Is Maskcard Safe?
Maskcard — Nerq Trust Score 48.2/100 (D grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25
Maskcard is a npm 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 npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).
Is Maskcard safe?
Trust Score Breakdown — Maskcard has a Nerq Trust Score of 48.2/100 (D). Measured across 2 independent trust signals (as of 2026-03-25).
What is Maskcard's trust score?
Maskcard 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 Maskcard?
Maskcard's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Maskcard and who maintains it?
| Author | tarymee |
| Category | npm Packages |
| Source | N/A |
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Safety Guide: Maskcard
What is Maskcard?
Maskcard is a Node.js package — A scratchcard plug-in based on canvas.(基于canvas的刮刮卡插件).
How to Verify Safety
Run npm audit to check for vulnerabilities. Review the package's GitHub repository for recent commits.
You can also check the trust score via API: GET /v1/preflight?target=maskcard
Key Safety Concerns for Node.js package
When evaluating any Node.js package, watch for: dependency vulnerabilities, malicious packages, typosquatting.
Measured Signals
Maskcard 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
- Maskcard 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.
Frequently Asked Questions
Is Maskcard Safe?
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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.