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🔎 Map Locations Using Nearby WiFi Access Points Most people search for WiFi networks just to connect… When I'm doing recon, one of my favorite ways to map a target's environment is analyzing nearby WiFi access points. This is my favorite method to find geo-related clues when other data...

14,981 Aufrufe • vor 23 Tagen •via X (Twitter)

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Once we started to work with large global retailers, we needed a better way to scale this process. Ideally, the staff at the store could do this themselves — rather than us flying our team across the world — and then we could lower the cost and timelines. So we built a self-serve version of our survey app, with a tutorial mode designed for beginners. Over time, we collected millions of data points, and so we were able to develop an algorithm which would auto-correct mistakes. In other words, if the surveyor accidentally placed their ground-truth location in the wrong place on the map, we could use our algorithms to detect it, and correct it. So now we have WiFi, and with and our efforts on producing a high quality survey, we have the best WiFi positioning available. With WiFi on its own, it’s achieving 3 meter accuracy. This is a great foundation to build on. WiFi + Motion data To refine this down to 1-meter accuracy, we realised that we could combine WiFi with the same technology behind self-driving cars and robotics: a motion system called SLAM (Simultaneous Localization and Mapping). SLAM uses the accelerometer, gyroscope and camera system to understand precise device motion. Imagine a car driving through a tunnel, using the motion since its last GPS ping to keep location accurate until it comes out the other side. On a phone, this technology is very reliable, and measures device motion with high precision. But SLAM is measuring motion within its own coordinate space, it’s not aligned with the real world. SLAM tracks the user’s relative motion, like “moved forward 2 meters, then turned left”, but does “forward” mean “north”, or some other direction? It’s not calibrated, so it could mean any location, any direction. We can’t rely on the compass to help us out with this, because phone compasses are notoriously incorrect — everyone knows the frustration of being sent the wrong way down a street. So our job was to align this motion data with the triangulation data we were receiving from WiFi. We designed an algorithm that could simulate every possibility, filter the unlikely scenarios, and hone in your location, using WiFi as an anchor. So WiFi gives us the initial blue dot, SLAM gives us motion, and as the user starts walking and we receive more data, our algorithms can refine location accuracy down to a consistent 1-meter accuracy. We’ve tested these algorithms in many locations, on hundreds of hours of ground-truth data:

Andrew Hart

90,946 Aufrufe • vor 1 Jahr

Here's a copy/paste prompt recipe and vid showing exactly how to ask an LLM for an interactive map with satellite/map layers + a georeferencer that lets you see how old maps correspond with modern geography. Today the computer can’t make good print maps (that's your hill to climb ) but it can, with five bucks and twenty minutes, make good interactive maps. No software/GIS knowledge necessary, you just need a few nouns and an LLM. Scroll to the bottom for the repo/live map if you want those. I'm using Claude Code as an extension in VS Code but you can use the Claude CLI, Cursor, whatever. 1) Let's grab an old cadastral map and see who owned big tracts of a city; I found this an 1854 map of Niagara Falls, NY I found in the Library of Congress: , grabbed the .jp2, saved as a jpg from photoshop. 2) Let's ask Claude Code for a map. You can see exactly what I did in the video but my prompt, sans simple "hey it's busted" debugging, is written out in the following paragraphs. I explain the map-specific nouns in brackets. You can likely dump this whole thing in your LLM window and it'll work; I'd try plan mode + skip permissions. THE PROMPT Make an interactive map with MapLibre GL JS [maplibre is a javascript mapping library, a FOSS version of Mapbox GL JS. This lets us display tiled map data and arbitrary images on the map] Add basemap toggles with Esri satellite, Carto Positron, and OSM [these map layers require no API keys for light usage; Carto Positron is a nice road map layer and OSM is ugly but comprehensive] Add a globe/mercator projection toggle [I think the globe looks better at low zooms] Add a layer panel on the left with visibility checkboxes and delete buttons. Add a search box on the map that flies to results, with deletable pin markers [Makes this easy to get to your area of interest] Include an interactive local georeferencer: drop a JPG, pick ground control points on a zoomable/pannable image viewer, place them on the map, watch it warp with a progress bar centered on the map. [The georeferencer uses math ("affine transform"??) to match points on the old map to points on the new map; generally you click road intersections on the old map, match them on the new map, repeat a dozen times and everything aligns] The georeferenced map overlay defaults to 25% opacity with a slider above the control point list. [I want it easy to see the underlying modern geography] Add Export/import control point buttons [this saves the control points as a JSON so you can save and reimport your work] Add a button to export the warped image as a GeoTIFF with a .prj [In case you want to add the georeferenced image to a real GIS program like QGIS] Look up all relevant docs before starting [Claude sometimes uses outdated stuff] Split everything into separate HTML/CSS/JS files [Claude tends to pile everything in index.html, which is hard to read] Use Optima font, base color #FEFAF6 [I just like this style] Let me test with a local server [it serves it on a simple server so you can nav your host to localhost:8000 and try it out] Log all errors [so you don't have to play telephone with the LLM describing what's busted] 3) Once your LLM finishes, test it out in your browser; if it doesn't work, ask the LLM to check logs. Repeat 'til functional. 4) After this works on your computer, you can show it to everyone by hosting it on GitHub: prompt with "write a README explaining what everything does, add it to a new GitHub repo, deploy using GitHub pages, gimme the live URL" Here's what Claude made for me, try it yourself: • Upload the JPG in the repo, which is linked below • "Add GCP" • Click somewhere recognizable on the old map, like the tip of an island or a road intersection • Click the matching point on the new map • Repeat til you have least 3x points • Hit "georeference" • You'll see the old map atop the new map; if you want a better fit, delete bad points or add a dozen new ones, hit georeference again, repeat Repo: Is this map robust? Human-maintainable? Elegant? Performant? Secure? No, but *your* personal web map need not be. It just needs to work for *your* narrow use case, because it’s *your* map.

