Is Passlib Safe?
Passlib — Nerq Trust Score 67.2/100 (B- grade). Score based on 2 independent trust signals. Last analyzed: 2026-08-11
Passlib is a Python package with a Nerq Trust Score of 67.2/100 (B-), based on 3 independent data dimensions. Last analyzed: 2026-08-11 Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-08-11. Machine-readable data (JSON).
Is Passlib safe?
Trust Score Breakdown — Passlib has a Nerq Trust Score of 67.2/100 (B-). Measured across 2 independent trust signals (as of 2026-08-11).
What is Passlib's trust score?
Passlib has a Nerq Trust Score of 67.2/100, 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 Passlib?
Passlib's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Passlib and who maintains it?
| Author | Eli Collins |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Passlib
What is Passlib?
Passlib is a Python package — comprehensive password hashing framework supporting over 30 schemes.
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=passlib
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Passlib has a Nerq Trust Score of 67/100 (B-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Passlib has a Trust Score of 67/100 (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.
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.