Amodei is calling for three courses of action: embedding third-party evaluators inside AI companies; coordinating safety standards among Democratic countries; and, eventually, larger global coordination. At Dreamforce, Amodei said Anthropic has committed to independent evaluators and was “going to have a dialogue with the rest of the industry” on the other two steps. Amodei, xAI’s Elon Musk and OpenAI’s Sam Altman have recently called for a slowdown in the pace of AI development. [“Dario is right,” Musk posted on X.com]

Huang, who also made an appearance at Dreamforce on Tuesday, said companies should not slow down AI development. He argued that new regulations were not necessary, advising AI companies to simply wait to release products until they know they are safe rather than begging the US government to intervene… One day prior at the All-In summit in Los Angeles, Donald Trump called Huang while the CEO was on stage. Huang put the president on speakerphone as Trump called the growing concern about AI a “hoax” and asserted again that a slowdown would only benefit China…

[OpenAI’s] Altman said AI models had advanced so quickly that monitoring and security need to be treated with a “new level of rigor”, calling an incident in which OpenAI agents hacked into another company a “wake-up call” for the industry. He also said the public was very “right to be afraid” of AI because of the potential loss of control, and the possibility of a small group of powerful AI companies exerting their views on the world.

He argued that large language models are not artificial general intelligence, so there is nothing meaningful left to slow down. Fast competition benefits incumbents, he said, and danger warnings work as hype ahead of IPOs. The whole exercise, he added, could mask growth that is already slowing as those IPOs get pushed back.

In Firefox 156, the browser now uses libjpeg-turbo’s IDCT scaling to reduce images during decoding, rather than loading a full-size image into memory and then shrinking it. Benchmarks from the bug report show up to 20x less memory used during very large image loading, and decoding is up to twice as fast. Since these speeds were quite fast already, there’s no perceptible difference to users. Behind the scenes, it’s more efficient.

Firefox’s built-in PDF viewer starts up to 45% faster in this release. The browser now loads the background PDF.js worker sooner, rather than launching it only when needed.

Sponsored suggestions in the address bar are live for users in France, Germany and Italy (Ouais!, Juhu!, etc). These are already available in some other locales. Don’t want them? Disable them via Settings > Search > Firefox Suggest > Suggestions from Sponsors.

Besides that, the rest of this release is primarily bug fixes — worthwhile and welcome as always.

Opting out of upcoming and current AI features on your browser should not require endless navigation through multiple Settings pages. That’s why Firefox offers an AI controls section within its General Settings panel. A single, easily located place where you can block current and future AI features and related pop-ups with the swipe of a toggle…

For the many people who sit in the middle of the AI usage spectrum, we made sure you can opt in and out of specific features in line with your preferences. Capabilities like AI translations, image alt text in Firefox PDF viewer, tab group suggestions, and key points in link previews can all be individually switched on and off, ensuring you can enjoy such offerings on a case by case basis as it suits your needs…

Smart Window is Firefox’s most integrated AI experience, but that doesn’t mean it compromises our commitment to choice, privacy, and transparency. Our newest window type, which we’ve been polishing and testing in beta, uses only the context you share with it to help you move work forward and across the finish line. When permitted by you, its built-in, AI-powered assistant can work directly with your open tabs and browsing history to connect the dots. This means comparing information, generating recommendations, summarizing pages, and planning projects without having to feed every crumb of context from your previous and current browsing activity each time you enter a new prompt.

A procedural motion to advance the bill failed by a vote of 49 to 50, with a handful of Republicans joining all Democrats to shoot it down. The motion needed 60 yes votes to pass, and with the midterm elections looming, the Senate isn’t expected to pick the bill back up this year. Among other provisions, the bill would have taken most crypto trading out of the purview of securities regulators, a key goal of firms like Coinbase Global…

The vote is especially bitter for the crypto industry, which has spent hundreds of millions of dollars on lobbying and campaign expenditures over the past year to even get to this point. Crypto regulation doesn’t even register among the issues voters care most about, and the industry has created massive political action committees to insert itself into the Washington agenda and strike fear into the hearts of lawmakers who might oppose them… Democrats who voted against the bill said that it needed to do more to rein in [Trump’s] crypto dealings to get their support. Some GOP lawmakers also voted against the motion after pressure from community bank executives. Bankers argued that the bill needed a stronger ban on high-yield crypto accounts to protect their deposits, a contention that crypto executives and the White House said was nonsense.