Evan Applegate

15,772 Aufrufe • vor 4 Monaten

⚠️Your phone scans for WiFi networks 24/7 📡 Even when you're not connected. This is what they build from those scans 🧵👇 Let me explain every single piece of this surveillance system so normies can understand what's happening to them right now. THE TARGET DEVICE PROFILE (Top Left) 📱 Device ID: DEV-7A3F9B First Seen: SUN 10:14 AM at CHURCH ⛪ That's YOU. One scan at church Sunday morning and you're permanently in their system. From that SINGLE capture, they mapped: • 36 WiFi networks you passed by 📶 • 7 locations in your daily life 📍 • Your complete daily routine 🔄 • 16 people you're regularly near 👥 All PASSIVELY. You didn't connect to any WiFi. Your phone just scanned. THE NETWORK MAP (Center) 🗺️ Each circle is a place in YOUR life identified by WiFi networks your phone detected: ⛪ CHURCH (purple): CalvaryChapel_Guest 🏠 HOME (dark blue): Smith_Family_5G 🏢 OFFICE (green): TechCorp_Internal 💪 GYM (pink): FitLife_Premium 🛒 GROCERY (green): FreshMart_WiFi ☕ COFFEE SHOP (orange): BlueMug_Public 🏫 KIDS' SCHOOL (pink): OakviewElem_Staff 🏘️ NEIGHBOR (blue): Johnson_Net_2.4G Your phone sees your neighbor's WiFi from your house → They know you live next door to that address 🏠 Your phone sees school WiFi → They know you have kids 👨‍👩‍👧‍👦 Your phone sees office WiFi 8am-5pm → They know where you work 💼 THE WIFI PROBE LOG (Bottom Left) 📊 This is the raw data your phone is SCREAMING into the void: 📡 PROBE: FitLife_Premium | -70dBm 📡 PROBE: FreshMart_WiFi | -65dBm 📡 PROBE: BlueMug_Public | -73dBm Every network. Every router. Every signal strength. They're building a TIMELINE of everywhere you go with PRECISION ⏱️ Signal strength tells them how CLOSE you are to each spot. THE AI INFERENCE ENGINE (Bottom Right) 🤖 Now AI takes that raw data and starts GUESSING about your life: 🏠 HOME: Smith_Family_5G detected every night = Your address identified 💼 WORK: TechCorp_Internal detected 8AM-5PM = Your employer identified 👨‍👩‍👧 FAMILY: OakviewElem detected = You have school-age kids ☕ ROUTINE: BlueMug_Public every morning = You're a coffee regular 🏘️ NEIGHBOR: Johnson_Net_2.4G = They mapped your neighborhood The AI doesn't just see locations 📍 It builds PATTERN RECOGNITION 🧠 You hit the gym every Monday/Wednesday at 6pm 💪 You grab coffee every weekday at 7:15am ☕ You're at church every Sunday 10am-11:30am ⛪ You shop groceries every Thursday evening 🛒 They know your routine better than your own family💀 THE PART EVERYONE MISSES ⚠️ This WiFi fingerprint thing? IT'S JUST ONE LAYER OF A SEVEN-LAYER SURVEILLANCE CAKE 🎂 📍 Geofence capture (grabbing your device ID at church/events) 📶 WiFi fingerprinting (what you're seeing here) 🔵 Bluetooth proximity logging (tracking who you're near) 📡 Cell tower triangulation (backup tracking when no WiFi) 🛰️ GPS coordinate harvesting (from apps demanding location permission) 📲 Device advertising ID (linking to your web browsing) 🕸️ Social graph mapping (connecting all your relationships) Each layer feeds the others 🔄 The geofence grabbed you at church ⛪ The WiFi mapped your entire life 🗺️ Bluetooth logged everyone you sat near 👥 Cell towers tracked you driving 🚗 GPS confirmed exact coordinates 🎯 Your ad ID linked your web history 💻 The social graph connected your whole network 🕸️ THEY BUILD A COMPLETE FILE ON YOU 📂 Who you are ✅ Where you live ✅ Where you work ✅ What you believe ✅ Who your friends are ✅ What your routines are ✅ What your weaknesses are ✅ All from PASSIVE SCANNING 📡 No warrant ❌ No consent ❌ No notification ❌ THE COMPANIES DOING THIS RIGHT NOW 🏢 This isn't conspiracy theory. Real companies selling this data TODAY: GroundTruth Selling church geofence data 📍⛪ Mobilewalla Profiling every device owner 📱👤 Placer.ai Tracking where you shop 🛒📊 Cuebiq Harvesting location pings 📡🎯 SafeGraph Selling POI visit patterns 🗺️💰 They call it "location intelligence for brands and campaigns" 🎯 Translation: They're selling your life 💰 WHAT YOU CAN DO (BUT IT'S NOT ENOUGH) 🛡️ 📱 iPhone: Settings > Privacy & Security > Location Services > System Services > Networking & Wireless > OFF 🤖 Android: Settings > Location > WiFi scanning > OFF But real talk? You're STILL vulnerable through Bluetooth and cell towers 📡 The only actual defense is leaving your phone at home 🏠 Which they KNOW you won't do 😏 WHY THIS MATTERS FOR POLITICAL TARGETING 🎯 🌍 Foreign governments BUY this data from brokers 🗳️ Political campaigns use it for micro-targeting 🎭 Influence operations identify high-value targets 📺 Propaganda gets personalized to YOUR movement patterns They know you go to church ⛪ They know your routine 🔄 They know your social circle 👥 Now they can hit you with AI-generated content designed SPECIFICALLY for someone with your exact profile 🤖 🔗THE TPUSA/SUPERFEED/AZ GOVERNMENT CONTROL/MAKE HEAVEN (HELL) CROWDED = CONNECTION 🔗 My TPUSA investigation documents Superfeed Technologies selling geofencing to churches and political orgs 📄 This WiFi fingerprinting layer is HOW they build the targeting profiles 🎯 Then they use those profiles for what they call "ministry outreach" ⛪ But it's SURVEILLANCE wrapped in religious language 🙏 Funded by FOREIGN MONEY💰 BOTTOM LINE ⚡ 📱 Your phone is a 24/7 surveillance device 📶 WiFi fingerprint is just ONE targeting layer 🏢 Commercial companies sell your complete life pattern 🌍 Foreign governments buy it 🎯 Political operations weaponize it And 99% of Americans have NO IDEA it's happening 💀 Share this if you think people should know they're being tracked 🔁💥

Danks

94,617 Aufrufe • vor 5 Monaten