CyberSecBulletin
CVE-2026-1839NVD status: Analyzed

huggingface/transformers: Deserialization of Untrusted Data

CVE-2026-1839 is a high-severity deserialization of untrusted data vulnerability in huggingface/transformers from Huggingface, with a CVSS 3.1 base score of 7.8 out of 10. It can be exploited with local access to the system by an unauthenticated attacker, but only if a user takes part, for example by opening a link or file. The record lists version v5.0.0rc3 as the first without the flaw, so updating huggingface/transformers to that release or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.39% chance of exploitation within 30 days, which is low compared with other CVEs.

Next patch cycle

High severity with no evidence of exploitation so far.

What to do

  1. Update huggingface/transformers to v5.0.0rc3 or a later version.
  2. Update Transformers to 5.0.0 or a later version.
  3. Because the attack needs a user to take part, warn users about unexpected links and files related to this product until it is patched.

Affected products and versions

VendorProductAffected versionsFixed in
Huggingfacehuggingface/transformersbefore v5.0.0rc3v5.0.0rc3
HuggingfaceTransformersbefore 5.0.0; 5.0.05.0.0

Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.

How the severity score breaks down

Attack vector
LocalThe attacker needs local access or must trick a user into running something.
Attack complexity
LowNo special conditions are needed; the attack works reliably.
Privileges required
NoneNo account or login is needed.
User interaction
RequiredA user must take an action such as opening a file or link.
Scope
UnchangedImpact stays within the vulnerable component.
Confidentiality
HighAll data handled by the component can be read.
Integrity
HighData or code can be modified at will.
Availability
HighThe component can be taken down completely.

Vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H. Scored by NVD.

Scoring systemScoreSeverityScored by
CVSS 3.17.8HighNVD
CVSS 3.06.5MediumCNA (huntr.dev)

Official description

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.

Source: the CVE record as published by its numbering authority, via NVD and CVE.org.

The underlying weakness: Deserialization of Untrusted Data

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

How developers prevent this class of flaw

  • If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
  • When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
  • Explicitly define a final object() to prevent deserialization.

More Deserialization of Untrusted Data vulnerabilities (CWE-502)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: total).
  3. Record last changed materially (score, affected products, status or references).

References

Technical write-ups (may include proof of concept)

Other vulnerabilities in huggingface/transformers

All huggingface/transformers vulnerabilities

Recent Deserialization of Untrusted Data vulnerabilities

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