Is Yargs Unparser Safe?
Yargs Unparser — Nerq Trust Score 72.8/100 (B grade). Score based on 2 independent trust signals. Last analyzed: 2026-04-12
Yargs Unparser is a npm package with a Nerq Trust Score of 72.8/100 (B), based on 3 independent data dimensions. Last analyzed: 2026-04-12 Security: 90/100. Popularity: 90/100. Data sourced from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-12. Machine-readable data (JSON).
Is Yargs Unparser safe?
Trust Score Breakdown — Yargs Unparser has a Nerq Trust Score of 72.8/100 (B). Measured across 2 independent trust signals (as of 2026-04-12).
What is Yargs Unparser's trust score?
Yargs Unparser has a Nerq Trust Score of 72.8/100, 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 Yargs Unparser?
Yargs Unparser's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Yargs Unparser and who maintains it?
| Author | satazor |
| Category | npm Packages |
| Source | N/A |
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Safety Guide: Yargs Unparser
What is Yargs Unparser?
Yargs Unparser is a Node.js package — Converts back a yargs argv object to its original array form.
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=yargs-unparser
Key Safety Concerns for Node.js package
When evaluating any Node.js package, watch for: dependency vulnerabilities, malicious packages, typosquatting.
Measured Signals
Yargs Unparser 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
- Yargs Unparser 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.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 65/100 |
| Popularity | 90/100 |
| Quality | 65/100 |
| Community | 50/100 |
Based on 5 dimensions. Data from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Yargs Unparser collect?
Yargs Unparser is a Node.js package maintained by satazor. It receives approximately 4,648,378 weekly downloads. Licensed under MIT.
As a development package, Yargs Unparser does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.
Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.
Full analysis: Yargs Unparser Privacy Report · Privacy review
Is Yargs Unparser secure?
Security score: 90/100. Yargs Unparser has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under MIT, allowing code inspection. Open-source packages allow independent security review of the source code.
Run your package manager's audit command (`npm audit`, `pip audit`, `cargo audit`) to check for known vulnerabilities in your dependency tree.
Full analysis: Yargs Unparser Security Report
How we calculated this score
Yargs Unparser's trust score of 72.8/100 (B) is computed from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (65/100), popularity (90/100), quality (65/100), community (50/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
Signals last measured on April 12, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON 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.