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...

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...

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-2026-31239

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...

PT-2026-40126

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 uses torch.load to load the pytorch model.bin weight file without enabling the security-restrictive...

CVE-2026-31239

The CVE-2026-31239 entry concerns the Mamba language model framework up to version 2.2.6. The issue is insecure deserialization (CWE-502) when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method uses torch.load() to load the pytorch_model.bin weight file...

Diffusers has a `trust_remote_code` bypass via `custom_pipeline` and local custom components

Background This vulnerability is found in the DiffusionPipeline.frompretrained flow, which is used to load a pipeline from the HuggingFace Hub. This function accepts an optional custompipeline keyword argument: the name of a Python file in the repo that contains a custom class inheriting from...

GHSA-J7W6-VPVQ-J3GM Diffusers has a `trust_remote_code` bypass via `custom_pipeline` and local custom components

Background This vulnerability is found in the DiffusionPipeline.frompretrained flow, which is used to load a pipeline from the HuggingFace Hub. This function accepts an optional custompipeline keyword argument: the name of a Python file in the repo that contains a custom class inheriting from...

PT-2026-39298

Name of the Vulnerable Software and Affected Versions Diffusers versions prior to 0.38.0 Description An issue exists in the DiffusionPipeline.from pretrained flow when loading pipelines from Hugging Face Hub repositories. The resolve custom pipeline and cls function in pipeline loading utils.py...

InstructLab Includes Functionality from Untrusted Control Sphere

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859 Instructlab: instructlab: arbitrary code execution due to hardcoded `trust_remote_code=true`

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

CVE-2026-6859 is a Red Hat advisory about a flaw in InstructLab where linux_train.py hardcodes trust_remote_code=True when loading models from HuggingFace. This enables arbitrary Python code execution if a user runs ilab train/download/generate with a malicious HuggingFace model, potentially lead...