Is Nab Python Safe?
Nab Python — Nerq Trust Score 59.5/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-09-01
Nab Python is a Python package with a Nerq Trust Score of 59.5/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-09-01 Security: 90/100. Popularity: 75/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-09-01. Machine-readable data (JSON).
Is Nab Python safe?
Trust Score Breakdown — Nab Python has a Nerq Trust Score of 59.5/100 (C). Measured across 2 independent trust signals (as of 2026-09-01).
What is Nab Python's trust score?
Nab Python has a Nerq Trust Score of 59.5/100, 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 Nab Python?
Nab Python's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Nab Python and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Nab Python
What is Nab Python?
Nab Python is a Python package — Index-backed provider, lockfile emitter, and downloader for nab.
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=nab-python
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Nab Python has a Nerq Trust Score of 60/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Nab Python has a Trust Score of 60/100 (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.