Medium severity · published Sep 25, 2025
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…
5.3
CVSS
0.4%
EPSS
No
On KEV
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 vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Confidentiality
Low
Integrity
None
Availability
None
Scope
Unchanged
Exploitation
Is it being used?
Exploit prediction (EPSS)0.4% · higher than 36% of CVEs
Exploited in the wildNo evidence yet
CISA KEVNot listed
Ransomware campaign useNot known
Affected products
Which versions
PY
Pytorch · Linuxfoundation
2.6.0 before 2.7.0 · source: NVD
References
NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-46153
CVE.org
https://www.cve.org/CVERecord?id=CVE-2025-46153
Third Party Advisory
https://gist.github.com/shaoyuyoung/4bcefba4004f8271e64b5185c95a248a
Third Party Advisory
https://gist.github.com/shaoyuyoung/e636f2e7a306105b7e96809e2b85c28a
Product
https://github.com/pytorch/pytorch/compare/v2.6.0...v2.7.0
Issue Tracking
https://github.com/pytorch/pytorch/issues/142853
Issue Tracking
https://github.com/pytorch/pytorch/pull/143460
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