System Admin Stuff

Saturday, 22 August 2026

Cloverleaf deal is latest example of Nvidia using its war chest to patch cracks in the AI bubble

Nvidia has made its fortune on the AI boom, but the company has a problem. It faces a growing number of roadblocks which, if left unchecked, could pop the bubble. Thus, the AI arms dealer has been forced to play a game of Whac-a-Mole, shoring up the foundations of its empire by investing its spoils into ensuring its customers don’t stop buying. The latest example of this came Friday, when Nvidia announced it’d become a minority investor in Cloverleaf. Founded in 2024, Cloverleaf specializes in laying the literal foundations – by which we mean the land and power – necessary to build bit barns so they can be leased by the cloud providers and model devs that actually pay the bills for Nvidia’s hardware. Nvidia can only sell as many GPUs as there are datacenters to put them, and those datacenters can only be deployed where there’s adequate power to support them. And since its latest round of GPUs can’t just be dropped into any old bit barn, Nvidia is going to need a lot more datacenter capacity, and by extension a lot more power. A new breed of datacenter Up until 2024, the majority of Nvidia’s systems were air-cooled. Supercomputers, like those built by Cray and Eviden, were the exception to the rule. Unless you were deploying tens of thousands of GPUs, its accelerators could be deployed just about anywhere with minimal modification to the facility. That began to change with Nvidia’s Blackwell generation. You could still get air-cooled systems from Nvidia and its partners, and it certainly sold a lot of eight-way HGX B200 boxes, but deploying its most powerful NVL72 systems required liquid cooling that not every facility was capable of supplying. Liquid-cooled facilities are harder to build than their air-cooled counterparts. Liquid-cooled racks tend to be more compute dense, and therefore heavier and power hungry to operate. That means in addition to larger UPS backups and beefier PDUs, these facilities now need a bunch of coolant distribution units (CDUs) to pump coolant around — about one for every one to three megawatts of compute capacity. Datacenters must be designed to support all this extra weight, and the problem is only going to get thornier as Nvidia transitions from roughly 250kW to 600kW racks starting next year. With Nvidia’s Rubin generation of GPUs, air-cooled GPUs may as well be a thing of the past, at least in the HGX and NVL-style form factors that power the majority of AI training and inference deployments today. For the first time, Nvidia is offering the chips only in liquid-cooled varieties. So, to sell its next-generation GPUs, Nvidia not only needs its customers to have adequate capacity, but also needs those facilities to offer the right mix of power and cooling. Right sizing for deployment It’s well established that Nvidia prioritizes customers with datacenters ready to fill. However, many of the GPU-slinger's biggest customers don’t actually own datacenters, but instead lease capacity from others. For example, Crusoe built OpenAI’s Stargate facility in Abilene, Texas, and Oracle runs it. Altman and crew are simply supplying the demand. So, Nvidia has invested in model devs and neocloud partners by helping them get financing or even investing directly in their businesses. Nvidia’s investments in OpenAI, CoreWeave, and Nebius are just a few examples. That works so long as the bit barns available for rent are the right size and shape for the hardware. But, as we noted earlier, many existing facilities aren’t. To further reduce friction and make it easier for its customers to find space to deploy its kit, Nvidia introduced its DSX platform last fall and officially launched it this spring. In a nutshell, DSX is a set of blueprints outlining exactly how much power, cooling infrastructure, and space are needed to support a given amount of compute. It also provides tools to optimize that compute to minimize wasted capacity. The power problem But even designing to a spec won’t do bit barn builders any good if they can’t get their hands on enough power. The proliferation of AI datacenters has begun to strain grid capacity, forcing many new ones to employ behind-the-meter power generation. For example, Nebius has begun using Bloom Energy's natural gas fuel cells to power its datacenters, rather than relying entirely on existing grid infrastructure. Nvidia’s investment in Cloverleaf is the latest example of how the GPU slinger is using the circular AI economy to its advantage. The terms of the deal haven’t been disclosed, but the benefits are obvious: Cloverleaf gets an influx of cash, while Nvidia gets greater control over the build process. As part of the deal, Cloverleaf is also embracing Nvidia’s DSX spec. In theory, this should enable bit barn builders to drop a DSX-compliant datacenter on a Cloverleaf-supplied site and be serving customers without delay. For Cloverleaf, Nvidia’s spec includes a wealth of power-related capabilities, including DSX Flex, which allows datacenters to scale back their workloads in response to grid conditions. So if grid demand spikes during a heat wave because everyone’s AC just kicked on, datacenters know it’s probably not a good idea to kick off another training run. The tech can also be used to offload demand onto onsite power generation or storage systems, like batteries — all things a company tasked with supplying powered sites for datacenters might be interested in. The deal is the latest example of how Nvidia is using its war chest to shore up cracks in the broader AI ecosystem before they become a problem. We wrote a few weeks ago about how the company was helping AI infrastructure startups secure financing in exchange for a share of the revenues, but it's now clear Nvidia is attacking potential roadblocks from every angle. ®

source https://www.theregister.com/systems/2026/08/22/cloverleaf-deal-is-latest-example-of-nvidia-using-its-war-chest-to-patch-cracks-in-the-ai-bubble/5291369

