Small photo of me somewhere in the Occitanie region in France, I have the Youth card for all students in Occitania.
Surely in the toilets of a well-known store?
It’s up to you to play the community of
OSINT !!
I've been building Velocity, a self-hosted OSINT platform inspired by platforms like Palantir Gotham, but designed around open intelligence sources.
The goal is to fuse live ADS-B, AIS, satellites, GPS jamming, internet outages, conflict events, news, and other OSINT feeds into a single operational picture instead of switching between dozens of separate tools. The feature set is already fairly extensive, so it takes some time to learn everything it can do.
There are still capabilities I'd like to add, including persistent video history, drone integration, 3D Gaussian splatting for immersive geospatial visualization, and more advanced sensor fusion and analytics.
This project has taken over two months of continuous development, monitoring, and refinement, and there's still plenty of work ahead. One of the biggest challenges is expanding the number and quality of available OSINT data sources.
AI is used as an analyst assistant rather than a replacement. It helps correlate data, identify patterns, and generate summaries, but findings are designed to remain evidence-driven and reviewed by the analyst.
I'd appreciate feedback from the OSINT community on what capabilities or data sources you'd like to see next.
GitHub here: https://github.com/AndrewCTF/osint-geospatial-console
I’m interested in learning OSINT. I want to be able to find someone’s address, name, or phone number just by having a photo of them or their username. Can you recommend some resources to get started? What tools do I need? Are there any fees associated with acquiring these tools? How long will it take me to master this skill if I dedicate an hour to learning every day? I’m very detail-oriented and proficient with computers. What are some effective ways to learn OSINT?
Hey I wanted to show my new Live Intelligence platform that i’ve been working on for months.
Need opinions.
Wi-Fi probe request harvesting and behavioral profiling.
Every phone constantly broadcasts "probe requests" — asking nearby air "are you my saved network?" — and these contain the SSIDs of every network the phone has ever connected to. Any laptop with a WiFi card that supports monitor mode (most do; check with iw list) can capture these passively with no hardware purchase. You'd put your card in monitor mode with airmon-ng, capture probe requests, and build a real-time analysis dashboard that: identifies unique devices (by MAC, with clustering for randomized MACs using timing correlation), infers their history (home network, workplace, coffee shops they've visited), tracks movement patterns over time, and demonstrates that MAC randomization is beatable through timing and SSID correlation attacks. Then you build the defensive tool: a detector that alerts when a device is being actively probed or tracked. Completely free. Very demonstrable in any public space with permission.
I'm working on a system that pulls geopolitical and cybersecurity events from open sources (official statements, satellite imagery, breach disclosures, conflict trackers, and sanctions filings) and tries to flag when a narrative around an event doesn't hold up against primary sources. Think less "who posted this?" and more "does the claim survive contact with the underlying data."
To be clear up front, this is about events, infrastructure, and narratives, not people. No individual tracking, no doxxing angle, nothing that touches a specific person's identity or location. I know that's a hard line here, and I want to stay well inside it.
Where I'm stuck is the verification layer. I can pull data fine (satellite feeds, news APIs, government bulletins, and breach databases), but turning "here are five sources saying different things" into "here's the most defensible version of what happened" is the actual hard problem. Right now my approach is source-tiering plus timestamp cross-referencing, but I suspect that's naive for anything state-actor-adjacent, where official sources themselves can be the disinfo.
For people who've done verification work on contested geopolitical or cyber claims: how do you actually weigh sources when even "primary" ones might be lying? Is there a methodology from journalism or intel work I should be borrowing instead of reinventing? And is "propaganda detection" even the right framing, or does that just invite bias accusations regardless of how neutral the pipeline is?
Genuinely looking for the failure modes here before I build more on a shaky foundation.
Salut ! Je cherche des sites d'OSINT pour rechercher des informations sur des personnes avec a la base peux d'informations a leurs sujet, par exemple seulement un nom et prénom, une ville ou un département ou est situé leur domicile. Auriez vous des liens a m'envoyer ?
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Hi! I'm French and relatively new to the OSINT world. 😊 I'm currently building my own OSINT bot as a personal learning project, so I'm still discovering how everything works.
I'm looking for a list of websites that specialize in data leaks so I can better understand the different types of publicly known sources and improve my project. I'm here to learn, so any advice or guidance would be greatly appreciated. Thanks in advance!
I wrote a Spanish company and officers search tool: https://mapasocietario.es - it works both in English and Spanish.
It is fully sourced from the Spanish corporate gazette, and differs from existing tools because:
It is graph-based. The exploration is free: double-clicking a node expands it and right-clicking on a node offers several options, including data preview
It includes sole shareholdings - the Spanish registry only allows 100% shareholdings to be included and this information is reflected in the graph
Accuracy: Several layers ensure accuracy, particularly when companies change names or provinces.
Additional data: there is a check for an officer's political affiliations, specifically with the Congress of Deputies.
Pathfinder and relationships: You can search the shortest path between two nodes in the graph and if you search more than one company in the same graph you can immediately surface any relationships.
NOTE: The NIF (tax ID) and other data may not be included in the data preview. However, it will be included when generating a due diligence report. This data is not strictly public and therefore, as a privacy-first platform, I decided to include it selectively - only when buying a due diligence report.
NOTE 2: The due diligence report includes an accurate AI analysis specifically tuned for the information present in the report. You can also add Spanish official financial statements (30 minutes delivery) and if you add the financial statements the AI will also include its financial analysis (which has been tuned on the Spanish general accounting rules).
Feel free to let me know if something is missing.
What do you think would help an investigative journalist?
Edit 28/6/2026:Thank you all you were extremely helpful!
Hi guys, I love digital investigations and pattern recognition. We all know about the big cases, but what are some lesser-known internet mysteries, ARG puzzles, or forgotten historical locations that were completely cracked open by everyday people using open-source intelligence? I’m looking for deep rabbit holes to dive into tonight. Drop your favorites! 💻🔍
Como achar o endereço IP real de um site com proxy rotativa, cloudflared, não tem como ver o código fonte, o site inteiro está em cachê, eles usam e abusam da WAF e por fim o domínio muda toda semana?
Hey everyone,
About 10 months ago, I shared the first version of my browser extension IntelHub here. Since then, it has completely evolved. It's no longer just a tool aggregator—it's now a full-blown, privacy-first investigation suite packed with capabilities.
Here is a quick taste of what’s inside v5.0:
🤖 Quad-Engine AI: Run parallel searches across Google AI, Brave Search, Phind, and Andi in-tab.
🔍 Deep Recon & Forensics: Extract EXIF/metadata (PDFs, Images, Docs), generate local file hashes, and run automated text profiling for crypto/emails/phones.
📊 Investigation Graph: Visually map entities and connect the dots right inside your browser.
👥 Local Facial Comparison: 100% offline, client-side facial recognition.
📱 Platform Intel: Telegram ID extraction, multi-engine reverse image search, domain safety scanning, and a Google Dorks builder.
🚀 What's Next? (Local AI for OPSEC) My next major focus is integrating local, self-hosted LLMs (like Ollama or LM Studio). The vision is to let you run AI summarization and entity extraction completely offline, keeping zero-trust OPSEC intact.
I'm sharing this across a couple of communities to gather as much feedback as possible. What new features, workflows, or tools would you want to see integrated next?
Check out the repo (and the full guide!) here: https://github.com/tomsec8/IntelHub
does anyone know of anything I can use to reverse search an email to potentially find social account names (ex X, Discord, Bluesky) anywhere?
any help is much appreciated!