Is Causalml Safe?
Causalml — Nerq Trust Score 64.5/100 (C+ grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Causalml is a Python package with a Nerq Trust Score of 64.5/100 (C+), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 60/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Causalml safe?
Trust Score Breakdown — Causalml has a Nerq Trust Score of 64.5/100 (C+). Measured across 2 independent trust signals (as of 2026-03-20).
What is Causalml's trust score?
Causalml has a Nerq Trust Score of 64.5/100, 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 Causalml?
Causalml's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Causalml and who maintains it?
| Author | Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Jing Pan, Mike Yung, Zhenyu Zhao |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Causalml
What is Causalml?
Causalml is a Python package — Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms.
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=causalml
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Causalml has a Nerq Trust Score of 64/100 (C+). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Causalml has a Trust Score of 64/100 (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.