PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
Fixes

Solution

No solution given by the vendor.


Workaround

No workaround given by the vendor.

History

Thu, 25 Sep 2025 19:15:00 +0000

Type Values Removed Values Added
Weaknesses CWE-1176
Metrics cvssV3_1

{'score': 5.3, 'vector': 'CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N'}

ssvc

{'options': {'Automatable': 'no', 'Exploitation': 'none', 'Technical Impact': 'partial'}, 'version': '2.0.3'}


Thu, 25 Sep 2025 14:30:00 +0000

Type Values Removed Values Added
Description PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
References

cve-icon MITRE

Status: PUBLISHED

Assigner: mitre

Published:

Updated: 2025-09-25T18:33:13.153Z

Reserved: 2025-04-22T00:00:00.000Z

Link: CVE-2025-46153

cve-icon Vulnrichment

Updated: 2025-09-25T18:32:30.058Z

cve-icon NVD

Status : Received

Published: 2025-09-25T15:16:12.603

Modified: 2025-09-25T19:15:46.473

Link: CVE-2025-46153

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

No data.