Is Apeye Core Safe?
Apeye Core — Nerq Trust Score 64.0/100 (C+ grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Apeye Core is a Python package with a Nerq Trust Score of 64.0/100 (C+), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 75/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Apeye Core safe?
Trust Score Breakdown — Apeye Core has a Nerq Trust Score of 64.0/100 (C+). Measured across 2 independent trust signals (as of 2026-03-20).
What is Apeye Core's trust score?
Apeye Core has a Nerq Trust Score of 64.0/100, 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 Apeye Core?
Apeye Core's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Apeye Core and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Apeye Core
What is Apeye Core?
Apeye Core is a Python package — Core (offline) functionality for the apeye library..
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=apeye-core
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Apeye Core 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
- Apeye Core 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.