TL;DR:
- Binance Wallet Security Center prevented potential losses of approximately $540 million in the first half of 2026.
- The system filtered 206 million spam transfers, detected 4.93 million high-risk transactions, and flagged 996,000 malicious approvals.
- Malicious entities nearly tripled from one quarter to the next, with AI serving as the primary tool behind the expansion in attack volume.
Binance recorded one of its most active periods in Web3 cybersecurity: its Wallet Security Center tool prevented potential losses of approximately $540 million during the first half of 2026, according to the company.
The system operates in real time from the moment a user opens a link, signs a transaction, or receives an unknown token, and acts at every stage of the attack chain.
According to the Hack3D H1 2026 report by CertiK, phishing incidents fell more than 50% year-over-year, yet total losses declined by only 10.8%, reaching approximately $370 million. This points to a shift in tactics: fewer mass attacks, greater precision per target. Data from ScamSniffer reaches the same conclusion: in January 2026 alone, signature phishing affected 4,741 victims and caused $6.27 million in losses, a jump of 207% compared to the previous month.
Binance Wallet Confronts the Full Attack Chain
Binance’s tool operates on three simultaneous fronts. First, it filtered around 206 million spam transfers, protecting 2.6 million users from bait tokens, fake sites, and address poisoning attempts. Second, it identified nearly 4.93 million high-risk transactions across 19 networks, combining transaction simulation with pre-confirmation alerts. Third, it exposed approximately 996,000 active malicious approvals that users had previously granted and that could continue to put their assets at risk.
The role of artificial intelligence is central on both sides of the conflict. Criminals use it to generate harmful code at scale, forge executive identities through deepfakes, and launch phishing sites at near-zero cost. Binance, for its part, applies AI to analyze token behavior logic, detect hidden backdoors, and classify website risk beyond surface appearances.
One specific case illustrates that capability: so-called siphon tokens, contracts with built-in traps that transfer funds without requiring any user approval, were identified through risk intent analysis before the attack could be completed.
AI Operates on Both Sides
Binance emphasizes that no system can replace the user’s final decision. Social engineering bypasses code entirely and targets human trust. For that reason, it recommends three habits: never sign what you do not understand, verify the authenticity of projects and individuals before interacting, and take ten seconds to scan the wallet from the Security Center section of the app to detect approvals worth revoking.