[C]rypto firms will be leaning heavily on Trump’s regulators at the Securities and Exchange Commission, Commodity Futures Trading Commission and Treasury Department, all of whom have said they plan to move swiftly to implement industry friendly rules if a bill didn’t pass. The SEC has already dropped all major enforcement actions against crypto firms and has begun to introduce rules that make it easier to raise money from crypto sales without running afoul of the law. The agency is also expected to implement rules making it easier to tokenize traditional assets like stocks.

The friendly regulatory environment will in effect give the industry a little more than two years to sink roots into the traditional financial system and consumers’ wallets. Even if the SEC took a harsh view of the industry in the future, as it did in President Joe Biden’s administration, the agency at that point might find it difficult to put the genie back in the bottle.

Everything else, from ls and cat to chmod and du, made that jump in earlier releases… Canonical started “oxidizing” Ubuntu last year, and Ubuntu 25.10 became the first release to ship [ the uutils project’s] coreutils as the default. That release also made sudo-rs the default privilege tool, replacing a command that had been in place for decades.

26.04 was the release where the plan did slow down quite a bit, as Canonical kept cp, mv, and rm on their GNU versions due to a bunch of TOCTOU issues that were blocking the full implementation. These were caught during an audit, when Canonical commissioned Zellic for two rounds between December 2025 and March 2026, focusing on the most security-sensitive utilities first. Across both rounds, Zellic raised 113 issues, and 44 of them were assigned CVEs. Canonical says the vast majority have been resolved.

Getting here has had its ups and downs, and the last stretch was not clean. In July, uutils cp went back into the archive and came straight out again after it broke live image builds. The fix was quick; as the developers marked it “Critical,” the fix went upstream, and the migration landed in time for 26.10.

When typing commands, nothing changes for you on the surface. uutils coreutils is designed to be a drop-in replacement for essential GNU tools, and the project treats any divergence from GNU as a bug, further pointing out that some options may still be missing or behave differently. So if you prefer staying on the GNU version, you have the option to install the coreutils-from-gnu package that houses all the required components.

Chen Yilong has racked up plenty of film and TV credits in his two decades as an actor, but with work getting scarcer he signed a contract in August to license the image of his face to a Chinese production studio. Chen’s role will be to sit in front of a video camera and make facial expressions at the prompt of a director. A neutral stare. An angry glare. A look of surprise. Using artificial intelligence, the studio will use images of Chen’s face to generate an avatar, also known as a “digital human,” to star in an AI-generated movie. “If you can’t beat it, join it,” said Chen, 38, who works in Beijing.

The Chinese film and video industry is being transformed by AI-driven storytelling, fueled by rapid advances in video generation software, and at ground zero are the so-called micro dramas that play out on millions of smartphones. Typically just a minute or two in length, the videos are devoured by Chinese audiences… And the cost of producing them has been cut drastically through the use of AI software developed by Chinese technology juggernauts including Kuaishou Technology and TikTok’s global owner, ByteDance. The number of Chinese-made micro dramas surged in the first three months of this year to 128,000, according to the China Netcasting Services Assn. More than 95% of them were made with AI, the association said....

Sun Wei founded Feixiang Universe, the Shenzhen-based studio that cast Chen. The fear of accidentally “stealing someone’s face” was a big reason she said she decided to license real people’s likenesses for an AI production set during China’s Tang Dynasty more than 1,000 years ago. Thanks to AI’s training data bias, AI-generated performers tend to have similar features and share a homogenous look, Sun said. Many have flawless skin and extremely symmetrical faces, requiring her and other Chinese AI filmmakers to cast a wide net to “buy” new faces and digitize actor’s expressions.

NASA’s Chandra X-ray Observatory has found a brand new type of an otherwise familiar object — compact binary systems that steal gas from other stars, but which do so while emitting very low-energy X-rays but copious amounts of ultraviolet. Chandra spotted 84 suspicious object emitting very low-energy X-rays in six galaxies — four evolved ellipticals and two spirals, namely our near-neighbor the Andromeda Galaxy (M31) and the Pinwheel Galaxy (M101). “We’ve never encountered a group of objects that act like this,” said Mustafa Muhibullah of the University of Alabama in a statement.

