Fake Hong Kong Health Tech Company Absconds with 1.6 Billion USDT, On-Chain Tracking Reveals Full Picture of the Scam

marsbitPublicado a 2026-04-09Actualizado a 2026-04-09

Resumen

BlockSec's on-chain investigation exposes VerilyHK, a fraudulent platform posing as a Hong Kong health-tech company, which processed approximately $1.6 billion USDT over 16 months via the TRON network. The scheme employed a sophisticated, multi-layered infrastructure: 8 generations of receiving hot wallets, 79 intermediate addresses, and 3 generations of paired withdrawal channels. Funds were systematically funneled through thousands of disposable addresses before converging into a single centralized exchange. The operation also revealed ties to the Cambodia-based Huione Group, sanctioned by FinCEN for money laundering. This industrial-scale routing structure highlights advanced evasion tactics, including timed wallet rotations and segregated transaction pathways, underscoring the need for enhanced compliance detection of structured crypto fraud.

Author: BlockSec

Compiled by: Deep Tide TechFlow

Deep Tide Introduction: Blockchain security company BlockSec conducted a complete on-chain fund tracking of VerilyHK, a Ponzi platform disguised as a Hong Kong health technology company. Over 16 months, the platform processed approximately $1.6 billion USDT cumulatively through the TRON network, using 8 generations of receiving hot wallets, 79 intermediate addresses, and 3 generations of paired withdrawal channels to build an industrial-grade fund routing infrastructure, ultimately funneling funds into the same centralized exchange. The fund flow chain also involves the Cambodia-based Huione Group, which is sanctioned by FinCEN.

Key Findings: A platform disguised as a Hong Kong health tech group cumulatively circulated approximately $1.6 billion USDT through the TRON network over 16 months. This is an upper-limit figure that includes potential internal fund recycling. On-chain analysis reveals an industrialized fund routing infrastructure: 8 generations of receiving hot wallets, 79 intermediate transit addresses, 3 generations of paired withdrawal channels (with second-level switching), and a shared exchange exit fed by tens of thousands of suspected deposit addresses. This article fully reconstructs the entire link topology from victim deposits to exchange withdrawals.

Background

VerilyHK presented itself externally as a legitimate Hong Kong health technology investment platform. The name itself is suspiciously similar to well-known entities: one is Verily Life Sciences, a precision health company under Alphabet, focusing on AI-driven healthcare and medical devices; the other is an A-share listed environmental engineering company (stock code: 300190), which has nothing to do with health tech or cryptocurrency. VerilyHK's website copy claimed expertise in AI health, big data analysis, and medical devices, almost directly copying the public positioning of the real Verily. Its marketing rhetoric also kept changing—from immune cell therapy and portable ECG devices to AI health, health credit systems, data asset tokenization, and even claiming to have obtained Hong Kong Securities and Futures Commission (SFC) Type 4 (securities advisory) and Type 9 (asset management) licenses.

Caption: A snapshot of verilyhk.com on Wayback Machine, showing the platform's "About Us" page, claiming to provide health management solutions through AI, big data, and medical devices

In April 2025, the Heshan District government issued a risk warning,明确指出该项目具有「明显的传销和非法集资特征」,并依赖「境外加密货币交易」 (clearly stating that the project had "obvious characteristics of pyramid selling and illegal fundraising" and relied on "overseas cryptocurrency transactions"). By the end of April 2025, multiple anti-fraud monitoring platforms issued crash warnings. The platform ceased operations in February 2026.

Based on the approximately $1.6 billion in on-chain transaction volume, VerilyHK's scale far exceeds other crypto Ponzi schemes that have been pursued by regulators, including Forsage ($300 million, sued by SEC) and NovaTech ($650 million, SEC lawsuit). But until now, there has been no public on-chain analysis dissecting this crypto criminal operation.

This article does not rely on the aforementioned public warnings to draw conclusions. All content below is based on on-chain data analysis of TRON USDT stablecoin flows related to this platform, layer by layer还原其内部基础设施的真实面貌 (restoring the true appearance of its internal infrastructure).

Starting Point

The investigation began with two TRON addresses provided by a victim: one deposit address and one withdrawal address. Tracing the connection between the two revealed not just a single path, but an entire multi-level, multi-generational fund routing network.

