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git clone https://github.com/droidrun/mobile-jev.gitTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 461 |
| Forks | 57 |
| Language | JavaScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 54/100 |
| Open Issues | 6 |
| Last Updated | 2026-09-17 |
| Created | 2026-09-17 |
| Platforms | node |
| Est. Tokens | ~15k |
Mobile Jev ▶ Watch the demo — Jev opens Uber, enters a route from San Francisco Airport to the Golden Gate Bridge, and reaches payment selection. The recorded task timer shows about 21 seconds for 9 actions. A completed booking is not demonstrated. One goal. A real Android phone. Jev makes the decisions. A standalone mobile agent for Mobilerun, powered by TypeSafe's Jev and the Mobilerun API.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: