VulnerabilityAnalyzed
CVE-2025-46153
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.
MEDIUM 5.3EPSS 0.42%
Does this matter?
Lower severity and a low EPSS score (0.42%). Track it; it rarely justifies an emergency change on its own.
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.
- CVSS 3.1
- 5.3 MEDIUMCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
- EPSS
- 0.42% probability · 35th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-1176
- Affected
- linuxfoundation/pytorch
- Source
- cve@mitre.org
References
- https://gist.github.com/shaoyuyoung/4bcefba4004f8271e64b5185c95a248aThird Party Advisory
- https://gist.github.com/shaoyuyoung/e636f2e7a306105b7e96809e2b85c28aThird Party Advisory
- https://github.com/pytorch/pytorch/compare/v2.6.0...v2.7.0Product
- https://github.com/pytorch/pytorch/issues/142853Issue Tracking
- https://github.com/pytorch/pytorch/pull/143460Issue Tracking, Patch
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.