29103 matches found
PT-2026-40058
The load model function in the neural magic training.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...
CVE-2026-31229
The ART (Adversarial Robustness Toolbox) package up to v1.20.1 contains an insecure deserialization vulnerability in its Kubeflow component’s model loading path. Loading model weights (e.g., model.pt) uses torch.load() without weights_only=True, allowing arbitrary Python object deserialization vi...
CVE-2026-31239
The CVE-2026-31239 entry concerns the Mamba language model framework up to version 2.2.6. The issue is insecure deserialization (CWE-502) when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method uses torch.load() to load the pytorch_model.bin weight file...
CVE-2026-31221
PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability CWE-502 in the checkpoint loading mechanism. The LightningModule.loadfromcheckpoint method, which is commonly used to load saved model states, internally calls torch.load without setting the...
CVE-2026-31223
The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability CWE-502 in the BaseLabeler.load method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load function on user-supplied file paths without any validation or...
CVE-2026-31222
The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability CWE-502 in the Trainer.load method of the Trainer class. The method loads model checkpoint files using torch.load without enabling the security-restrictive weightsonly=True parameter. This default behavior allows...
CVE-2026-31223
The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability CWE-502 in the BaseLabeler.load method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load function on user-supplied file paths without any validation or...
CVE-2026-31238
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...
OptiMate 安全漏洞
OptiMate is an AI model optimization tool library developed by Nebuly. There is a security vulnerability in OptiMate. This vulnerability stems from the loadmodel function in the neuralmagictraining.py script, which loads model files using torch.load, without enabling the weightsonly=True paramete...
PT-2026-40192
Deserialization of untrusted data in Microsoft Office SharePoint allows an authorized attacker to execute code over a network...
CVE-2026-31224
The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability CWE-502 in the MultitaskClassifier.load method of the MultitaskClassifier class. The method loads model weight files using torch.load without enabling the security-restrictive weightsonly=True parameter. This...
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...
OptiMate 安全漏洞
OptiMate is an AI model optimization tool library developed by Nebuly. There is a security vulnerability in OptiMate. This vulnerability stems from the loadmodel function in the neuralmagictraining.py script, which loads the statedict.pt file using torch.load, without enabling the weightsonly=Tru...
Pytorch-Lightning 安全漏洞
PyTorch-Lightning is an open-source lightweight PyTorch wrapper developed by Lightning AI in the United States. It is used for high-performance AI research. Versions of PyTorch-Lightning prior to 2.6.0 contain security vulnerabilities. These vulnerabilities stem from the...
imgaug 安全漏洞
imgaug is a image enhancement tool library developed by Alexander Jung, used for data augmentation in machine learning. Imgaug versions 0.4.0 and earlier contain security vulnerabilities. These vulnerabilities stem from the BackgroundAugmenter class using the Python pickle module for...
Machine Learning Engineering Open Book 安全漏洞
Machine Learning Engineering Open Book is a collection of methodologies for training and fine-tuning large language models developed by Stas Bekman. There is a security vulnerability in Machine Learning Engineering Open Book. This vulnerability arises from the use of the torch-checkpoint-shrink.p...
CVE-2026-31229
The Adversarial Robustness Toolbox ART thru 1.20.1 contains an insecure deserialization vulnerability CWE-502 in its Kubeflow component's model loading functionality. When loading model weights from a file e.g., model.pt during robustness evaluation, the code uses torch.load without the...
CVE-2026-31234
Horovod thru 0.28.1 contains an insecure deserialization vulnerability CWE-502 in its KVStore HTTP server component. The KVStore server, used for distributed task coordination, lacks authentication and authorization controls, allowing any remote attacker to write arbitrary data via HTTP PUT...
Horovod 安全漏洞
Horovod is a distributed training framework developed by Horovod OpenSource, based on TensorFlow, Keras, PyTorch, and Apache MXNet. Horovod versions 0.28.1 and earlier contain security vulnerabilities. These vulnerabilities stem from the lack of authentication and authorization controls in the...
PT-2026-40125
Name of the Vulnerable Software and Affected Versions Ludwig framework versions prior to 0.10.5 Description The model serving component is subject to insecure deserialization. When initiating a model server via the ludwig serve command, the framework utilizes the torch.load function to load model...