Is Aioinfluxdb Safe?
Aioinfluxdb — Nerq Trust Score 53.2/100 (C- grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25
Aioinfluxdb is a Python package with a Nerq Trust Score of 53.2/100 (C-), based on 3 independent data dimensions. Last analyzed: 2026-03-25 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).
Is Aioinfluxdb safe?
Trust Score Breakdown — Aioinfluxdb has a Nerq Trust Score of 53.2/100 (C-). Measured across 2 independent trust signals (as of 2026-03-25).
What is Aioinfluxdb's trust score?
Aioinfluxdb has a Nerq Trust Score of 53.2/100, 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 Aioinfluxdb?
Aioinfluxdb's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Aioinfluxdb and who maintains it?
| Author | Byeonghoon Yoo |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Aioinfluxdb
What is Aioinfluxdb?
Aioinfluxdb is a Python package — InfluxDB v2 Python SDK with asyncio support.
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=aioinfluxdb
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Aioinfluxdb has a Nerq Trust Score of 53/100 (C-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Aioinfluxdb has a Trust Score of 53/100 (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.