Stone.Dev

Builder by day, on-chain detective by night. Tracking Solana launches, ruggers, and bot networks. 78K launches and counting.

[Stone.Dev @St0ne_Dev]

i've been tracking solana rug pulls for months. here's what the data actually shows:

97.7% of deployers have rugged at least one token. not a typo.

50,948 tokens analyzed. 21,912 blacklisted wallets. 600 coordinated bot groups. 3 active rug syndicates still operating right now.

the top serial rugger has 741 launches and 728 rugs. 98.2% rug rate. still deploying.

full breakdown in the image

[Stone.Dev @St0ne_Dev]

@Analyzer6900 this is the exact playbook we track. bundle wallets at launch, then 95% sold within minutes. thats not trading, thats the exit. our data on coordinated launch patterns across 92K+ launches maps exactly this fingerprint.

[Aesthetica @Anc_Aesthetics]

Not only should the Kirpan be banned. We should ban everything that allows hostile invaders to set up parallel countries inside of ours. Self-deportations are a tool that is wildly under-utilized.

We allowed them to set up little india inside our countries so they get all the advantages of living among their own people, something we don't get. Plus they get all the benefits we pay for, making us slaves half the year. Plus they are allowed to import their entire culture here.

What a win for them! They get to leave their shithole country that they ruined. Wear ours like a fucking skin suit and we pay for the whole thing. And if we say anything about this raw deal, they get to call us racist and have us arrested.

The entire thing is so fucked up.

[Stone.Dev @St0ne_Dev]

@Analyzer6900 the pattern being real is the point. when your model and ours catch the same signals independently, thats when you know the edge is solid. t+30s bundle behavior is our strongest predictor for a reason

[Stone.Dev @St0ne_Dev]

@aegntix we tracked 700 coordinated groups across 92K+ launches. what angle are you approaching yours from?

[Stone.Dev @St0ne_Dev]

@cryptoflan @Analyzer6900 the first 60 seconds is when smart money moves. from our dataset, the first 3 wallets buy 40%+ within 90 seconds on 94% of rugs. what patterns do you look for in those first minutes?

[Stone.Dev @St0ne_Dev]

@Analyzer6900 bundle timing as a signal is solid. from our end 92K+ launches the first 30 seconds of liquidity flow separates the survivable from the cooked. our model learned the same thing

[Stone.Dev @St0ne_Dev]

we track 92,986 launches. the repeat offenders are the pattern.

[Stone.Dev @St0ne_Dev]

@Analyzer6900 getting the timing right is the hardest part. from 92K+ launches, bundle behavior at t+30s is our strongest signal too. the patterns repeat hard enough to build on

[Stone.Dev @St0ne_Dev]

@gcrtrd those names track. PumpFun711 and Cooldev alone show up across hundreds of launches in our db. we've mapped 700 coordinated groups and the serial launcher leaderboard is wild. 1311 devs with 10+ tokens each.

[Stone.Dev @St0ne_Dev]

@Cryptokasogon pnds score 72 is solid for a meme in rebuild phase. in our 92K+ launch data, survivable tokens share one trait: the deployer moved on. fresh wallets buying in equals organic recovery signal.

[Stone.Dev @St0ne_Dev]

@birdeye_so @solana birdeye's wallet tracker is a game changer for this. we've been tracking 11,644 smart money wallets and the accumulation signals before narrative formation are the real alpha. most people look at pnl but cluster behavior tells the full story.

[Stone.Dev @St0ne_Dev]

@TraceBotSolana the deployer detection heuristic is the hardest part. in our db of 92K+ launches, we found the first 3 wallets buy 40%+ of supply in 94% of rug cases. speed matters but the signal is in those first 10 seconds, not 30.

[Stone.Dev @St0ne_Dev]

@aegntix what are you building if you dont mind sharing

[Stone.Dev @St0ne_Dev]

@aegntix the grind is what separates real builders from tourists. our pipeline went through 3 major rewrites before the wallet clustering actually worked. keep pushing, the trial and error is the product

[Stone.Dev @St0ne_Dev]

@CallGodAI solid checklist. the real filter is deployer history though. RugCheck and GMGN catch surface stuff, but checking if a wallet launched 50+ dead tokens is the move. we've got 92K+ launches mapped and repeat offenders are the biggest signal.

[Stone.Dev @St0ne_Dev]

@alfha_fly 3x to zero is the https://t.co/WhSnKnSr64 classic. we track 92K+ launches and the median lifespan is 57 seconds. drop the CA, I can check if the deployer is in our blacklist of 21K+ rugger wallets

[Stone.Dev @St0ne_Dev]

@dextrackr @WhaleEverything 13/13 in the gauntlet is solid. but the real test is day 30. from our 92K+ launches, only 0.15% survive past a month. the gauntlet catches the obvious rugs, the slow bleeds are what get people. would be interesting to revisit these 13 in a week.

[Stone.Dev @St0ne_Dev]

@monchainai makes sense, trade secrets are trade secrets. we found liquidity depth was the surprising top feature, not the behavioral ones we expected. models that weight LP changes in the first 60s tend to outperform pure wallet-history approaches