Is Bagel Safe?
Bagel — Nerq Trust Score 53.2/100 (C- grade). Based on analysis of 2 trust dimensions, it is has notable safety concerns. Last updated: 2026-05-13.
Use Bagel with some caution. Bagel is a Python package with a Nerq Trust Score of 53.2/100 (C-), based on 3 independent data dimensions. Below the recommended threshold of 70. Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-25. Machine-readable data (JSON).
Is Bagel safe?
CAUTION — Bagel has a Nerq Trust Score of 53.2/100 (C-). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
What is Bagel's trust score?
Bagel has a Nerq Trust Score of 53.2/100, 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 Bagel?
Bagel's strongest signal is security at 90/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Bagel and who maintains it?
| Author | Neurobagel Developers |
| Category | Python Packages |
| Source | N/A |
Bagel Across Platforms
Same developer/company in other registries:
Similar Pypi by Trust Score
Safety Guide: Bagel
What is Bagel?
Bagel is a Python package — Automatic parsing of subjects' tabular data and imaging metadata into Neurobagel graph-compatible JSONLD files..
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=bagel
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Bagel has a Nerq Trust Score of 53/100 (C-) and has not yet reached Nerq trust threshold (70+). This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Bagel has a Trust Score of 53/100 (C-).
- Review carefully before use — below trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 50/100 |
| Popularity | 0/100 |
| Quality | 65/100 |
| Community | 35/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Bagel collect?
Privacy assessment for Bagel is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Bagel secure?
Security score: 90/100. Bagel has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under MIT License Copyright (c) 2022 - Neurobagel Project, Origami Lab, McGill University, allowing code inspection. 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.
Full analysis: Bagel Security Report
Bagel Across Platforms
Same developer/company in other registries:
How we calculated this score
Bagel's trust score of 53.2/100 (C-) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (50/100), popularity (0/100), quality (65/100), community (35/100). 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 May 13, 2026. Data version: 0.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.