CVE-2026-31239: 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 weightsonly=True parameter. This allows the deserialization of arbitrary Python objects via the pickle module.
Published May 12, 2026 · Updated May 27, 2026
Affected packages
mamba-ssm
- Ecosystem
- PyPI
- Affected
- <= 2.2.6
- Fixed in
- No patched version yet
- Check
pip show mamba-ssm
Advisory details
From the GitHub Advisory Database (CC BY 4.0).
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 weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by publishing a malicious model repository on HuggingFace Hub. When a victim loads a model from this repository, arbitrary code is executed on the victim's system in the context of the mamba process.
References
How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology
