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 RayBytes · Codex Skill · ★ 1.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ChatMock safe to install? View the security audit →
ChatMock Allows Codex to work in your favourite chat apps and coding tools. Install Homebrew pipx / pip GUI Download from releases (macOS & Windows) Docker See DOCKER.md Getting Started The server runs at by default. Use as your base URL for OpenAI-compatible apps. Usage Python python from openai import OpenAI client = OpenAI( baseurl="http://127.0.0.1:8000/v1", apikey="anyth
| Stars | 1,534 |
| Forks | 211 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 72.9423735407052/100 |
| Open Issues | 12 |
| Last Updated | 2026-09-01 |
| Created | 2025-08-15 |
| Platforms | cli, codex, python |
| Est. Tokens | ~14k |
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ChatMock is OpenAI & Ollama compatible API powered by Codex. It is categorized as a Codex Skill with 1.5k GitHub stars.
ChatMock is primarily written in Python. It covers topics such as ai, chatgpt, codex.
You can find installation instructions and usage details in the ChatMock GitHub repository at github.com/RayBytes/ChatMock. The project has 1.5k stars and 211 forks, indicating an active community.
ChatMock is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ChatMock on Agent Skills Hub include awesome-ChatGPT-repositories, codexia, py-gpt. 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: