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...

CosyVoice 安全漏洞

CosyVoice is an open-source voice generation and AI voice cloning platform developed by FunAudioLLM. CosyVoice has a security vulnerability. This vulnerability arises from the model loading process, where the .pt files in the user-specified directory are loaded using torch.load, without enabling...

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...

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...

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...

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...

PT-2026-40192

Deserialization of untrusted data in Microsoft Office SharePoint allows an authorized attacker to execute code over a network...

PT-2026-40060

Name of the Vulnerable Software and Affected Versions PyTorch-Lightning versions 2.6.0 and earlier Description An insecure deserialization issue exists in the checkpoint loading mechanism. The load from checkpoint function in LightningModule internally calls torch.load without the weights only=Tr...

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...

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-2026-31224

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-2026-31222

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-2026-31235

The imgaug library thru 0.4.0 contains an insecure deserialization vulnerability in its BackgroundAugmenter class within the multicore.py module. The class uses Python's pickle module to deserialize data received via a multiprocessing queue in the augmentimagesworker method without any safety...

CVE-2026-31237

The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 through its predict method. When a user provides a dataset file path to the predict method, the framework automatically determines the file format. If the file is a pickle .pkl file, it is loaded using...

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...

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...

PT-2026-40121

Name of the Vulnerable Software and Affected Versions Horovod versions prior to 0.28.2 Description The KVStore HTTP server component, used for distributed task coordination, lacks authentication and authorization controls. This allows a remote attacker to write arbitrary data using HTTP PUT...

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...

CVE-2026-31222

The Snorkel library prior to v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in Trainer.load(), where model checkpoints are loaded with torch.load() without weights_only=True. This allows deserialization of arbitrary Python objects via Pickle, enabling remote code execution w...