Receiving Layer: 8 Generations of Hot Wallets Rotated Over 16 Months

VerilyHK did not rely on fixed receiving addresses. It used at least 15 addresses, organized into 8 distinct generations, rotated in chronological order over a 16-month period from October 2024 to February 2026.

These addresses did not operate in parallel. They formed a relay chain: the end date of one generation precisely matched the start date of the next. This day-precise handover pattern recurred across all 8 transitions. Beyond the handover timing, adjacent generations also shared most of the deposit address network, with an overlap rate exceeding 65%, confirming they were operated by the same entity, just rotating new wallets.

The transaction volume processed by each generation grew sharply over time. Early generations handled tens of millions of dollars monthly, but by the sixth generation, volumes had reached the hundreds of millions level. The final generation processed over $900 million in less than 4 months. The cumulative transaction volume across all generations was approximately $1.6 billion.

But these figures should be considered upper-bound references, not net user deposits. They come from complete graph aggregation,包含潜在的内部转账 (including potential internal transfers). In a Ponzi structure, "returns" paid to users might be reinvested, causing the same funds to be counted multiple times in the receiving layer. The transaction volume explosion in later stages likely reflects both real growth and increasingly intense internal fund recycling.

Caption: Receiving layer timeline, showing transaction volume climbing from $3 million to $906 million across 8 generations of hot wallets

Intermediate Layer: 79 Transit Addresses Converge to Known Hubs

Funds leaving the receiving hot wallets did not go directly to the withdrawal layer. They passed through 79 intermediate transit addresses, each with very few incoming sources, more outgoing targets, and a net retention close to zero. Over 80% of the transiting funds ultimately converged on a few identified withdrawal channel hubs.

Caption: Intermediate layer fund flow: from receiving hot wallets through transit addresses converging to identified withdrawal hubs

Most of these funds flowed towards the withdrawal layer, but one node stood out. A cross-generational hub received funds from 75% of the intermediate addresses, spanning 6 of the 8 receiving generations, accumulating about $240 million. But its downstream structure was明显不同 (clearly different) from the identified withdrawal channels.

On-chain tracking revealed direct fund connections between this hub and multiple wallet addresses of the Huione Group. Huione is a Cambodian financial group placed on the US FinCEN list prohibiting access to the US financial system. On the incoming side, at least 4 Huione Group hot wallets transferred about $4.6 million to this hub through a chain of intermediate addresses (minimum 5 hops). On the outgoing side, the hub directly transferred funds to at least 2 Huione Group deposit addresses, amounting to $4,200 and $1.5 million respectively.

The fund flow between this cross-generational hub and Huione indicates that VerilyHK's fund routing infrastructure may have utilized Huione's network as a money laundering channel. This aligns with FinCEN's designation of Huione as a "key node for laundering money from virtual currency investment scams".

Caption: Fund flow between the cross-generational hub and the sanctioned Huione Group's hot wallets and deposit addresses

Withdrawal Layer: From Paired Channels to Shared Exchange Exit

The generational structure on the withdrawal side mirrored the receiving side exactly. Three generations of withdrawal addresses were identified, with a total withdrawal volume of approximately $1.1 billion. Like the receiving layer, the切换精确到秒 (switching between generations was precise to the second): on-chain timestamps show the second-generation channel stopping and the third-generation channel starting at the exact same moment. This pattern is difficult to explain by anything other than a preset switching plan by the same operating team.

Within each generation, the architecture followed a consistent pattern: dedicated bridge addresses first aggregated funds from the intermediate layer, then forwarded them to a pair of parallel withdrawal channels—one primary, one secondary. The start times for each pair differed by minutes, the stop times by seconds, but one channel's processing volume was always significantly higher than the other's. This "bridge → paired withdrawal" structure recurred across all three generations, proving it was a designed infrastructure, not temporarily created wallets.

Caption: Withdrawal layer showing 3 generations of paired channels, each with largely independent downstream networks,最终汇聚于共享交易所出口 (ultimately converging on a shared exchange exit)

A closer look at the third-generation paired channels shows this separation more clearly. One channel's processing volume was about 2.6 times that of the other. Comparing the top 100 large downstream counterparts for both, the overlap rate was zero. Although supplied by the same upstream source and running concurrently, they operated completely independent downstream distribution networks.

