Chasing Your Tail (CYT) https://github.com/ArgeliusLabs/Chasing-Your-Tail-NG A comprehensive #WiFi probe request analyzer that monitors and tracks wireless devices by analyzing their probe requests. The system integrates with #Kismet for packet capture and WiGLE API for #SSID#geolocation analysis, featuring advanced #surveillance#detection capabilities. Features Real-time Wi-Fi monitoring with Kismet integration Advanced surveillance detection with persistence scoring Automatic GPS integration - extracts coordinates from Bluetooth GPS via Kismet GPS correlation and location clustering (100m threshold) Spectacular KML visualization for Google Earth with professional styling and interactive content Multi-format reporting - Markdown, HTML (with pandoc), and KML outputs Time-window tracking (5, 10, 15, 20 minute windows) WiGLE API integration for SSID geolocation Multi-location tracking algorithms for detecting following behavior Enhanced GUI interface with surveillance analysis button Organized file structure with dedicated output directories Comprehensive logging and analysis tools Requirements Python 3.6+ Kismet wireless packet capture Wi-Fi adapter supporting monitor mode Linux-based system WiGLE API key (optional)
#夸克网盘#青龙#自动转存#签到#任务#Script#Task#quark#Docker 夸克网盘自动签到转存脚本 功能亮点: • 自动签到:每日自动完成签到,领取网盘奖励; • 自动转存:对持续更新的资源自动转存,减少手动操作; • 命名整理:统一文件命名规则,便于管理; • 推送提醒:支持消息推送,实时获取动态; • 刷新媒体库:自动刷新媒体库,配合 Alist、rclone、Emby,实现自动追更。 适用场景: 适合网盘重度用户和资源收集者,大幅提升资源管理效率。 📢 群聊: @TossLab 🎈 频道: @TossLabChannel ❤️不想错过精彩内容,请打开 #频道通知,你的 #阅读#点赞#转发 便是我发帖的最大动力!
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搜索 #geolocation
@djangoproject · Post #241 · 2017/01/25 13:30
http://www.aparat.com/v/4yGhH #Geolocation apps with #Django. Latitude, longitude, altitude, and even #iBeacons can be leveraged to enable geo-targeted experiences. But how do we build and optimize the server-side components to handle these requirements? Using a combination of libraries and techniques, we will illustrate these concepts. In this discussion everything from #map clustering and caching, to distance calculations and polygonal layering will be demonstrated using Django, #GeoDjango, #Redis, and #PostGIS as our tool belt.