Security audit of enescingoz/colab-llm · Agent Tool by enescingoz · ★ 119
Yes — colab-llm passed AgentSkillsHub's rule-based security scan with no dangerous patterns detected. As with any third-party skill, confirm what credentials it requests before production use.
What it is: This repository provides a ready-to-use Google Colab notebook that turns Colab into a temporary server for running local LLM models using Ollama. It exposes the model API via a secure Cloudflare tunnel, allowing remote access from tools like curl or ROO Code in VS Code — no server setup or cloud deployment required.
No dangerous patterns were detected: no credential exfiltration, no obfuscated downloads, no sandbox-escape attempts, no prompt-injection markers.
| Security grade | ✓ SAFE |
| Quality score | 60/100 |
| GitHub stars | 119 |
| Language | Jupyter Notebook |
| Last updated |
This is AgentSkillsHub's free basic audit: an automated rule-based scan covering SlowMist's 11 red-flag categories (credential exfiltration, obfuscated payloads, sandbox escape, prompt injection, and more) across 117,000+ open-source AI agent skills and MCP servers, refreshed every 8 hours. A SAFE grade is a scan result, not a guarantee — deep 5-dimension audits (code · credentials · vendor · supply-chain · operational) are available for enterprise. Audited: 2026-07-03.