Is Sdk Metrics Safe?
Sdk Metrics — Nerq Trust Score 80.5/100 (A- grade). Score based on 2 independent trust signals. Last analyzed: 2026-09-07
Sdk Metrics is a npm package with a Nerq Trust Score of 80.5/100 (A-), based on 3 independent data dimensions. Last analyzed: 2026-09-07 Security: 90/100. Popularity: 100/100. Data sourced from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-09-07. Machine-readable data (JSON).
Is Sdk Metrics safe?
Trust Score Breakdown — Sdk Metrics has a Nerq Trust Score of 80.5/100 (A-). Measured across 2 independent trust signals (as of 2026-09-07).
What is Sdk Metrics's trust score?
Sdk Metrics has a Nerq Trust Score of 80.5/100, earning a A- grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Sdk Metrics?
Sdk Metrics's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Sdk Metrics and who maintains it?
| Author | dyladan |
| Category | npm Packages |
| Source | N/A |
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Safety Guide: Sdk Metrics
What is Sdk Metrics?
Sdk Metrics is a Node.js package — OpenTelemetry metrics SDK.
How to Verify Safety
Run npm audit to check for vulnerabilities. Review the package's GitHub repository for recent commits.
You can also check the trust score via API: GET /v1/preflight?target=@opentelemetry/sdk-metrics
Key Safety Concerns for Node.js package
When evaluating any Node.js package, watch for: dependency vulnerabilities, malicious packages, typosquatting.
Measured Signals
Sdk Metrics has a Nerq Trust Score of 80/100 (A-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Sdk Metrics has a Trust Score of 80/100 (A-).
- 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 | 80/100 |
| Popularity | 100/100 |
| Quality | 70/100 |
| Community | 60/100 |
Based on 5 dimensions. Data from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Sdk Metrics collect?
Sdk Metrics is a Node.js package maintained by dyladan. It receives approximately 26,269,983 weekly downloads. Licensed under Apache-2.0.
As a development package, Sdk Metrics 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: Sdk Metrics Privacy Report · Privacy review
Is Sdk Metrics secure?
Security score: 90/100. Sdk Metrics has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under Apache-2.0, 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: Sdk Metrics Security Report
How we calculated this score
Sdk Metrics's trust score of 80.5/100 (A-) is computed from npm registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (80/100), popularity (100/100), quality (70/100), community (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.
Signals last measured on September 07, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API) · Dated observation record
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.