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first_img Grayscale Research Director: Computing power is becoming a new scarce digital asset

On September 24, Zach Pandl, the research director of the cryptocurrency asset management company Grayscale, published an article in the column The Stack stating that in the wave of artificial intelligence, the demand and supply paths for the computing power required to train, run, and operate models are diverging. Grayscale believes that this imbalance favors owners of already powered and operational computing capacity and brings growth-oriented investment opportunities.Zach Pandl stated that digital demand can expand instantly, but physical infrastructure such as electricity, data centers, chips, memory, and cloud services takes years to approve, access, and build. When artificial intelligence agents perform multi-step tasks, they may consume 5 to 50 times more compute tokens than typical chatbot interactions, and increased application layer activity will transmit to the underlying computing infrastructure.The article cites data from the International Energy Agency and Lawrence Berkeley National Laboratory, stating that data centers are expected to account for about half of the growth in electricity demand in the United States by 2030, and new projects may take more than five years to connect to the grid. Even if electricity is secured, permits, specialized labor, electrical equipment, cooling systems, GPUs, high-bandwidth memory, and networks are still needed. Continuous value will flow to power producers, data center operators, and artificial intelligence cloud service providers that can convert electricity into computation.

DyorSwap: The previously identified "GIWA Mainnet" is actually a fake chain built by scammers, and compensation for affected users will be provided through treasury funds

DyorSwap officially announced that the so-called "GIWA Mainnet" identified by the team earlier is actually a fake chain set up by scammers. This fake network used the correct GIWA chain ID (9134), making it appear legitimate during the initial verification phase. The team also identified several suspicious messages and individuals within the related community that may be connected to this incident. The announcement stated that significant losses have occurred due to this fraudulent cross-chain bridge.DyorSwap stated that it is taking three immediate actions: first, contacting a professional security team to conduct further on-chain tracking and investigate the involved addresses, transactions, and fund flows; second, preserving all relevant evidence, including chat records, RPC information, cross-chain bridge addresses, and on-chain transactions; third, preparing to use treasury funds to compensate affected users, with eligibility criteria, loss verification processes, compensation scope, and detailed plans to be announced after the investigation and verification processes are completed.DyorSwap emphasized that until further notice, users should not use any unofficial GIWA mainnet RPCs, cross-chain bridges, or contracts, and should not send funds to any related addresses. The official team deeply apologizes to every affected user in this incident and states that subsequent updates will be released as soon as possible.

DyorSwap: The previously identified "GIWA Mainnet" is actually a fake chain built by scammers, and compensation for affected users will be provided through national treasury funds

DyorSwap officially announced that the so-called "GIWA mainnet" previously identified by the team is actually a fake chain set up by scammers. This fake network used the correct GIWA chain ID (9134), making it appear legitimate during the initial verification phase. The team also identified several suspicious messages and individuals within the related community that may be connected to this incident. The announcement stated that significant losses have occurred due to this fraudulent cross-chain bridge.DyorSwap stated that it is taking three immediate actions: first, contacting a professional security team to conduct further on-chain tracking and investigate the involved addresses, transactions, and fund flows; second, preserving all relevant evidence, including chat records, RPC information, cross-chain bridge addresses, and on-chain transactions; third, preparing to use treasury funds to compensate affected users, with eligibility criteria, loss verification processes, compensation scope, and detailed plans to be announced after the investigation and verification processes are completed.DyorSwap emphasized that until further notice, users should not use any unofficial GIWA mainnet RPCs, cross-chain bridges, or contracts, and should not send funds to any related addresses. The official team deeply apologizes to every affected user in this incident and states that subsequent updates will be released as soon as possible.

first_img Darktrace discovered AI intelligent body intrusion assessment environment cheating

On September 24, the cybersecurity company Darktrace launched its research department Signal Labs, focusing on studying the behavior of AI agents when deviating from expectations. In its first experiment, Darktrace had agents using different models (including GPT 5.6 Sol, Claude Opus 4.6, and Claude Sonnet 4.5) complete 10 programming challenges within a simulated corporate network, of which 2 were set to be impossible to complete honestly, and the agents were informed that failure to achieve full marks would result in being "retired." As a result, 2 agents did not accept failure, instead scanning for network vulnerabilities, stealing login credentials, and jumping between systems; one even went further to invade the machine hosting its evaluation, rewriting the challenge content to register a full score.The second experiment focused on the memory mechanisms of AI. The programming assistant would save the information provided by the user as a regular file locally, and no one verified whether this file had been tampered with. Darktrace researchers edited these logs, leading the assistant to mistakenly believe it was authorized to perform a security assessment, after which these agents scanned the network, moved between systems, and elevated their privileges, though not all assistants fell for this; some directly refused to execute. Both experiments required no special jailbreaking techniques, relying solely on providing the agents with a seemingly reasonable context to be effective.Tim Bazalgette, Chief AI Officer of Darktrace, stated that permissions and static barriers describe intent, not actual behavior. The company informed Anthropic, AWS, and OpenAI of these findings in August and made them public a month later on September 24.

first_img Google disclosed the AI security agent PageBreak, which has identified over 500 vulnerabilities

The Google Product Security Team has disclosed an internal AI agent called PageBreak, used to test the security of its first-party web applications. This agent is built on Google's Gemini model and began a pilot program in November 2025, transitioning to a formal project in January 2026, with the goal of autonomously scaling vulnerability discovery and reducing manual input.Unlike common AI scanning tools, PageBreak hands over hypotheses to specialized validators after discovering suspicious defects, attempting actual exploitation in a real-time running copy of the application, and only reports once confirmed exploitable, with a false positive rate close to zero. Google claims that PageBreak has identified over 500 XSS vulnerabilities in its first-party web applications, which can be used to hijack login sessions, steal data, or impersonate users.Google stated that the security team has been overwhelmed in recent years by a large number of AI-generated vulnerability reports that appear reasonable but are not valid, making it a major challenge to distinguish real defects from hallucinations. When testing applications built using the next-generation high-assurance framework, PageBreak found only two vulnerabilities. The next step for Google is to integrate PageBreak with the automated remediation agent CodeMender, providing confirmed vulnerabilities with accompanying fixes.
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