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 Anil-matcha · Agent Tool · ★ 3.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-generative-ai-apps safe to install? View the security audit →
🎨 Awesome Generative AI Apps 50+ open-source generative AI apps you can clone, deploy, and monetize. AI Platforms · Image Generators · Video Tools · Virtual Try-Ons · AI SaaS Templates · Platform Integrations Every template is production-ready with Google OAuth · Stripe Billing · One-click Vercel deploy <img src="https://img.shields.io/github/last-commit/Anil-matcha/awesome-gener
| Stars | 3,259 |
| Forks | 470 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 58.7074183593543/100 |
| Open Issues | 13 |
| Last Updated | 2026-09-17 |
| Created | 2023-11-10 |
| Platforms | cli, node |
| Est. Tokens | ~17k |
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awesome-generative-ai-apps is 50+ open-source generative AI apps you can clone, deploy, and monetize — image generators, video tools, virtual try-ons, AI SaaS templates, and platform integrations. One-click Vercel deploy on every . It is categorized as a Agent Tool with 3.3k GitHub stars.
awesome-generative-ai-apps is primarily written in JavaScript. It covers topics such as ai-apps, ai-image-generator, ai-saas.
You can find installation instructions and usage details in the awesome-generative-ai-apps GitHub repository at github.com/Anil-matcha/awesome-generative-ai-apps. The project has 3.3k stars and 470 forks, indicating an active community.
awesome-generative-ai-apps is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awesome-generative-ai-apps on Agent Skills Hub include Text-To-Video-AI, Generative-Media-Skills, awesome-generative-ai. 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: