Key Takeaways
- Bybit’s AI monitoring system blocked $300 million in suspected scam withdrawals in Q4 2025, protecting more than 4,000 users.
- The exchange uses a three-tier framework combining real-time blockchain analysis, human intervention and industry collaboration.
- The initiative follows February’s $1.5 billion hack, as Bybit works to rebuild trust through stronger AI-driven defenses.
As crypto scams grow more sophisticated — and more automated — exchanges are racing to prove they can keep up.
Bybit says it may have found a way to do exactly that.
In the fourth quarter of 2025 alone, the company claims its AI-driven on-chain monitoring system blocked and recovered roughly $300 million in suspected scam withdrawals, shielding thousands of users from potentially devastating losses.
The announcement comes as global crypto fraud losses ballooned to an estimated $17 billion in 2025, with AI-powered impersonation schemes driving much of the surge.
Against that backdrop, Bybit is positioning its security overhaul not just as damage control, but as a model for how exchanges can fight back.
A $300 Million Quarter
Bybit said its system identified 350 high-risk addresses linked to fraudulent activity during Q4.
By intercepting associated withdrawals, the exchange prevented what it estimates could have amounted to $300 million in losses.
The company said it directly protected more than 4,000 users during that period.
David Zong, Bybit’s Head of Group Risk Control, described the system as part of a broader push to combine automation with shared intelligence across the industry.
“By integrating AI-driven on-chain monitoring with real-time intelligence from industry partners like TRM, Elliptic and Chainalysis, we not only just protect Bybit users, but also help map the DNA of fraudulent networks,” Zong said. “We are sharing these standardized monitoring clues across the ecosystem because a safer industry for one is a safer industry for all.”
The company also reported securing $4.32 million in frozen assets for 335 fraud victims during the quarter.
How Bybit’s AI System Works
At the core of Bybit’s strategy is a three-tier risk-control framework designed to detect, intervene and recover — often before funds leave the platform.
The first layer relies on AI-powered blockchain monitoring.
Proprietary algorithms scan transactions across multiple networks, including cross-chain bridges and crypto mixers, tools frequently used to obscure illicit flows.
The system analyzes wallet behavior, transaction patterns and historical data to flag anomalies in real time.
When the software detects suspicious activity, the second layer activates: immediate alerts to Bybit’s risk-control team.
Human analysts review flagged transactions, contact users as needed, and pause withdrawals pending verification.
If a scam is confirmed, the exchange freezes the funds and begins recovery procedures.
The final tier focuses on prevention at scale.
Bybit adds confirmed high-risk addresses to shared databases and works with blockchain analytics firms such as Chainalysis, TRM Labs and Elliptic to trace funds across decentralized exchanges, peer-to-peer networks and laundering routes.
According to the company, those collaborations have helped freeze more than $40 million in stolen funds.
The approach reflects a shift from reactive response to proactive disruption.
Identifying fraud patterns early and cutting off exit routes before funds disappear into complex laundering chains.
Security After Bybit’s Biggest Crisis
Bybit’s security push follows one of the most damaging episodes in its history.
In February 2025, the exchange suffered a $1.5 billion hack. It is widely described as the largest crypto heist on record, attributed to North Korea’s Lazarus Group.
Attackers compromised an Ethereum cold wallet through malware and phishing tactics, sending shockwaves through the market and reigniting debates about centralized exchange security.
Bitcoin fell sharply in the aftermath, and scrutiny intensified around custody practices and internal controls across the industry.
Since then, Bybit has framed its AI expansion as part of a broader rebuilding effort — not only to strengthen internal defenses, but also to demonstrate that exchanges can respond decisively to increasingly automated criminal tactics.
The Bigger Picture
Crypto fraud has evolved far beyond basic phishing emails.
AI-generated impersonation scams now convincingly mimic legitimate investment firms, public figures and even exchange representatives.
Fraudsters use automation to scale operations rapidly, target victims across jurisdictions and move funds across chains within minutes.
That shift has forced exchanges into an arms race.
Bybit argues that combining machine learning, real-time intervention and coordinated blacklisting represents a workable defense model.
Whether it becomes an industry standard remains to be seen, but the company’s Q4 numbers underscore how central AI-driven monitoring has become to exchange survival.
For an industry still rebuilding trust after high-profile collapses and hacks, the message is clear: security is no longer just infrastructure — it is strategy.
And in a year when crypto crime hit record highs, exchanges that fail to adapt may not get a second chance.
Prashant Jha is a seasoned crypto journalist based in Delhi, India, with a Bachelor’s Degree in Computer Science Engineering. Passionate about the evolving world of blockchain and cryptocurrencies, he has been a dedicated voice in the industry since 2018. Prashant’s expertise lies in regulatory reporting, where he unravels complex legal and financial developments with clarity and precision. Before joining CCN in 2024, he honed his craft at Cointelegraph, establishing himself as a trusted name in crypto journalism.
His coverage spans major industry events, including the high-profile collapses of FTX, Three Arrows Capital (3AC), and LUNA, offering readers insightful analyses of their regulatory and market implications. Prashant’s technical background enables him to bridge the gap between intricate blockchain technology and its real-world applications, making his work accessible to novices and experts.
Beyond his professional pursuits, Prashant is an avid music enthusiast, often exploring diverse genres to unwind. A sports lover, he has a particular passion for cricket and frequently engages in discussions about the game. His multifaceted interests and sharp journalistic instincts make him a valuable contributor to CCN, where he continues shaping the crypto landscape's narrative.
