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Source channel @olddriverGDstudy · Post #49 · Mar 24

江湖舔狗传 江湖者,江湖也! 各兄弟五湖四海汇聚一堂,为的是个情字,讲的是个义字,说的是个道理。 江湖上无数前辈好汉,忍饥挨饿,夜以继日,通宵达旦,上下求索,陷过无数的坑,踏破无数双鞋换得了有限的几个极品资源,未曾敢占为己有,而是毫无保留,无私公布奉献。 这一切为什么?为的是天下草根、屌丝们,不受仙人跳之苦,不遭各种骗费之难,不枉花了辛苦搬砖的银两盘缠,这是多么高尚的精神,多么高贵的品质啊! 江湖就是江湖,林子大了什么鸟儿都有,舔狗们也像病毒般出没,为害人间。这些禽兽毫无尊严、毫无底线,从溜须拍马、到阿谀奉承,从冷屁股到甜盘子全方位无死角。 舔狗,做着劝婊子从良的梦,抱着救风尘女子出火坑的“崇高”的性幻想,岂不知自己已是婊子口中的笑话! 江湖有江湖的规矩,江湖有江湖的原则,江湖有江湖的风貌,江湖有江湖的脾气。 我知舔狗是死不光的,这一车死光了,下一车还在路上。 但舔狗永远不过是个道具而已,又何必自作多情。 舔狗,你听,电话声已响起,你的钟到了!闭上臭嘴,滚出去把门关上! 作者:41秒哥 标签:#语录

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Libreware

@libreware · Post #1512 · 09/28/2025, 11:58 AM

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)

djangoproject

@djangoproject · Post #241 · 01/25/2017, 01:30 PM

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.