The vulnerability of the bernoulli_p function in the decompose() function of the PyTorch machine learning framework allows attackers to compromise the confidentiality of the protected information.

The vulnerability of the bernoullip function in the PyTorch machine learning framework’s decompose method is related to inefficient calculations by the central processor. Exploiting this vulnerability could allow a malicious actor to compromise the confidentiality of the protected information...

Unspecified Vulnerability in PyTorch (CNVD-2025-23286)

PyTorch is a Python package open-sourced by PyTorch. PyTorch suffers from a security vulnerability that stems from an inconsistency between the bernoullip decomposition function and the CPU implementation, no details of the vulnerability are provided at this time...

Inefficient CPU Computation

Overview torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration Affected versions of this package are vulnerable to Inefficient CPU Computation due to inconsistent behavior in the bernoullip function when used in RNG nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d. An...

Inefficient CPU Computation

Overview Affected versions of this package are vulnerable to Inefficient CPU Computation due to inconsistent behavior in the bernoullip function when used in RNG nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d. An attacker can cause unintended or incorrect dropout behavior in neural network layers b...