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 leepokai · Codex Skill · ★ 56
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is jev-guard safe to install? View the security audit →
jev-guard A security hook for coding agents, powered by Jev. Auto mode, for every coding agent Claude Code's auto mode is described as: "A separate classifier model reviews actions before they run, blocking anything that escalates beyond your request, targets unrecognized infrastructure, or appears driven by hostile content Claude read." That is exactly the job jev-guard does — as three typed questions to Jev (, , ) instead of a proprietary classifier — and it does it for Codex, Copilot, Gemini, Cursor, pi, OpenCode and ACP editors too, with the same policy and the same session memory everywhere. If you want auto mode outside Claude Code, or a second
| Stars | 56 |
| Forks | 8 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 68.4977398091511/100 |
| Last Updated | 2026-10-02 |
| Created | 2026-09-17 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~17k |
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jev-guard is Auto mode for every coding agent, built on Jev: risk-scores every tool call with session context (deny / ask / allow), flags prompt injection in results, checks skills and plugins. Claude Code, Codex,. It is categorized as a Codex Skill with 56 GitHub stars.
jev-guard is primarily written in JavaScript. It covers topics such as ai-agents, claude-code, codex.
You can find installation instructions and usage details in the jev-guard GitHub repository at github.com/leepokai/jev-guard. The project has 56 stars and 8 forks, indicating an active community.
jev-guard is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to jev-guard on Agent Skills Hub include jev-review, agent-skills, rampart. 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: