Is Annotated Types Safe?
Annotated Types — Nerq Trust Score 65.2/100 (B- grade). Score based on 2 independent trust signals. Last analyzed: 2026-08-18
Annotated Types is a Python package with a Nerq Trust Score of 65.2/100 (B-), based on 3 independent data dimensions. Last analyzed: 2026-08-18 Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-08-18. Machine-readable data (JSON).
Is Annotated Types safe?
Trust Score Breakdown — Annotated Types has a Nerq Trust Score of 65.2/100 (B-). Measured across 2 independent trust signals (as of 2026-08-18).
What is Annotated Types's trust score?
Annotated Types has a Nerq Trust Score of 65.2/100, 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 Annotated Types?
Annotated Types's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Annotated Types and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Annotated Types
What is Annotated Types?
Annotated Types is a Python package — Reusable constraint types to use with typing.Annotated.
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=annotated-types
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Annotated Types has a Nerq Trust Score of 65/100 (B-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Annotated Types has a Trust Score of 65/100 (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.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 58/100 |
| Popularity | 100/100 |
| Quality | 40/100 |
| Community | 35/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Annotated Types collect?
Annotated Types is a Python package maintained by Unknown. It receives approximately 186,994,318 weekly downloads.
As a development package, Annotated Types 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: Annotated Types Privacy Report · Privacy review
Is Annotated Types secure?
Security score: 90/100. Annotated Types has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
License information not available. 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: Annotated Types Security Report
How we calculated this score
Annotated Types's trust score of 65.2/100 (B-) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (58/100), popularity (100/100), quality (40/100), 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.
Signals last measured on August 18, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON 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.