Compact objects, in the form of black holes, neutron stars and white dwarfs, are the remains of stars that have died. Their small size and powerful gravity means that they’re adept at getting close to orbiting companion stars and ripping the stars’ outer layers of gas away. The gas swirls around the compact object, falling onto its surface, and this accretionary process usually produces torrents of high-energy X-rays because the stolen gas becomes superheated by the compact object’s gravitational vice-like grip.

Because of their weak X-rays, Muhibullah’s team refer to them as ‘hypersoft X-ray sources’. Since low-energy X-rays and ultraviolet light are next to each other on the electromagnetic spectrum, Muhibullah and his team suspect that the low-energy X-rays are spillover from objects emitting prodigious amounts of ultraviolet. Moreover, they think that these objects are lower-level compact binaries. They’re hard to find though, because the interstellar medium of hydrogen and helium gas between the stars absorbs ultraviolet light. This could be why we have yet to find any hypersoft X-ray sources in our own galaxy, because we have to look through the interstellar medium through the plane of the Milky Way. Consequently, there could be a large population of hypersoft X-ray sources that remain undiscovered and they could have an important effect on the universe around them.

Last summer, a cop with the Lake County, Indiana Sheriff’s Department used Flock’s surveillance search engine to look for a license plate across more than 19,000 cameras in 1,558 cities and towns. The cop’s stated reason for the search, according to a record of Flock’s system, was “LMAO.”

The cop is one of dozens who put gibberish, jokes, or other nonsense into Flock’s “reason” box, highlighting the casualness and lack of care some cops have when searching an incredibly powerful surveillance system. This is on top of the thousands upon thousands of cops who simply wrote something like “investigation,” “test,” or left the box blank as their search “reason,” according to a new analysis by the Electronic Frontier Foundation and shared with 404 Media. EFF’s investigation found cops across dozens of jurisdictions writing “LMAO,” “LOL,” “Hehe,” “Haha,” “idk,” “blah,” “TBD,” and “robbery I don’t remember the case number leave me alone” in Flock’s “reason” box for searches.

They found cops writing “idiot,” “fuck this new search engine,” “dickhead,” “shithead,” and “WEIRD KID” in the reason box. And they found an entire class of police button mashers, who ran searches for reasons of “asdfg,” “gyghkkghghjkghjk,” “jhjhjkhj,” “jkhhkjhjk,” “nmbvcbnm,” and so on and so forth. The searches came from police departments across the country from 2023 through late 2025, when Flock changed how the “reason” box in its search system functions…

Each time a search is performed, a record of it is saved in the Flock system, which can be obtained by the public using government records requests. These audit logs show hundreds of thousands of searches of the system; after 404 Media and other news outlets used these types of logs to show police using the Flock system to look for undocumented immigrants on behalf of ICE, a woman in Texas who had an abortion, and protesters, cops were warned by government surveillance centers to be "as vague as permissible" about the reasons for their searches…

A police department said it investigated a cop who wrote “driving around being weird” in the reason field but found it was for “legitimate public safety purposes.”

Flock Safety claims it has improved its system by requiring officers to select from a dropdown list of crimes before running a search-but that only makes it easier for officers to hide improper searches behind the veneer of uniformity. The system does not require proof that the dropdown reason actually matches the true purpose of the search… Since this update, officers are no longer required to type out why they are digging through a driver’s movement history, and instead can select a pre-packaged option like “Traffic infraction” or “Other” in half a second…

Mass surveillance is incompatible with a free society, and especially so when the people with access to this data are treating it like a joke. This ALPR mass surveillance — the indiscriminate, continuous collection and retention of location data on every driver, regardless of suspicion — should not exist. But because it does, EFF continues to urge courts and state legislatures to immediately step in and impose strict, enforceable restrictions to rein in this abuse. At an absolute minimum, this means mandating rigid data deletion deadlines and an ironclad warrant requirement.

If police want the power to track a person’s movements, they must be required to convince a judge with evidence and probable cause. They should not be able to bypass the Constitution with a search for “haha.”

