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 →
by ashishb · Agent Tool · ★ 167
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is amazing-sandbox safe to install? View the security audit →
Amazing Sandbox () Amazing Sandbox (AS) is for running various tools inside a Docker sandbox. [x] Prevents malicious packages from having full disk access and stealing data [x] Prevents AI agents from mistakenly deleting all files on your disk [x] Optionally, run packages like linters [air-gapped](https://en.wikipe
| Stars | 167 |
| Forks | 12 |
| Language | Go |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 74.7256175682062/100 |
| Last Updated | 2026-09-16 |
| Created | 2025-12-17 |
| Platforms | go |
| Est. Tokens | ~17k |
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amazing-sandbox is Amazing Sandbox - run third-party tools and AI agents securely on your machine. It is categorized as a Agent Tool with 167 GitHub stars.
amazing-sandbox is primarily written in Go. It covers topics such as developer-tools, devops, security-tools.
You can find installation instructions and usage details in the amazing-sandbox GitHub repository at github.com/ashishb/amazing-sandbox. The project has 167 stars and 12 forks, indicating an active community.
amazing-sandbox is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to amazing-sandbox on Agent Skills Hub include claude-code-skills, code-abyss, lazy-bird. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: