Is Safetensors Safe?
Safetensors — Nerq Trust Score 55.0/100 (C grade). Based on analysis of 2 trust dimensions, it is has notable safety concerns. Last updated: 2026-03-31.
Use Safetensors with some caution. Safetensors is a Python package with a Nerq Trust Score of 55.0/100 (C), based on 3 independent data dimensions. It is below the recommended threshold of 70. Security: 65/100. Popularity: 95/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-31. Machine-readable data (JSON).
Is Safetensors safe?
CAUTION — Safetensors has a Nerq Trust Score of 55.0/100 (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 Safetensors's trust score?
Safetensors has a Nerq Trust Score of 55.0/100, 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 Safetensors?
Safetensors's strongest signal is popularity at 95/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Safetensors and who maintains it?
| Author | Unknown |
| Category | pypi |
| Source | N/A |
Safetensors Across Platforms
Same developer/company in other registries:
Similar Pypi by Trust Score
Safety Guide: Safetensors
What is Safetensors?
Safetensors is a Python package.
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=safetensors
Key Safety Concerns for Python packages
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Safetensors has a Nerq Trust Score of 55/100 (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
- Safetensors has a Trust Score of 55/100 (C).
- Review carefully before use — below trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 65/100 |
| Privacy | 80/100 |
| Reliability | 90/100 |
| Transparency | 50/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Safetensors collect?
Safetensors is a Python package maintained by Unknown. It receives approximately 16,620,935 weekly downloads.
As a development package, Safetensors 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: Safetensors Privacy Report · Privacy review
Is Safetensors secure?
Security score: 65/100. Safetensors 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: Safetensors Security Report
Safetensors Across Platforms
Same developer/company in other registries:
How we calculated this score
Safetensors's trust score of 55.0/100 (C) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (65/100), privacy (80/100), reliability (90/100), transparency (50/100), 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 March 31, 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.