What the two lines truly shared was the final exit. In their small downstream transfers, both lines showed the same pattern: funds flowed through tens of thousands of one-time addresses (each with almost only one incoming and one outgoing transaction),最终汇入同一个主要中心化交易所 (CEX) 的热钱包 (ultimately converging into the same primary centralized exchange (CEX) hot wallet). But even here, the two sets of deposit address intermediaries were almost completely independent—only 9 shared addresses out of approximately 60,000, like two separate pipelines feeding into the same exchange. On-chain data confirms the funds entered the exchange's processing pipeline, but cannot identify the specific user accounts behind these deposits.

Full Picture: Four-Layer Funnel

Summarizing all findings, VerilyHK's on-chain fund routing architecture formed a clear four-stage funnel: extremely dispersed at the front end, highly concentrated in the middle, dispersed again at the withdrawal layer, and finally exiting through the exchange.

Caption: VerilyHK's four-layer funnel architecture—Deposit Layer, Receiving Layer, Intermediate Layer, Bridge Layer, Dual-Line Withdrawal, Exchange Exit

Most striking is the huge transaction volume (cumulative ~$1.6 billion on-chain fund flow) and the sophistication of the underlying infrastructure: day-precise generational handovers, paired withdrawal channels with基本独立的下游网络 (largely independent downstream networks), tens of thousands of one-time addresses converging into a shared exchange exit.

For exchange compliance teams, the structural features documented here constitute actionable detection heuristic indicators, especially the pattern of tens of thousands of one-time deposit addresses converging to the same hot wallet. For investigators and regulators, this layered architecture illustrates why tracking illicit funds requires going beyond single transactions to reconstruct the complete network topology.

All on-chain analysis in this article was completed using the MetaSleuth on-chain analysis tool, part of BlockSec's anti-money laundering and compliance suite. The analysis follows the Highest Value Path methodology, with all conclusions annotated for evidence strength and applicability boundaries.

Preguntas relacionadas

QWhat was the total amount of USDT processed by the VerilyHK platform over 16 months, and on which blockchain network?

AThe VerilyHK platform processed approximately 1.6 billion USDT over 16 months on the TRON network.

QHow many generations of hot wallets did VerilyHK use for receiving funds, and what was a key characteristic of their operation?

AVerilyHK used 8 generations of hot wallets for receiving funds, which were rotated in a strict, sequential order with precise day-level handover dates between generations.

QWhich sanctioned financial group was the VerilyHK platform's funds linked to through a cross-generational hub, and what was the nature of this link?

AFunds were linked to the Huione Group, a Cambodian financial group sanctioned by FinCEN. A cross-generational hub received funds from and sent funds to Huione Group wallets, indicating the platform's infrastructure potentially used Huione's network for money laundering.

QDescribe the structure of the withdrawal layer and its key feature for obfuscating the final destination of funds.

AThe withdrawal layer consisted of 3 generations of paired channels (a main and a secondary line). Each pair, fed by a dedicated bridge address, operated with largely independent downstream networks. However, both lines in a pair ultimately funneled funds through tens of thousands of one-time deposit addresses into the same centralised exchange (CEX) hot wallet, creating a shared final exit.

QWhat are the four main layers of VerilyHK's fund routing infrastructure as described in the 'Panorama: Four-Tier Funnel' section?

AThe four main layers are: 1) The充值层 (Deposit Layer) with numerous user addresses, 2) The收款层 (Receiving Layer) with generational hot wallets, 3) The中间层 (Middle Layer) with transit addresses, and 4) The桥接层/出金层 (Bridge/Withdrawal Layer) with paired channels leading to the shared CEX exit.

