Is Media Split Safe?
Media Split — Nerq Trust Score 46.2/100 (D grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25
Media Split is a npm package with a Nerq Trust Score of 46.2/100 (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 Media Split safe?
Trust Score Breakdown — Media Split has a Nerq Trust Score of 46.2/100 (D). Measured across 2 independent trust signals (as of 2026-03-25).
What is Media Split's trust score?
Media Split has a Nerq Trust Score of 46.2/100, 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 Media Split?
Media Split's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Media Split and who maintains it?
| Author | nevermnd |
| Category | npm Packages |
| Source | N/A |
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Safety Guide: Media Split
What is Media Split?
Media Split is a Node.js package — Split audio (and video) files.
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=media-split
Key Safety Concerns for Node.js package
When evaluating any Node.js package, watch for: dependency vulnerabilities, malicious packages, typosquatting.
Measured Signals
Media Split has a Nerq Trust Score of 46/100 (D). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Media Split has a Trust Score of 46/100 (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.