1759 matches found
CVE-2026-31252
CosyVoice thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e 2025-30-21 contains an insecure deserialization vulnerability CWE-502 in its model loading component. The framework uses torch.load to load model weight files e.g., llm.pt, flow.pt, hift.pt without enabling the security-restrictive...
EUVD-2026-29558
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...
EUVD-2026-29562
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-2026-29560
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...
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 via the predict method. An attacker can execute arbitrary code by supplying a maliciousl...
GHSA-WCR3-GM9F-F87Q Ludwig framework is vulnerable to insecure deserialization through its predict() method.
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 contains an insecure deserialization vulnerability in BackgroundAugmenter class within multicore.py module
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...
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
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...
Ludwig framework is vulnerable to insecure deserialization in its model serving component
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...
GHSA-XP5Q-5Q7G-Q26R Ludwig framework is vulnerable to insecure deserialization in its model serving component
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...
GHSA-G82G-J283-HJ97 imgaug contains an insecure deserialization vulnerability in BackgroundAugmenter class within multicore.py module
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...
EUVD-2026-29552
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...
GHSA-MF8F-X4R3-JM8C Horovod contains an insecure deserialization vulnerability in its KVStore HTTP server component
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...
EUVD-2026-29508
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...
EUVD-2026-29506
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...
EUVD-2026-29507
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...
Deserialization of Untrusted Data
Overview snorkel is an A system for quickly generating training data with weak supervision Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the load function of the BaseLabeler class, which uses the pickle.load method on user-supplied file paths without...
GHSA-FQ92-QC8F-482V Snorkel BaseLabeler.load uses an unsafe pickle.load
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...
Snorkel Trainer.load uses an unsafe torch.load
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...
Snorkel BaseLabeler.load uses an unsafe pickle.load
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...