Is Agentsphere Safe?
Agentsphere — Nerq Trust Score 57.8/100 (C grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Agentsphere is a Python package with a Nerq Trust Score of 57.8/100 (C), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 15/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Agentsphere safe?
Trust Score Breakdown — Agentsphere has a Nerq Trust Score of 57.8/100 (C). Measured across 2 independent trust signals (as of 2026-03-20).
What is Agentsphere's trust score?
Agentsphere has a Nerq Trust Score of 57.8/100, 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 Agentsphere?
Agentsphere's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Agentsphere and who maintains it?
| Author | agentsphere |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Agentsphere
What is Agentsphere?
Agentsphere is a Python package — Agentsphere SDK that give agents cloud environments.
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=agentsphere
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Agentsphere has a Nerq Trust Score of 58/100 (C). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Agentsphere has a Trust Score of 58/100 (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.