Is Webcolors Safe?
Webcolors — Nerq Trust Score 73.2/100 (B grade). Score based on 2 independent trust signals. Last analyzed: 2026-08-11
Webcolors is a Python package with a Nerq Trust Score of 73.2/100 (B), based on 3 independent data dimensions. Last analyzed: 2026-08-11 Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-08-11. Machine-readable data (JSON).
Is Webcolors safe?
Trust Score Breakdown — Webcolors has a Nerq Trust Score of 73.2/100 (B). Measured across 2 independent trust signals (as of 2026-08-11).
What is Webcolors's trust score?
Webcolors has a Nerq Trust Score of 73.2/100, earning a B grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Webcolors?
Webcolors's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Webcolors and who maintains it?
| Author | James Bennett |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Webcolors
What is Webcolors?
Webcolors is a Python package — A library for working with the color formats defined by HTML and CSS..
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=webcolors
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Webcolors has a Nerq Trust Score of 73/100 (B). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Webcolors has a Trust Score of 73/100 (B).
- 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.
Frequently Asked Questions
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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.