Is Bme68X Safe?
Bme68X — Nerq Trust Score 56.8/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Bme68X is a Python package with a Nerq Trust Score of 56.8/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 15/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Bme68X safe?
Trust Score Breakdown — Bme68X has a Nerq Trust Score of 56.8/100 (C). Measured across 2 independent trust signals (as of 2026-03-20).
What is Bme68X's trust score?
Bme68X has a Nerq Trust Score of 56.8/100, 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 Bme68X?
Bme68X's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Bme68X and who maintains it?
| Author | Nathan |
| Category | Python Packages |
| Source | N/A |
Bme68X Across Platforms
Same developer/company in other registries:
Similar Pypi by Trust Score
Safety Guide: Bme68X
What is Bme68X?
Bme68X is a Python package — Python interface for BME68X sensor and BSEC.
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=bme68x
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Bme68X has a Nerq Trust Score of 57/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Bme68X has a Trust Score of 57/100 (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.