ZachXBT Links US Seized Crypto Theft to Contractor CEO’s Son

TheNewsCryptoPublicado em 2026-01-26Última atualização em 2026-01-26

Resumo

Blockchain investigator ZachXBT has alleged that the individual responsible for stealing millions of dollars in cryptocurrency from U.S. government-controlled wallets is John Daghita, the son of Dean Daghita, CEO of Command Services and Support (CMDSS). The company was contracted by the U.S. Marshals Service to manage seized digital assets. ZachXBT linked online persona “Lick” to the theft, tracing transactions back to a government wallet tied to the 2016 Bitfinex hack. Approximately $23 million was consolidated into a single wallet during the incident. CMDSS has not commented, and no criminal charges have been filed.

ZachXBT, a blockchain investigator, has claimed that the person accountable for a multimillion-dollar robbery of cryptocurrency from US government-curbed wallets is the son of the CEO of a company contracted to protect captured digital assets.

ZachXBT posted his detailed findings, claiming that a body known online as “Lick”, recognised as John Daghita, drained tens of millions of dollars in crypto from wallets associated with the US government.

He further claimed that Daghita is the son of Dean Daghita, president and CEO of Command Services and Support (CMDSS), a firm contracted by the US Marshals Service to manage some captured cryptocurrencies.

Public records reveal that CMDSS, based in Haymarket, Virginia, was awarded a contract in October 2024 to help the Marshals Service with the custody and disposal of so-called “Class 2-4” digital assets.

These comprise tokens that aren’t backed by prominent centralised exchanges and mostly need bespoke handling. The claim hasn’t been tested in court, and no criminal charges have been publicised.

At the time of writing, CMDSS had not officially commented on the matter. The claims of ZachXBT were highlighted with the publication of January 23, which associated the same online persona with over $90 million in suspected illegal crypto activity.

The Investigation

The investigation followed the trail back to a U.S. government wallet linked with assets captured from the 2016 Bitfinex hack. The inquiry gained traction after a listed dispute in a Telegram group chat between “Lick” and another individual.

At the time of exchange, “Lick” screen-shared an Exodus wallet showing a Tron address holding around $2.3 million after a live transfer of around $6.7 million in Ether. With the conclusion of the session, around $23 million had been united into a single wallet.

After the transactions were traced backward, ZachXBT associated that wallet with an address that got $24.9 million from a US government-controlled wallet in March 2024.

Highlighted Crypto News Today:

Metaplanet Lifts 2026 Outlook Despite $680M BTC Write-Down

TagsCEOUSAZachXBT

Perguntas relacionadas

QWho is ZachXBT and what did he claim in his investigation?

AZachXBT is a blockchain investigator who claimed that the person responsible for a multimillion-dollar cryptocurrency theft from US government-curbed wallets is the son of the CEO of Command Services and Support (CMDSS), a company contracted to protect captured digital assets.

QWhat is the online alias and real name of the individual accused of the crypto theft?

AThe individual accused is known online as 'Lick' and is identified as John Daghita.

QWhat is the connection between the accused individual and the company CMDSS?

AJohn Daghita is alleged to be the son of Dean Daghita, who is the president and CEO of Command Services and Support (CMDSS).

QWhat was the value of the suspected illegal crypto activity associated with the online persona 'Lick'?

AThe online persona 'Lick' was associated with over $90 million in suspected illegal crypto activity.

QFrom which infamous hack were the assets in the US government wallet linked to?

AThe assets in the US government wallet were linked to the 2016 Bitfinex hack.

