Is Bio Embeddings Cpcprot Safe?
Bio Embeddings Cpcprot — Nerq Trust Score 48.2/100 (D grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25
Bio Embeddings Cpcprot is a Python package with a Nerq Trust Score of 48.2/100 (D), based on 3 independent data dimensions. Last analyzed: 2026-03-25 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).
Is Bio Embeddings Cpcprot safe?
Trust Score Breakdown — Bio Embeddings Cpcprot has a Nerq Trust Score of 48.2/100 (D). Measured across 2 independent trust signals (as of 2026-03-25).
What is Bio Embeddings Cpcprot's trust score?
Bio Embeddings Cpcprot has a Nerq Trust Score of 48.2/100, earning a D grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Bio Embeddings Cpcprot?
Bio Embeddings Cpcprot's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Bio Embeddings Cpcprot and who maintains it?
| Author | Amy Lu |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Bio Embeddings Cpcprot
What is Bio Embeddings Cpcprot?
Bio Embeddings Cpcprot is a Python package — Parameter-efficient pretrained model for obtaining protein embeddings..
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=bio-embeddings-CPCProt
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Bio Embeddings Cpcprot has a Nerq Trust Score of 48/100 (D). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Bio Embeddings Cpcprot has a Trust Score of 48/100 (D).
- The score is a measured composite — it is not a suitability judgment. Evaluate the individual signals against your own requirements.
- Query the current measured values via the Nerq API.
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Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.