Salesforce partners not seeing meaningful revenue from Agentforce AI platform, report says

Salesforce partners say they have yet to see any meaningful revenue from Agentforce, two years after the CRM giant launched its AI platform, promising spectacular growth. That's according to a recent report from TD Cowen, which surveyed Salesforce partners and found muted interest in the technology, designed to let users build AI agents for customer interactions. The survey of partners in the US, Europe, and Asia found growing customer interest in Agentforce, but no revenue yet. Asked about interest in Agentforce AI Agents, 11 percent of respondents said they had not seen much immediate interest, while 56 percent said they expected to see interest but needed time for initiatives to mature. A third of partners said there was strong interest in Agentforce as they were starting to see buying and trial activity. However, none were seeing Agentforce become a driver of bookings activity. The report also noted weaker commercial growth among partners across Salesforce's portfolio. A third were meeting or beating targets as opposed to 43 percent in the previous quarter. “Agentforce adoption [is] still subdued," the report said. Salesforce did not immediately return a request for comment. In its most recent results for Q1 FY2027, ended April 30, the CRM vendor said its current remaining performance obligation – a measure of future contract values – had grown 14 percent year over year to $33.6 billion, “propelled by Agentforce, Data 360, and Slack, partially offset by softness in commerce and Tableau.” “We are seeing incredible demand for Agentforce with annual recurring revenue now greater than $1 billion,” CEO Marc Benioff told analysts. Salesforce has backed Agentforce to help it beat the so-called SaaSapocalypse — where AI agents perform common enterprise tasks and obviate the need for software upgrades. It says Agentforce will help customers build, test, deploy, manage, and orchestrate AI agents in the enterprise. The TD Cowen report is not the only dark cloud over the strategy. Last month, a report from KeyBanc Capital Markets cited its CIO survey, which found customers did not view the CRM plan favorably. "Our checks and customer conversations have not been strong, nor has the feedback been on Agentforce. What we can piece together in the disclosed numbers does not signal building momentum and, most recently, our CIO survey delivered another blow with Salesforce being a standout for the wrong reasons," the report said. KeyBanc found that partners and customers thought enterprise data was not coherent enough to do meaningful AI work and that Agentforce, “as a product, just isn't there." ®

source https://www.theregister.com/saas/2026/08/21/salesforce-partners-not-seeing-meaningful-revenue-from-agentforce-ai-platform-report-says/5291167

