Ledger users suspected victims of large-scale crypto theft attack; on-chain analysts report losses exceeding $86 million

According to Lookonchain monitoring, an address sold 262.78 ETH, converted the proceeds to approximately 643,000 USDC, and deposited the funds into Hyperliquid. Around 40 minutes ago, the trader opened a 40x leveraged short position on BTC, with a size of 305.51 BTC, a notional value of roughly $25.4 million, entry price of $83,067.70, liquidation price of $84,086.03, and is now holding an unrealized profit of $17,000.

Former U.S. Commodity Futures Trading Commission (CFTC) commissioner Mike Selig stated that the CFTC’s proposed crypto asset regulatory framework will establish a federal-level regulatory system to protect exchange customers from risks including fraud, market manipulation, and customer fund theft, preventing a repeat of the FTX collapse. Selig pointed out that the CFTC is working to introduce market-based regulatory mechanisms for crypto exchanges, while critics opposing these measures and backing the status quo could objectively benefit fraudsters, manipulators, and those who misappropriate customer funds. He warned that the absence of such regulation could create opportunities for another figure like Sam Bankman-Fried.

According to PeckShield monitoring, the attacker targeting the 79thVault hot wallet (used for 79AU operations) has returned 15,000 BNB tokens to the project team’s designated wallet address, valued at approximately $11 million. Separately, the attacker had previously deposited 30 BNB into KuCoin. The disposition of the remaining funds remains unclear. Earlier, the 79thVault on BNB Chain suffered an estimated $12.5 million loss, likely due to a private key leak. The team’s operational hot wallet typically only handles small transfers to the reward pool. However, recently, this address transferred 2.01 million 79AU tokens from trading pairs to external addresses in seven separate transactions, with amounts of 10,000, 100,000, 100,000, 300,000, 500,000, 500,000, and 500,000 units respectively.

A gambler (or possibly a hacker) sold 262.78 $ETH for 643K $USDC and deposited it into Hyperliquid, then opened a 40x short on 305.51 $BTC ($25.4M) 40 minutes ago. Liquidation price: $84,086.03

Key pre-market news for U.S. stocks is as follows: 1. Morgan Stanley bullish on SpaceX: $300 price target, citing long-term growth potential from enterprise AI, computing power expansion, and U.S. manufacturing revival. 2. Apple plans to hold a new product event around Oct. 27, with expected launches including a touchscreen Mac and new iPad mini. Separately, Nikkei reports Apple is cutting iPhone 18 Pro orders due to weak demand. 3. SpaceX announces an agreement to acquire a nationwide low-band spectrum asset portfolio. 4. Nvidia may adopt Intel’s Foveros packaging technology; the chipmaker will invest in rival semiconductor firm D-Matrix. 5. Coreweave is discussing data center partnerships with South Korea. 6. Market news: Netflix is undergoing a restructuring that will impact roughly 5% of its workforce, with an announcement possibly coming as early as next week. 7. Data center firm Firmus, reportedly backed by Nvidia, is seeking $3 billion in funding after shelving its IPO plans.

Beating AI News: Former Doubao desktop product manager Zhong Erxin has open-sourced iPhone Use, allowing Codex to directly operate real iPhones. Users only need to issue tasks in natural language, and Codex can open apps, read pages, tap, swipe, input Chinese, and search and organize lists. The entire operation process is viewable in real time in Codex’s sidebar. The project is built on Appium’s WebDriverAgent (WDA), a mobile automation tool based on Apple’s XCTest framework. Developers first install WDA on the iPhone via Xcode, then send Codex’s instructions to the device via the Mac-based MCP service, with WDA executing actions like taps and inputs. No jailbreaking is required, nor is a separate Appium Server deployment needed. To cut down on AI overhead from repeatedly viewing screenshots, iPhone Use prioritizes reading system-provided UI control data to directly identify button text, positions, and statuses. For unrecognizable or occluded controls, it falls back to screenshots for the model to determine tap coordinates. It also supports batch execution of continuous operations to reduce model call counts. The sidebar’s real-time feed is pulled via WDA’s independent screen stream, eliminating the need for repeated screenshots. Currently, iPhone Use’s official tutorial still requires a USB connection to the phone; first-time use requires Xcode to sign and install WDA. Apple supports wireless debugging, and WDA is network-accessible, but the project has not yet released a complete wireless connection configuration solution.