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-2026-31237

The Ludwig framework (up to version 0.10.4) is reported to be vulnerable to insecure deserialization (CWE-502) in its predict() function. If a user supplies a dataset file path to predict(), Ludwig attempts to determine the file format and, when encountering a pickle (.pkl) file, loads it via pan...

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...

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...

PT-2026-40119

The CosyVoice project thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e 2025-30-21 contains an insecure deserialization vulnerability CWE-502 in its model loading process. When loading model files .pt from a user-specified directory via the --model dir argument, the code uses torch.load withou...

PT-2026-40122

Name of the Vulnerable Software and Affected Versions imgaug versions prior to 0.4.0 Description Insecure deserialization occurs in the BackgroundAugmenter class within the multicore.py module. The augment images worker function uses Python's pickle module to deserialize data from a multiprocessi...

CVE-2026-31214

The vulnerability CVE-2026-31214 affects the torch-checkpoint-shrink.py script in the ml-engineering project, commit 0099885db36a8f06556efe1faf552518852cb1e0 (2025-20-27). The script uses torch.load() to process PyTorch checkpoint files (.pt) without enabling weights_only=True, allowing the deser...

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...

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-2026-31221

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-2026-31224

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-2026-31218

The CVE concerns the optimate project’s neural_magic_training.py, where _load_model() deserializes a state_dict.pt with torch.load() without enabling weights_only=True. This enables deserialization of arbitrary Python objects via Pickle, allowing a remote attacker to provide a crafted state_dict....

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...

Snorkel 安全漏洞

Snorkel is an open-source system developed by Snorkel that uses weak supervision to quickly generate training data. Versions of Snorkel prior to v0.10.0 contain security vulnerabilities. These vulnerabilities stem from the BaseLabeler class’s BaseLabeler.load method, which uses the unsafe...

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...

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...

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...

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...

CVE-2026-31238

The Ludwig framework (up to 0.10.4) is vulnerable to insecure deserialization (CWE-502) in its model serving component. Starting a model server (ludwig serve) loads model weight files with torch.load() without enabling weights_only=True, allowing deserialization of arbitrary Python objects via pi...