Linux Foundation The Linux Foundation PyTorch

PyTorch: `torch.load` with `weights_only=True` leads to remote code execution

In PyTorch <=2.4.1, the RemoteModule has Deserialization RCE. NOTE: this is disputed by multiple parties because this is intended behavior in PyTorch distributed computing.

In PyTorch before trunk/89695, torch.jit.annotations.parse_type_line can cause arbitrary code execution because eval is used unsafely.

PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files

Pytorch before version v2.2.0 was discovered to contain a use-after-free vulnerability in torch/csrc/jit/mobile/interpreter.cpp.

PyTorch pt2 Loading deserialization

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).

PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption

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

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

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 before v2.2.0 has an Out-of-bounds Read vulnerability via the component torch/csrc/jit/mobile/flatbuffer_loader.cpp.

PyTorch LossCTC.cpp torch.nn.functional.ctc_loss denial of service

PyTorch torch.jit.jit_module_from_flatbuffer memory corruption

PyTorch torch.mkldnn_max_pool2d denial of service

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

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.

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

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.

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

PyTorch torch.jit.script memory corruption

PyTorch torch.nn.utils.rnn.pad_packed_sequence memory corruption

PyTorch torch.nn.utils.rnn.unpack_sequence memory corruption

PyTorch torch.lstm_cell memory corruption

PyTorch CUDACachingAllocator.cpp torch.cuda.memory.caching_allocator_delete memory corruption

PyTorch before v2.2.0 was discovered to contain a heap buffer overflow vulnerability in the component /runtime/vararg_functions.cpp. This vulnerability allows attackers to cause a Denial of Service (DoS) via a crafted input.

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).

PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization