Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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| n/a | n/a | affected |
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No data.
No data.
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| State-spaces | Mamba |
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| Source | ID | Title |
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Github GHSA |
GHSA-pq2f-x424-6fjm | mamba language model framework vulnerable to insecure deserialization when loading pre-trained models from HuggingFace Hub |
No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.409% probability within 30 days)
| Type | Values Removed | Values Added |
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| Metrics |
ssvc
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| Type | Values Removed | Values Added |
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| Title | Insecure Deserialization in Mamba Language Model Framework 2.2.6 Allows Remote Code Execution |
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| Metrics |
cvssV3_1
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| First Time appeared |
State-spaces
State-spaces mamba |
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| Vendors & Products |
State-spaces
State-spaces mamba |
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| Title | Insecure Deserialization in Mamba Language Model Framework 2.2.6 Allows Remote Code Execution | |
| Weaknesses | CWE-502 |
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| Description | 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 |
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