Home/CVE/The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization (CWE-502) when loading pre-train
CVE

CVE-2026-31239

The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization (CWE-502) when loading pre-train

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.

CRITICAL · CVSS 9.8 EPSS 0.00054
Schedule remediation
  • CVSS base score ≥ 7.0
Sigma rules0 YARA rules0

Weakness Classification

Affected Packages

1
Language-ecosystem packages (from OSV) tied to this CVE, with the version that fixes it - the dependency-level detail NVD doesn’t carry.
PyPI mamba-ssm CRITICAL

Scoring & Timeline

9.8
CRITICAL · CVSS v3.1 · cve@mitre.org
View on NVD
Attack Vector
Network Adjacent Local Physical
Attack Complexity
Low High
Privileges Required
None Low High
User Interaction
None Required
Scope
Unchanged Changed
Confidentiality
None Low High
Integrity
None Low High
Availability
None Low High
Published to NVD12 May 2026 · 06:16 PM
CVSS VectorCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
🔗

References & Sources

2
Source URLs (vendor pages, mailing lists, write-ups). Exploit/PoC links are in their own section above to avoid duplication.
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