Tax Evasion Goes Digital: Criminals Shift To Novel Crypto Instruments – Analysts

bitcoinistPublicado em 2026-05-22Última atualização em 2026-05-22

Resumo

Italian police uncovered a tax fraud case worth over $1 million where the suspect used novel Bitcoin-based tools, the Ordinals protocol and BRC-20 token standard, to conceal undeclared capital gains. The individual allegedly created and sold tokens, funneling profits back into a primary Bitcoin wallet in a repeated cycle to avoid tax records. Analysts from Chainalysis note that while tax evasion using cryptocurrency is not new, methods are becoming more creative, with bad actors increasingly turning to NFTs, DeFi, and new token standards. However, a fundamental weakness exists: the blockchain provides a permanent, unchangeable record of all transactions. Blockchain intelligence tools can trace these transactions and link them to individuals, especially when combined with data from exchanges. This case demonstrates that technical novelty does not guarantee anonymity. The tax gap remains a significant issue globally, with studies showing low reporting rates among crypto owners. As new digital assets generate wealth, the discrepancy between on-chain activity and declared income is drawing increased scrutiny from investigators worldwide.

An Italian police unit cracked a tax fraud case worth over a million dollars — and at the center of it was not a secret bank account or a shell company, but Bitcoin inscriptions.

A New Way To Hide Old Money

Italy’s Economic and Financial Police Unit in Foggia uncovered a scheme in which a suspect allegedly used the Bitcoin Ordinals protocol and the BRC-20 token standard to generate and conceal roughly 1 million euros, or about $1.1 million, in undeclared capital gains.

According to blockchain analytics firm Chainalysis, the suspect created tokens using those tools, listed them on marketplaces, sold them for far more than they originally cost, and funneled the profits back into a primary Bitcoin wallet.

The cycle repeated — earnings went straight into new inscriptions, keeping the money moving and off tax records.

Introduced in 2023, the Ordinals protocol works by assigning a serial number to a satoshi, the smallest unit of Bitcoin, and embedding data such as images or text into a Bitcoin transaction. The BRC-20 standard builds on that by letting users deploy, mint, and transfer tokens directly on the Bitcoin blockchain.

Tax Authorities Playing Catch-Up

Tax evasion through crypto is not new. What is changing is how creative the methods are getting. Chainalysis said bad actors are increasingly turning to NFTs, decentralized finance protocols, and emerging token standards in hopes of keeping wealth hidden from authorities. The firm published its findings Wednesday.

BTCUSD now trading at $77,065. Chart: TradingView

Compliance data suggests the problem runs deep. A study released in March found that only 32% to 56% of US crypto owners report their gains to tax authorities. In Norway, that figure dropped to just 12%, based on research published in August 2024.

Meanwhile, the US Internal Revenue Service puts the country’s gross tax gap — the total taxes legally owed but not collected — at around $606 billion.

A Trail That Never Disappears

Despite the technical creativity behind schemes like the one in Italy, Chainalysis said there is a built-in weakness in using crypto to hide money. The blockchain keeps a permanent record of every transaction, and that record cannot be changed or deleted.

The Fatal Flaw Of Crypto Fraud

Blockchain intelligence tools are capable of rebuilding a complete financial network and comparing it with information crypto exchanges are required to disclose, making it possible to trace transactions back to suspected tax cheats. Officials said the Italian case shows that technical novelty does not equal anonymity.

As new types of digital assets continue to appear and generate income, analysts say the gap between actual on-chain wealth and what people declare on their taxes will draw more attention from investigators around the world.

Featured image from Tax Central, chart from TradingView

Perguntas relacionadas

QWhat novel digital tools were allegedly used by a suspect in Italy to conceal undeclared capital gains?

AThe suspect allegedly used the Bitcoin Ordinals protocol and the BRC-20 token standard to generate and conceal the undeclared capital gains.

QAccording to Chainalysis, what are some of the crypto-based methods increasingly being used by bad actors to hide wealth from tax authorities?