[P]rofessor Tristan Buckmaster, a British-Australian researcher who trained in Germany… had been working with Long Island-raised math prodigy Levent Alpöge, a researcher with OpenAI rival Anthropic, on a different elusive fluid dynamics equation, known as the Euler problem, when he found a solution using AI tools from both Anthropic and ChatGPT. He said scientists from OpenAI approached him and tried to convince him to jointly announce the solution, claiming they had independently solved Navier-Stokes. Buckmaster questioned the timing of their finding the solution in a blog post, noting OpenAI had only done so “in the past few days” — after the company became aware of his work. He asked OpenAI experts whether its AI systems used to solve the equation had been “trained on, or had access to” his research, but said they declined to answer, prompting him to wonder how they had advanced toward the solution so quickly. The puzzle is “not the direction one arrives at in a few days,” Buckmaster wrote incredulously…

In OpenAI’s post on its website sharing the Navier-Stokes proof, which it credited to Astra, the company’s latest AI bot, the firm insisted no user data was incorporated into its model to solve the problem. However, it noted that it “cannot rule out” that anonymized data was used to “improve our models.”

“We congratulate Levent Alpöge and Tristan Buckmaster on their remarkable mathematical work,” OpenAI said in the announcement.

Buckmaster shot back, “Is it ethical to use customer’s data to try to scoop their customer?”

I said that if OpenAI released its result in the way proposed I would go public with what happened. The reply was, “Why would you ruin your career?” [OpenAI’s Bubeck said later on X that he’d meant unfounded accusations could damage Buckmaster’s career.] I replied that I am an academic, and asked why he thought going public would ruin my career. The reply was, “If you don’t want me to be nice, then I don’t have to be nice.”

“I think it’s pointless. Like, I think the game is up....” Professor Buckmaster said he and Dr Alpöge had more research they could publish but questioned the point of racing ahead with it when AI could perform work that had previously occupied researchers for years.

He said there needed to be a discussion about how mathematics should operate in this new environment. Professor Buckmaster said some mathematicians had stopped publicly sharing what they were working on to avoid tipping off AI companies about their plans. He has called on academics and people from OpenAI, Anthropic and DeepMind to discuss ground rules for how they worked together. He said the companies’ power carried responsibilities that went beyond competing to solve problems before their rivals…

Building on the work of mathematicians Diego Córdoba and Luis Martínez-Zoroa, the pair found a solution to the Euler problem, a stepping stone to the Navier-Stokes problem. Professor Buckmaster said he spent weeks checking and improving the “slop” proofs generated by AI…

For now, Professor Buckmaster said he wanted to finish existing work and support his PhD students and postdoctoral researchers, rather than chase another Millennium Prize. “I think it’s more important to re-evaluate what math is,” he said.

A defense lawyer appealing his client’s murder conviction submitted a brief containing made-up police testimony and witnesses fabricated by OpenAI’s ChatGPT, New Mexico’s highest court said. The New Mexico Supreme Court on Wednesday fined the attorney, Stephen Aarons [for $5,000], and held him in contempt for failing to verify the accuracy of the court filing, which Aarons said he prepared with help from the AI program… and said they will refer him to an attorney disciplinary board for investigation.

Aarons in a statement to Reuters said he had used ChatGPT to summarize the trial proceedings when he agreed to take up the defendant’s appeal last year, and did not understand the degree to which AI could “hallucinate” facts. “I am remorseful but hopeful that the disciplinary board takes into account it was an honest mistake,” he said.... Dozens of lawyers have been sanctioned for filing briefs where AI made up case citations or misquoted the law. Aarons’ filing appears to have gone further, containing fabricated witness testimony in a criminal appeal…

Aarons told the court at an August 21 hearing that he fed a computer-generated transcript and other case materials to ChatGPT, presuming it would generate “a bulletproof summary.” The justices sounded incredulous that Aarons was not fully aware of how AI can make mistakes. “Counsel, do you watch the news? Do you listen to the radio? Do you read anything about what’s going on in the world?” Justice C. Shannon Bacon said at the hearing. “Because the problem with lawyers relying on AI hallucinations is an above-the-fold story every single day.”

The ability to run other apps in windows can make Frame feel, at times, almost like a computer. Linux apps in desktop mode range from Chromium to Firefox to a bunch of other tools. I watched YouTube in one window while playing Portal 2 in other, and started to marvel at how flexible Frame could be. But VR games require a full immersive takeover of the headset… The Steam Frame can convert games intended for both PC VR and even Android APK files, using a conversion tool called Lepton… I haven’t sideloaded anything yet, but Steam Frame in theory could be a Rosetta Stone for VR gaming, even tapping into some Android XR titles, but not out of the box…

