Deserialization of untrusted data can occur in versions of the Keras framework running versions 3.11.0 up to but not including 3.11.3, enabling a maliciously uploaded Keras file containing a TorchModu
A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `sa
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 fr
The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True.
One can create a specially crafted .keras model archive that, when loaded via Model.l
Deserialization of untrusted data can occur in versions 23.3.2.0 and newer of the MindsDB platform, enabling a maliciously uploaded model to run arbitrary code on the server when interacted with.
Deserialization of untrusted data can occur in versions 2.4.0 or newer of the Cleanlab project, enabling a maliciously crafted datalab.pkl file to run arbitrary code on an end user’s system when the d
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
A deserialization vulnerability exists in Volcengine's verl 3.0.0, specifically in the scripts/model_merger.py script when using the "fsdp" backend. The script calls torch.load() with weights_only=Fal
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 sc
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.from_pretrained() method us
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
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.loa
Deserialization vulnerability of untrusted data in the ability module.
Impact: Successful exploitation of this vulnerability may affect availability.
CWE‑502: Deserialization of Untrusted Data vulnerability exists that could cause arbitrary code execution with administrative privileges when a locally authenticated attacker sends a crafted data stre
Deserialization of untrusted data issue exists in BizRobo! all versions. If this vulnerability is exploited, an arbitrary code is executed on the Management Console.
The vendor provides the workaroun
MooreThreads torch_musa through all versions contains an unsafe deserialization vulnerability in torch_musa.utils.compare_tool. The compare_for_single_op() and nan_inf_track_for_single_op() functions
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 f
The Keras.Model.load_model method, including when executed with the intended security mitigation safe_mode=True, is vulnerable to arbitrary local file loading and Server-Side Request Forgery (SSRF).
LLama Factory enables fine-tuning of large language models. Prior to version 1.0.0, a critical vulnerability exists in the `llamafy_baichuan2.py` script of the LLaMA-Factory project. The script perfor
The CosyVoice project thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e (2025-30-21) contains an insecure deserialization vulnerability (CWE-502) in its model loading process. When loading model fi
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