SCANNING huggingface/transformers...
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
This report is generated on demand by querying the GitHub API for repository metadata and published security advisories, then cross-referencing our curated database of known supply-chain incidents (xz-utils, event-stream, ua-parser-js, colors.js, tj-actions, Codecov, and more). Results are cached for 24 hours. We do not scan repository code or dependencies — for that, see Snyk or Socket. Verdict: CLEAN ≥80, CAUTION 50–79, COMPROMISED<50.
Repo looks clean but the live deployment might still be exposing headers, CORS, or SSL misconfigurations.
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