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MEDIUM severity

CVE-2026-1839 — transformers

MEDIUMFix: huggingface/transformers@03c8082

CVE-2026-1839 is a medium-severity (CVSS 6.5) Deserialization of Untrusted Data vulnerability in transformers. A fix is available for transformers — see the affected versions and patch details below.

Arbitrary Code Execution via Unsafe torch.load() in Trainer Checkpoint Loading in huggingface/transformers

Also known asGHSA-69w3-r845-3855PYSEC-2026-2288
Published
Updated
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Nov 10, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for CVE-2026-1839.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk+0.01%
Lower risk than most CVEs33th percentile — riskier than 33% of all scored CVEsHighest risk
0.00%0.30%0.59%0.89%0.0%0.4%May 26Sep 26Nov 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

1 pkg affected
🐍transformers

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

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.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItransformersall versions5.0.0rc3pip install --upgrade 'transformers==5.0.0rc3'

Affected Products

1 product · 4 configurations
Application
transformershuggingface
< 5.0.0
1 version
5.0.0

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for transformers, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update transformers to 5.0.0rc3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-1839 is resolved across your whole dependency graph.

  3. Workarounds

    Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatModerate
Workaround published by Red Hat
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.
Source: Red Hat security advisory for CVE-2026-1839 (CC BY 4.0)

Frequently Asked Questions

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 arbi
O3 Security · Impact-Aware SCA

Is CVE-2026-1839 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2026-1839: transformers RCE — Fixed in 5.0.0rc3