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GHSA-fgcw-684q-jj6r

HIGHFix: huggingface/transformers@676559d

GHSA-fgcw-684q-jj6r is a high-severity (CVSS 8) CWE-829 vulnerability in transformers. O3 Security confirms whether GHSA-fgcw-684q-jj6r is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

huggingface/transformers: Arbitrary Code Execution During Model Initialization in the LightGlue Model Loading Path

Also known asCVE-2026-5241PYSEC-2026-2290
Published
Jun 3, 2026
Updated
Jul 21, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed

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 LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the trust_remote_code parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using AutoModel.from_pretrained() with trust_remote_code=False, the LightGlueConfig reads the trust_remote_code value from the untrusted config.json file and propagates it into nested AutoConfig.from_pretrained() calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItransformersall versions5.5.0

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. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    Update transformers to 5.5.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-fgcw-684q-jj6r is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 pinpoints whether GHSA-fgcw-684q-jj6r is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-fgcw-684q-jj6r. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagat
O3 Security · Impact-Aware SCA

Is GHSA-fgcw-684q-jj6r in your dependencies?

O3 detects GHSA-fgcw-684q-jj6r across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.