Is Sqlmodel Safe?
Sqlmodel — Nerq Trust Score 71.8/100 (B grade). Based on analysis of 2 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-06-16.
Yes, Sqlmodel is safe to use. Sqlmodel is a Python package with a Nerq Trust Score of 71.8/100 (B), based on 3 independent data dimensions. Recommended for production use. Security: 90/100. Popularity: 90/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-12. Machine-readable data (JSON).
Is Sqlmodel safe?
YES — Sqlmodel has a Nerq Trust Score of 71.8/100 (B). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.
What is Sqlmodel's trust score?
Sqlmodel has a Nerq Trust Score of 71.8/100, 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 Sqlmodel?
Sqlmodel's strongest signal is security at 90/100. No known vulnerabilities have been detected. It meets the Nerq Verified threshold of 70+.
What is Sqlmodel and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
Sqlmodel Across Platforms
Same developer/company in other registries:
Similar Pypi by Trust Score
Safety Guide: Sqlmodel
What is Sqlmodel?
Sqlmodel is a Python package — SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness..
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=sqlmodel
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Sqlmodel has a Nerq Trust Score of 72/100 (B) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Sqlmodel has a Trust Score of 72/100 (B).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 90/100 |
| Popularity | 90/100 |
| Quality | 40/100 |
| Community | 35/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Sqlmodel collect?
Sqlmodel is a Python package maintained by Unknown. It receives approximately 3,113,789 weekly downloads.
As a development package, Sqlmodel 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: Sqlmodel Privacy Report · Privacy review
Is Sqlmodel secure?
Security score: 90/100. Sqlmodel 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: Sqlmodel Security Report
How we calculated this score
Sqlmodel's trust score of 71.8/100 (B) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (90/100), popularity (90/100), 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 June 16, 2026. Data version: 1.0.
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.