Is Vault Client Safe?
Vault Client — Nerq Trust Score 55.0/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-10-01
Vault Client is a Python package with a Nerq Trust Score of 55.0/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-10-01 Security: 90/100. Popularity: 45/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-10-01. Machine-readable data (JSON).
Is Vault Client safe?
Trust Score Breakdown — Vault Client has a Nerq Trust Score of 55.0/100 (C). Measured across 2 independent trust signals (as of 2026-10-01).
What is Vault Client's trust score?
Vault Client has a Nerq Trust Score of 55.0/100, 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 Vault Client?
Vault Client's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Vault Client and who maintains it?
| Author | Sergey Urvanov |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Vault Client
What is Vault Client?
Vault Client is a Python package — This library implements wrapper for ....
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=vault-client
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Vault Client has a Nerq Trust Score of 55/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Vault Client has a Trust Score of 55/100 (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.