Is Chatbotapi Safe?
Chatbotapi — Nerq Trust Score 52.2/100 (C- grade). Score based on 2 independent trust signals. Last analyzed: 2026-03-20
Chatbotapi is a Python package with a Nerq Trust Score of 52.2/100 (C-), based on 3 independent data dimensions. Last analyzed: 2026-03-20 Security: 90/100. Popularity: 0/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-20. Machine-readable data (JSON).
Is Chatbotapi safe?
Trust Score Breakdown — Chatbotapi has a Nerq Trust Score of 52.2/100 (C-). Measured across 2 independent trust signals (as of 2026-03-20).
What is Chatbotapi's trust score?
Chatbotapi has a Nerq Trust Score of 52.2/100, 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 Chatbotapi?
Chatbotapi's strongest signal is security at 90/100. No known vulnerabilities have been detected.
What is Chatbotapi and who maintains it?
| Author | HilFing |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Chatbotapi
What is Chatbotapi?
Chatbotapi is a Python package — Library to make AI chatbot with other additional utilities.
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=ChatbotAPI
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Chatbotapi has a Nerq Trust Score of 52/100 (C-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Chatbotapi has a Trust Score of 52/100 (C-).
- 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.