‘Circle had 6 hours to freeze funds’ – ZachXBT slams CEO after DRIFT hack

ambcryptoОпубліковано о 2026-04-02Востаннє оновлено о 2026-04-02

Анотація

In the past 24 hours, Drift Protocol on Solana suffered a $285 million hack, including the theft of Circle’s USDC. Blockchain investigator ZachXBT accused Circle of failing to freeze $230 million in stolen USDC that was bridged from Solana to Ethereum via CCTP, despite having a 6-hour window to act. He criticized Circle and its CEO Jeremy Allaire for incompetence, alleging they use compliance buzzwords without real implementation. The hack impacted 11 protocols, with Ranger Finance losing $900K. Although Solana’s Chief Product Officer called it an isolated incident, the event raised broader DeFi security concerns. Circle’s stock extended its decline, with indicators showing oversold conditions and continued selling pressure.

In the past 24 hours, another security threat has occurred in crypto. Drift Protocol [DRIFT], built on the Solana [SOL] blockchain, lost about $285 million in a hack that stole several coins, including stablecoins like Circle’s USDC.

Circle is currently undergoing its second fix, just a few days after facing accusations of failing to protect customers. A week ago, they froze 16 wallets that showed clear business transactions after a request that had errors.

However, they have since started to unfreeze some of these 16 wallets.

With the incident proving some level of incompetence, another accusation by ZachXBT has arisen, linking it with the Drift Protocol hack.

ZachXBT accuses Circle of failure to protect customers

As per ZachXBT, Circle Protocol [CRCL] failed to freeze $230 million USDC from the exploit. The amount was bridged from Solana to Ethereum [ETH] via CCTP. ZachXBT said,

6 hours is how long Circle had to freeze stolen funds from the $280M+ Drift hack.

The blockchain investigator accused them of sleeping while more than 100 transactions were happening, even though it was three hours after the hack incident. He labeled Circle and the CEO, Jeremy Allaire, as bad actors for the industry.

Users were wondering how such a well-known DeFi app did not have a special monitoring place. In response, ZachXBT said Circle uses buzzwords like “compliance” and “regulated” without actual implementation. He noted,

Who believes them unbeknownst of the problem

Impact on the broader crypto market

Meanwhile, several protocols had confirmed impacts following the Drift exploit, as per a post by SolanaFloor. About 11 protocols suspended most of their activity, with Ranger Finance losing $900K.

However, the Chief Product Officer at the Solana Foundation assured users of security and a bounce back for the whole chain. He clarified,

“This is an isolated incident and says nothing about Solana DeFi or any other Solana product...But I know the Solana DeFi community will pick up the pieces and rebuild fast as only Solana can.

For the broader crypto market, this incident raises concerns about the security of DeFi protocols and their position, even as regulations seek to curb malicious activities done through these protocols.

Circle stock extends its price decline

On the charts, Circle stock extended its decline that started after the first acquisition seven days ago. However, it is trading above the previous higher high at $90, but such news could lead to a breakdown.

Furthermore, CRCL was seeing capital leave as the Money Flow Index (MFI) dropped to 19. This indicated the stock was oversold, with Bull Bear Power (BBP) showing seller dominance.

Final Summary

ZachXBT accuses Circle of not freezing the $230 million USDC bridge from Solana to Ethereum.
Circle’s stock declined even though the Chief Product Officer at Solana assured users of a bounce back.

Трендові криптовалюти

CitreaCTR

wrapped stUSDTWSTUSDT

Velodrome FinanceVELODROME

BrevisBREV

PancakeSwapCAKE

JUSTJST

Пов'язані питання

QWhat was the total amount lost in the Drift Protocol hack and which stablecoin was involved?

AThe Drift Protocol hack resulted in a loss of about $285 million, which included stablecoins like Circle's USDC.

QAccording to ZachXBT, how much time did Circle have to freeze the stolen USDC funds and what was the amount?

AZachXBT stated that Circle had 6 hours to freeze $230 million in USDC that was stolen and bridged from Solana to Ethereum.

QWhat accusation did ZachXBT make against Circle and its CEO regarding the hack?

AZachXBT accused Circle and its CEO, Jeremy Allaire, of being 'bad actors for the industry' for failing to freeze the stolen funds despite having ample time and multiple transactions occurring.

QHow did the Solana Foundation's Chief Product Officer characterize the Drift Protocol incident?

AThe Chief Product Officer at the Solana Foundation characterized the incident as an 'isolated incident' that does not reflect on Solana DeFi or other Solana products, and expressed confidence that the community would rebuild quickly.

QWhat was the impact on Circle's stock (CRCL) following the news of the hack and the accusations?

ACircle's stock extended its price decline, with the Money Flow Index dropping to 19, indicating the stock was oversold, and Bull Bear Power showing seller dominance.

