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28.8 Million Queries: The AI Heist That Tripped No Alarms
Authored by Joseph Hoefer via RealClearDefense,
When we picture intellectual property theft, we picture a break-in. A hacker slips past the firewall, copies the source code, and disappears. So, when an American AI company tells Congress that China just pulled off the largest extraction campaign it's ever recorded, the natural assumption is that someone cracked the vault.
Nobody broke in. And that's exactly what makes this threat so difficult for Washington to address.
Last week, Anthropic told the Senate Banking Committee that operators affiliated with the Chinese conglomerate Alibaba ran roughly 28.8 million queries with its Claude models through nearly 25,000 fraudulent accounts between April and June. According to the company, the goal was not to steal the model. It was to harvest its answers, then use those answers to train a competing Chinese system at a fraction of the cost.
This technique is called distillation, and not all of it is sinister. Training a smaller model on the outputs of a larger one is a routine and legitimate practice when a company does it with its own systems. What Anthropic alleges is something else: unauthorized extraction from a competitor's proprietary service, carried out at industrial scale through fake accounts that violated its terms of use. The line between ordinary engineering and a national-security problem runs right through that word "unauthorized."
The unsettling part is how ordinary the attack looks from the outside. The operators signed up, gained access, and asked questions, millions of them, aimed at the model's most valuable skills: writing software and reasoning through complex tasks step by step. The model did precisely what it was built to do. No alarm tripped, because from the system's perspective, nothing went wrong. A determined competitor simply walked through the front door, at enormous scale, to approximate years of American research by learning from the model's outputs.
That is a genuinely new kind of problem, and it scrambles the usual playbook.
The instinct in Washington has been to treat Chinese AI gains as a hardware story. Keep advanced chips out of Beijing's hands, the thinking goes, and you slow its progress. That instinct isn't wrong. Compute is a real chokepoint... China keeps trying to smuggle chips and route around the controls, and tightening those rules is sound policy.
But chip controls were designed to stop someone from building a powerful model. They do nothing to stop someone from quietly copying the behavior of a model that already exists.
You can wall off the foundry and leave the storefront wide open. That is the gap distillation walks through, and it is why a hardware-only strategy, however necessary, cannot be the whole answer.
The stakes are not only strategic. Every successful extraction campaign compresses years of research and billions of dollars of private investment into millions of automated queries, undermining the incentives that made American frontier AI leadership possible in the first place. This is what intellectual property theft looks like in the age of AI: not stolen code, but a copied teacher. Alibaba is simply the first vivid example, and it won't be the last.
The encouraging news is that the government has already named the problem. In April, the White House science office issued a memo warning that foreign entities, mostly based in China, are running "industrial-scale campaigns to distill U.S. frontier AI systems," and it committed the administration to better information sharing and defensive coordination with industry. The House Foreign Affairs Committee advanced a bill that would track these extraction attempts and authorize sanctions against the companies behind them. And in response to the Alibaba disclosure, Sens. Bill Hagerty (R-Tenn.) and Andy Kim (D-N.J.) are pushing an amendment to this year's defense bill directing the Commerce Department to penalize Chinese firms caught doing it.
That bipartisan momentum is the right reflex. To work, the response must match the attack, and that means treating model extraction like any other strategic economic attack rather than a routine business dispute.
Two priorities follow. First, detection is a shared problem, yet companies fight it alone. The fake accounts and evasion patterns show up across multiple American labs, but legal uncertainty discourages competitors from comparing notes. Congress can give them clear permission to share threat signals with one another and with the government, the way banks already share intelligence on fraud. Second, deterrence must reach the storefront, not just the foundry. If a Chinese lab can lose access to American chips for smuggling them, it should face comparable consequences for systematically abusing American AI services to copy them.
America has spent years debating how to keep advanced AI out of China's hands. The harder question may be how to keep China's AI companies from quietly learning everything they can from the models we place online for the world to use. Last week's disclosure put a number on it: 28.8 million questions, asked through the front door. Washington has finally started looking at the right entry point. Now it needs to figure out how to lock it.
Joseph Hoefer is a principal and chief AI officer at Monument Advocacy, where he leads the firm's AI policy practice.
