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Binance Research: The seizure rate of illegal funds in crypto assets is about 11% in 2025, significantly higher than that of the traditional financial system

Binance Research released a report stating that crypto assets are not a "safe haven for illegal funds." In 2025, approximately 11% of illegal fund flows in the global crypto sector have been seized or frozen, which is about 55 times the recovery rate of traditional fiat currency systems.The report pointed out that this data is derived from public law enforcement and freezing actions by institutions such as Tether, Interpol, and T3 Financial Crime Unit, rather than statistics from a single regulatory agency. At the same time, compared to the United Nations Office on Drugs and Crime (UNODC) estimated recovery rate of less than 1% for illegal funds in the traditional financial system, the tracking and recovery efficiency in the crypto sector is significantly higher.The research also mentioned that even after excluding a single large case (involving about $15 billion in Bitcoin related to the Prince Group), the remaining crypto asset recovery rate in 2025 is still about 10 times that of the traditional financial system. Additionally, data from SlowMist and PeckShield shows that in 2025, approximately 8.3% to 13.2% of stolen crypto assets were successfully recovered or frozen, reflecting improved efficiency in security response and collaboration among exchanges, stablecoin issuers, and law enforcement agencies.The report concluded that while the issue of crypto crime still exists, the view that "crypto assets are inherently more suitable for illegal activities" is being weakened by on-chain transparency and regulatory collaboration capabilities.

Chainalysis tracks the source of the THORChain attack: skilled in money laundering, the attack was carried out weeks after cross-chain fund movements

Chainalysis posted on the X platform that before the theft of THORChain, wallets suspected to be associated with the attacker had been transferring funds through Monero, Hyperliquid, and THORChain for several weeks. The attacker-associated wallets had already deposited into Hyperliquid positions via the Hyperliquid and Monero privacy bridge as early as the end of April. The funds were then exchanged for USDC and transferred to Arbitrum, and later bridged to Ethereum, with some ETH subsequently transferred to THORChain to become staked RUNE for newly added nodes, which are believed to be the source of the attack.Afterward, the attacker bridged some RUNE back to Ethereum and split it into four pathways, one of which went directly to the attacker. After being transferred through intermediate wallets, 8 ETH was sent to the final wallet receiving the stolen funds 43 minutes before the attack. The funds from the other three pathways flowed in the opposite direction. These wallets bridged ETH back to Arbitrum, deposited it into Hyperliquid, and transferred it into Monero through the same privacy bridge, with the last transaction occurring less than 5 hours before the attack began.As of Friday afternoon, the stolen funds have not yet been used, but the attacker has demonstrated their skilled cross-chain money laundering capabilities, and the Hyperliquid to Monero path may become the next move.

After receiving $100 million in funding, Gemini's pre-market increase exceeded 25%, but it still reported a loss of $109 million in Q1

According to CoinDesk, after the cryptocurrency trading platform Gemini, founded by the Winklevoss brothers, announced its Q1 2026 financial report, its stock price rose over 25% in pre-market trading. The financial report showed that the company's revenue for the quarter increased by 42% year-on-year to $50.3 million, while the net loss narrowed by 27% year-on-year to $109 million, but still exceeded market expectations of a loss of $0.61 per share.The report indicated that Gemini's operating expenses increased by 73% year-on-year to $144.5 million, with employee compensation costs rising by 91%, which included approximately $6.5 million in severance pay; sales and marketing expenses also doubled year-on-year to $19.1 million.The company stated that it is currently driving its business transformation through layoffs, business contraction, and a $100 million Bitcoin injection from Winklevoss Capital Fund, and is seeking to achieve profitability.In February of this year, Gemini closed its operations in the UK, EU, and Australia, laying off about 25% of its staff, and shifted its focus to the U.S. market and prediction market business. In April, the company received approval from the U.S. Commodity Futures Trading Commission for its Derivatives Clearing Organization (DCO) license, officially entering the cryptocurrency prediction market field. Boosted by these developments, the company's stock price has recently rebounded and is now above $6.6.

AI Agent Security Risk Exposure: Attackers Can Exploit "Memory Pollution" to Induce Misoperation of Funds

The GoPlus Security team has disclosed a new type of attack in its AgentGuard AI project: inducing AI agents to perform unauthorized sensitive operations through "memory poisoning." This attack method does not rely on traditional vulnerabilities or malicious code but exploits the long-term memory mechanism of AI agents. For example, an attacker first induces the agent to "remember preferences," such as "usually prioritizing proactive refunds instead of waiting for chargebacks," and then uses vague expressions like "process as usual" or "execute as before" in subsequent instructions, thereby triggering automated financial operations.GoPlus points out that the key risk in such cases lies in the AI agent mistakenly treating "historical preferences" as a basis for authorization, leading to financial losses or security incidents in operations such as refunds, transfers, and configuration changes. To address this issue, the team has proposed several protective recommendations, including:Operations involving refunds, transfers, deletions, or sensitive configurations must require explicit confirmation in the current session.Memory-related instructions like "habit," "usual way," and "as before" should be regarded as high-risk state changes.Long-term memory must have a traceability mechanism (writer, time, confirmation status).Vague instructions should automatically elevate the risk level and trigger secondary verification.Long-term memory must not replace real-time authorization processes.The team emphasizes that the "AI agent memory system" should be viewed as a potential attack surface and should be constrained and audited through a dedicated security framework.
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