PT-2026-40125

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 weights only=True...

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...

webpack-dev-server 安全漏洞

webpack-dev-server is an open-source application developed by webpack. Versions of webpack-dev-server prior to version 5.2.3 contained security vulnerabilities. These vulnerabilities stemmed from exposure to cross-origin code. When it provided services through non-potentially trusted sources, suc...

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-2026-31218

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-2026-31221

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-2026-31214

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...

PT-2026-40062

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-2026-31214

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-2026-31219

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...

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...

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 Trainer class’s Trainer.load method, which uses torch.load to load model...

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 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...

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-2026-31219

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...

CVE-2026-31219

The connected documents confirm a concrete vulnerability in the optimate project: the _load_model() (or load_model()) function in neural_magic_training.py deserializes a single model file passed via --model using torch.load() without weights_only=True, enabling arbitrary Python object deserializa...

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...

CVE-2026-31217

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 allows arbitrary code execution. When a user supplies a directory path via the --model command-line argument, the function reads a module.py file from...