected: All versions prior to CUDA Toolkit 12.9 Update 1
guessed Create a notification for this product.
NVIDIA nvJPEG Affected: All versions prior to nvJPEG 25.03
guessed Create a notification for this product.
Show details on NVD website
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.


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Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.