澳大利亚金融监管机构警告称,尽管自4月以来每月都在下降,但加密货币诈骗仍在继续

币界网Pubblicato 2024-08-18Pubblicato ultima volta 2024-08-19

币界网报道:

澳大利亚金融市场行为监管机构ASIC周日透露,去年它协调了600多起加密货币骗局的清除工作,这是破坏针对数十亿澳元储蓄的在线投资骗局的更广泛努力的一部分。

澳大利亚证券和投资委员会表示,它已帮助打击了5530起虚假投资平台诈骗、1065起网络钓鱼诈骗超链接和615起加密投资诈骗。

据估计,去年这些骗局共造成了13亿美元的损失,这些损失是通过虚假新闻文章和当地公众人物的深度伪造视频传播的。

监管机构在一份声明中表示:“ASIC提醒所有消费者对促进在线交易和加密货币投资的社交媒体超链接保持警惕。”。

ASIC表示,平均每天有20个网站被关闭,骗子继续适应并寻找新的方法来引诱受害者。

ASIC将可疑网站转介给专门从事检测和破坏网络犯罪的第三方公司。

一旦确认恶意活动,删除过程就开始了,包括识别可以协助将攻击脱机的相关方。

目标网站通常包括向澳大利亚人提供投资骗局的虚假或冒名顶替实体,如欺诈性交易平台和加密货币投资骗局。

ASIC网站按月删除中断能力。资料来源:澳大利亚证券投资委员会。

在一个例子中,ASIC表示,它收到了一名澳大利亚消费者的投资骗局报告,该消费者被一个在线加密骗局欺骗,谎称自己受到国际监管,交易量达数十亿美元。

ASIC表示:“在ASIC将网站转介给删除提供商一小时后,网站被删除。”。“ASIC通过其投资者警报名单发出警告,警告了其他潜在投资者。”

虽然在4月份比特币减半事件发生前后,与加密货币相关的骗局激增,但监管机构提供的数据显示,与上月相比,这一数字有所下降。

这在很大程度上追踪了全球趋势,Chainalysis在1月份透露,去年加密货币骗局下降了29%。

这家区块链分析公司上周表示,加密货币犯罪分子已经开始将注意力从去中心化平台转移到中心化交易所,在日益复杂的攻击中采用先进的社会工程策略。

Letture associate

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

The Bitcoin mining industry is undergoing its most complex structural adjustment since inception. Despite Bitcoin's price holding near $61,000 and the network hash rate approaching a record 1 ZH/s, miner profitability is deteriorating. The industry is operating close to its breakeven point, with the 2028 halving expected to accelerate consolidation. The challenges extend beyond the halving's subsidy reduction; the industry's revenue model has yet to successfully transition towards a fee-driven structure. Increasingly, mining companies are evolving from simple Bitcoin producers into infrastructure and energy operators, including providers of AI/HPC computing power. Competition is shifting from pure hash rate expansion to business model upgrades. Economic pressure is evident. The theoretical daily mining revenue at current prices is around $78 million, yet the actual figure is only about $33 million—a 136% gap. Transaction fees remain low at roughly $220k daily, far below historical implied levels. With a current estimated industry-wide breakeven price near $65,000, mining alone is struggling to generate ideal profits. The 2028 halving is projected to push the fundamental production cost floor to approximately $93,289. This will likely accelerate a shift towards consolidation among larger, well-capitalized miners with diversified revenue streams. Competitive advantage will belong to institutionalized players with access to low-cost energy, AI/HPC hosting operations, and stronger balance sheets. In essence, Bitcoin mining is transitioning from a "mining business" to an "infrastructure business." Future profitability and resilience will depend less on block rewards and more on diversified income sources like energy management and computational infrastructure services. For investors, the key question is not the halving itself, but which miners can successfully navigate this business model transformation.

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BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

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This is How God Karpathy Uses Claude?

Andrej Karpathy, a prominent figure in AI, has reportedly joined Anthropic, leading to a noticeable decrease in his open-source contributions and social media activity. A document claiming to be his personal "CLAUDE.md" file—a set of instructions for the Claude AI to follow within a specific codebase—has been circulating online. While its authenticity is unverified, the content aligns closely with Karpathy's publicly shared principles on effective AI-assisted programming. The document outlines key rules for AI coding assistants, emphasizing the importance of reading existing code thoroughly before writing new code to maintain consistency. It advises against over-engineering, advocating for simple, surgical modifications that match the project's existing style. Other guidelines include clarifying assumptions upfront, writing meaningful tests, thoughtful debugging, and carefully considering dependencies. The core message is that these principles help prevent common AI coding failures, such as introducing unnecessary abstractions, style drift, or making invisible architectural decisions. The community has noted that even experts like Karpathy require detailed instructions to guide AI effectively, akin to managing a junior developer. A related GitHub repository, "andrej-karpathy-skills," which encapsulates these ideas, is reported to significantly reduce Claude's code error rate. Ultimately, the advice stresses that the best CLAUDE.md is tailored to one's own tech stack and coding practices.

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This is How God Karpathy Uses Claude?

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