Linuxfoundation

In wlan STA driver, there is a possible out of bounds read due to an incorrect bounds check. This could lead to remote (proximal/adjacent) information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS09812521; Issue ID: MSV-3421.Show less

A vulnerability was found in docarray up to 0.40.1. It has been rated as critical. Affected by this issue is the function __getitem__ of the file /docarray/data/torch_dataset.py of the component Web API. The manipulation leads to improperly controlled modification of object prototype attributes ('prototype pollution'). The attack may be launched remotely. The exploit has been disclosed to the public and may be used. The vendor was contacted early about this disclosure but did not respond in any way.Show less

containerd is an open-source container runtime. A bug was found in the containerd's CRI implementation where containerd, starting in version 2.0.1 and prior to version 2.0.5, doesn't put usernamespaced containers under the Kubernetes' cgroup hierarchy, therefore some Kubernetes limits are not honored. This may cause a denial of service of the Kubernetes node. This bug has been fixed in containerd 2.0.5+ and 2.1.0+. Users should update to these versions to resolve the issue. As a workaround, disable usernamespaced pods in Kubernetes temporarily.Show less

containerd is a container runtime. A time-of-check to time-of-use (TOCTOU) vulnerability was found in containerd v2.1.0. While unpacking an image during an image pull, specially crafted container images could arbitrarily modify the host file system. The only affected version of containerd is 2.1.0. Other versions of containerd are not affected. This bug has been fixed in containerd 2.1.1. Users should update to this version to resolve the issue. As a workaround, ensure that only trusted images are used and that only trusted users have permissions to import images.Show less

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.Show less

A vulnerability, which was classified as problematic, was found in PyTorch 2.6.0. Affected is the function torch.nn.functional.ctc_loss of the file aten/src/ATen/native/LossCTC.cpp. 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 name of the patch is 46fc5d8e360127361211cb237d5f9eef0223e567. It is recommended to apply a patch to fix this issue. The security policy of the project warns to use unknown models which might establish malicious effects.Show less

In DA, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege, if an attacker has physical access to the device, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS09625423; Issue ID: MSV-3033.Show less

A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0. This issue affects the function torch.cuda.memory.caching_allocator_delete of the file c10/cuda/CUDACachingAllocator.cpp. The manipulation leads to memory corruption. An attack has to be approached locally. The exploit has been disclosed to the public and may be used.Show less

A vulnerability classified as problematic has been found in PyTorch 2.6.0. Affected is the function torch.jit.jit_module_from_flatbuffer. 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.Show less

A vulnerability classified as critical was found in PyTorch 2.6.0. This vulnerability affects the function torch.lstm_cell. The manipulation leads to memory corruption. The attack needs to be approached locally. The exploit has been disclosed to the public and may be used.Show less

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.Show less

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.Show less

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.Show less

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.Show less

containerd is an open-source container runtime. A bug was found in containerd prior to versions 1.6.38, 1.7.27, and 2.0.4 where containers launched with a User set as a `UID:GID` larger than the maximum 32-bit signed integer can cause an overflow condition where the container ultimately runs as root (UID 0). This could cause unexpected behavior for environments that require containers to run as a non-root user. This bug has been fixed in containerd 1.6.38, 1.7.27, and 2.04. As a workaround, ensure that only trusted images are used and that only trusted users have permissions to import images.Show less

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.Show less

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.Show less

In da, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure, if an attacker has physical access to the device, with no additional execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS09291294; Issue ID: MSV-2062.Show less