AAccording to Chainalysis, bad actors are increasingly turning to NFTs, decentralized finance protocols, and emerging token standards to hide wealth.

QWhat is the inherent weakness of using crypto to hide money, as highlighted by the article?

AThe inherent weakness is that the blockchain maintains a permanent, unchangeable record of every transaction, creating a traceable trail.

QWhat is the estimated gross tax gap in the United States, as mentioned in the article?

AThe US Internal Revenue Service estimates the country's gross tax gap to be around $606 billion.

QBased on the article's example, what does the Italian tax fraud case demonstrate about technical novelty in crypto?

AThe Italian case demonstrates that technical novelty in crypto does not equal anonymity, and transactions can be traced back to suspects using blockchain intelligence tools.

Leituras Relacionadas

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

A discussion on Zhihu about "AI relay stations" shifted the niche developer topic of "cheap tokens" into broader user awareness. Users moved beyond simply questioning the legitimacy of these services to focus on practical concerns: Where do cheap tokens truly come from? Is the model being accessed the real one? Can relay stations see prompts, code, and API keys? For occasional users, are the risks worth it? The core debate centered less on price and more on trust. A primary worry is model authenticity—the risk of "model swapping," where users paying for a premium model might be routed to a cheaper one, creating an information asymmetry. Others argued that cost comparisons matter; while cheaper than official pay-as-you-go APIs, relay stations may not be the lowest-cost option versus subscriptions, domestic models, or free tiers, making user needs assessment crucial. Speculation about token sources ranged from legitimate bulk discounts to gray-area methods like account sharing or exploiting regional pricing. This opacity makes risk assessment difficult for users. Data security emerged as a critical concern, especially for enterprise use. When processing sensitive information like code, contracts, or client data, the inability to verify a relay station's data handling, retention, or access policies poses significant compliance and confidentiality risks. The evolving consensus suggests relay stations can be used cautiously for low-sensitivity, disposable tasks (e.g., summarizing public info, simple translation). However, they should not be the default for sensitive, professional, or production workflows involving proprietary data, Agents, or automated systems. Recommendations include avoiding large prepayments, not relying on a single service, using test prompts to monitor quality, anonymizing data where possible, and keeping official channels as backups. Ultimately, the discussion framed tokens not just as a billing unit but as a measure of real cost encompassing price, model integrity, data security, and service stability. The popularity of relay stations highlights user demand for affordable access, but the debate underscores a key trade-off: the savings from cheap tokens may come at the price of trust, transparency, and control over one's data and AI experience.

marsbitHá 11m

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

marsbitHá 11m

In-Depth Research Report on TradFi: The Convergence Wave of Crypto and Traditional Finance

In 2026, the crypto industry is undergoing a profound infrastructure-level transformation—TradFi assets are migrating on-chain at an unprecedented pace. According to CoinGecko's Q1 2026 report, the total value locked (TVL) of tokenized real-world assets (RWA) has surpassed $31 billion, a nearly 4x increase from $7.8 billion at the beginning of 2025, with the sector’s aggregate market capitalization reaching $19.3 billion. Among these, the market cap of tokenized stocks surged from $2 million to $486 million, with Q1 spot trading volume reaching $15.1 billion—a single quarter already surpassing the entire second half of 2025. RWA perpetual contract Q1 trading volume reached a staggering $524.8 billion, far exceeding the $313 billion for all of 2025. Meanwhile, BlackRock's BUIDL fund has reached $2.3 billion in scale and has filed for two new tokenized funds, signaling that the world's largest asset manager's tokenization strategy is evolving from pilot to product suite expansion. HTX, as a core participant in the crypto exchange sector, officially launched TradFi perpetual futures products including NVDA, AAPL, MSFT, META, and SPY in 2026, enabling crypto users to gain 24/7 trading access to core U.S. equities. Boston Consulting Group predicts that global tokenized asset scale could reach $16 trillion by 2030, while McKinsey offers a conservative estimate of approximately $2 trillion. The on-chain migration of TradFi assets is no longer a "future narrative" but a structural transformation unfolding in real time, as crypto exchanges evolve from single crypto asset trading platforms toward "multi-asset-class trading infrastructure."

