Is Ipinfo Db Safe?
Ipinfo Db — Nerq Trust Score 59.0/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-11-01
Ipinfo Db is a Python package with a Nerq Trust Score of 59.0/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-11-01 Security: 90/100. Popularity: 45/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-11-01. Machine-readable data (JSON).
Is Ipinfo Db safe?
Trust Score Breakdown — Ipinfo Db has a Nerq Trust Score of 59.0/100 (C). Measured across 2 independent trust signals (as of 2026-11-01).
What is Ipinfo Db's trust score?
Ipinfo Db has a Nerq Trust Score of 59.0/100, earning a C grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Ipinfo Db?
Ipinfo Db's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Ipinfo Db and who maintains it?
| Author | IPinfo |
| Category | Python Packages |
| Source | N/A |
Ipinfo Db Across Platforms
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Safety Guide: Ipinfo Db
What is Ipinfo Db?
Ipinfo Db is a Python package — Official Python free database library for IPinfo.
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=ipinfo-db
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Ipinfo Db has a Nerq Trust Score of 59/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Ipinfo Db has a Trust Score of 59/100 (C).
- 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.