Pytorch
CVE-2025-46153
MEDIUM
Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
Primary rating from NVD.
CVSS VectorNVD
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
Lifecycle Timeline
3Blast Radius
ecosystem impact- 331 pypi packages depend on torch (291 direct, 42 indirect)
Ecosystem-wide dependent count for version 2.6.0.
DescriptionCVE.org
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.
AnalysisAI
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,. Rated medium severity (CVSS 5.3), this vulnerability is remotely exploitable, no authentication required, low attack complexity.
Technical ContextAI
This vulnerability is classified under CWE-1176. 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. Affected products include: Linuxfoundation Pytorch. Version information: before 3.7.0.
RemediationAI
A vendor patch is available. Apply the latest security update as soon as possible. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.
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Same technique Information Disclosure
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SUSE
Severity: MediumShare
External POC / Exploit Code
Leaving vuln.today