AI companies are burning books, advocates complain to FTC

AI companies are buying loads of physical books, hoovering up the texts for model training, and then physically destroying the originals. A group of 18 advocacy organizations on Friday asked the US Federal Trade Commission to investigate the book butchering and knowledge hoarding. Fresh details of the practice emerged earlier this year via document disclosures in Bartz v. Anthropic PBC, a copyright case brought by authors of books that the AI company used for training without permission. Anthropic's book scan-and-destroy operation was known as "Project Panama." It was described in a 2024 internal memo as "our effort to destructively scan all the books in the world." Anthropic gave the operation a codename "because we don’t want it to be known that we are working on this," the court exhibit explains. "This document is visible to all Anthropic employees, but you should avoid talking about it in public areas, and the fact that we are working on this should not be shared with anyone outside Anthropic." Older books turn out to be valuable for AI training because they're unpolluted by AI-generated text, which has been seeping into recent written work. And destroying books once they've been scanned avoids the cost of storage. In some circumstances, scan-and-destroy operations may support fair use claims. In the Bartz case, the district court accepted the argument that a physical book can be digitized and destroyed, substituting the electronic copy for the physical book in a transformative act of fair use. But that didn't work out for the Internet Archive. Anthropic, which did not respond to a request for comment, is not the only company consuming and trashing texts. A recent report found Amazon has been participating in book scanning and shredding. Amazon also did not respond to a request for comment. The subject has become a public relations headache, in part because of the barbarism of book destruction and its association with authoritarian regimes, and in part because of the broad backlash against AI companies for pillaging public resources in pursuit of private gain. Intermediaries appear to be feeling the heat. ISBNdb, which reportedly helped broker the acquisition of books for destructive scanning, recently disavowed the practice. The biz noted last month, "We've removed a recent landing page, 'Printed Books Sourcing for Your AI LLMs Dataset Needs.' It was part of exploring demand, and we've chosen to pivot away from that direction." In light of these revelations, civil society groups want the FTC to look into book buy-and-destroy operations on the basis that they prevent competing AI developers and the public from accessing those resources. "The secretive and reckless way that major AI companies like Anthropic and Amazon are acting shows that there is real smoke here that the FTC needs to investigate," Kate Oh, special advisor to the Demand Progress Education Fund, said in a statement provided to The Register. The groups' letter [PDF] casts scan-and-destroy operations primarily as anticompetitive – the FTC being notionally a competition watchdog – but it hints at the anti-democratic consequences of monopolized knowledge. "Through their practice of permanently destroying books en masse and thus removing those non-renewable resources from broader access, AI companies are engineering a future where only the wealthiest incumbents can build high-quality AI models and operate as the sole holders of humanity's written works – after having destroyed the originals to get there," the letter says. We're unaware of whether any texts have been shifted entirely into AI models without leaving any physical copies. But then how would anyone verify that when AI companies refuse to divulge their training data? The letter asks the FTC to answer that question: "What the public record does not establish – and cannot, from the outside – is how often the destroyed physical books are the last or among the last surviving copies of a given work." ®

source https://www.theregister.com/ai-and-ml/2026/08/21/ai-companies-are-burning-books-advocates-complain-to-ftc/5291299

New SynkLoader malware pushed in Microsoft Teams phishing campaign

A previously unknown malware family dubbed SynkLoader is being distributed in Microsoft Teams phishing campaigns to steal credentials via a fake lock screen. [...]

source https://www.bleepingcomputer.com/news/security/new-synkloader-malware-pushed-in-microsoft-teams-phishing-campaign/

US Bank investigates LockBit's claims as ransomware crims set pay-or-leak deadline

US Bank says that it's investigating ransomware crew LockBit’s claims that it breached the financial institution and stole data, which the crims threaten to leak on September 3 unless the bank pays an extortion demand. “We’re aware of claims regarding a potential cybersecurity incident,” Lee Henderson, US Bank VP of public affairs, said in an emailed statement to The Register. The bank declined to answer specific questions about the claims, including whether it has communicated with the extortionists and how much LockBit demanded. If the extortionists’ claims are true, and even if the bank pays the ransom demand, there’s still no guarantee that the digital thieves will delete the stolen files. When cops took down an earlier iteration of LockBit in 2024, they found evidence that the crooks retained victim data - even after the victims paid the extortion demands. “At this time, there is no indication that our internal systems are impacted and no evidence of unauthorized access to our network,” Henderson continued. “US Bank takes the security and privacy of our clients' and employees' information very seriously. We continue to investigate and closely monitor these claims and remain, as always, vigilant in our efforts to mitigate potential exposure to cyber events.” LockBit added the bank to its leak site late Wednesday night, and gave the bank 14 days to pay a ransom demand or else see its data dumped online. The post doesn’t say how many files the crew allegedly stole, or what they contained. In February 2024, international cops seized servers, domain infrastructure, and decryption keys in an effort to dismantle the notorious ransomware group, and in May 2024, they outed LockBitSupp's true identity - although Dmitry Yuryevich Khoroshev, a Russian national, remains at large. In September 2025, however, LockBit reemerged with its new LockBit 5.0 ransomware variant. LockBit’s latest claims follow previous third-party breaches affecting US Bank customers’ data, and at least one law firm says that it’s considering a class-action lawsuit against US Bank National Association, the primary banking subsidiary of US Bancorp, on behalf of a small group of customers whose credit card information may have been exposed in a third-party security snafu that reached the bank through its vendor, Fidelity National Information Services. US Bank reportedly found out about the third-party incident on May 7, and in June, began notifying 537 customers, all Massachusetts residents, that their names, mailing addresses, and credit card numbers may have been stolen by the digital crooks. Customers’ Social Security numbers, online banking credentials, and account balances reportedly weren’t accessed. A much larger incident affecting around 11,000 customers occurred in 2022, after a different vendor “accidentally shared” a file containing personal information associated with closed US Bank credit card accounts, including names, addresses, Social Security numbers, dates of birth, closed account numbers, and outstanding balances.®

source https://www.theregister.com/security/2026/08/20/us-bank-investigates-lockbits-claims-as-ransomware-crims-set-pay-or-leak-deadline/5290560