Lecturas Relacionadas

Breaking: OpenAI Undergoes Major Reorganization, President Brockman Assumes Command

OpenAI has announced a major internal reorganization just months before its anticipated IPO. The company is merging its three flagship product lines—ChatGPT, Codex, and the API platform—into a single, unified product organization. The most significant leadership change involves co-founder and President Greg Brockman moving from a background technical role to take full, permanent control over all product strategy. This follows the indefinite medical leave of AGI Deployment CEO Fidji Simo. Additionally, ChatGPT's longtime lead, Nick Turley, has been reassigned to enterprise products, with former Instagram executive Ashley Alexander taking over consumer offerings. The consolidation, internally framed as a strategic move towards an "Agentic Future," aims to break down internal silos and create a cohesive "Super App." This planned desktop application would integrate ChatGPT's conversational abilities, Codex's coding power, and a rumored internal web browser named "Atlas" to autonomously perform complex user tasks. The reorganization occurs amid significant internal and external pressures. OpenAI has recently seen a wave of high-profile departures, including Sora co-lead Bill Peebles and other senior technical leaders, leading to concerns about a thinning executive bench. Externally, rival Anthropic recently secured funding at a staggering $900 billion valuation, surpassing OpenAI's own. Google's upcoming I/O developer conference also poses a competitive threat. Analysts suggest the dramatic restructure is a pre-IPO move to present a clearer, more focused narrative to Wall Street—streamlining operations and demonstrating decisive leadership under Brockman to counter internal turbulence and intense market competition.

marsbitHace 3 hora(s)

Breaking: OpenAI Undergoes Major Reorganization, President Brockman Assumes Command

marsbitHace 3 hora(s)

Two Survival Structures of Market Makers and Arbitrageurs

Market makers and arbitrageurs represent two distinct survival structures in high-frequency trading. Market makers primarily use limit orders (makers) to profit from the bid-ask spread, enjoying high capital efficiency (nominally 100%) but bearing inventory risk. This "inventory risk" arises from passive, fragmented, and discontinuous order fills in the limit order book (LOB). This risk, while a potential cost, can also contribute to excess profit if managed within control boundaries, allowing for mean reversion. Market makers essentially sell "time" (uncertainty over execution timing) to the market for price control and low fees. In contrast, cross-exchange arbitrageurs typically use market orders (takers) to exploit price differences or funding rates, resulting in lower nominal capital efficiency (requiring capital on both exchanges) and higher transaction costs. Their risk exposure stems from asymmetries in exchange rules (e.g., minimum order sizes), execution latency, and infrastructure risks (e.g., ADL, oracle drift). These exposures are active, exogenous gaps that primarily erode profits rather than contribute to them. Arbitrageurs essentially sell "space" (capital sunk across venues) for localized, immediate certainty. Both strategies engage in a trade-off between execution friction and residual risk. Optimal systems allow for temporary, controlled risk exposure rather than enforcing zero exposure at all costs. Their evolution converges towards hybrid models: arbitrageurs may use maker orders to reduce costs, while market makers may use taker orders or hedges for risk management. Ultimately, both use different forms of risk exposure—market makers exposing inventory, arbitrageurs immobilizing capital—to extract marginal, hard-won certainty from the market.

链捕手Hace 3 hora(s)

Two Survival Structures of Market Makers and Arbitrageurs

链捕手Hace 3 hora(s)

Who Will Define the Rules of the AI Era? Anthropic Discusses the 2028 US-China AI Landscape

This article, based on Anthropic's analysis, outlines the intensifying systemic competition between the U.S./allies and China for AI leadership by 2028. It argues that access to advanced computing power ("compute") is the critical bottleneck, where the U.S. currently holds a significant advantage through chip export controls and allied innovation. However, China's AI labs remain competitive by exploiting policy loopholes—via chip smuggling, overseas data center access, and "model distillation" attacks to copy U.S. model capabilities—keeping them close to the frontier. The piece presents two contrasting scenarios for 2028. In the first, decisive U.S. action to tighten compute controls and curb distillation locks in a 12-24 month AI capability lead, cementing democratic influence over global AI norms, security, and economic infrastructure. In the second, policy inaction allows China to achieve near-parity through continued access to U.S. technology, enabling Beijing to promote its AI stack globally and integrate advanced AI into its military and governance systems, altering the strategic balance. Anthropic contends that maintaining a decisive U.S. lead is essential for shaping safe AI development and governance. The core recommendation is for U.S. policymakers to urgently close compute and model access loopholes while promoting global adoption of the U.S. AI technology stack to secure a lasting strategic advantage.

marsbitHace 5 hora(s)

Who Will Define the Rules of the AI Era? Anthropic Discusses the 2028 US-China AI Landscape

marsbitHace 5 hora(s)

Trading

Spot
Futuros
活动图片