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Flash

Slow Fog: Udesk customer service script was implanted with malicious code that can steal user session data and replace recharge addresses

According to Slow Fog's disclosure, its security personnel discovered that the script udeskApi.2026-10-16.cached.js related to the Udesk customer service system was implanted with a malicious loader during routine threat intelligence checks. This loader hides the address through hexadecimal encoding and asynchronously loads the remote script deeps.js (sourced from udeskqlobal[.]com, note that the domain name starts with the letter q). This script reads accessible Cookies, localStorage, and sessionStorage on the page, intercepts form and login/authentication requests, and sends data to udeskqlobal[.]com/c.php. Attackers may use this to impersonate sessions or take over accounts. This data collection behavior is not restricted by the target site's rules, and unmatched pages may also be affected.According to Slow Fog's analysis, this script also targets three types of sites: mgbx[.]com, bikingex[.], and bitxex[.]io, scanning the recharge page every 200 milliseconds and replacing identified recharge addresses with preset BTC, EVM, TRON, Solana, LTC, and DOGE addresses. At the same time, the script manipulates the clipboard API, replaces copy buttons, and intercepts copy events, making users see and copy tampered addresses. If users transfer funds to this address, the money will flow into the attacker's address.

OpenAI announced the model breakthrough index time hypothesis

OpenAI recently announced that its AI model has cracked the Exponential Time Hypothesis, abbreviated as ETH, which has been a longstanding conjecture in computer science for over twenty years, and is not related to Ethereum. This hypothesis focuses on how difficult particularly hard problems are, using the Boolean Satisfiability Problem (SAT) as an example: given a set of logical conditions, is there an assignment that makes all conditions true simultaneously? As the problem size increases, the best-known methods essentially can only try possible answers one by one, with the time cost growing exponentially with the size. The Exponential Time Hypothesis further asserts that such problems cannot be significantly accelerated, and there are no truly sub-exponential time efficient algorithms.Since its proposal in 1999, this hypothesis has been a crucial cornerstone of theoretical computer science, with numerous papers proving that certain problems are hard and that some algorithms are close to optimal based on it. If the Exponential Time Hypothesis were to be overturned, it would imply that many problems considered nearly impossible to solve faster might theoretically have better solutions. OpenAI claims that its model has found a deterministic algorithm that can accurately count the number of solutions to the k-SAT problem in sub-exponential time, and it has been formally verified using Lean. If this result withstands expert scrutiny, it will directly challenge the Exponential Time Hypothesis.

Anthropic publicly submitted its Nasdaq IPO application, with the stock code "ANT"

Anthropic publicly submitted its Nasdaq IPO application, with the stock code "ANT".Anthropic's revenue for the first half of the year was $16.3 billion. Anthropic may not be able to achieve or maintain profitability in the future.As of June 30, 2026, Anthropic reported a net loss of $80.7 billion for the six-month period. Goldman Sachs and Morgan Stanley are leading Anthropic's IPO.Anthropic disclosed that the company expects to pay Google up to approximately $11.45 billion before 2033 and to pay approximately $161.2 billion in rent under its leasing arrangements with Broadcom during the lease term (excluding interest).Anthropic stated that computing and infrastructure costs are expected to continue to increase in absolute terms and will become the company's largest operating expense in the foreseeable future. The company believes that its existing cash and cash equivalents are sufficient to meet operational funding and other needs for at least the next 12 months, but also warned that it may need to seek additional financing earlier than currently anticipated.In terms of safety, Anthropic mentioned that it has recently delayed the pre-training of its next-generation cutting-edge foundational model by more than a month to strengthen safety measures and prevent the leakage of model weights. The company also noted that as AI systems gradually automate AI research and development, associated risks will increase.
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