Binance’s in-chain research team played a significant role in the arrest of a suspect involved in the ZKasino fraud, providing crucial guidance to law enforcement. The crypto community’s overall response primarily directed Binance’s Crime Compliance and Investigation team to probe the fraudulent gambling platform.
Researchers Examined All Smart Contracts
The researchers combined on-chain tracking and open-source intelligence (OSINT) methods to identify the attacker by examining all of ZKasino’s smart contracts. The Binance investigation team stated:
“We conducted a type of behavioral network analysis to identify the person behind ZKasino and similarly the signatories behind these addresses.”
After identifying the suspect behind the smart contracts, Binance informed law enforcement about the account owner who committed the fraud. Subsequently, the Financial Information and Investigation Service (FIOD) arrested the 26-year-old suspect on April 29, and according to FIOD’s report dated May 3, $12.2 million worth of crypto, real estate, and luxury cars were seized. This development marks the first arrest in the ZKasino fraud case, indicating that the platform’s promises, which led to investors losing at least $33 million in crypto assets, would never be fulfilled.
Binance Assisted Law Enforcement
Binance successfully froze millions of dollars worth of crypto stolen from ZKasino after law enforcement received a search warrant for the attacker’s accounts. Binance’s investigation team, in collaboration with the law enforcement they worked with, stated that they identified one of the suspects’ accounts, which enabled them to recover the funds.
The Binance research team also supported Dutch authorities with on-chain monitoring, helping to determine the flow of funds and understand how the malicious ZKasino smart contracts were set up. Known as a rug pull, this exit scam quietly began siphoning user funds before drawing at least 10,515 Ethereum from over 10,000 investors.
Crypto exchange Binance’s research team noted that past comments made by the suspect greatly aided the community in identifying the scammer. For instance, some comments made under a pseudonym used by this person on Twitter were retrospectively suspicious and caught the attention of investors. These comments also mentioned the scammer’s desire to receive some type of prison sentence. Despite the arrest, there is evidence that the stolen funds are still being moved, indicating multiple attackers involved in the incident.
