No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
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🔒 Is llm-typesafe safe to install? View the security audit →
LLM plugin for accessing Jev and other TypeSafe AI models
| Stars | 19 |
| Forks | 2 |
| Language | Python |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 62.8532470179338/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-22 |
| Created | 2026-09-22 |
| Platforms | python |
| Est. Tokens | ~2k |
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llm-typesafe is LLM plugin for accessing Jev and other TypeSafe AI models. It is categorized as a AI Tool with 19 GitHub stars.
llm-typesafe is primarily written in Python.
You can find installation instructions and usage details in the llm-typesafe GitHub repository at github.com/simonw/llm-typesafe. The project has 19 stars and 2 forks, indicating an active community.
llm-typesafe is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: