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VulnerabilityPublished Updated

CVE-2025-2953: PyTorch 2.6.0+cu124

Affects pytorchSource GCVE Database

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Not known to be exploited · CVSS 5.5 Medium.

Data as of 6 Nov 2026, 15:10 UTC

CVSS 3.1 base score
5.5Medium
How severe the flaw is on the 0–10 CVSS scale.
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 30 Mar 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: 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 6 Nov 2026.

What to do

Affected software

ProductAffectedFixed in
Ubuntu 26.10pytorchpkg:deb/ubuntu/pytorch?arch=source&distro=stonkingOther threatsAffected
  • =2.9.1+dfsg-1~exp1ubuntu2
  • =2.12.1+dfsg-1
Fixed in–
Ubuntu 25.10pytorchpkg:deb/ubuntu/pytorch?arch=source&distro=questingOther threatsAffected
  • =2.6.0+dfsg-5build1
  • =2.6.0+dfsg-7
Fixed in–
Ubuntu 22.04 LTSpytorchpkg:deb/ubuntu/pytorch?arch=source&distro=jammyOther threatsAffected
  • =1.7.1-7
  • =1.8.1-4
Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Users should follow the PyTorch security policy advice to avoid using unknown or untrusted models that might cause malicious effects.

Description

A denial of service vulnerability has been identified in PyTorch 2.6.0+cu124 affecting the function torch.mkldnn_max_pool2d. The issue requires local access to exploit and has a medium severity rating. Public exploit code exists, but the actual existence of the vulnerability is currently uncertain. The PyTorch project advises caution when using unknown models due to potential malicious effects.

References

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