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13:07
Flowdesk Head of Sales announces the establishment of Hyper Holdings Global to drive institutional capital into Hyperliquid
Foresight News reports that Flowdesk's US Sales Director Hans Birringer announced on X the establishment of Hyper Holdings Global, describing the organization as a consortium of investors, institutions, and entrepreneurs aiming to bridge traditional finance with the Hyperliquid ecosystem. Its first step is forming a strategic partnership with Grayscale to launch the Grayscale Hyperliquid Staking ETF (HYPG). Birringer noted that Grayscale has been deeply involved in the crypto asset space for over a decade, maintains close relationships with US regulators and policymakers, launched the first publicly traded Bitcoin fund, and helped establish the legal precedent for the approval of spot crypto ETPs. He stated that HYPG will serve as the gateway for long-term institutional capital to enter the Hyperliquid ecosystem, with participation from institutions and individuals including Multicoin Capital, Hypurrdash, MotusAk, and others.
12:59
Strategy CEO now holds a total of 4% of the global bitcoin supply
According to ChainCatcher, Strategy CEO Phong Le stated that global markets and various industries are experiencing uncertainty. During this period, Strategy has accumulated holdings of 4% of the world's Bitcoin.
12:55
Monad team shares formal verification practices, discovers multiple on-chain security vulnerabilities overlooked during AI model audits
Foresight News reported that the Monad development team, Category Labs, shared their experience using formal verification methods to identify vulnerabilities in key modules of the Monad blockchain. They disclosed several vulnerabilities that cutting-edge large models such as Claude Opus 4.8 and Codex failed to detect during code review, but which were successfully caught during the formal verification process. These issues involve the "Reserve Balance" design in Monad's asynchronous execution mechanism and undefined behavior in C++ during storage optimization in MIP-8. The team believes that, compared to directly asking the models to "review code," first writing precise correctness propositions and then asking the model to find counterexamples is more likely to expose hidden vulnerabilities. At present, formal verification can already be greatly assisted by AI.
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