Is Maskdata Safe?
Maskdata — Nerq Trust Score 48.2/100 (D grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25
Maskdata 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 Maskdata safe?
Trust Score Breakdown — Maskdata has a Nerq Trust Score of 48.2/100 (D). Measured across 2 independent trust signals (as of 2026-03-25).
What is Maskdata's trust score?
Maskdata 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 Maskdata?
Maskdata's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Maskdata and who maintains it?
| Author | sumukha.hs |
| Category | npm Packages |
| Source | N/A |
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Safety Guide: Maskdata
What is Maskdata?
Maskdata is a Node.js package — Node module to mask various kinds of data in the required formats.
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=maskdata
Key Safety Concerns for Node.js package
When evaluating any Node.js package, watch for: dependency vulnerabilities, malicious packages, typosquatting.
Measured Signals
Maskdata 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
- Maskdata 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
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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.