About $7.8 billion was stolen from various pyramid and Ponzi schemes in 2022. In addition, $1.5 billion in cryptocurrency was lost due to illegal activities in online shadow markets, and another $3.7 billion was lost due to hacking attacks.
According to the TRM Labs report, in 2022, attackers stole about $13 billion through various types of cryptocurrency fraud and hacking attacks, including pyramid schemes, insider trading, and phishing attacks.
TRM Labs analysts stressed that despite the fall in cryptocurrency prices due to the market downturn in 2022, cryptocurrency fraud has not slowed down. For example, cryptocurrency investment fraud grew 200%, from $907 million in 2021 to $2.57 billion in 2022.
The most significant losses last year for crypto users were due to pyramid and Ponzi schemes, which resulted in fraudsters stealing more than $7.8 billion. In total, losses from this type of fraud accounted for almost half of last year’s losses. Notably, about 40% of the total investment fraud schemes conducted in 2022 involved the use of the Tether (USDT) stablecoin. Analysts have stated the use of the stablecoin in Ponzi schemes has nearly doubled since 2021.
The largest Ponzi schemes in 2022 were:
- Forsage. The company promised investors high returns on Ethereum and BNB Chain, raising nearly $974 million from investors.
- Meta Force. The company raised $574 million in investment.
- Trade Coin Club. The company raised about $295 million from investors to fund its cryptocurrency exchange.
The report also noted that about $1.5 billion in cryptocurrency was stolen last year due to illegal activities in the network of shadow online markets. And hacking attacks on blockchain projects allowed attackers to seize another $3.7 billion.
Recall that the number of phishing attacks on the crypto market increased by 40% in 2022. Also, cybercriminals began to actively use new kinds of malware to steal cryptocurrencies, which made this type of illegal taking of users’ money one of the most popular in the last year, along with scams in social networks.
