Vulnerabilities

A vulnerability was identified in PyTorch 2.10.0.

PyTorch is a Python package that provides tensor computation.

An issue was discovered in PyTorch v2.5 and v2.7.1.

An issue in pytorch v2.7.0 can lead to a Denial of Service (DoS) when a PyTorch model consists of torch.Tensor.to_sparse() and torch.Tensor.to_dense() and is compiled by Inductor.

A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tensor.view-torch.mv() and is compiled by Inductor, leading to a Denial of Service (D…

A Name Error occurs in pytorch v2.7.0 when a PyTorch model consists of torch.cummin and is compiled by Inductor, leading to a Denial of Service (DoS).

pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nan_to_num-.long().

A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).

pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.

An issue in the component torch.linalg.lu of pytorch v2.8.0 allows attackers to cause a Denial of Service (DoS) when performing a slice operation.

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 fo…

In PyTorch before 2.7.0, bitwise_right_shift produces incorrect output for certain out-of-bounds values of the "other" argument.

In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results.

In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error.

In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistance(p=2) produces incorrect results.

PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system.

A vulnerability, which was classified as problematic, was found in PyTorch 2.6.0.

A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0.

A vulnerability classified as problematic has been found in PyTorch 2.6.0.

A vulnerability classified as critical was found in PyTorch 2.6.0.

A vulnerability classified as critical has been found in PyTorch 2.6.0.

A vulnerability was found in PyTorch 2.6.0.

A vulnerability was found in PyTorch 2.6.0.

A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124.

A vulnerability was found in PyTorch 2.6.0+cu124.