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...

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...

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...

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...

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...

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...

Deserialization of Untrusted Data

Overview mamba-ssm is a Mamba state-space model Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the frompretrained process. An attacker can execute arbitrary code by publishing a malicious model repository on HuggingFace Hub and having a victim load a mode...

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...

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...

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-2026-29562

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...

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...

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-2026-29555

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 --modeldir argument, the code uses torch.load without...

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...

EUVD-2026-29557

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...

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...

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 MultitaskClassifier.load function. An attacker can execute arbitrary code by supplying a maliciously crafted mode...

EUVD-2026-29505

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...