CVE-2025-46153

MEDIUM
2025-09-25 [email protected]
5.3
CVSS 3.1
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CVSS Vector

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
Unchanged
Confidentiality
Low
Integrity
None
Availability
None

Lifecycle Timeline

3
Analysis Generated
Mar 28, 2026 - 19:14 vuln.today
Patch Released
Mar 28, 2026 - 19:14 nvd
Patch available
CVE Published
Sep 25, 2025 - 15:16 nvd
MEDIUM 5.3

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.

Analysis

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 Context

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.

Affected Products

Linuxfoundation Pytorch.

Remediation

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.

Priority Score

27
Low Medium High Critical
KEV: 0
EPSS: +0.1
CVSS: +26
POC: 0

Vendor Status

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CVE-2025-46153 vulnerability details – vuln.today

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