Is C4M Pyspice Safe?
C4M Pyspice — Nerq Trust Score 50.5/100 (C- grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
C4M Pyspice is a Python package with a Nerq Trust Score of 50.5/100 (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 C4M Pyspice safe?
Trust Score Breakdown — C4M Pyspice has a Nerq Trust Score of 50.5/100 (C-). Measured across 2 independent trust signals (as of 2026-03-20).
What is C4M Pyspice's trust score?
C4M Pyspice has a Nerq Trust Score of 50.5/100, 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 C4M Pyspice?
C4M Pyspice's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is C4M Pyspice and who maintains it?
| Author | Staf Verhaegen |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: C4M Pyspice
What is C4M Pyspice?
C4M Pyspice is a Python package — Temporary fork of PySpice with extra commits.
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=c4m-PySpice
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
C4M Pyspice has a Nerq Trust Score of 50/100 (C-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- C4M Pyspice has a Trust Score of 50/100 (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.