CVE-2025-46153
mediumpriority · track · 0EPSS 0.004 · 36 %ileDEEURUUSEPSS · scored 2026-10-27
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
Technical severity, 0–10. One row per scoring source.
base score 0–10 · higher = more severe · hover a vector to decode
ssvc
A stakeholder decision — act, attend, or track — from exploitation and impact.
weaknesses
The CWE weakness classes this flaw belongs to.
affected products (11)
Products and version ranges known to be affected.
advisories (3)
Vendor and ecosystem advisories describing this.
- WID-SEC-W-2025-2139PyTorch: Mehrere SchwachstellenDeutsch2025-09-25csaf · cert_bundDE
Ein Angreifer kann mehrere Schwachstellen in PyTorch ausnutzen, um Informationen offenzulegen, einen Denial-of-Service-Zustand zu erzeugen oder andere nicht näher spezifizierte Angriffe durchzuführen.
- BIT-pytorch-2025-461532025-10-05vendor · osvUS
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.
- PYSEC-2025-2022025-09-25vendor · osvUS
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.
also known as (7)
Other names and identifiers for this entity.
sources
Which sources assert this record, and when.
references (16)
External citations — patches, advisories, analysis.
- https://gist.github.com/shaoyuyoung/4bcefba4004f8271e64b5185c95a248acnnvd
- https://gist.github.com/shaoyuyoung/e636f2e7a306105b7e96809e2b85c28acnnvd
- https://github.com/pytorch/pytorch/compare/v2.6.0...v2.7.0cnnvd
- https://github.com/pytorch/pytorch/issues/142853cnnvd
- https://github.com/pytorch/pytorch/pull/143460cnnvd
- https://pytorch.org/get-started/previous-versions/?ajs_aid=277996d0-7b09-4ed6-9cea-e4ec582778fbPatchcnnvd
- https://gist.github.com/shaoyuyoung/4bcefba4004f8271e64b5185c95a248aenisa_euvd
- https://gist.github.com/shaoyuyoung/e636f2e7a306105b7e96809e2b85c28aenisa_euvd
Attackers weaponise vulnerabilities like this against internet-exposed services. See what is exposed on your perimeter with a free passive scan.
Free scan