Czy Backrefs jest bezpieczny?
Backrefs — Nerq Trust Score 74.2/100 (Ocena B). Na podstawie analizy 2 wymiarów zaufania, jest ogólnie bezpieczny, ale z pewnymi zastrzeżeniami. Ostatnia aktualizacja: 2026-04-05.
Tak, Backrefs jest bezpieczny w użyciu. Backrefs to Python package with a Nerq Trust Score of 74.2/100 (B), based on 3 independent data dimensions. It is recommended for production use. Security: 90/100. Popularity: 90/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-05. Dane odczytywalne maszynowo (JSON).
Czy Backrefs jest bezpieczny?
YES — Backrefs has a Nerq Trust Score of 74.2/100 (B). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.
Jaki jest wynik zaufania Backrefs?
Backrefs ma Nerq Trust Score 74.2/100 z oceną B. Ten wynik opiera się na 2 niezależnie mierzonych wymiarach, w tym bezpieczeństwie, konserwacji i adopcji społeczności.
Jakie są kluczowe ustalenia bezpieczeństwa dla Backrefs?
Najsilniejszy sygnał Backrefs to bezpieczeństwo na poziomie 90/100. Nie wykryto znanych luk w zabezpieczeniach. It meets the Nerq Verified threshold of 70+.
Czym jest Backrefs i kto go utrzymuje?
| Autor | Unknown |
| Kategoria | pypi |
| Źródło | N/A |
Podobne Pypi wg wyniku zaufania
Safety Guide: Backrefs
What is Backrefs?
Backrefs is a Python package — A wrapper around re and regex that adds additional back references..
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=backrefs
Key Safety Concerns for Python packages
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Backrefs has a Nerq Trust Score of 74/100 (B) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Backrefs has a Trust Score of 74/100 (B).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Szczegółowa analiza wyniku
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Privacy | 80/100 |
| Reliability | 90/100 |
| Transparency | 50/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
Jakie dane zbiera Backrefs?
Backrefs is a Python package maintained by Unknown. It receives approximately 2,722,423 weekly downloads.
As a development package, Backrefs 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.
Pełna analiza: Raport prywatności Backrefs · Privacy review
Czy Backrefs jest bezpieczny?
Security score: 90/100. Backrefs 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.
Pełna analiza: Raport bezpieczeństwa Backrefs
Jak obliczyliśmy ten wynik
Backrefs's trust score of 74.2/100 (B) 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)
Często zadawane pytania
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Disclaimer: Wyniki zaufania Nerq to zautomatyzowane oceny oparte na publicznie dostępnych sygnałach. Nie stanowią rekomendacji ani gwarancji. Zawsze przeprowadzaj własną weryfikację.