HTX LearnHá 14m

In-Depth Research Report on TradFi: The Convergence Wave of Crypto and Traditional Finance

HTX LearnHá 14m

Blocked Its Own Treasure, WeChat AI Steps Up

Tencent's stock surged over 10% on June 2nd amid reports that WeChat, with 1.43 billion monthly users, is finalizing tests for a native AI Agent. The reported feature, accessible by swiping right from the main interface, allows users to issue commands in natural language. The AI then decomposes tasks and automatically calls upon relevant Mini Programs within WeChat to complete actions like ordering food, booking tickets, or making payments, creating a closed-loop service execution system. This strategic shift follows the internal conflict and subsequent "blocking" of Tencent's standalone AI app, Yuanbao, by WeChat for violating sharing rules during a 2026 Spring Festival promotion. The incident highlighted a lack of internal consensus and exposed the weakness of competing in the standalone AI assistant arena against rivals like ByteDance's Doubao (345M MAU) and Alibaba's Qianwen. The new WeChat AI Agent aims to leverage WeChat's unique assets—its massive user base, standardized Mini Program APIs, WeChat Pay, and identity system—to move from simple content generation to actual task execution. Analysts note this changes the competitive landscape from model benchmarks to which AI can connect to more real-world services. However, success depends on key variables: the capability of Tencent's underlying Hunyuan model, managing massive inference costs, and redesigning incentives for Mini Program developers whose traffic might be bypassed. The move is seen as an attempt to keep user service intent within WeChat's ecosystem as AI begins to redefine how users access services.

marsbitHá 1h

Blocked Its Own Treasure, WeChat AI Steps Up

marsbitHá 1h

ByteDance Adopts Arm CPUs, Jensen Huang: So Sad I Didn't Buy Arm

**Summary:** At Computex 2026, Arm CEO Rene Haas announced that ByteDance and Oracle have adopted Arm's self-designed Arm AGI data center CPU. The company expects significant revenue growth from this product, projecting $20 billion in demand for the 2027/2028 fiscal years. Haas noted that restricting AI-capable CPUs from the US to China is nearly impossible due to their widespread applications. Arm's stock has surged dramatically this year, notably rising 16% after NVIDIA's Arm-based Vera CPU and RTX Spark announcements. A highlight was the informal, humorous on-stage conversation between Haas and NVIDIA CEO Jensen Huang. Huang joked about NVIDIA's failed attempt to acquire Arm and playfully lamented selling his Arm shares. Both executives showed a clear sense of camaraderie and shared regret over the missed merger. Key technical topics were discussed: 1. **AI PC Design:** Huang explained NVIDIA's RTX Spark superchip (with a 20-core Arm CPU) is designed for future AI agents that will autonomously run and use tools on PCs, blending local and cloud processing. 2. **Agent vs. OS:** Huang emphasized the operating system remains crucial, as AI agents rely on its APIs and tools to function. 3. **Growth Constraints:** He identified the shift to "useful AI" that generates profitable tokens as a primary driver for immense, almost limitless, computational demand. Haas outlined Arm's strategy across PC and data centers. For PCs, Arm collaborates with partners like NVIDIA and MediaTek, offering its compute subsystem (CSS) for custom SoCs. In data centers, its Arm AGI CPU (built on TSMC's 3nm process) has gained major partners including OpenAI, Meta, and now ByteDance and Oracle. Arm presented a multi-year roadmap for its in-house CPU line. The article concludes that while GPUs dominated the AI training race, the explosion of AI agents is shifting significant focus to CPUs for inference, state management, and tool orchestration. The industry is trending towards vertical integration, with companies like cloud providers designing chips and chip/IP firms offering full solutions, all competing to deliver more efficient computing per watt.

marsbitHá 1h

ByteDance Adopts Arm CPUs, Jensen Huang: So Sad I Didn't Buy Arm

marsbitHá 1h

Trading

Spot
Futuros
活动图片