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  • cardanoCardano (ADA) $ 0.249269
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  • susdssUSDS (SUSDS) $ 1.08
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  • litecoinLitecoin (LTC) $ 55.70
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  • avalanche-2Avalanche (AVAX) $ 9.35
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  • usdt0USDT0 (USDT0) $ 0.998824
  • the-open-networkToncoin (TON) $ 1.32
  • crypto-com-chainCronos (CRO) $ 0.069828
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  • tether-goldTether Gold (XAUT) $ 4,718.86
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  • syrupusdcsyrupUSDC (SYRUPUSDC) $ 1.15
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  • bitget-tokenBitget Token (BGB) $ 1.94
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  • ondo-financeOndo (ONDO) $ 0.261103
  • kucoin-sharesKuCoin (KCS) $ 8.47
  • gatechain-tokenGate (GT) $ 7.37
  • quant-networkQuant (QNT) $ 73.41
  • jupiter-perpetuals-liquidity-provider-tokenJupiter Perpetuals Liquidity Provider Token (JLP) $ 4.00
  • pump-funPump.fun (PUMP) $ 0.001812
  • morphoMorpho (MORPHO) $ 1.90
  • united-stablesUnited Stables (U) $ 1.00
  • eutblSpiko EU T-Bills Money Market Fund (EUTBL) $ 1.23
  • polygon-ecosystem-tokenPOL (ex-MATIC) (POL) $ 0.095825
  • jito-staked-solJito Staked SOL (JITOSOL) $ 124.46
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  • kelp-dao-restaked-ethKelp DAO Restaked ETH (RSETH) $ 2,404.69
  • kaspaKaspa (KAS) $ 0.034341
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  • binance-peg-wethBinance-Peg WETH (WETH) $ 2,262.26
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  • nexoNEXO (NEXO) $ 0.909561
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  • wbnbWrapped BNB (WBNB) $ 759.61
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  • ignition-fbtcFunction FBTC (FBTC) $ 76,389.00
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  • syrupusdtsyrupUSDT (SYRUPUSDT) $ 1.11
  • official-trumpOfficial Trump (TRUMP) $ 2.87
  • stable-2​​Stable (STABLE) $ 0.029040
  • vechainVeChain (VET) $ 0.007370
  • binance-staked-solBinance Staked SOL (BNSOL) $ 108.24
  • beldexBeldex (BDX) $ 0.080229
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  • ousgOUSG (OUSG) $ 115.01
  • hash-2Provenance Blockchain (HASH) $ 0.010439
  • xdce-crowd-saleXDC Network (XDC) $ 0.029802
  • new-x-ceo-is-backNEW X CEO IS BACK (XFLOKI) $ 0.506041
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  • ghoGHO (GHO) $ 0.999076
  • solv-btcSolv Protocol BTC (SOLVBTC) $ 76,461.00
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  • bonkBonk (BONK) $ 0.000006
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  • mantle-staked-etherMantle Staked Ether (METH) $ 2,455.82
  • layerzeroLayerZero (ZRO) $ 1.59
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  • resolv-wstusrResolv wstUSR (WSTUSR) $ 1.13
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  • ether-fiEther.fi (ETHFI) $ 0.457015
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California Shuts Down 26 Crypto Scam Sites Tied to $4.6 Million in Losses

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California Shuts Down 26 Crypto Scam Sites Tied to $4.6 Million in Losses

California authorities ramped up their fight against crypto fraud, taking down 26 fraudulent crypto websites and revealing over $4.6 million in consumer losses in 2024.

In a Monday statement, the California Department of Financial Protection and Innovation, or DFPI, said it identified seven new scam types with the help of its “Crypto Scam Tracker.”

The tracker processed over 2,600 complaints, exposing fake Bitcoin mining, crypto job scams, and crypto gaming frauds, along with misleading AI investment schemes.

“As crypto scams evolve, DFPI’s Crypto Scam Tracker helps empower consumers to stay vigilant,” DFPI Commissioner KC Mohseni said in a statement.

In a separate report, the California Department of Justice, or DOJ, said it took down 42 scam websites operated by international fraudsters, uncovering $6.5 million in losses from promises of high returns.

The rise of “pig-butchering” scams has fueled the surge in fraud, with the DOJ’s report pointing to a troubling increase in these schemes.

In a pig-butchering scheme, fraudsters build false relationships with victims via social media or dating apps, only to later manipulate them into investing in non-existent cryptocurrency projects.

When the victims try to withdraw their funds, they’re left empty-handed.

“Scammers can use deception and emotional manipulation to take advantage of people looking for connection,” said California Attorney General Rob Bonta.

Blockchain analysis firm Chainalysis reported last month that there’s been a nearly 40% increase in pig butchering scam revenue compared to 2023, with a nearly 210% increase in victim deposits.

This form of fraud alone accounts for a large portion of the $9.9 billion in total scam-related crypto losses tracked by Chainalysis in 2024.

In the report, Elad Fouks, head of fraud products at Chainalysis, said generative AI could be used to amplify and scale up crypto fraud and crimes.

Fouks said GenAI generates realistic fake content, including “websites and listings” used to power investment scams and purchase scams, making these attacks “more convincing and harder to detect.”

Edited by Stacy Elliott.

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