1188 matches found
EUVD-2025-31127
Malicious code in bioql PyPI...
EUVD-2025-31133
Malicious code in bioql PyPI...
EUVD-2025-11856
Malicious code in bioql PyPI...
EUVD-2025-31109
Malicious code in bioql PyPI...
EUVD-2025-31131
Malicious code in bioql PyPI...
EUVD-2025-29442
Malicious code in bioql PyPI...
EUVD-2025-29476
Malicious code in bioql PyPI...
EUVD-2025-29365
Malicious code in bioql PyPI...
EUVD-2025-6954
Malicious code in bioql PyPI...
EUVD-2025-13418
Malicious code in bioql PyPI...
EUVD-2025-6932
Malicious code in bioql PyPI...
EUVD-2025-9636
Malicious code in bioql PyPI...
EUVD-2025-8856
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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