OSINT Tip: a phone number returned a facebook account in leaked data, how can you verify it?
A common OSINT question: is the account genuinely tied to the number you're investigating, or is it outdated or false data?
Solution; don't treat a single source as your final answer. Verify it with multiple sources.
Case example: In the example shown, the phone number was linked to a facebook account that is now unavailable (deleted by the user or the platform). The leaked data showed the full name, email and other details. I checked the number's names/tags on Truecaller and Eyecon and both returned the same name as the facebook profile. This is an additional data point supporting the link between the number and the account.
Similarly, investigate the email address and compare it with the initial output to further strengthen or challenge the finding.
Telegram bots used;
1. https://t.co/UTDhrYnAjF
2. https://t.co/rOGuAhBLB8
#osint #phonenumber #leaks
🔎 How I track data leaks on Telegram before they hit the news
Most people hear about a breach after the damage is already done.
By that point, the data may have been copied, resold, reposted, and scattered across different channels.
I built LeakHunt to teach people how to watch the places where leaks usually show up first.
One lesson covers how investigators use Telegram to monitor breach and leak activity in real time.
You’ll learn how to:
✅ Find the Telegram channels where leaks are often posted early
✅ Set up monitoring so new posts are easier to catch
✅ Trace a leak back to the likely breach source
✅ Review sample data safely without exposing your own identity
This is the same approach I use to track breaches before they become public.
LeakHunt has helped train students from a community of 13,000+.
🔗 Course link: https://t.co/8O2VkAXBio
P.S. ♻️ Repost if you found this helpful.
🔎 My Favorite Tool for Finding People by their Faces
Most people reach for Google or Yandex when they need a reverse image search.
That's fine for objects, landmarks, screenshots, or finding the original version of an image.
Faces are different.
PimEyes searches by face, not by the exact photo.
So if the same person appears somewhere else online with a different background, haircut, lighting, or group of people, it can still return a match.
What it can do:
✅ Search the open web using one clear face photo
✅ Return matches quickly, often within a few seconds
✅ Show where that face appears on websites
✅ Send alerts when a new match appears
Real-life OSINT example 👇
I’ve used it in people-search work when a name search went nowhere.
One face match led to an old blog post, and that post gave the person’s employer.
Worth noting ⚠️
PimEyes searches the open web. It does not cover everything, and full access requires a paid plan.
🔗 Website link: https://t.co/ef6oevLI0a
__________
P.S. ♻️ Repost if you found this helpful.
A single Gmail address leaks a surprising amount of personal data.
Instead of wasting time with manual searches, this article shows you how to use GHunt to automatically pull hidden profile details, location history, and account metadata in minutes.
https://t.co/9PaqUpQOAY
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Your Data Isn't As Safe As You Think.
Right now, your email might be sitting on the dark web. Your password too. Your old accounts. Things you forgot even existed. Osintly helps you find it.
You can't protect what you don't know is out there.
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An OSINT platform designed for data collection and analysis.
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Legendary OSINT
A curated list of OSINT tools & resources. The sources where I got this from include newsletters, Telegram groups, curated startpages, GitHub repos, and other public collections.
Source: https://t.co/0uPaEjYIDa