Cybercriminals in the Indian state of Rajasthan are using stablecoins like USDT to funnel illicit loot to scam operators outside the country. According to local media, Rajasthan law enforcement has arrested several money mules who played a critical role in converting over inr 1 crore (approximately $115,546) into Tether (USDT) before funneling it to international cybercriminal networks. Superintendent of Police Arshad Ali revealed that the funds, sourced from digital scams like “digital arrest” frauds, were routed through local mules into cryptocurrency and sent to exchanges based in Dubai and France. He further speculated that the masterminds behind these scams are likely operating from these countries. These cybercriminals typically acquire bank accounts, ATM cards, mobile phones, and SIM cards from locals, allowing them to deposit illicit funds on local crypto exchanges. During a recent arrest, police recovered four mobile phones and eight SIM cards from the suspects, which were linked to their crypto laundering activities. You might also like: Crypto scammers use fake job interviews to enable backdoor malware attacks Previously, authorities had taken down a similar money laundering ring where USDT was leveraged, leading to the arrest of 15 suspects, the report added. USDT, the largest stablecoin by market capitalization, has long been a preferred choice for scammers due to its stability, liquidity, and pseudo-anonymity. As such, Tether has come under fire for facilitating illegal activities and, in some cases, helping circumvent international sanctions. To combat these cases, in May 2024, Tether said it was working with Chainalysis to develop a transaction monitoring platform that would track secondary market activity and identify suspicious transactions. Subsequently, in September, the stablecoin issuer partnered with blockchain network Tron and TRM labs to establish the T3 Financial Crime Unit to monitor illegal activity involving USDT on the Tron network. Read more: Scammers bagged over $500k from 15+ X breaches
