Linuxfoundation Pytorch vulnerabilities
31 vulnerabilities
Known vulnerabilities in Linuxfoundation Pytorch, newest first, with CVSS severity, EPSS, KEV listings, ransomware use and the affected versions.
CVE-2025-63396debianpytorch+3
EPSS score0.13%
An issue was discovered in PyTorch v2.5 and v2.7.1. Omission of profiler.stop() can cause torch.profiler.profile (PythonTracer) to crash or hang during finalization, leading to a Denial of Service (DoS).CVE-2025-2999chainguardpy3.10-torch-2.3-cuda-12.4+13EPSS score0.20%
A vulnerability was found in PyTorch 2.6.0. It has been rated as critical. Affected by this issue is the function torch.nn.utils.rnn.unpack_sequence. The manipulation leads to memory corruption. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used.CVE-2025-2149chainguardpy3.10-torch-2.3-cuda-12.4+8EPSS score0.26%
A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point leads to improper initialization. The attack needs to be approached locally. The complexity of an attack is rather high. The exploitation is known to be difficult. The exploit has been disclosed to the public and may be used.CVE-2025-2148chainguardpy3.10-torch-2.3-cuda-12.4+8EPSS score0.44%
A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler._call_end_callbacks_on_jit_fut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult.CVE-2025-2953chainguardlibtorch-cuda-12.4+42EPSS score0.26%
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects.CVE-2025-2998chainguardpy3.10-torch-2.3-cuda-12.4+8EPSS score0.20%
A vulnerability was found in PyTorch 2.6.0. It has been declared as critical. Affected by this vulnerability is the function torch.nn.utils.rnn.pad_packed_sequence. The manipulation leads to memory corruption. Local access is required to approach this attack. The exploit has been disclosed to the public and may be used.CVE-2025-55551debianpytorch+3EPSS score0.42%
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.CVE-2025-55560debianpytorch+3EPSS score0.41%
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.CVE-2025-55558debianpytorch+3EPSS score0.45%
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).CVE-2025-55553debianpytorch+3EPSS score0.41%
A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).CVE-2025-55552debianpytorch+3EPSS score0.42%
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.CVE-2025-55554debianpytorch+3EPSS score0.32%
pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nan_to_num-.long().CVE-2025-55557debianpytorch+3EPSS score0.41%
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).CVE-2025-46149debianpytorch+3EPSS score0.36%
In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error.CVE-2025-46148debianpytorch+3EPSS score0.40%
In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistance(p=2) produces incorrect results.CVE-2025-46152debianpytorch+3EPSS score0.45%
In PyTorch before 2.7.0, bitwise_right_shift produces incorrect output for certain out-of-bounds values of the "other" argument.CVE-2025-46153debianpytorch+3EPSS score0.42%
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.CVE-2025-46150debianpytorch+3EPSS score0.39%
In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results.CVE-2025-32434chainguardpy3.10-torch-2.3-cuda-12.4+4EPSS score2.37%
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.CVE-2025-3000chainguardkserve-huggingfaceserver-cuda-13.3+55EPSS score0.20%
A vulnerability classified as critical has been found in PyTorch 2.6.0. This affects the function torch.jit.script. The manipulation leads to memory corruption. It is possible to launch the attack on the local host. The exploit has been disclosed to the public and may be used.