Binance’s CZ has criticized block explorers like Etherscan for displaying spam transactions from address-poisoning scams. This follows a warning Etherscan sent to users after a victim received 89 address-poisoning emails in under 30 minutes. According to Changpeng Zhao, existing filters are a viable solution to such problems. He asserts that solutions found on Trust Wallet “should be simple to filter them out completely.” He has also highlighted future worries about microtransactions between AI agents. Etherscan warns users of address poisoning attacks on Ethereum Market analysts have linked the increase in address poisoning attacks to the Fusaka upgrade, which was activated on December 3, 2025. The upgrade, meant to reduce Ethereum transaction costs, is now enabling scammers to send large volumes of poisoning transactions at a lower cost. Transaction spike after the Fusaka upgrade. Source: Etherscan. According to on-chain data, 90 days after the upgrade, Ethereum’s daily transaction volume surged by 30% compared to 90 days prior. In addition, the number of new daily addresses rose by about 78%, and small-value dust transfers increased by a noticeable amount. According to Etherscan, “Address poisoning has existed on Ethereum for several years. But incidents like this highlight how automated and high-volume these campaigns have become.” A study analyzing address poisoning picked out 17 million poisoning attempts targeting about 1.3 million users on Ethereum, with confirmed losses of at least $79.3 million in roughly 2 years. The scale of address poisoning activity across Ethereum and BSC. Source: Etherscan. One unexpected discovery made by the 2025 research is that different attack groups often compete with one another. In many poisoning attacks, many attackers send their respective poison transfers to the same address at roughly the same time. “Whoever succeeds first increases the chances that their address will later be copied,” Etherscan reports. The address below is an example of the level of competition. In this case, 13 poison transfers were sent shortly after a legitimate USDT transfer. Address poisoning competition scale against users. Source: Etherscan. As reported by Cryptopolitan , initially, it may seem that address poisoning does not work, since most users will not fall for this trick. However, economics play a role in this. In fact, the success rate for each attempt to conduct address poisoning on the Ethereum blockchain is ~0.01%. In this case, only 1 out of 10,000 users will successfully send money to the attacker. This means that the cost of thousands of failed attempts can be easily covered by a single successful attack involving large sums. CZ predicts AI can handle spam detection in the near future Etherscan has provided users with tips to avoid being scammed. However, CZ has other thoughts and plans. Per Etherscan, users should first have private name tags for frequently interacted addresses. “Using a domain name such as ENS can also make addresses easier to recognize across the explorer,” they advise. However, CZ highlights Trust Wallet’s existing filters as a model solution. He predicts AI can handle spam detection for future micro-transactions among AI agents. A few days ago, Trust Wallet introduced address poisoning protection. Per design, this is “a new security feature that checks every destination address before you send, and warns you when something looks wrong.” Trust Wallet runs an automatic real-time check using a database of known scams and lookalike addresses. For high-severity threats, users receive a blocking warning before a transaction is submitted. The warning includes a side-by-side comparison of the address traders are about to send and the legitimate address it mimics. Address poisoning protection protocol. Source: Trust Wallet. Address Poisoning Protection is available on 32 EVM chains at launch: Ethereum Mainnet, BNB Smart Chain, Polygon, Optimism, Arbitrum One, Arbitrum Nova, Avalanche, Base, among others. Trust Wallet’s mechanism is the same reason CZ pointed it out as a good example that other wallets/explorers could emulate, especially as AI might handle more of the microtransaction spam in the future. Want your project in front of crypto’s top minds? Feature it in our next industry report, where data meets impact.