Hackers poison arrayref Rust crate to push infostealer malware

Hackers compromised the maintainer account behind the widely used Rust crate arrayref to introduce malware that executed on developers' systems during compilation. [...]

source https://www.bleepingcomputer.com/news/security/hackers-poison-arrayref-rust-crate-to-push-infostealer-malware/

Rogue ransomware affiliate poses as data recovery firm to steal payments

A suspected ransomware affiliate is posing as a ransomware recovery service called "Ransom Busters," contacting the victims before the attacks become public and claiming to be able to provide decryption keys and delete stolen data for a fee. [...]

source https://www.bleepingcomputer.com/news/security/rogue-ransomware-affiliate-ransom-busters-poses-as-data-recovery-firm/

Sakura Internet hack exposes data of up to 1.36 million accounts

Japanese cloud and data center service provider Sakura Internet disclosed that hackers accessed its sales management system, where customer contract and membership information is stored. [...]

source https://www.bleepingcomputer.com/news/security/sakura-internet-hack-exposes-data-of-up-to-136-million-accounts/

Hackers compromise 14,500 Dahua web cameras in 35-day campaign

In a large-scale campaign that researchers dubbed CameraSwarm, hackers compromised more than 14,500 Dahua IP cameras mostly in Ukraine and Russia. [...]

source https://www.bleepingcomputer.com/news/security/hackers-compromise-14-500-dahua-web-cameras-in-35-day-campaign/

OpenAI's overhead will rise 20 percent for some workloads as it hardens security

OpenAI on Tuesday said its decision to suspend model training work, implemented after unreleased, unsupervised AI models hacked HuggingFace, remains in effect as the AI biz tries to implement stronger security measures. Some of those measures will increase compute overhead by 20 percent of the observed inference workload. An OpenAI spokesperson told The Register that those costs reflect internal research and won't be passed on directly to customers. The company has not revealed what portion of its total inference compute is subject to such monitoring now, or under its prior monitoring regime. "We have paused some frontier RL [reinforcement learning] training to ensure that we can meet the appropriate alignment, security and monitoring standards for the new level of capabilities in front of us," OpenAI CEO Sam Altman wrote in a social media post. "Model progress is now extremely rapid, and we always said we would take action if we felt that model capabilities were outstripping the pace of safety and alignment." Altman said he still expects new models, presumably the delayed Astra, will ship soon. The training pause affects further-out releases. OpenAI in its post reiterated its plans to focus on monitoring, model alignment, and security measures to prevent its models from running amok as they did last month. Following the HuggingFace incident, OpenAI "paused frontier model inference in research clusters for runs that could execute code or use tools that could access the internet." The biz said it allows some workloads to run, but paused others until they can be moved under a more stringent security regime that includes sandboxing, network isolation, and continuous security testing. "Our largest planned frontier RL (reinforcement learning) run remains on hold while we conduct smaller-scale training and evaluations to assess model behavior, validate our safeguards, and establish more evidence of alignment before proceeding," the company wrote. Reinforcement learning refers to the trial-and-error process by which AI agents "learn" about their environment by being rewarded for desired outcomes. OpenAI also said it is expanding its monitoring of the chain-of-thought process, the technique that sees "thinking" models break down tasks into discrete steps and produce intermediate text output for each step. The company's prior approach focused on high-risk workloads, specifically internal deployments of frontier models and frontier RL training runs. In contrast, OpenAI says, its new monitoring setup covers all RL training and evaluations involving tools for models at the capability level of GPT-5.6 Sol or higher. And with the determination that Astra possesses critical cyber capabilities, OpenAI added an additional monitoring requirement that covers all inference with Astra, not just RL training and testing. "These safeguards require meaningful compute," OpenAI said. "Our current estimates put monitoring overhead at roughly 20 percent of the inference compute being monitored, though the cost varies substantially across training and evaluation workloads." OpenAI expects to share more details about the implementation of its monitoring scheme in a future post. In research published last year, the company said that chain-of-thought monitoring is an effective way to detect model misbehavior, but cautioned that directly optimizing models to strictly follow instructions "does not eliminate all misbehavior and can cause a model to hide its intent." If you choose to believe the company's assurance that it will not pass on the cost of model thought policing to customers, it follows that OpenAI's losses will increase. It's difficult to imagine that would be a sustainable stance if OpenAI goes public. But given the company's reported $600+ billion in AI infrastructure commitments and its expectation to remain unprofitable until at least 2030, what's a bit more expense for the sake of uncertain security? ®

source https://www.theregister.com/ai-and-ml/2026/08/19/openais-overhead-will-rise-20-percent-for-some-workloads-as-it-hardens-security/5289303

