1373 matches found
EUVD-2025-11856
Malicious code in bioql PyPI...
EUVD-2025-29365
Malicious code in bioql PyPI...
EUVD-2025-6932
Malicious code in bioql PyPI...
EUVD-2025-11538
Malicious code in bioql PyPI...
EUVD-2025-31131
Malicious code in bioql PyPI...
EUVD-2022-0222
Malicious code in bioql PyPI...
EUVD-2024-2191
Malicious code in bioql PyPI...
EUVD-2024-1105
Malicious code in bioql PyPI...
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.
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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 (DoS).
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In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results.
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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).
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In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error.
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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.
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A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).
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SUSE CVE-2025-46148
In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistancep=2 produces incorrect results...
SUSE CVE-2025-46149
In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error...
SUSE CVE-2025-46150
In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results...
SUSE CVE-2025-46153
PyTorch before 3.7.0 has a bernoullip 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 fallbackrandom=True...