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CVE

CVE-2026-31239

mamba language model framework vulnerable to insecure deserialization when loading pre-trained models from HuggingFace Hub
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CVE

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 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.

Package Versions Affected

Package Version
patch Availability
No items found.

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CVSS Version

Severity
Base Score
CVSS Version
Score Vector
C
H
U
9.8
-
3.1
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
C
H
U
0
-
3.1
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
C
H
U
-

Related Resources

No items found.

References

https://nvd.nist.gov/vuln/detail/CVE-2026-31239, https://github.com/state-spaces/mamba, https://www.notion.so/CVE-2026-31239-35d1e1393188810d9baedfbd8363f396

Severity

9.8

CVSS Score
0
10

Basic Information

Ecosystem
Base CVSS
9.8
EPSS Probability
0.00054%
EPSS Percentile
0.16995%
Introduced Version
0
Fix Available

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