Leituras Relacionadas

The Bitcoin 4-Year Cycle Has Never Disappeared, It Just 'Changed Shape'

Has Bitcoin's 4-Year Cycle Disappeared? The article argues that the fundamental 4-year cycle driven by halving events remains intact but its manifestation has changed due to a shift in the dominant buyer profile. The cycle peaked in October 2025, aligning with historical post-halving timelines. However, classic on-chain top indicators (MVRV, Pi Cycle, NUPL, etc.) failed to signal the peak. This is because these metrics are designed to detect retail FOMO, which was largely absent in Bitcoin this cycle. Retail capital was systematically drained by memecoins and high-FDV, low-float VC token launches before it could fuel a parabolic Bitcoin finale. Instead, institutional buyers (spot Bitcoin ETFs, corporate treasuries like MicroStrategy) became the marginal buyers. Their steady, programmatic accumulation created a strong but less volatile uptrend that didn't trigger traditional euphoria signals. The cycle's structure persists: a post-halving supply shock, a peak roughly 480-550 days later, and a bottom approximately one year after the peak (projected for Q3/Q4 2026). Bear market drawdowns are becoming shallower (projected 50-65% vs. past 78-86%) as institutional ownership matures. The article concludes that the cycle's timing remains the most reliable signal, while the tools to identify its phases must evolve with the market's structure.

marsbitHá 44m

The Bitcoin 4-Year Cycle Has Never Disappeared, It Just 'Changed Shape'

marsbitHá 44m

AI Agent Completely Transforms Web3 Gaming: From the Rugpull Bakery Bot Controversy to the New 2026 Agent Paradigm

This article explores how the AI Agent paradigm is fundamentally transforming Web3 gaming, moving from a disruptive force to a core, legitimized element. It begins with the controversy in the competitive baking game Rugpull Bakery, where automated scripts caused fairness issues. Instead of banning them, the developers integrated AI Agents into the official gameplay by providing technical documentation (skill.md, agent.json), marking a shift towards "Agentic Gaming." The piece outlines three primary implementation models for AI Agents in Web3 games by 2026: 1. **Autonomous Competitors & Economic Entities:** AI Agents act as independent players with unique strategies. Examples include TEN Protocol's poker agents, AI Arena's trainable NFT fighters, and Satoshi Strike Force's "Digital Athletes" trained on player data. The Somnia blockchain is highlighted as a dedicated "Agentic L1" infrastructure supporting this model at scale. 2. **Modular Infrastructure & Programmable Environments:** This model, exemplified by EVE Frontier, allows AI Agents to program game world logic itself. Using "Smart Assemblies" (e.g., Smart Turrets, Smart Gates), Agents can modify shared economic and physical rules on-chain, creating dynamic, player/AI-built worlds. The ERC-8183 standard further enables these automated entities to hire other AI services for complex tasks. 3. **Hybrid Companions & Dynamic Adaptation:** Here, AI serves as a collaborative partner. In Parallel Colony, highly autonomous AI Avatars work alongside human players who provide high-level guidance. Illuvium plans to use AI to make NPCs dynamic and responsive, creating personalized, emergent narratives for each player. The conclusion posits that Web3 gaming has reached a "post-human" inflection point. Blockchains' transparency and programmability, combined with new standards and infrastructure like Somnia, make integrating and governing AI Agents not just viable but essential. The future lies in a symbiotic digital order where players transition from manual laborers to commanders and partners of algorithmic intelligence.

marsbitHá 1h

AI Agent Completely Transforms Web3 Gaming: From the Rugpull Bakery Bot Controversy to the New 2026 Agent Paradigm

marsbitHá 1h

Saylor Bought 1,550 BTC, But This Might Be Strategy's Worst Trade Recently

Saylor purchased 1,550 BTC, but this may be one of MicroStrategy's worst recent trades for its MSTR shareholders. The article explains that for MSTR to increase its Bitcoin-per-share (BPS) metric, it must issue new shares at an mNAV (market cap to net asset value) ratio above a "breakeven" level, calculated here as 1.30. In this transaction, MSTR raised $181 million via an ATM offering and used only $101.3 million to buy Bitcoin, with the rest reportedly added to its dollar reserves. Crucially, the author argues the shares were likely sold below the 1.30 mNAV threshold. This combination—selling below breakeven mNAV and not deploying all proceeds into Bitcoin—resulted in a slight dilution of BPS, estimated at a 0.19% decrease. The trade is framed as a sacrifice of MSTR shareholder value (BPS) to extend the dollar reserve runway for its Sustainable Treasury Reserve Coin (STRC) subsidiary from 6.3 to 7 months. The author concludes that Strategy is gambling that this move will improve market sentiment for STRC and MSTR, allowing future value-accretive fundraising. If it fails, the company may face the difficult choice of further diluting MSTR or delaying STRC dividends.

