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Recently, we partnered with @Alphalysiun, using Web2 data science tools to analyze and dissect the Doginals ecosystem - pushing the limits of insight and on-chain intelligence.
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On July 23rd, 2025 I was contacted here on X to do deep research on several DRC20 and NFT projects linked to one wallet: **NTJ4X** — the same one I exposed in my last thread as the center of a massive scam loop in the #Doginals ecosystem. The scope was simple: manually track every interlinked wallet connected to different token launches. One of the main requests was a Python script to analyze **Dosu** and its connected wallets. The person agreed there’s a big entity behind it all that needs watching closely. The goal: identify ALL wallets affiliated with 10 highly suspected addresses — wallets that still hold $Dosu or are clearly controlled by the same person/entity, even if the transfers are disguised as normal market trades or wallet-to-wallet shuffling. There are lots of shady networks in Doginals, but spotting the alpha wash nets is complicated. So I mapped out a strategic plan, contacted my team at @WebgeckoLabs, and we got to work: - Mine and collect every single $Dosu transaction from launch day to today - Run Python scripts to map interconnections on the wallet graph - Check centralized exchange deposits from the key wallets This is how I pulled one of the deepest #Doginals investigations yet. Thread continues 👇
Step 1: Data Mining
The contact gave me the exact 10 wallets to start with (including NTJ4X and Diough). I went straight to DoggyMarket explorer and pulled every transaction for those 10 wallets from day one. Then I expanded the scope: scraped the entire Dosu transaction history from launch until the present date. I cross-referenced everything with activity in Doginal Maxi Biz, Mini Doge, and Doginal Dragons to spot hidden patterns and connections. Finally, I extracted the full list of Dosu holders with their addresses and exact balances. This gave me the complete dataset I needed to start mapping the network. Thread continues 👇
"We're too small to be a target."
"Nobody's going to bother with our TVL."
"We'll worry about security when we scale."
Attackers don't filter by market cap. They filter by exploitability. The smaller you are, the less likely anyone is watching - and they know it.
@premium@premium we subscribed for the x premium package on the 21st of january and till now it hadnt been activated in our account... kindly see to this
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