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Owned by Osint

The OSINT Club!

11 members • Free

OSINT Club is where curious minds, researchers, entrepreneurs, and digital explorers come together to master Open-Source Intelligence (OSINT).

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Skoolers

174.8k members • Free

8 contributions to The OSINT Club!
OSINT Challenge 003
You’re looking at a photo taken from a rooftop bar. Your task: geolocate the exact location (including name of the establishment). 🌍 🔎 Hints to Guide You: • Pay attention to the skyline and the distinctive tower on the left. • Look closely at the river running through the scene. • The photo is taken from a terrace overlooking the water, with a clear view of the skyline. 📍 Can you pinpoint the exact building this was taken from? Drop your answers — building name, coordinates, or Google Maps link — in the comments below
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OSINT Challenge 003
What is SOCMINT?
🔎 SOCMINT: Social Media Intelligence for OSINT Investigators - check out the classroom! Social media is one of the richest sources of open-source intelligence. SOCMINT is the practice of collecting and analyzing data from platforms like Facebook, Twitter/X, Instagram, TikTok, Reddit, and others to uncover insights, patterns, and connections. Here’s a quick breakdown of tools, tactics, and strategies to add to your OSINT toolkit: 🛠️ Tools for SOCMINT • Sherlock / WhatsMyName → find usernames across hundreds of platforms. • Twint → scrape Twitter/X data without the API. • Social Bearing → analyze hashtags, users, and mentions. • Creepy / Echosec / Maltego → advanced social media data collection and visualization. • Wayback Machine / Archive.today → recover deleted or changed posts. 🎯 Tactics to Apply • Username Pivoting → track a handle across multiple platforms. • Metadata Extraction → pull hidden details from images, videos, or uploaded documents. • Hashtag & Keyword Tracking → monitor trends or communities. • Cross-Referencing → connect profiles by profile pictures, bios, or posting styles. • Network Mapping → visualize connections between friends, followers, or group members. 🧭 Key Strategies for SOCMINT Success 1. Think Like the User → If you were them, what platforms would you use? What usernames might you reuse? 2. Look for Context Clues → Backgrounds in images, language used, or time zones often reveal location and culture. 3. Archive Everything → Posts can vanish quickly. Always capture screenshots or archive links. 4. Combine with Other OSINT Disciplines → Social media is even more powerful when paired with geolocation, image verification, and breach data. 5. Stay Ethical → Only use publicly available information. Respect privacy and stay within legal limits. ✅ Pro Tip: Even a single username or hashtag can open the door to an entire digital footprint. 💬 What’s your go-to tactic or tool for SOCMINT investigations? Share it below so we can all learn from each other
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What is SOCMINT?
OSINT Challenge 002
🕵️ OSINT Challenge 002 A satellite snapshot. A location. Your task: Identify the name of the business or property. 🌍 Hints: - Use Image OSINT to find the location. - Look for the specific owner to validate your guesses. Can you find the exact spot? Drop your best guess below. 👇
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OSINT Challenge 002
What do you want to use OSINT for?
Drop some information on what you're interested in! What do you guys like? What do you want to find out?
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What do you want to use OSINT for?
Saturday OSINT Special!
Article Spotlight: Have LLMs Finally Mastered Geolocation? https://www.bellingcat.com/resources/how-tos/2025/06/06/have-llms-finally-mastered-geolocation/ Bellingcat recently conducted a sweeping geolocation test with 500 trials across 25 unpublished travel photos, asking top AI models—from OpenAI, Google, Anthropic, Mistral, to xAI—to pinpoint their locations using just the image and the prompt: “Where was this photo taken?” Key Takeaways: • ChatGPT models (o3, o4-mini/mini-high), outperformed Google Lens in accuracy, particularly in urban scenes. • Traditional LLMs like Gemini and Claude struggled significantly, often only identifying the continent. • In one standout example, ChatGPT o4-mini accurately located a scene on the Swiss Jura Foothills near Zürich—where none of the others could. • That said, LLMs still struggle with rural settings and often hallucinate—highlighting that they can assist, but shouldn’t replace traditional geolocation methods. OSINT Implications: • Use AI to assist, not decide: LLMs can highlight subtle visual cues—language, architecture, foliage—that help narrow down your search. • Always cross-verify: Follow up on AI-generated leads using Google Maps, Street View, or reverse image searches. • Prompt smartly: Whenever you use an AI tool for geolocation, keep your prompt neutral and supply no extra context—just like Bellingcat did. Try It Yourself: Pick a challenging image, then try this workflow: 1. Ask an LLM (e.g. ChatGPT) to guess the location based on visual clues. 2. Cross-check using maps, street views, or image databases. 3. Compare results to see how much AI helped—and where it missed. Let’s discuss—what clues did the AI catch that you didn’t? Have you spotted model hallucinations in real cases?
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Osint Club
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@cyber-guy-5572
OSINT Club!

Active 4d ago
Joined Sep 1, 2025