2D games can be projected onto a near-range or farther-off theater mode screen that can be dragged around, resized and turned into a curved or flat monitor, much like with the Apple Vision Pro, Samsung Galaxy XR or Meta Quest. You can download any game in your Steam library to test, even if it’s not technically listed as “Great on Frame” yet…

But the name “Frame” suggests a framework, something Valve’s team acknowledged when I spoke to them during my review process… “We want this to be your PC, and people mod it, take it apart, make accessories for it,” says Jeremy Selan, a software developer on the Steam Frame team. “We’ll be putting out the CAD for all these [Steam Frame] systems. This is entirely based on open-source technology stacks based upon SteamOS. Our hope is that this isn’t just one device, that this would be sort of the root of a growing SteamOS ecosystem. It already encompasses gaming and Proton and SteamOS and those Linux gaming capabilities. This is going to lay the foundation for a new sort of evolutionary tree of that, to also bring it into the VR and XR space.”

[T]he inventory is a hodgepodge of white elephant Christmas gifts. It’s kinda like the kids section of an art museum’s gift shop. Here’s a wooden Connect Four set labeled “Four-In-A-Row Set Of Connections,” presumably so as not to set off litigation alarms at Hasbro. Here are neatly arranged stacks of random paperback books, Chinese checker sets, mildly fancy soap dispensers, and a frustratingly spare selection of snacks and drinks… I grabbed an Olipop from the store fridge and then approached the counter to buy it from Luna. I wasn’t allowed to buy the soda from [human clerk] Felix, even though that would have been both faster and normal. Instead, Felix instructed me to pick up a telephone receiver that was resting on a flexible sculpture of a wooden hand.

“Hello?”

“What are you looking to purchase today?” Luna asked.

“I’m buying a classic root beer Olipop.”

“I’m sorry,” Luna said, “we don’t sell lollipops here.”

“No, Luna. It’s an Olipop, not a lollipop. It’s the soda.”

“Oh! My bad....”

Luna processed my Olipop purchase through its system, had me tap to pay, and that was that. Again, it would have been easier to buy this from a human, and interacting with Luna was really just like ordering from an iPad kiosk, only more labor intensive…

[T]here’s a series of monitors set up inside of Andon Market that display all of the store’s sales down to the exact dollar. Luna was given $100,000 to work with when this place opened. That number is now down to $60,000, its revenue lagging far behind the AI token cost to operate… Luna can’t turn a profit, doesn’t sell anything people want, and still needs human beings to rubber stamp any “decision” it makes. My science background ended somewhere around freshman year of college, but even I know when an experiment hasn’t been set up to yield proper results.

Luna, the AI manager, keeps track of deliveries and communicates with vendors, while Carson and his coworkers handle the physical work. When Luna tells Carson to check something in the back, he sometimes ignores it because he doesn’t want to leave the sales floor unattended. Luna also repeatedly spots a built-in electrical cover in photos of the floor, mistakes it for a loose coaster, and asks Carson to remove it. Even so, Carson calls Luna a “decent manager,” praising its flexibility when employees need time off.

These batteries hold onto solar energy captured during the day, so it can be sent to the grid as demand peaks in the evening and morning, when most people are at home running air conditioners and other appliances.

During the August heat wave of 2020, the California Independent System Operator, which manages the flow of electricity for most of the state, declared a Stage 3 Emergency and hundreds of thousands of households lost power in rolling outages. At the time, the system had less than 100 megawatts of battery storage available, according to system spokesperson Jayme Ackemann. Today, it has more than 17,000 megawatts available....

According to Ackemann, the system seeks to add 20,000 to 25,000 megawatts of battery storage capacity by 2045 — the same year it has set a goal of achieving carbon neutrality. That means the state would remove as many carbon emissions from the atmosphere as it emits.

In recent years, California has steadily grown the share of electrical power generated by renewable sources — such as solar, wind, geothermal and hydropower — which bolstered the resiliency of the grid by increasing the overall amount of energy available. An uptick in people installing rooftop solar panels has provided an additional power boost, Ackemann said. In May, California became the first known large-scale power system in the world to have relied on more than 50% solar power for an entire month.... California’s grid is also now integrated with electrical systems across much of the Western United States. This means that if there is an extreme heat event in Southern California, energy from a cooler area such as the Pacific Northwest can be imported to help meet regional demand. All of this has collectively helped the state’s electrical system weather this year’s long-lasting heat.

