Is Bandit Safe?
Bandit — Nerq Trust Score 79.2/100 (B+ grade). Score based on 2 independent trust signals. Last analyzed: 2026-07-21
Bandit is a Python package with a Nerq Trust Score of 79.2/100 (B+), based on 3 independent data dimensions. Last analyzed: 2026-07-21 Security: 90/100. Popularity: 90/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-07-21. Machine-readable data (JSON).
Is Bandit safe?
Trust Score Breakdown — Bandit has a Nerq Trust Score of 79.2/100 (B+). Measured across 2 independent trust signals (as of 2026-07-21).
What is Bandit's trust score?
Bandit has a Nerq Trust Score of 79.2/100, 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 Bandit?
Bandit's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Bandit and who maintains it?
| Author | PyCQA |
| Category | Python Packages |
| Source | N/A |
Bandit Across Platforms
Same developer/company in other registries:
Similar Pypi by Trust Score
Safety Guide: Bandit
What is Bandit?
Bandit is a Python package — Security oriented static analyser for python code..
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=bandit
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Bandit has a Nerq Trust Score of 79/100 (B+). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Bandit has a Trust Score of 79/100 (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 | 100/100 |
| Popularity | 90/100 |
| Quality | 65/100 |
| Community | 35/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Bandit collect?
Bandit is a Python package maintained by PyCQA. It receives approximately 4,953,591 weekly downloads. Licensed under Apache-2.0.
As a development package, Bandit 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: Bandit Privacy Report · Privacy review
Is Bandit secure?
Security score: 90/100. Bandit 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: Bandit Security Report
Bandit Across Platforms
Same developer/company in other registries:
How we calculated this score
Bandit's trust score of 79.2/100 (B+) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (100/100), popularity (90/100), quality (65/100), 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 July 21, 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.