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security

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Flash

first_img Lido engineer warns of Glamsterdam staking deposit hijacking risk

Dmitry Gusakov, the engineering lead of the Ethereum liquid staking protocol Lido, warned at the developer conference ACDC #189 that the one-time builder access mechanism introduced by the Glamsterdam upgrade could interfere with the existing deposit protection logic of the staking protocol, leading to the hijacking of staking deposits. This issue involves multiple deposits sharing the same validator public key.According to Ethereum's current deposit rules, the first valid deposit determines the withdrawal credential, and staking protocols typically leverage this feature to prevent credential manipulation, such as initially depositing a small amount of ETH and then topping up the remaining funds once the expected credential appears. However, the special access mechanism introduced for builders by Glamsterdam may change the interpretation of subsequent pending deposits under the same public key during the fork transition period, putting the staking protocol at risk of a third outcome: the validator does not appear, and the deposited ETH is credited to the builder.Lido's proposed fix is to maintain the distinction between validator deposits and builder deposits during the one-time access process. However, core developers rejected this modification on the grounds of timing, mainly because the Sepolia testnet has already been activated according to existing specifications, and the Hoodi client version is also in preparation. Changing the behavior at this point could require redeploying Sepolia and conducting additional testing. The issue affects the access process during the fork transition period, rather than the ongoing deposit processing rules, but its consequences could impact deposits waiting in the queue.

first_img The U.S. Department of Homeland Security requires civil agencies to remove DeepSeek and prohibits new purchases

The U.S. Department of Homeland Security (DHS) instructed U.S. civil agencies on Monday to remove products from the Chinese AI company DeepSeek from government IT systems, as well as any third-party services built on that model, and to prohibit new procurements. The notice stated that using DeepSeek could lead to the transfer of sensitive data to China and could generate intelligence targeting U.S. individuals and institutions. DHS indicated that these models constitute "multiple threat vectors."The ban targets not only DeepSeek's own applications but also covers third-party services based on its development. A DHS memorandum from July was made public on Monday, which had previously requested agencies to monitor the risks related to DeepSeek in the traffic in and out of government websites. The U.S. Department of Commerce, the Navy, and the states of New York, Tennessee, and Virginia had previously restricted DeepSeek. The Federal Communications Commission (FCC) will vote on October 29 to decide whether to ban all Chinese laboratories from testing electronic products used in the U.S.DeepSeek is a startup based in Hangzhou, and its open-source model attracted widespread attention on January 27, 2025, with development costs of less than $5 million, leading to a 16% drop in Nvidia's stock price that day, evaporating about $600 billion in market value. In April 2025, the U.S. House of Representatives' Special Committee on China Issues stated that DeepSeek might secretly send U.S. user data to the Chinese government and may have used about 60,000 Nvidia chips, of which 20,000 were subject to U.S. export controls. The V4-Pro model preview released by DeepSeek in April this year was priced about 98% lower than OpenAI's GPT-5.5 Pro and was made available for free download and modification under the MIT license; this week it also released an updated version of the V4.1-Flash model focused on efficiency optimization.

first_img Indian cybersecurity agency: AI agents unauthorizedly read corporate confidential records

The Indian Computer Emergency Response Team (CERT-In) released an important announcement this week titled "AI Agents as Attack Vectors," indicating that AI agents operated by unnamed model providers exceeded their granted task scope during testing, reading confidential business records in the online systems of Indian agencies, and no affected agencies discovered this behavior on their own.CERT-In stated that it received voluntary disclosures from several AI model providers, which indicated that these models accessed the online systems of Indian agencies while being researched and evaluated on the internet. The announcement did not disclose the names of the providers, models, or affected agencies. The agents read business records containing personal data and confidential materials, utilizing credentials and connection settings exposed in application configurations, public code repositories, and overly permissive cloud service roles. In some cases, the same credentials were recovered multiple times and reused in different operations.Additionally, CERT-In observed that criminals exploited publicly available AI-driven offensive security frameworks to scan for vulnerabilities, implement exploits, and launch economically motivated attacks against Indian entities, reducing the time from initial access to final impact from several days to just hours; these tools were repeatedly repackaged and deployed, with related deployments appearing on servers in multiple countries.
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