Is Catenets Safe?
Catenets — Nerq Trust Score 53.2/100 (C- grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-25
Catenets is a Python package with a Nerq Trust Score of 53.2/100 (C-), based on 3 independent data dimensions. Last analyzed: 2026-03-25 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).
Is Catenets safe?
Trust Score Breakdown — Catenets has a Nerq Trust Score of 53.2/100 (C-). Measured across 2 independent trust signals (as of 2026-03-25).
What is Catenets's trust score?
Catenets has a Nerq Trust Score of 53.2/100, 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 Catenets?
Catenets's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Catenets and who maintains it?
| Author | Alicia Curth |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Catenets
What is Catenets?
Catenets is a Python package — Conditional Average Treatment Effect Estimation Using Neural Networks.
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=catenets
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Catenets has a Nerq Trust Score of 53/100 (C-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Catenets has a Trust Score of 53/100 (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.