Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by webcoyote · Codex Skill · ★ 179
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🔒 Is clodpod safe to install? View the security audit →
ClodPod - Run AI agents in a macOS VM sandbox ClodPod creates a macOS virtual machine sandbox configured to run applications like Claude Code, Open AI Codex, Google Gemini, and Cursor Agent. It facilitates disabling AI permission prompts so you can get work done without risking your entire computer. ClodPod maps any number of your project directories into the virtual machine so AI agents can work on your code while remaining isolated from your host computer. ClodPod virtual machines include Xcode and common development tools, and it's easy to extend to add your own development tools and configuration files.
| Stars | 179 |
| Forks | 18 |
| Language | Shell |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 63.7512260966467/100 |
| Open Issues | 4 |
| Last Updated | 2026-08-30 |
| Created | 2025-09-01 |
| Platforms | claude-code, cli, codex, gemini |
| Est. Tokens | ~12k |
These tools work well together with clodpod for enhanced workflows:
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clodpod is Run AI agents isolated inside an macOS virtual machine. Configured to run Claude Code, OpenAI Codex, Cursor Agent, Google Gemini.. It is categorized as a Codex Skill with 179 GitHub stars.
clodpod is primarily written in Shell. It covers topics such as claude-code, macos, sandbox.
You can find installation instructions and usage details in the clodpod GitHub repository at github.com/webcoyote/clodpod. The project has 179 stars and 18 forks, indicating an active community.
clodpod is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to clodpod on Agent Skills Hub include agent-sessions, claude-forge, claude-notifications-go. 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: