Is Aiopinboard Safe?
Aiopinboard — Nerq Trust Score 56.5/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Aiopinboard is a Python package with a Nerq Trust Score of 56.5/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Aiopinboard safe?
Trust Score Breakdown — Aiopinboard has a Nerq Trust Score of 56.5/100 (C). Measured across 2 independent trust signals (as of 2026-03-20).
What is Aiopinboard's trust score?
Aiopinboard has a Nerq Trust Score of 56.5/100, 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 Aiopinboard?
Aiopinboard's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Aiopinboard and who maintains it?
| Author | Aaron Bach |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Aiopinboard
What is Aiopinboard?
Aiopinboard is a Python package — A Python 3, asyncio-based library for the Pinboard API.
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=aiopinboard
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Aiopinboard has a Nerq Trust Score of 56/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Aiopinboard has a Trust Score of 56/100 (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.