Meta and Google mobile apps gorge on user data: Study

A study of mobile apps claims that Meta collects three times as much user data on average as tools published by Apple or Microsoft. Google is also one of the worst data-scavenging offenders. The research was conducted by the reassuringly named Surfshark, a VPN and security tools provider. It found that Meta's apps were the most "data-hungry," declaring an average of 25 out of 35 possible data types, compared with seven or eight for apps from Apple and Microsoft. The findings are based on privacy information submitted by developers to Apple's App Store, rather than independent observation of what the apps transmit. They count the number of data types an app may collect, not the amount or frequency of collection, and do not mean that every category is gathered from every user. Surfshark examined 171 iOS apps published by Google, Apple, Microsoft, Amazon, and Meta, making this a comparison of five tech giants rather than the wider app market. Google accounted for 29 of the 40 apps declaring the broadest data collection, although it was also overrepresented in the sample, with 44 apps – more than any other publisher. Nine of Meta's 12 apps made the top 40. The 29 Google apps declared between 18 and 26 data types each. Amazon Alexa was the most data-hungry non-Meta app, listing 28. All the Meta apps studied declared the collection of device IDs, product interactions, performance information, and crash data, Surfshark says. Nine listed precise location data, which the researchers argued went beyond what the apps were likely to need, while seven listed browsing history. Although Google's apps listed fewer data types on average than Meta's, they ranked as the most data-hungry in six App Store categories: Photo & Video, Music, Entertainment, Utilities, Health & Fitness, and Developer Tools. All the Google apps examined listed device IDs, diagnostic information, and performance data, while many declared search histories, purchase histories, photos or videos, email addresses, and usernames. Amazon's apps commonly listed device IDs, email addresses, names, performance information, product interactions, and crash data. Eleven declared precise location data, while one listed browsing history – Amazon Shopper. Apps from Microsoft and Apple declared the fewest data types on average among those Surfshark examined, although neither emerged entirely empty-handed. The data types most commonly listed by Microsoft apps included crash data, device IDs, email addresses, names, diagnostic and performance information, product interactions, and user IDs. Two also declared browsing history. Safari was the only Apple app to list browsing history, while six Apple apps declared precise location data. Other commonly listed types included device IDs, email addresses, and performance information. "Our research shows that the Big Tech business model is often built on an insatiable appetite for user information," said Surfshark research lead Dr Luis Costa. "When these giants weave together search history, purchase habits, and precise GPS coordinates across dozens of different apps, they are building a detailed digital map of users' lives." m®

source https://www.theregister.com/personal-tech/2026/08/18/meta-and-google-mobile-apps-gorge-on-user-data-study/5289171

Comcast turns your Xfinity WiFi into a home motion detector

Comcast is promoting WiFi-based motion detection as a part of its new Xfinity Shield home protection platform, allowing routers and wireless devices to detect people moving through a home without cameras or motion sensors. [...]

source https://www.bleepingcomputer.com/news/security/comcast-turns-your-xfinity-wifi-into-a-home-motion-detector/

Siemens and Reinhausen turn up the voltage for hungry AI racks

Siemens and fellow German engineering biz Reinhausen are developing a solid-state transformer (SST) to deliver 800-volt DC power directly to increasingly dense AI datacenter racks. As AI hardware grows hotter and hungrier, server farm operators are looking to overhaul how power moves through their data halls. One approach, favored by Nvidia and other industry heavyweights, is distribution at 800 VDC. The two electrical enterprises are therefore developing a modular SST capable of converting medium-voltage AC at up to 36 kV into a stable 800 VDC output for downstream distribution. Siemens says that the SST will provide a compact, galvanically isolated alternative to conventional multistage AC-to-DC power conversion architectures, reducing intermediate conversion stages and enabling more efficient delivery to high-density AI infrastructure. According to Reinhausen, datacenters supporting AI workloads are among the industry's most demanding power consumers. Sudden load spikes can strain servers, storage, and cooling systems, reducing performance and potentially causing outages. "Our technology enables AI datacenters to operate with the efficiency and reliability they require," said Reinhausen managing director Wilfried Breuer. "Solid-state transformers are critical for these large and power intensive structures. They enable higher efficiency, direct grid-to-rack DC conversion, and a reduced footprint. This collaboration will further strengthen our leading position in the electrification of datacenters," commented Siemens CEO of Electrification and Automation, Stephan May. As The Register reported late last year, Nvidia sees 800 VDC power distribution as the way forward for AI infrastructure, and says the shift will be necessary to support IT racks drawing 1 MW or more. That may sound far-fetched when average rack density has only just passed 11 kW, according to Uptime Institute, but hyperscalers such as Google are already planning for megawatt-scale racks. Nvidia has also developed its own MGX-compatible 800 VDC power rack, which it says will arrive "in the second half of 2026." Siemens and Reinhausen said that they intend to industrialize their datacenter SST, but did not say when it would become commercially available. We asked for clarification. Another German electrical firm, Infineon, is also backing 800 VDC and positioning its silicon carbide (SiC) power semiconductors for use in the infrastructure. ®

