CVE intelligence and bounded remediation
CVE-2026-1839 — A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code execution
A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code execution. The `_load_rng_state()` method in `src/transformers/trainer.py` at line 3059 calls `torch.load()` without the `weights_only=True` parameter. This issue affects all versions of the library supporting `torch>=2.2` when used with PyTorch versions below 2.6, as the `safe_globals()` context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as `rng_state.pth`, which can execute arbitrary code when loaded. The issue is resolved in version v5.0.0rc3.
- Severity
- High
- CVSS
- 7.8 (3.1)
- Published
- 2026-04-07
- CISA KEV
- Not currently listed
- Ecosystem
- software/application
- Weaknesses
- CWE-502
Affected products
- huggingface / transformers
- huggingface / transformers / 5.0.0
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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