Is Fashionfit Safe?
Fashionfit — Nerq Trust Score 48.2/100 (D grade). Based on analysis of 2 trust dimensions, it is has notable safety concerns. Last updated: 2026-04-27.
Exercise caution with Fashionfit. Fashionfit is a npm package with a Nerq Trust Score of 48.2/100 (D), based on 3 independent data dimensions. Below the recommended threshold of 70. 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 Fashionfit safe?
NO — USE WITH CAUTION — Fashionfit has a Nerq Trust Score of 48.2/100 (D). It has below-average trust signals with significant gaps in security, maintenance, or documentation. Not recommended for production use without thorough manual review and additional security measures.
What is Fashionfit's trust score?
Fashionfit 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 Fashionfit?
Fashionfit's strongest signal is security at 90/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Fashionfit and who maintains it?
| Author | loomisgitarrist |
| Category | npm Packages |
| Source | N/A |
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Safety Guide: Fashionfit
What is Fashionfit?
Fashionfit is a Node.js package — FashionFit: Virtual try-on component allowing users to upload a model and clothing to visualize fit and style..
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=fashionfit
Key Safety Concerns for Node.js package
When evaluating any Node.js package, watch for: dependency vulnerabilities, malicious packages, typosquatting.
Trust Assessment
Fashionfit has a Nerq Trust Score of 48/100 (D) and has not yet reached Nerq trust threshold (70+). This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Fashionfit has a Trust Score of 48/100 (D).
- Review carefully before use — below trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 50/100 |
| Popularity | 0/100 |
| Quality | 40/100 |
| Community | 35/100 |
Based on 5 dimensions. Data from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Fashionfit collect?
Privacy assessment for Fashionfit is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Fashionfit secure?
Security score: 90/100. Fashionfit has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
License information not available. 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: Fashionfit Security Report
How we calculated this score
Fashionfit's trust score of 48.2/100 (D) is computed from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (50/100), popularity (0/100), quality (40/100), community (35/100). 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.
This page was last reviewed on April 27, 2026. Data version: 0.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.