source https://www.theregister.com/on-prem/2026/08/17/siemens-and-reinhausen-turn-up-the-voltage-for-hungry-ai-racks/5288565

Hacker claims 3.6 million Azure account records stolen from major companies

A threat actor is selling employee databases allegedly stolen from the Microsoft Azure infrastructure of multiple Fortune 500 companies after gaining access using compromised credentials. [...]

source https://www.bleepingcomputer.com/news/security/hacker-claims-36-million-azure-account-records-stolen-from-major-companies/

Pokémon Center data breach exposes customer info, cancels some orders

Pokémon Center is notifying customers in the United Kingdom and Germany that it suffered a third-party data breach after hackers stole customer personal and order information from third-party logistics provider CEVA Logistics. [...]

source https://www.bleepingcomputer.com/news/security/pokemon-center-data-breach-exposes-customer-info-cancels-some-orders/

SafePal data breach impacts 39,798 customers, stolen info for sale

Cryptocurrency hardware wallet provider SafePal is warning of a data breach affecting about 39,798 customers after a flaw was exploited to steal customer order information, and a threat actor is now claiming to be selling the stolen data. [...]

source https://www.bleepingcomputer.com/news/security/safepal-data-breach-impacts-39-798-customers-stolen-info-for-sale/

Anthropic confirms Claude is down in major outage affecting multiple services

Claude is experiencing a major outage, with users reporting login problems and degraded performance across several Anthropic services. [...]

source https://www.bleepingcomputer.com/news/artificial-intelligence/anthropic-confirms-claude-is-down-in-major-outage-affecting-multiple-services/

Large-scale DDoS attacks disrupted Threema secure messaging service

Multiple distributed denial-of-service (DDoS) attacks targeted the Threema secure messaging service earlier this week, causing severe disruptions to communications. [...]

source https://www.bleepingcomputer.com/news/security/large-scale-ddos-attacks-disrupted-threema-secure-messaging-service/

New AmnesiaStealer macOS malware hijacks browser sessions via remote control

A new information-stealing malware called AmnesiaStealer, which targets macOS users via ClickFix attacks, includes a streaming module that allows the attacker to interactively control the victim's web browser. [...]

source https://www.bleepingcomputer.com/news/security/new-amnesiastealer-macos-malware-hijacks-browser-sessions-via-remote-control/

Stopping a cyberattack while walking your dog - defensive AI security CEO says it's not ruff to do

