TRM Labs Reports $35B Lost to Crypto Scams Worldwide in 2025

TheNewsCryptoОпубліковано о 2026-03-05Востаннє оновлено о 2026-03-05

Анотація

TRM Labs reports that crypto-enabled fraud resulted in an estimated $35 billion in global losses in 2025, with over $100 million affecting New Yorkers. The actual figure may exceed $200 billion due to underreporting. Criminals use advanced tactics like social engineering and AI, moving funds rapidly across wallets and chains, making recovery difficult. The report emphasizes the need for better law enforcement training, advanced blockchain and AI tools, and modernized regulations like the RIP OFF Act to combat increasingly sophisticated crypto crime networks.

Blockchain intelligence firm TRM Labs warns that crypto‐enabled fraud and illicit flows increased in 2025, with an estimated $35 billion in crypto moving into scam schemes globally and over $100 million tied to fraud affecting just New Yorkers

According to the 2026 TRM labs reports released on March 4, these mentioned figures probably understate the true scale of losses, “When underreporting is factored in, total annual losses likely exceed USD 200 billion worldwide.

While, Global Head of Policy at TRM Labs, Ari Redbord said, “Where we work with local, state and federal law enforcement, regulators, financial institutions, and national security agencies in New York and around the globe to detect, investigate, and disrupt illicit activity in the digital asset ecosystem and beyond.”

The report points out how advanced crypto crime networks are, as they increasingly use social engineering and AI techniques to target victims, also that scam funds are frequently transferred across several crypto wallets and chains in a matter of 24 to 48 hours, making recovery exceedingly challenging.

Monitoring Illicit Crypto Activity

Crypto scams can happen across countries, but New York City police action begins where the victim reports it. They bring various proofs such as transaction copy, screenshots, chat messages, QR codes and other.

According to the report, tracking the flow of stolen money requires the use of certain digital identifiers, such as wallet addresses, transaction hashes, and domain names. If these critical identifiers are not accurately recorded, if investigators are not trained to recognize, the likelihood of stopping the fraud decreases

Equipping Law Enforcement

The report suggests, “We must accelerate education and place advanced investigative tools in the hands of our frontline officers and prosecutors at the same pace that bad actors are scaling their operations. As criminal networks grow faster and more technologically sophisticated, our training, capabilities, and deployment of resources must move just as quickly — if not faster.”

Additionally, Blockchain and AI tools are necessary for the NYPD and district attorney offices to track cross-chain activity, identify wallets, facilitators, and laundering networks, and trace stolen cryptocurrency. Without these tools, law enforcement only sees part of the bigger picture in crypto crime.

Also, the report mentioned, The RIP OFF Act (Restoring Integrity and Preventing Outright Fraud in Financial Systems Act), which is a New York State law that modernizes fraud statutes to reflect how large‐scale, organized fraud schemes operate. It also explicitly covers virtual currencies and strengthens rules against hiding or evading reporting requirements.

Пов'язані питання

QAccording to TRM Labs, what was the estimated global loss to crypto scams in 2025?

AAn estimated $35 billion was lost to crypto scams globally in 2025.

QWhat does the report say is the likely true scale of worldwide annual losses when underreporting is factored in?

AWhen underreporting is factored in, the total annual losses likely exceed $200 billion worldwide.

QWhat two modern techniques do advanced crypto crime networks increasingly use to target victims, as mentioned in the report?

AAdvanced crypto crime networks increasingly use social engineering and AI techniques to target victims.

QWhat specific New York State law is mentioned in the report that modernizes fraud statutes to cover virtual currencies?

AThe RIP OFF Act (Restoring Integrity and Preventing Outright Fraud in Financial Systems Act) is the New York State law mentioned.

QWhat does the report identify as a major challenge in recovering stolen crypto funds?

AA major challenge is that scam funds are frequently transferred across several crypto wallets and chains within 24 to 48 hours, making recovery exceedingly difficult.

Пов'язані матеріали

"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.

marsbit11 хв тому

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

marsbit11 хв тому

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.

marsbit54 хв тому

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

marsbit54 хв тому

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.

marsbit59 хв тому

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

marsbit59 хв тому

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.

marsbit59 хв тому

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

marsbit59 хв тому

Coldcard exploit sparks Bitcoin flight, ‘bullish’ crypto consolidation: Hodler’s Digest, August 2

A Coldcard hardware wallet exploit led to estimated losses of 1,367 BTC ($88.6 million), causing a spike in small Bitcoin transfers as users moved funds to centralized exchanges and other custody methods. In U.S. politics, the Clarity Act faces hurdles with time running out for a Senate vote, amid debates over ethics rules and crypto regulation. Major crypto firms like Coinbase reported disappointing Q2 earnings, while an analyst notes the industry is entering a significant consolidation phase, with revenue concentrating in a few dominant protocols like Hyperliquid and Pump.fun. Bitcoin's price decline continued, though some analysts suggest the market may have bottomed. Other news includes Telegram's legal troubles in Russia and Australia, layoffs at Pump.fun ahead of token distributions, and a White House staffer accused of insider betting leaving his post.

cointelegraph1 год тому

Coldcard exploit sparks Bitcoin flight, ‘bullish’ crypto consolidation: Hodler’s Digest, August 2

cointelegraph1 год тому

Торгівля

Спот