CVE-2026-31239

The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.frompretrained method uses torch.load to load the pytorchmodel.bin weight file without enabling the security-restrictive...

PT-2026-45457

An issue in ESA AnomalyMatch before 1.3.1 allow attackers to execute arbitrary code via crafted model checkpoint files. The affected components load model files from session directories using torch.load with unrestricted deserialization...

CVE-2025-51480 affecting package pytorch for versions less than 2.2.2-15

CVE-2025-51480 affecting package pytorch for versions less than 2.2.2-15. A patched version of the package is available...

CVE-2026-31218

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 is vulnerable to insecure deserialization CWE-502. When loading a model state dictionary from a statedict.pt file via torch.load, the function does not...

CVE-2026-44484

A flaw was found in PyTorch Lightning. This deep learning framework introduced functionality that could be leveraged as a credential harvesting mechanism. A remote attacker could exploit this to obtain sensitive user credentials, leading to significant information disclosure and potential further...

a2 (>=0.1.0 <=0.3.17), abnativ (>=1.1.0 <=1.2.9) +356 more potentially affected by CVE-2026-2652 via mlflow (>=0.8.2 <=3.10.1)

mlflow PYPI version =0.8.2, =0.1.0, =1.1.0, =0.0.5, =0.1.0, =0.1.0, =1.7.0, =1.7.0, =1.8.0, =1.7.0, =1.7.0, =0.1.1, =0.1.5 - anovos =1.1.0 and more Source cves: CVE-2026-2652 Source advisory: OSV:GHSA-75CM-X2W3-8MGF...

CVE-2026-44484

PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism...

EUVD-2026-30303

PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism...

CVE-2026-44484

PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism...

CVE-2026-44484

PyTorch Lightning PyPI package versions 2.6.2 and 2.6.3 have been compromised, introducing functionality consistent with a credential harvesting mechanism. This is reflected across CVE-2026-44484 and associated advisories (GHSA-w37p-236h-pfx3; OSV). The root cause is under investigation; affected...

CVE-2026-44484 Compromise of PyTorch Lightning PyPi Package Versions

PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism...

CVE-2026-44484 Compromise of PyTorch Lightning PyPi Package Versions

PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism...

PyTorch Lightning 安全漏洞

PyTorch Lightning is an open-source deep learning model pre-training and fine-tuning framework developed by Lightning AI. Version 2.6.2 and 2.6.2 of PyTorch Lightning contain security vulnerabilities, which stem from the introduction of features similar to those used in credential collection...

Linux Distros Unpatched Vulnerability : CVE-2026-31221

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability CWE-502 in the checkpoint loading mechanism. The...

CVE-2026-31214

The torch-checkpoint-shrink.py script in the ml-engineering project in commit 0099885db36a8f06556efe1faf552518852cb1e0 2025-20-27 contains an insecure deserialization vulnerability CWE-502. The script uses torch.load to process PyTorch checkpoint files .pt without enabling the security-restrictiv...

Deserialization of Untrusted Data

Overview ludwig is a Declarative machine learning: End-to-end machine learning pipelines using data-driven configurations. Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the model serving process. An attacker can execute arbitrary code on the system by...

GHSA-PQ2F-X424-6FJM mamba language model framework vulnerable to insecure deserialization when loading pre-trained models from HuggingFace Hub

The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.frompretrained method uses torch.load to load the pytorchmodel.bin weight file without enabling the security-restrictive...

EUVD-2026-29561

The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load without enabling the security-restrictive weightsonly=True...

EUVD-2026-29503

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 is vulnerable to insecure deserialization CWE-502. When a user provides a single model file path e.g., .pt or .pth via the --model command-line argumen...

EUVD-2026-29511

The Adversarial Robustness Toolbox ART thru 1.20.1 contains a remote code execution vulnerability in its Kubeflow component. The robustness evaluation function for PyTorch models uses the unsafe eval function to dynamically evaluate user-supplied strings for the LossFn and Optimizer parameters...