Bybit earns $300M for thousands of users through AI-enhanced fraud prevention: Report

In addition to the reset, Bybit blocked 3 million attempts to top up data related to plans to take over the account in 2025.

Bybit has reported that $300 million has been recovered for thousands of users, while crypto fraud remains high across the industry.

The exchange attributes these efforts to an AI-powered fraud detection system that intervenes before people lose their money.

Results of the security initiative

Bybit shared the results of its 2025 Security Initiative, stating on social media,

“We raised the bar in 2025, stopping $300 million in fraud and fraud through our new AI risk framework.”

The announcement comes as crypto fraud continues to weigh heavily on the sector, with data from Chainalysis showing that $17 billion of digital assets will be lost in scams and scams by 2025.

The report shows that in the fourth quarter alone, the exchange showed 500 million dollars for review. Of this amount, $300 million was successfully blocked and recovered, protecting the deposits of more than 4,000 users.

During the same period, Bybit’s proprietary AI models identified 350 high-risk investment fraud addresses using blockchain data, protecting 8,000 people from potential withdrawal losses. The company also reported that in 2025, more than 3 million credential attempts related to account takeover attempts were blocked.

In addition, its system automatically flagged 350 suspicious addresses and manually flagged another 600 addresses through internal ticketing operations, preventing another $1 million in potential fraud losses.

You may also like:

David Zong, head of the risk control group at Bybit, said in a statement that the company’s goal in 2025 is to transform risk control into an active and intelligent watchdog through the integration of AI and supply chain monitoring.

“By integrating AI-driven on-chain monitoring with real-time intelligence from industry partners like TRM, Elliptic and Chainalysis, we’re not only protecting Bybit users, but also helping to map the DNA of fraud networks,” he said.

A three-tiered risk framework

Bybit’s protection model structure divides potential fraud scenarios into three escalating levels while maintaining normal trading activity. At the lowest risk level, the platform uses big data analytics to detect unusual activity, such as mass exodus to newly created addresses, and uses automated surveys to support its risk operations team in blacklisting suspicious destinations.

Real-time alerts during the revocation process for medium-risk situations, such as accounts identified by credential filling databases or linked to suspicious revocation addresses. This, in turn, leads individuals to consider transactions that may be influenced by social engineering tactics.

At the highest level, wallet addresses associated with confirmed fraud are subject to immediate revocation and a mandatory one-hour cooling-off period.

The report outlines standardized monitoring metrics for wider industry use, including a credential filling engine, real-time AI pattern recognition for pig slaughter streams, an integrated intelligence hub that combines tools from TRM Labs, Elliptic and Chainalysis, and an international tracking model for chain tracking.