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 TornadoInsight · Agent Tool · ★ 109
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Sora-FullStack safe to install? View the security audit →
Featured in: AI Video Generation & Editing: Seedance, Kling & Subtitles
SoraFlows SoraFlows is a browser interface for OpenAI Sora,can generate, edit, share text/picture-to-video simply. Try Demo here 👉 SoraFlows One-Click to get a well-designed cross-platform Sora web UI Follow SoraFlows on Product Hunt. English Roadmap [ ] Login [ ] Login with Github OAuth [ ] Login with Google OAuth [ ] Login with Email [ ] Login with WeChat login [ ] Payments [ ] Stripe payments [ ] Tools [ ] Prompt Editor [ ] Features [ ] Voice to text [ ] Text to speech [ ] Voice clone [ ] Support for OSS [ ] Deploy [ ] Add support fo
| Stars | 109 |
| Forks | 4 |
| Language | TypeScript |
| Category | Agent Tool |
| Quality Score | 61.2225836348166/100 |
| Last Updated | 2025-09-27 |
| Created | 2025-09-27 |
| Platforms | browser, docker, node |
| Est. Tokens | ~487k |
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Sora-FullStack is OpenAi-Sora (SoraFlows) is an open-source, cross-platform web application for AI-powered video creation and editing using the latest OpenAI Sora model. Effortlessly generate, edit, and share videos fr. It is categorized as a Agent Tool with 109 GitHub stars.
Sora-FullStack is primarily written in TypeScript. It covers topics such as ai-tools, ai-video, chatgpt.
You can find installation instructions and usage details in the Sora-FullStack GitHub repository at github.com/TornadoInsight/Sora-FullStack. The project has 109 stars and 4 forks, indicating an active community.
The top alternatives to Sora-FullStack on Agent Skills Hub include sdk, ai-media-generator, OpenReels. 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: