CRITICAL9.8CVE-2025-32434PyTorch: `torch.load` with `weights_only=True` leads to remote code execution from 0, < 2.6.0
CRITICAL9.8CVE-2025-32434PyTorch: `torch.load` with `weights_only=True` leads to remote code execution from 0, < 2.6.0
CRITICAL9.8CVE-2024-48063In PyTorch <=2.4.1, the RemoteModule has Deserialization RCE. from 0, < 2.5.0
CRITICAL9.8PyTorch vulnerable to arbitrary code execution
from 0, < 1.13.1
CRITICAL9.8PyTorch vulnerable to arbitrary code execution
from 0, < 767f6aa49fe20a2766b9843d01e3b7f7793df6a3 | from 0, < 1.13.1
HIGH8.8PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files
from 0, < 2.10.0
HIGH7.8PyTorch pt2 Loading deserialization
from 0, <= 2.10.0
HIGH7.8Pytorch use-after-free vulnerability
from 0, < 2.2.0
HIGH7.8Pytorch use-after-free vulnerability
from 0, < 9c7071b0e324f9fb68ab881283d6b8d388a4bcd2, < 9c7071b0e324f9fb68ab881283d6b8d388a4bcd2 | from 0, < 2.2.0
HIGH7.5An 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…
from 0, < 2.7.1
HIGH7.5A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tens…
from 0, < 2.7.1
HIGH7.5A 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 Ser…
from 0, < 2.7.1
HIGH7.5A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).
from 0, < 2.7.1
HIGH7.5pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.
from 0, < 2.9.0
HIGH7.5An 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 ope…
from 0, < 2.9.0
HIGH7.5PyTorch heap buffer overflow vulnerability
from 0, < 2.2.0
HIGH7.5PyTorch heap buffer overflow vulnerability
from 0, < b5c3a17c2c207ebefcb85043f0cf94be9b2fef81, < b5c3a17c2c207ebefcb85043f0cf94be9b2fef81 | from 0, < 2.2.0
MEDIUM5.5PyTorch torch.jit.jit_module_from_flatbuffer memory corruption
from 0, <= 2.6.0-NA
MEDIUM5.5Pytorch before v2.2.0 has an Out-of-bounds Read vulnerability via the component torch/csrc/jit/mobile/flatbuffer_loader.cpp.
from 0, < 7c35874ad664e74c8e4252d67521f3986eadb0e6, < 7c35874ad664e74c8e4252d67521f3986eadb0e6 | from 0, < 2.2.0
MEDIUM5.3pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nan_to_num-.long().
from 0, < 2.9.0
MEDIUM5.3PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU imp…
>= 2.6.0, < 2.7.0
MEDIUM5.3In PyTorch before 2.7.0, bitwise_right_shift produces incorrect output for certain out-of-bounds values of the "other" argument.
>= 2.6.0, < 2.7.0
MEDIUM5.3In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results.
>= 2.6.0, < 2.7.0
MEDIUM5.3In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error.
>= 2.6.0, < 2.7.0
MEDIUM5.3In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistance(p=2) produces incorrect results.
from 0, < 2.7.0
MEDIUM5.3PyTorch torch.nn.utils.rnn.pad_packed_sequence memory corruption
from 0, <= 2.6.0
MEDIUM5.3PyTorch torch.nn.utils.rnn.pad_packed_sequence memory corruption
from 0, <= 2.6.0-NA
MEDIUM5.3PyTorch torch.jit.script memory corruption
from 0, < 2.13.0
MEDIUM5.0PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption
from 0, <= 2.6.0
MEDIUM5.0PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption
from 0, <= 2.6.0-cu124
LOW3.3An issue was discovered in PyTorch v2.5 and v2.7.1.
from 0, <= 2.5.0-NA, <= 2.7.1-NA
LOW3.3PyTorch LossCTC.cpp torch.nn.functional.ctc_loss denial of service
from 0, < 2.8.0
LOW3.3PyTorch torch.mkldnn_max_pool2d denial of service
from 0, < 2.7.1-rc1
LOW3.3PyTorch torch.mkldnn_max_pool2d denial of service
from 0, <= 2.6.0+cu124
LOW2.5PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization
from 0, <= 2.6.0
LOW2.5PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization
from 0, <= 2.6.0-cu124
—PyTorch CUDACachingAllocator.cpp torch.cuda.memory.caching_allocator_delete memory corruption
from 0, <= 2.6.0-NA
—PyTorch torch.lstm_cell memory corruption
from 0, <= 2.6.0-NA
—PyTorch torch.nn.utils.rnn.unpack_sequence memory corruption
from 0, <= 2.6.0-NA