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HYPE $81.48 -1.94%
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ZEC $825.72 -2.21%

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first_img XRP ETF saw a net inflow of 170 million USD for 11 consecutive days, with Goldman Sachs ranking first among institutional holders

The US spot XRP ETF has recorded net inflows for 11 consecutive trading days, attracting approximately $170 million in funds during this period. Since its launch in November last year, the cumulative net inflow of these funds has reached about $1.68 billion. As of Wednesday morning, the trading price of XRP was around $1.33, down from about $1.45 on August 27, but still higher than the $1 level in mid-August.According to the disclosures in the 13F filings, Goldman Sachs is the largest institutional holder of the XRP ETF, holding approximately $87.4 million, while Jane Street and Millennium Management hold $16.6 million and $16.2 million, respectively. Investment advisors are the largest category of holders, accounting for about $120 million of the disclosed $183 million, while hedge funds hold about $25 million, and brokers and banks hold approximately $17 million and $14 million, respectively.However, institutional holdings and fund inflows measure different dimensions: the 13F filings reflect the holdings as of June 30, while the continuous inflows record new funds from the end of August to early September. These data only reflect the total holdings of the ETF and not the complete exposure of investors to XRP; institutions like Goldman Sachs may hedge part of the price risk through futures or other instruments. The next round of 13F filings will be released in November.

Analysis: Bitcoin is experiencing its first hash rate bear market, highlighting the opportunities for large mining companies to scale up mining

Rapha Zagury, CEO of Twenty One Capital and founder of Elektron Energy, stated during his speech at Bitcoin Asia 2026 that the Bitcoin network is experiencing its first-ever bear market in hashrate. The hashrate of the Bitcoin network was close to 1.3 ZH/s at the end of last year, but has since been slowly declining, with the duration of this decline from the historical peak now setting a record. Zagury believes that Bitcoin mining is not simply a "good business" or "bad business"; it largely depends on where the mining company stands on the cost curve. Mining companies with lower energy costs and higher machine efficiency can maintain higher profit margins, while those with high energy costs and low equipment efficiency may be forced to shut down.Currently, while the Bitcoin hashrate price has improved compared to before, it is still at a relatively low level when measured against historical standards. When the price of Bitcoin rises faster than the growth of the network's hashrate, mining is more likely to outperform BTC. For companies, he believes that the best risk-adjusted allocation is not simply choosing to "buy BTC" or "mine," but rather a combination of both; however, if only $1 can be allocated, he suggests prioritizing the purchase of BTC. Regarding energy issues, Zagury stated that energy consumption itself does not imply waste; energy is the foundation of economic development and human progress. He believes that one of the greatest characteristics of Bitcoin mining is its highly flexible load, as mining machines can quickly turn on and off based on energy supply, thus helping the grid absorb idle or surplus electricity and enhancing grid stability to some extent. Additionally, he believes that Bitcoin mining is generating "option value" that was not previously apparent, including aspects such as energy utilization, market share, proximity to the Bitcoin protocol, and infrastructure. With the growing demand for AI and high-performance computing (HPC), the existing energy and data center infrastructure of mining companies may also gain additional application scenarios such as AI computing power. Currently, among large publicly listed mining companies, there are fewer and fewer that can continue large-scale Bitcoin mining, and the industry is at a critical stage where the energy revolution intersects with the Bitcoin revolution.

first_img OpenAI's new model Astra can autonomously discover and exploit software vulnerabilities, rated as "critical" in cybersecurity capability level

OpenAI stated that its upcoming Astra model can autonomously discover previously unknown software vulnerabilities and convert them into usable attack vectors without human intervention, making it the company's first model to reach the "Critical" cybersecurity capability level threshold. In a blog post released on Tuesday, OpenAI mentioned that according to its Preparedness Framework, reaching this level means the model can discover zero-day vulnerabilities and develop usable exploit code in hardened real systems without human involvement, or design and execute attacks based solely on a high-level objective.In testing, Astra achieved a 100% score in benchmark tests for developing exploit code based on known vulnerabilities and discovered two previously unknown vulnerabilities in another internal test. Additionally, the model successfully broke through a hardened browser sandbox and executed commands on the host machine, while gaining root access by exploiting multiple weaknesses in the operating system. OpenAI stated that it has delayed some of Astra's development progress to enhance security measures and plans to make its advanced cybersecurity capabilities available only to selected testers.This capability is particularly relevant to the cryptocurrency industry, as software vulnerabilities can be converted into financial losses within minutes. CoinDesk reported in June that increasingly powerful AI models can compress the process of searching code, discovering misconfigurations, and assembling attacks from days or weeks to machine speed. Security researchers noted at the time that the significant change was not the emergence of new categories of attacks, but rather the dramatically increased speed at which existing vulnerabilities are discovered and exploited.
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