Is Brainiac Safe?
Brainiac — Nerq Trust Score 50.8/100 (C- grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Brainiac is a Python package with a Nerq Trust Score of 50.8/100 (C-), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Brainiac safe?
Trust Score Breakdown — Brainiac has a Nerq Trust Score of 50.8/100 (C-). Measured across 2 independent trust signals (as of 2026-03-20).
What is Brainiac's trust score?
Brainiac has a Nerq Trust Score of 50.8/100, 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 Brainiac?
Brainiac's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Brainiac and who maintains it?
| Author | Mason Swanson |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Brainiac
What is Brainiac?
Brainiac is a Python package — Various Components For Use In An Artificial Intelligence System Which Are Totally Usable On Their Own.
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=Brainiac
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Brainiac has a Nerq Trust Score of 51/100 (C-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Brainiac has a Trust Score of 51/100 (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.