Corma CEO Alon Pluda says his AI security startup aims to close the "defense gap," where models are better at offensive security. He tells the story of one customer, a security executive who was walking his dog when he received a notification on his watch from a Corma agent. “It said, 'I just caught a live attack. I need your permission to block it,'” Pluda told The Register in an interview. The security boss approved the agent’s action; the agent blocked the malware and the attacker from moving across the company’s network and mitigated the intrusion in under 10 minutes, Pluda said. The customer later described "walking outside with his dog, and blocking a real-live attack with his AI coworker" as "one of the most magical moments of his year," Pluda recalled. Pluda founded Corma about a year ago. And yes, all you Lord of the Rings nerds, the company gets its name from the Elven word for “ring.” “We’re building the one ring to rule them all, but this time for the defenders to have this power.” Earlier this week, the company announced $60 million in seed funding led by Sequoia Capital, alongside Khosla Ventures and Coatue. He told us that his startup is working with Fortune 100 companies, and training models to achieve “superintelligence for defensive cybersecurity.” Models from OpenAI, Anthropic, and Google are “amazingly good” at coding and language, and this includes finding and fixing bugs, and orchestrating tools across multi-step workflows, he explained. “When you combine it with agentic capabilities, they move from being incredible vulnerability researchers to end-to-end attackers,” Pluda said. “So inherently, what we’ve seen in the last few months is the models getting exponentially better at offensive security, like we saw with the OpenAI and Hugging Face incident.” But these same models aren’t as skilled at carrying out defensive security tasks that don’t involve scanning code for vulnerabilities and misconfigurations, he said. “The vast majority of defensive security tasks don’t have anything to do with code.” Corma recently tested four frontier models - Claude Opus 4.8, GPT-5.5, Grok 4.3, and DeepSeek V4 - as both attackers and defenders across the same fake company and its networks, built to closely mirror a multi-business enterprise. The attacker’s task was to plant a backdoor and the defender’s task was to find it and stop the attack. Closing the defensive gap Corma ran all four models against each other in every attacker and defender pairing, including each model against itself, with 15 independent engagements per pairing for 241 scored engagements. Across all of these, the models successfully implanted a persistent backdoor in 85 percent of their runs. However, these same models only detected 19 percent of attacks. “That speaks to the inherent imbalance we are trying to solve,” Pluda said. “The general foundation models are getting exponentially better at offensive security, but haven't been able to improve on the same rate on defensive security. So our mission is to close this gap, and make sure the defenders win in this intelligence-versus-intelligence game - or war.” Corma calls this the defensive gap, and says it has to do with the data these models are trained on and the objectives they are trained against, which lend themselves to offensive security. Defensive security, however, involves reading logs, events, configurations, audit trails, and on-disk state. This is “structured machine data that is neither prose nor source, and a small share of what these models see in training,” according to Corma’s research. “They appear to read it less reliably.” Plus, defensive reasoning is more open-ended, while offense has a straightforward goal - like “make this work” or “break this” and a checkable finish. Agentic defenders “Defensive security,” according to Pluda, “is about finding needles in the haystack.” Corma’s models power its AI agents, which organizations can deploy like “team members” who then operate across defensive security tasks. “It’s a generalized workforce, and you can assign it to whatever security tasks you want.” Fortune 100 and 500 organizations across healthcare, financial services, energy, critical infrastructure, retail, and other sectors have deployed Corma’s AI workforce across their environments, according to the startup. These early deployments, we’re told, have reduced threat response times by more than 94 percent, expanded security coverage by 15 times across different security functions, and uncovered multi-stage attack campaigns. “If you can get AI that is smart enough, intelligent enough, knows the domain enough, optimizes for the right things enough, and you can actually trust it, end to end, all the way to responding to real-live attacks, you can reduce all of these metrics significantly,” Pluda said. “And you can cover way more ground than what is possible with just human intelligence.”®

source https://www.theregister.com/security/2026/08/16/stopping-a-cyberattack-while-walking-your-dog-defensive-ai-security-ceo-says-its-not-ruff-to-do/5288126

The what, why, and how of pull requests and source comments

Veteran Microsoft engineer Raymond Chen has weighed in on the difference between a pull request description and comments embedded in the code. Both matter, but they serve very different purposes. As Chen noted on his The Old New Thing dev blog: "The PR description is a point-in-time statement, providing information that is relevant to the code review itself. "It is an exercise in persuasive writing: You are trying to convince the approver that your change should be accepted." And sticking text in the source? "Comments in the code are for talking about the code itself. What is the correct way to call this function? Does it have specific prerequisites? This information is durable: It is information that remains useful even after the pull request completes." We'd argue that commit messages should be considered as well, but the distinction between PR descriptions and code comments is timely, given the volume of pull requests being generated by AI coding tools alongside some occasionally "interesting" annotations. Then again, anyone complaining about comments in AI-generated code would be wise to inspect those written decades ago by one of this writer's former colleagues. They consisted of pages apologizing to whichever future programmer had to untangle the spaghetti of C++ lurking through a maze of modules. Another colleague refused to annotate their code at all, insisting it was "self-commenting." These days, an honest comment might read: "This was written by , and I have no idea how the heck any of it works." It echoes another perennial developer dispute: whether code should be indented with tabs or spaces. In 2024, another Microsoft veteran, Larry Osterman, took a decidedly fence-sitting position: tabs were fine when storage was at a premium, but spaces now make more sense "because it always works and it's always consistent." Chen's position on tabs versus spaces is not widely known, but his broader opinion on code formatting was straightforward: "I don't care how you format your source code. It's your source code." He did suggest making any wholesale change in layout or formatting a separate check-in, so maintainers aren't faced with an epic diff dominated by a new style guide. All of which brings us back to Chen's distinction: the PR description explains why maintainers should accept a change, while comments preserve what future programmers need to understand the code. ®

source https://www.theregister.com/offbeat/2026/08/16/the-what-why-and-how-of-pull-requests-and-source-comments/5287914

Why tiny JPEGs look different in Chrome

A while back, when chatting with a colleague over their computer, I noticed that a logo did not look exactly the same as it did on mine. It looked thinner on theirs and more faithful to the original image. It was rendered at 15px; here is an upscaled version.