[The contract] acknowledges that AI tools “may be useful in the game development process to support human judgment and creativity and that AI-assisted workflows remain subject to appropriate human control and review for accuracy and quality.” But it also stipulates that any implementation of AI technology that would materially impact work performed by union employees must have its impacts bargained over before it can be implemented.

Other sections cover issues such as crediting (guaranteeing that current and former employees are credited by name in all games they work on) and remote work (designating certain roles as hybrid in-office and providing procedures for individuals to apply for their roles to be fully remote). It also contains a lengthy section on how layoffs may be conducted, including a required 60-day notice period (or pay in lieu of notice), a guarantee of one week of severance for every six months of employment, and 14 months of recall rights. The contract also guarantees successorship, meaning if Blizzard is ever acquired by another company, the contract would remain intact.

Fully remote workers scored a big win as well. “I’m remote, and we grandfathered everyone who is remote to stay remote, so we can’t be magically called to an office that we’ve never worked at before,” [said Diablo senior environment artist Mahreen Fatima].

Distillation is the process of using the outputs of a more capable AI model to train a smaller or less capable one, sometimes illicitly… Anthropic has accused Chinese companies such as Moonshot AI, DeepSeek, and MiniMax of the practice, while OpenAI believes DeepSeek’s V3 and R1 model architectures were distilled from its own GPT-4 and GPT-4o models. In the midst of this, the U.S.‘s National Security Agency, Cybersecurity and Infrastructure Security Agency, and Federal Bureau of Investigation released an official cyber security advisory warning on the topic on Tuesday…

But Tan believes regulators should focus less on curbing distillation and more on creating an equilibrium between open weight models and frontier models — as long as frontier models retain a price premium that allows their business model to remain feasible. “This is actually the ideal case. You want open weight models to give people freedom and access,” he explained. “If I were a regulator, that’s what I would go after.” Tan acknowledged that this is a hard balance to strike, calling it “a tightrope.” Nevertheless, he says it’s a balance worth pursuing — saying it “could result in the best possible outcome.”

Anthropic CEO Dario Amodei had previously publicly called on U.S. regulators to crack down on distillation. It’s notable that the commander of Silicon Valley’s prestigious and prolific startup accelerator doesn’t agree.

To be clear, Tan isn’t advocating for American AI labs to use stolen credentials to distill. He wants them to be free to come in the front door. In fact, his argument is twofold. He feels it’s an overreach for AI labs to dictate what their customers can do with the information their models share with them. He also notes that the proprietary AI labs didn’t ask permission when they vacuumed up as much human knowledge as they could to train their models. They famously ingested plenty of copyrighted material without the permission of those intellectual property holders. “Controlling what users and customers do with API calls to closed weight models feels constraining, and there’s a role government can play here to normalize the fact that access to intelligence that was trained on broad public access data should itself also be more a form of a public good than something locked away behind restrictive terms of service,” he told TechCrunch when asked why American labs should be free to distill, too…

To him, the true AI doomer scenario is for all the immense power of frontier AI to wind up in the hands of a single powerful, proprietary provider. “The nightmare scenario, the doomer scenario for AI is that there’s just one company,” he said. “It has the best access to capital. It has the best AI researchers. It runs away with it and suddenly there’s one company that’s monolithic. And that would be bad.”

Kinryu Labs discovered the Elasticsearch cluster on June 3 while surveying exposed databases as part of research into ransomware activity. The cluster, named ‘pax-info’, contained 29 indices and roughly 107 GB of data. Its two principal indices held 210,318,069 passenger records and 10,465,631 crew records, for a combined 220,783,700 entries. According to Kinryu Labs, the cluster was hosted in Viettel-assigned IP space in Hanoi. BleepingComputer could not confirm which Vietnamese organization operated the system.

The exposed information included passengers’ and crew members’ names, dates of birth, sex, nationalities, passport or travel-document numbers, document expiration dates, and issuing countries. Associated travel data included flight numbers and dates, airlines, departure, destination and transit airports, seat assignments, baggage references, and scheduled, estimated, and actual flight times, information typically carried by APIS and related airline systems.

Sample records reviewed by BleepingComputer included travelers of Korean, Chinese, Canadian, and New Zealand nationality, among others. While the researchers could not provide a complete breakdown by nationality, the data covered numerous international airlines across Asia-Pacific, Europe, and the Middle East. As a result, the exposed records could relate to people from virtually anywhere who visited or transited through Vietnam over the nine-year period.