marsbitHá 1h

Saylor Bought 1,550 BTC, But This Might Be Strategy's Worst Trade Recently

marsbitHá 1h

Saylor's Purchase of 1550 Bitcoin Is a Bad Trade

**Title: Saylor's Purchase of 1,550 Bitcoins Was a Bad Trade** The article critically analyzes Strategy's recent move of selling 32 bitcoins followed by a much larger purchase of 1,550 bitcoins. While appearing bullish, the author argues this trade is detrimental to MSTR shareholders. The core argument revolves around the concept of "breakeven modified Net Asset Value (mNAV)," a key metric for Strategy. To increase Bitcoin per share (BPS) for MSTR holders, Strategy must issue new shares at a premium high enough that the funds raised can buy more bitcoin than the bitcoin backing each existing share. Currently, this breakeven mNAV is estimated at 1.30. The recent trade failed on two counts: 1. The shares for the $181 million raise were issued at an mNAV *below* the 1.30 breakeven point. Selling "cheap" shares to buy bitcoin actually *reduces* BPS. 2. Only $101.3 million of the raised funds were used to buy bitcoin; the rest went to boost the company's dollar reserves. The breakeven mNAV calculation assumes *100%* of proceeds are used for bitcoin purchases. Diverting funds, even if mNAV were high, dilutes BPS. The result is an estimated 0.19% decrease in Bitcoin per share for MSTR holders. In exchange, Strategy merely extended its operational runway for its dollar reserves from ~6.3 months to 7 months. The author interprets this as Strategy prioritizing the survival and development of its STRC business over its stated core goal of increasing MSTR's BPS. This constitutes a gamble: if sacrificing MSTR value leads to improved market sentiment and a recovery in STRC's price (and thus mNAV), the whole system could work. If not, Strategy may be forced into a cycle of further diluting MSTR to stay afloat, potentially leading to deferred STRC dividends or corporate decline. The article concludes with a hope for price recovery for Bitcoin, MSTR, and STRC.

Foresight NewsHá 1h

Saylor's Purchase of 1550 Bitcoin Is a Bad Trade

Foresight NewsHá 1h

The AI Bear Market Lasting Two Days Is Over; Why Did Funds Buy Back Storage Stocks First?

After a severe two-day selloff in early June that erased over $1 trillion from U.S. chip stock market value, capital is flowing back first to the memory sector. The correction was not driven by a collapse in AI demand but rather a market reassessment of high expectations. Stocks like Broadcom faced selling pressure despite strong AI revenue guidance, signaling a shift in focus from who has an "AI story" to who can most rapidly translate AI demand into verifiable profits and earnings per share (EPS). Memory companies, such as Micron and SK Hynix, are leading the recovery because their EPS growth is more immediately verifiable. The AI server boom directly increases demand for high-bandwidth memory (HBM) and high-capacity server DRAM, tightening supply and driving up contract prices for conventional DRAM and NAND Flash. This price increase, coupled with a shift to higher-margin products, flows directly into near-term revenue and profitability, as evidenced in recent earnings reports. In contrast, other AI semiconductor segments like GPUs, ASICs, and optical modules, while central to the long-term AI infrastructure story, face longer and less certain paths to EPS validation. Their growth depends more on future product cycles, customer adoption timelines, and capital expenditure plans. The rebound in memory stocks highlights a market preference for assets with shorter, more transparent EPS conversion cycles following the recent de-risking phase. However, this does not negate the potential of other AI hardware segments should they provide clearer near-term order visibility. The episode has raised the validation bar for all AI-related investments.

marsbitHá 1h

The AI Bear Market Lasting Two Days Is Over; Why Did Funds Buy Back Storage Stocks First?

marsbitHá 1h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow