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
| Link | Resource |
|---|---|
| https://gist.github.com/shaoyuyoung/4bcefba4004f8271e64b5185c95a248a | Third Party Advisory |
| https://gist.github.com/shaoyuyoung/e636f2e7a306105b7e96809e2b85c28a | Third Party Advisory |
| https://github.com/pytorch/pytorch/compare/v2.6.0...v2.7.0 | Product |
| https://github.com/pytorch/pytorch/issues/142853 | Issue Tracking |
| https://github.com/pytorch/pytorch/pull/143460 | Issue Tracking Patch |
Configurations
History
No history.
Information
Published : 2025-09-25 15:16
Updated : 2025-10-03 17:56
NVD link : CVE-2025-46153
Mitre link : CVE-2025-46153
CVE.ORG link : CVE-2025-46153
JSON object : View
Products Affected
linuxfoundation
- pytorch
CWE
CWE-1176
Inefficient CPU Computation
