Is Cattrs Safe?
Cattrs — Nerq Trust Score 78.8/100 (B+ grade). Based on analysis of 2 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-04-01.
Yes, Cattrs is safe to use. Cattrs is a Python package with a Nerq Trust Score of 78.8/100 (B+), based on 3 independent data dimensions. It is recommended for production use. Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-01. Machine-readable data (JSON).
Is Cattrs safe?
YES — Cattrs has a Nerq Trust Score of 78.8/100 (B+). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.
What is Cattrs's trust score?
Cattrs has a Nerq Trust Score of 78.8/100, 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 Cattrs?
Cattrs's strongest signal is popularity at 100/100. No known vulnerabilities have been detected. It meets the Nerq Verified threshold of 70+.
What is Cattrs and who maintains it?
| Author | Unknown |
| Category | pypi |
| Source | N/A |
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Safety Guide: Cattrs
What is Cattrs?
Cattrs is a Python package — Composable complex class support for attrs and dataclasses..
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=cattrs
Key Safety Concerns for Python packages
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Cattrs has a Nerq Trust Score of 79/100 (B+) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Cattrs has a Trust Score of 79/100 (B+).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Privacy | 80/100 |
| Reliability | 90/100 |
| Transparency | 85/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Cattrs collect?
Cattrs is a Python package maintained by Unknown. It receives approximately 18,276,054 weekly downloads. Licensed under MIT.
As a development package, Cattrs does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.
Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.
Full analysis: Cattrs Privacy Report · Privacy review
Is Cattrs secure?
Security score: 90/100. Cattrs has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under MIT, 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: Cattrs Security Report
How we calculated this score
Cattrs's trust score of 78.8/100 (B+) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), privacy (80/100), reliability (90/100), transparency (85/100), maintenance (60/100). 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 April 01, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
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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.