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Where It Costs The Most To Own A Car In America
Buying a car is only the beginning. Every year afterward, drivers face a steady stream of expenses—from insurance and fuel to repairs and taxes—that can add up to thousands of dollars.
Using data from LendingTree, Visual Capitalist's Dorothy Neufeld created this map comparing average annual car ownership costs across every U.S. state and Washington D.C., excluding car payments, revealing where those ongoing expenses place the biggest burden on drivers.
The Annual Car Ownership Costs by StateHere’s how annual ownership costs compare across the country.
Rank State or District Average Annual Cost of Car Ownership2025 1 Nevada $6,119 2 Florida $5,682 3 Louisiana $5,663 4 Michigan $5,350 5 Colorado $5,151 6 Alabama $5,099 7 Arizona $5,060 8 Oklahoma $5,021 9 Georgia $5,014 10 Utah $4,977 11 Arkansas $4,947 12 California $4,900 13 Kentucky $4,862 14 Wyoming $4,859 15 New Mexico $4,855 16 Missouri $4,819 17 Mississippi $4,792 18 Indiana $4,787 19 Rhode Island $4,711 20 Texas $4,636 21 Montana $4,548 22 Kansas $4,542 23 North Dakota $4,540 24 Delaware $4,538 25 Tennessee $4,532 26 Illinois $4,521 27 South Dakota $4,493 28 Minnesota $4,435 29 Connecticut $4,419 30 New Jersey $4,413 31 Oregon $4,340 32 Nebraska $4,307 33 Washington $4,306 34 Maryland $4,302 35 New York $4,253 36 Pennsylvania $4,181 37 South Carolina $4,176 38 North Carolina $4,157 39 Iowa $4,146 40 Hawaii $4,114 41 West Virginia $4,102 42 Virginia $4,061 43 Wisconsin $3,963 44 District of Columbia $3,925 45 Massachusetts $3,834 46 Vermont $3,829 47 Idaho $3,781 48 Alaska $3,682 49 Ohio $3,544 50 Maine $3,543 51 New Hampshire $3,030 -- 🇺🇸 U.S. Average $4,507
Costs do not include car payments. Sales taxes combine state and local taxes, annualized over 6.5 years based on an average used car price of $27,177.
Annual ownership costs range from roughly $3,000 in New Hampshire to more than $6,100 in Nevada, meaning two drivers with the same vehicle could face a difference of more than $3,000 every year based solely on where they live.
Seven of the 15 most expensive states are in the South, largely because of elevated insurance premiums. Florida and Louisiana rank near the top for insurance costs, while California stands out for high fuel prices and repair expenses rather than insurance alone.
Why Some States Cost Thousands More Than OthersThe price of a vehicle may be similar nationwide, but the cost of keeping it on the road can change significantly by state.
Insurance is often the biggest source of variation, ranging from over $3,400 annually in Nevada to around $1,200 in Maine. Premiums reflect everything from accident frequency and vehicle theft to repair costs, weather-related claims, and state insurance regulations. In 13 states, insurance alone accounts for at least half of total ownership costs.
Fuel prices, registration fees, and sales taxes add another layer. Drivers in states with longer average commutes or higher gasoline prices typically spend more each year, while repair costs can also differ depending on labor rates and vehicle demand.
Driving Is One of America’s Biggest Household ExpensesTransportation is one of the largest household expenses after housing, making recurring vehicle costs an important part of overall affordability. While consumers often focus on a car’s purchase price or monthly payment, insurance, fuel, repairs, and taxes can add thousands of dollars each year, and those costs depend heavily on where they live.
That burden is especially significant in communities where driving is a necessity rather than a choice. Beyond commuting, vehicles are essential for work, school, childcare, and everyday errands, making recurring ownership costs difficult to avoid.
As insurance premiums, repair bills, and maintenance costs continue to rise, the cost of keeping a car on the road remains a core part of the broader cost-of-living conversation alongside housing, healthcare, and utilities.
To learn more about this topic, check out this graphic on America’s slowest depreciating cars.
Tyler Durden Mon, 07/13/2026 - 18:00