CVE-2026-31219

The optimate project, an AI model optimization tool library by Nebuly, contains an insecure deserialization (CWE-502) vulnerability in the _load_model() function of the neural_magic_training.py script (commit a6d302f912b481c94370811af6b11402f51d377f). The issue occurs because the function uses to...

PT-2026-40057

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 loading a model state dictionary from a state dict.pt file via torch.load, the function does...

CVE-2026-31218

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 is vulnerable to insecure deserialization CWE-502. When loading a model state dictionary from a statedict.pt file via torch.load, the function does not...

OptiMate security vulnerabilities

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...

CVE-2026-31219

The loadmodel function in the neuralmagictraining.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 argumen...

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-2026-31219

The loadmodel function in the neuralmagictraining.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 argumen...

OptiMate security vulnerabilities

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...

Pytorch-Lightning security vulnerabilities

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-2026-31214

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-2026-31214

The torch-checkpoint-shrink.py script within the ml-engineering project (specifically commit 0099885db36a8f06556efe1faf552518852cb1e0) is vulnerable to insecure deserialization (CWE-502). The script utilizes torch.load() to process PyTorch checkpoint files (.pt) without enabling the security-rest...

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-2026-31221

PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() (and related checkpoint loading paths) call torch.load() without weights_only=True, allowing deserialization of ...

CVE-2026-31234

Horovod versions up to and including 0.28.1 are vulnerable to an insecure deserialization (CWE-502) flaw within its KVStore HTTP server component. The KVStore server, utilized for distributed task coordination, lacks necessary authentication and authorization controls, which enables a remote atta...

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...

PT-2026-40126

Name of the Vulnerable Software and Affected Versions mamba versions prior to 2.2.7 Description Insecure deserialization occurs when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from pretrained function uses torch.load to load the pytorch model.bin weight file without...

CVE-2026-31239

The mamba language model framework (version 2.2.6 and earlier ) is vulnerable to insecure deserialization (CWE-502) when loading pre-trained models from the HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method utilizes torch.load() to process the pytorch_model.bin weight file without th...

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-2026-31238

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...

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...