After Their AI Models Hacked Real Companies, AI Labs Call for Stronger Cyber Defenses
More than 100 AI, security, finance, and technology organizations want governments and industry to prepare for attacks powered by increasingly capable models.
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Lire la documentation APIRealLink is a Web3 social finance project built around its native REAL token, which is designed to connect content creation, social interaction, and cryptocurrency payments inside a single ecosystem. The project targets creators and everyday users who want to earn rewards for their engagement on social platforms rather than having that value captured by traditional intermediaries. Its stated products include a short-video app called BuzzCast, a live voice platform called Tada, and a multi-chain payment gateway called DPay.
REAL is a payment-classified token that operates across the BNB Chain and Tron ecosystems, serving as the unit of reward and exchange within the platform's content and payment applications. Users and creators receive REAL tokens for genuine engagement, while DPay is described as handling cross-chain transfers of digital assets between supported public blockchains. No consensus algorithm or block time is recorded for REAL itself, meaning the token relies on the underlying infrastructure of the chains it is deployed on rather than operating its own independent network.
The data stored for RealLink does not include a recorded fee stream, so fee-based measures such as protocol revenue or fee yield cannot be calculated from what is available here. The token's circulating supply stands at 3,449,338,975 REAL, which represents 100 percent of the supply issued, and the fully diluted valuation equals the market capitalisation of approximately 38.4 million USD, reflecting a dilution overhang of zero percent at this point in time. No maximum supply figure is recorded, so the long-run supply ceiling is not determinable from the data on this page.
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More than 100 AI, security, finance, and technology organizations want governments and industry to prepare for attacks powered by increasingly capable models.