DOJ Charges Connecticut Man in $950,000 Crypto Investment Fraud

TheNewsCryptoPublicado a 2026-02-13Actualizado a 2026-02-13

Resumen

A 24-year-old Connecticut man, Elmin Redzepagic, has been charged with a 21-count indictment for allegedly orchestrating a crypto investment fraud scheme that resulted in approximately $950,000 in losses. According to the DOJ, Redzepagic promised investors substantial returns by trading cryptocurrency on their behalf. Instead of investing the funds, he transferred them to an offshore gambling platform, Stake.com. He faces multiple charges including wire fraud, international money laundering, and making false statements to the IRS. Redzepagic appeared in court, denied the charges, and was released on a $500,000 bond. This case emerges amid a broader increase in crypto-related fraud, with losses reaching $370.3 million in January 2026 alone.

A Connecticut man has been charged with a 21-count indictment for allegedly running a crypto fraud scheme that defrauded several investors and lost $950,000 of their funds. As the U.S. Attorney’s Office for the District of Connecticut announced on February 12.

According to the DOJ release, his name is Elmin Redzepagic, a 24-year-old who asked for funds from investors by promising to trade crypto on their behalf and generate substantial returns. Once he got victims, he told them they had earned a substantial profit but had to pay additional fees, which were gas fees to withdraw it, as the incident happened between approximately May 2021 and March 2025.

Further, he claimed he was part of a team that included an individual known as “The Chef,” who was described as the alleged ringleader. However, it remains unclear whether that ringleader is a separate individual who has not yet been identified.

But, as promised, he did not invest the funds in crypto; instead, he sent them to an offshore gambling platform named Stake.com, which led to a loss of $950,000 victims’ funds

Then, on January 20, 2026, he was charged with, “seven counts of wire fraud, an offense that carries a maximum term of imprisonment of 20 years on each count; 11 counts of international money laundering, an offense that carries a maximum term of imprisonment of 20 years on each count; and three counts of making a false statement to IRS Criminal Investigation agents, an offense that carries a maximum term of imprisonment of five years on each count,” as per the DOJ release.

Finally, he appeared in the federal court in Hartford on February 12, where he denied the charges and did not admit to the crime; however, the judge released him on a $500,000 bond.

Digital Asset Fraud Climbs

With that, according to blockchain security firm CertiK, crypto frauds and breaches totaled $370.3 million in January 2026, the biggest monthly figure in over a year. The figure indicates an almost fourfold rise year on year from January 2025 losses, mainly through phishing and social engineering scams.

While Connecticut case highlights the retail-focused crypto fraud, as scams and phishing attacks continue to account for a significant share of digital asset losses.

Highlighted Crypto News:
U.S. Bankers Urge OCC to Slow Crypto Trust Bank Charters

Preguntas relacionadas

QWhat is the total amount of funds that Elmin Redzepagic is accused of defrauding from investors?

A$950,000

QWhat specific charges did the DOJ bring against Elmin Redzepagic, and what are the maximum prison sentences for each?

AHe was charged with seven counts of wire fraud (max 20 years per count), eleven counts of international money laundering (max 20 years per count), and three counts of making a false statement to IRS agents (max 5 years per count).

QInstead of investing the funds in cryptocurrency as promised, what did Redzepagic do with the victims' money?

AHe sent the funds to an offshore gambling platform named Stake.com.

QAccording to the blockchain security firm CertiK, what was the total value of crypto fraud and breaches in January 2026?

A$370.3 million

QWhat was the outcome of Elmin Redzepagic's court appearance on February 12?

AHe pleaded not guilty to the charges and was released on a $500,000 bond.

Lecturas Relacionadas

How Likely is it for TradeXYZ to Go Solo from Hyperliquid?

The article analyzes the possibility of TradeXYZ, a dominant project on Hyperliquid's HIP-3 real-world asset (RWA) perpetual contracts market, splitting off to build its own independent trading platform. With TradeXYZ commanding over 90% of HIP-3 volume and over 35% of Hyperliquid's total open interest, its leverage and influence are significant. The primary motive for a split is seen as capturing the underlying protocol fees, of which TradeXYZ currently receives only half. However, several factors strongly discourage such a move. First, replicating Hyperliquid's high-performance infrastructure would be challenging and could degrade TradeXYZ's product quality. Second, Hyperliquid serves as a crucial distribution channel, with most users accessing TradeXYZ's liquidity through its frontend. Third, the close, trusting relationship between the founders of both projects makes a hostile "betrayal" unlikely. The conclusion is that a split would likely result in a lose-lose scenario. Hyperliquid would lose its main growth narrative and see its valuation impacted, while TradeXYZ would face immense technical hurdles, lose its primary user channel, and damage its reputation. Instead of a full separation, the more probable path is for TradeXYZ to negotiate better terms while deepening integration, focusing on enhancing its own brand and user ownership.

marsbitHace 20 min(s)

How Likely is it for TradeXYZ to Go Solo from Hyperliquid?

marsbitHace 20 min(s)

"Teletubbies" Robot Cleaning Service, $30/Hour, Pure·Manual·Intelligence

Anthropomorphic "Teletubby" robot offers cleaning services in San Francisco at $30/hour, but it's entirely remote-controlled. The robot, created by startup Tau Robotics, can perform household tasks like washing hands, mopping floors, and taking out trash. While the initial demo videos appear impressive and are notably shown at normal speed (unlike many sped-up robot demos), the company reveals the actions are performed via human teleoperation, not autonomous AI. Tau Robotics, founded in 2024, argues this "cheat" is a strategic way to bridge the current capability gap, ensure task completion, and collect real-world home data to eventually train autonomous systems. Their service features three robot models: Chelsea for kitchens/bathrooms, Elon for regular tidying with memory, and Tony for deep cleaning. Priced at $30 per hour, it's cheaper than average human cleaners in the US. The article discusses the broader challenge of deploying humanoid robots in homes, comparing Tau's approach to others like China's Ziliang and the US's 1X Neo, which also use teleoperation. A key reason for choosing a humanoid form is to make remote control more intuitive for human operators. The piece also notes the potential "emotional value" of having a humanoid servant. The service is currently invite-only in San Francisco.

marsbitHace 34 min(s)

"Teletubbies" Robot Cleaning Service, $30/Hour, Pure·Manual·Intelligence

marsbitHace 34 min(s)

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHace 1 hora(s)

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHace 1 hora(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHace 1 hora(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHace 1 hora(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHace 1 hora(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHace 1 hora(s)

Trading

Spot