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Deserialization of Untrusted Data

CVE-2026-1839

High
7.8/10

Summary

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.

  • LOW
  • LOCAL
  • HIGH
  • UNCHANGED
  • REQUIRED
  • NONE
  • HIGH
  • HIGH

CWE-502 - Deserialization of Untrusted Data

Deserialization of untrusted data vulnerabilities enable an attacker to replace or manipulate a serialized object, replacing it with malicious data. When the object is deserialized at the victim's end the malicious data is able to compromise the victim’s system. The exploit can be devastating, its impact may range from privilege escalation, broken access control, or denial of service attacks to allowing unauthorized access to the application's internal code and logic which can compromise the entire system.

References

Advisory Timeline

  • Published