fangcun-scam-radar@1.0.0
VERIFIED· install onlyPublisher claims: "理财防割韭菜识别助手。当用户遇到"老师荐股/带单"、"9元/免费理财课"、"保本高收益"、"内幕消息"、可疑理财App/平台，想自查风险、验证对方是否持牌时使用。对话式十问采集，用户零格式门槛。只教通用识别特征+给持牌查验入口+列命中事实，绝不替用户给"某产品/课程/平台是骗局"的定性判断，不荐股不代操作。适合所有被理财营销包围的普通人。" Observed in sandbox: no network, touches nothing outside the project, writes no memory.
Coverage
Nothing executable in the bundle ran; the trace covers the install step only.- Tested
- every file read, file written and host contacted by what ran
- Not tested
- use of the skill by an agent
Is [email protected] safe to install?
KillerSkills ran it in the KillerSkills honeypot sandbox (1 scenario; nothing executable in the bundle ran; the trace covers the install step only) on 2026-11-13 and scored it 90/100 (Verified). In what ran, nothing we could detect went wrong: no undeclared network egress, no credential reads, no persistent instruction writes. What it does with a real credential was not observed; the static findings and the publisher carry the rest of the score. Summary: no network, touches nothing outside the project, writes no memory.
Behavior trace
Honeypot run · 0 s · 1 scenarios · 0 deviationsStatic findings
return subprocess.run(Fix: Build commands from fixed arguments, never from interpolated strings; prefer an API client over shelling out.python radar_check.py --input case.json [--output report.md]Fix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why.Cost to the agent
Tokens estimated at four characters each. Skills load their instruction text when triggered; the figure is what that costs.
Known vulnerabilities
Vulnerability advisories (OSV) cover npm and PyPI packages; this registry has no advisory database.