Пов'язані матеріали

Upbit Rebalances 864B SHIB In Internal Wallet Move

South Korean cryptocurrency exchange Upbit moved a total of 864 billion SHIB (worth approximately $4 million) between its internal wallet addresses. The activity, involving transfers of 384 billion SHIB outbound and 480 billion SHIB inbound, occurred following a 36% SHIB price rally. On-chain data indicates this was a routine internal wallet rebalancing operation by the exchange, not a sell-off or liquidation event. The article cautions that while large on-chain transfers are highly visible, they require proper context and wallet labeling to interpret correctly. In this case, the movement between known Upbit addresses does not inherently signal a change in market supply or selling pressure for SHIB.

bitcoinist53 хв тому

Upbit Rebalances 864B SHIB In Internal Wallet Move

bitcoinist53 хв тому

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

This article introduces a novel training paradigm for generative models called Explorative Modeling (XM), which enables true end-to-end training. Traditionally, powerful generative models like autoregressive and diffusion models are not trained end-to-end. They are trained to predict a single small step but require iterative multi-step sampling for inference. This "exposure bias" leads to error accumulation and limits performance. The core challenge XM addresses is "mode blurring." In generative tasks, a single input (e.g., "generate a dog") corresponds to many valid outputs (multiple modes). Standard training objectives like reconstruction loss force the model to average these modes, producing unrealistic, blurry outputs. To avoid this, existing models break generation into many small, almost deterministic steps, sacrificing end-to-end training. XM tackles this by restructuring the training loop itself. Its key insight is to amplify "generative expressivity." For each training input, instead of generating one sample, the model generates K candidate outputs. Only the candidate closest to the real data is used for computing the loss and updating the model via backpropagation. This simple "best-of-K" mechanism is implemented as a short for-loop. By exploring multiple possibilities, the model learns to distribute its guesses across different modes rather than collapsing to their uninformative average. The paper demonstrates that "exploration" acts as a new, powerful scaling axis. Gains from XM increase with model size, data scale, and compute. Experiments show improvements in FID scores for image generation and significant efficiency gains, sometimes outperforming larger models without exploration. When pushed to the limit, XM enables fully single-step, end-to-end generative models. In robotics tasks, an "Explorative Policy" matched the performance of a 100-step Diffusion Policy with a single forward pass, drastically improving inference speed. While the best-of-K concept is not entirely new, the authors' contribution lies in formally understanding it as a direct method to boost generative expressivity without fragmenting the generation process. This work suggests that as models scale, enhancing exploration during training may become crucial for overcoming fundamental performance bottlenecks.

marsbit54 хв тому

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

marsbit54 хв тому

A Maximum of 20 Submissions Per Person? DeepMind Researcher Satirically 'Petitions' Against ICLR's New Rule

The International Conference on Learning Representations (ICLR) 2027 has introduced a new submission rule limiting authors to a maximum of 20 papers per conference. This policy, announced due to a 68% surge in submissions for ICLR 2026 that strained the review system, aims to ensure fair and informative peer review. Google DeepMind researcher Dan Roy responded with a sarcastic petition on X, calling the 20-paper cap "absurd" and claiming it would slow AI progress. His post mockingly argued that AI agents can now produce incremental research and that large language models (LLMs) already handle all reviewing, so output should be maximized. This satire critiques the broader trend of AI's role in academia, referencing a 2025 study that found about 21% of ICLR 2026 reviews were likely fully AI-generated. Roy's underlying point questions whether simply capping submissions addresses the systemic issue of AI potentially flooding conferences with agent-written papers and AI-assisted reviews. The debate highlights tensions between managing submission volume and maintaining research quality as AI tools become pervasive.

marsbit58 хв тому

A Maximum of 20 Submissions Per Person? DeepMind Researcher Satirically 'Petitions' Against ICLR's New Rule

marsbit58 хв тому

Coldcard Vulnerability Leads to $89 Million Theft, Sparking Largest On-Chain Migration Since FTX Collapse

A security vulnerability in Coldcard hardware wallets led to the theft of 1,367.05 BTC (approx. $89 million) from 4,585 addresses, according to Galaxy Research. The flaw, caused by insufficient randomness in seed phrase generation for specific firmware versions, triggered a massive migration of funds as users moved assets to new, secure wallets. This event caused the largest on-chain movement of small Bitcoin transactions since the FTX collapse, distorting key market indicators like active addresses and exchange deposits, and significantly dampening market sentiment. The incident also highlighted challenges in cybersecurity investigations, as researchers reported that safety guardrails on mainstream U.S. AI models hindered the analysis of attack patterns, forcing them to use an open-source Chinese AI model for forensic work. This underscores a dilemma in balancing AI security restrictions with the need for rapid response in tracing stolen crypto assets.

marsbit1 год тому

Coldcard Vulnerability Leads to $89 Million Theft, Sparking Largest On-Chain Migration Since FTX Collapse

marsbit1 год тому

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School

The AI boom is facing an unexpected bottleneck: a severe shortage of skilled construction workers and electricians. As tech giants like Meta, OpenAI, and Alphabet race to build massive data centers—such as OpenAI's $16 billion "Stargate" project—they are hitting a critical labor wall. The U.S. needs an estimated 130,000 more electricians, 240,000 construction workers, and 150,000 supervisors by 2030 for AI infrastructure alone, but tens of thousands of electrician jobs go unfilled each year. While AI companies offer high premiums, with electricians earning up to $280,000 annually, worker scarcity still causes massive losses—delays on a single project can cost $14.2 million per month. The complexity of building AI data centers, which require immense power (equivalent to powering hundreds of thousands of homes), sophisticated electrical systems, and advanced liquid cooling solutions, demands highly skilled technicians who are in short supply. To combat this, companies are investing heavily in training. Meta has committed $115 million to a free training school offering tuition, housing, and stipends, targeting 5,000 new workers. OpenAI is partnering with unions to secure skilled labor. These efforts are paying off, with a significant rise in Gen Z interest in trade schools over college. However, the power demands are staggering. AI data centers are driving a rapid surge in electricity consumption, projected to account for up to 12% of U.S. power use by 2028 and raising costs for consumers. Furthermore, the construction boom is project-based, leading to a potential future glut of trained workers once building peaks, which could depress wages industry-wide. The race for AI supremacy now depends as much on skilled hands as on advanced chips.

marsbit2 год тому

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School