CVE-2025-2953
MEDIUMCVSS Vector
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Lifecycle Timeline
4Description
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects.
Analysis
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Rated medium severity (CVSS 4.8), this vulnerability is low attack complexity. Public exploit code available and no vendor patch available.
Technical Context
This vulnerability is classified under CWE-404. A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects. Affected products include: Linuxfoundation Pytorch.
Affected Products
Linuxfoundation Pytorch.
Remediation
No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.
Priority Score
Vendor Status
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External POC / Exploit Code
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