What is AutoSentinel?
AutoSentinel is a AI tool that A self-evolving autonomous smart contract auditor that experiments on its own auditing methodology using an autoresearch-inspired loop. It audits smart contracts for vulnerabilities using static analy. It has a Nerq Trust Score of 40/100 (E). 0 GitHub stars. Published by 0x6ffa1e00509d8b625c2f061d7db07893b37199bc. Last analyzed September 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 0 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
What AutoSentinel Does
AutoSentinel is a agent in the AI tool category. A self-evolving autonomous smart contract auditor that experiments on its own auditing methodology using an autoresearch-inspired loop. It audits smart contracts for vulnerabilities using static analysis, LLM reasoning, and fuzz testing — then benchmarks, mutates, and improves its strategy autonomou. It is published by 0x6ffa1e00509d8b625c2f061d7db07893b37199bc and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use AutoSentinel
AutoSentinel is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.
Details
| Author | 0x6ffa1e00509d8b625c2f061d7db07893b37199bc |
|---|---|
| Category | AI tool |
| License | Not specified |
| Type | agent |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 0/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=autosentinel
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| MarkItDown | 42 | 92.8K |
| Filesystem | 50 | 89.4K |
| Time | 50 | 89.4K |
| Sequential Thinking | 50 | 89.4K |
| Fetch | 50 | 89.4K |
Frequently Asked Questions
Last updated September 2026. Trust scores based on automated analysis of public data.