Scikit Learn est-il sûr ?

Scikit Learn — Nerq Trust Score 88.0/100 (Note A). Sur la base de l'analyse de 2 dimensions de confiance, il est considéré comme sûr. Dernière mise à jour : 2026-04-05.

Oui, Scikit Learn est sûr à utiliser. Scikit Learn est un package Python avec un Nerq Trust Score de 88.0/100 (A), basé sur 3 dimensions de données indépendantes. It is recommandé pour une utilisation en production. Security: 90/100. Popularity: 100/100. Données de PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Dernière mise à jour: 2026-04-05. Données lisibles par machine (JSON).

Scikit Learn est-il sûr ?

YES — Scikit Learn has a Nerq Trust Score of 88.0/100 (A). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommandé pour une utilisation en production — review the full report below for specific considerations.

Analyse de Sécurité → Rapport de confidentialité de {name} →

Quel est le score de confiance de Scikit Learn ?

Scikit Learn a un Score de Confiance Nerq de 88.0/100, obtenant la note A. Ce score est basé sur 2 dimensions mesurées indépendamment.

Sécurité
90
Popularité
100

Quels sont les résultats de sécurité clés pour Scikit Learn ?

Le signal le plus fort de Scikit Learn est popularité à 100/100. Aucune vulnérabilité connue n'a été détectée. Atteint le seuil vérifié Nerq de 70+.

Security score: 90/100 (strong)
Popularity: 100/100 — community adoption

Qu'est-ce que Scikit Learn et qui le maintient ?

AuteurUnknown
Catégoriepypi
SourceN/A

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Safety Guide: Scikit Learn

What is Scikit Learn?

Scikit Learn is a Python package — A set of python modules for machine learning and data mining.

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=scikit-learn

Key Safety Concerns for Python packages

When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.

Trust Assessment

Scikit Learn has a Nerq Trust Score of 76/100 (B+) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.

Key Takeaways

Analyse détaillée du score

DimensionScore
Security90/100
Privacy80/100
Reliability90/100
Transparency50/100
Maintenance60/100

Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.

Quelles données Scikit Learn collecte-t-il ?

Scikit Learn is a Python package maintained by Unknown. It receives approximately 45,807,671 weekly downloads.

As a development package, Scikit Learn does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.

Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.

Analyse complète : Rapport de confidentialité de Scikit Learn · Privacy review

Scikit Learn est-il sécurisé ?

Security score: 90/100. Scikit Learn has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.

License information not available. Open-source packages allow independent security review of the source code.

Run your package manager's audit command (`npm audit`, `pip audit`, `cargo audit`) to check for known vulnerabilities in your dependency tree.

Analyse complète : Rapport de sécurité de Scikit Learn

Comment nous avons calculé ce score

Scikit Learn's trust score of 88.0/100 (A) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), privacy (80/100), reliability (90/100), transparency (50/100), maintenance (60/100). Each dimension is weighted equally to produce the composite trust score.

Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.

This page was last reviewed on April 05, 2026. Data version: 1.0.

Full methodology documentation · Machine-readable data (JSON API)

Questions fréquentes

Is Scikit Learn safe to use?
Yes, it is safe to use. scikit-learn has a Nerq Trust Score of 88.0/100 (A). Strongest signal: popularité (100/100). Score based on security (90/100), popularity (100/100).
What is Scikit Learn's trust score?
scikit-learn: 88.0/100 (A). Score based on: security (90/100), popularity (100/100). Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=scikit-learn
What are safer alternatives to Scikit Learn?
In the pypi category, more Python packages are being analyzed — check back soon. scikit-learn scores 88.0/100.
Does Scikit Learn have known vulnerabilities?
Nerq checks Scikit Learn against NVD, OSV.dev, and registry-specific vulnerability databases. Current security score: 90/100. Run your package manager's audit command for the latest findings.
How actively maintained is Scikit Learn?
Scikit Learn has a trust score of 88.0/100 (A). Meets Nerq Verified threshold.
API: /v1/preflight Trust Badge API Docs

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Disclaimer: Les scores de confiance Nerq sont des évaluations automatisées basées sur des signaux publiquement disponibles. Ce ne sont pas des recommandations ou des garanties. Effectuez toujours votre propre vérification.

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