Is Anylabeling Safe?
Anylabeling — Nerq Trust Score 69.5/100 (B- grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Anylabeling is a Python package with a Nerq Trust Score of 69.5/100 (B-), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 45/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Anylabeling safe?
Trust Score Breakdown — Anylabeling has a Nerq Trust Score of 69.5/100 (B-). Measured across 2 independent trust signals (as of 2026-03-20).
What is Anylabeling's trust score?
Anylabeling has a Nerq Trust Score of 69.5/100, earning a B- grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Anylabeling?
Anylabeling's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Anylabeling and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Anylabeling
What is Anylabeling?
Anylabeling is a Python package — Effortless data labeling with AI support.
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=anylabeling
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Anylabeling has a Nerq Trust Score of 70/100 (B-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Anylabeling has a Trust Score of 70/100 (B-).
- 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.