CVE intelligence and bounded remediation
CVE-2026-31239 — mamba language model framework thru security vulnerability
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.
- Severity
- Critical
- CVSS
- 9.8 (3.1)
- Published
- 2026-05-12
- CISA KEV
- Not currently listed
- Ecosystem
- python/pypi
- Weaknesses
- CWE-502
Affected products
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Matched remediation archetype
Unsafe deserialization and object reconstruction
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Check exposure
- Inventory serialization formats accepted from requests, queues, caches, files, cookies, and cross-service messages.
- Trace whether untrusted input can select classes, types, callbacks, constructors, or object hooks during decoding.
- Identify signing, schema validation, trust-boundary, and compatibility settings for each decoder.
Remediate safely
- Replace native object deserialization with a data-only format and explicit schema validation.
- If replacement is not immediate, use a safe decoder with a minimal type allowlist and disable polymorphic or executable hooks.
- Update the affected library and add inert tests for unknown types, extra fields, malformed nesting, and unsigned data.
Authoritative sources
Complete CVE record and remediation plan
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