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)
#青龙更新 青龙 v2.18.1 更新说明 青龙 v2.18.1 发布!本次更新优化功能并修复问题: • 新增功能:内置 QLAPI 增加环境变量和系统通知 API。 • 调整:移除 nedb 和 sentry,不再支持 2.10.x 版本自动迁移。 • 修复:多语言翻译问题改进。 更新方法: • 面板更新:系统设置 -> 其他设置 -> 检查更新 • 容器内更新:执行 ql update • Debian 用户:直接同步更新。 • 宿主机更新:运行命令 docker run --rm -v /var/run/docker.sock:/var/run/docker.sock containrrr/watchtower -cR <容器名> 版本镜像: • 正式版:whyour/qinglong:latest • Python3.10 正式版:whyour/qinglong:python3.10 • Debian 版:whyour/qinglong:debian • Python3.10 Debian 版:whyour/qinglong:debian-python3.10 • NPM 安装:npm i -g @whyour/qinglong 📢 群聊: @TossLab 🎈 频道: @TossLabChannel ❗️ ❗️ ❗️ ❗️ ❗️ ❗️ ❗️ ❗️ 🔘折腾系列频道 - 全面介绍 🔘境外离岸银行教程合集目录 🔘折腾实验室优质Github项目合集
Hashtags
找到 2 条相似帖子
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.