[…]
If you squint, or take a step back, the one from Chrome looks thicker. A bit weird, but swapping the image for an SVG fixed it. Still, I was curious: why was it rendering like this in the first place?

I did some digging and found a nifty optimization that Chrome uses when rendering JPEGs at small scales.
↫ Guillaume Técher

I love it when people detail their discoveries like this.

source https://www.osnews.com/story/145793/why-tiny-jpegs-look-different-in-chrome/

Hackers arrested over €30M bank fraud exploiting service provider flaw

Four cybercriminals were arrested in Brazil, and three others were charged in Europe over allegations that they exploited a vulnerability at a service provider, allowing them to withdraw funds from Commerzbank customers' bank accounts. [...]

source https://www.bleepingcomputer.com/news/security/hackers-arrested-over-30m-bank-fraud-exploiting-service-provider-flaw/

Apple sends new ‘Threat Notification’ alerts over mercenary spyware attacks

You're not alone if you just received an "Apple Threat Notification" saying it detected a "mercenary spyware attack targeted at your iPhone." [...]

source https://www.bleepingcomputer.com/news/apple/apple-sends-new-threat-notification-alerts-over-mercenary-spyware-attacks/

Ukraine shuts down 94 fraudulent call centers, seize millions in cash

Authorities in Ukraine shut down 94 fraudulent call centers across the country that lured people into investment scams or tried to obtain access to bank accounts. [...]

source https://www.bleepingcomputer.com/news/security/ukraine-shuts-down-94-fraudulent-call-centers-seize-millions-in-cash/

Akira hackers disable EDR with Safe Mode, steal data but fail to encrypt

An Akira ransomware affiliate disabled the endpoint detection and response (EDR) solution on a compromised system by restarting the machine into Safe Mode with Networking. [...]

source https://www.bleepingcomputer.com/news/security/akira-hackers-disable-edr-with-safe-mode-steal-data-but-fail-to-encrypt/

Hackers breach govt webmail while running parallel crypto fraud

The Jewelbug hacker group has been carrying out espionage operations targeting governments and militaries while also engaging in cryptocurrency fraud. [...]

source https://www.bleepingcomputer.com/news/security/hackers-breach-govt-webmail-while-running-parallel-crypto-fraud/

Hundreds of fake Chrome VPN extensions route traffic through a proxy

More than 737 browser extensions published on the Chrome Web Store impersonated well-known VPN and proxy services while routing users' traffic through SOCKS5 proxies operated by a single provider. [...]

source https://www.bleepingcomputer.com/news/security/hundreds-of-fake-chrome-vpn-extensions-route-traffic-through-a-proxy/

Delphi 13 Community Edition released

Delphi is still very much a thing, and still very much in active development. The current stewards of Delphi, Embarcadero, released the Delphi 13 Community Edition today.

Delphi Community Edition is a full-featured, free edition of Delphi for building native applications with the Delphi language. It includes a professional IDE, visual designers, integrated compilers and debuggers, the VCL framework for Windows development, and the FireMonkey framework for creating native applications from a shared codebase across Windows, macOS, iOS, and Android.

It is designed for students, hobbyists, freelancers, and small teams that meet the Community Edition license requirements.
↫ Marco Cantu at the Embarcadero blog

Delphi has been around since 1995, first released for Windows 3.1. It’s both a programming language, a variant of Object Pascal, and the accompanying IDE and related tooling and frameworks, originally developed by legendary company Borland. This latest version of course adds a number of new features to the programming language, and further improves the IDE as well, this time with a brand new 64bit version. The two frameworks for visual application development, VCL and FireMonkey, have also been updated and improved.

Sadly, it’s not open source, and the Community Edition is intended for mostly non-commercial, hobbyist use. If you want to actually earn any money using Delphi, you’re going to have to step up to Delphi 13 Florence, which isn’t free.

source https://www.osnews.com/story/145742/delphi-13-community-edition-released/

Cisco warns of ASA and FTD VPN flaw exploited to crash devices

Cisco is warning that a high-severity denial-of-service vulnerability in Secure Firewall ASA and Threat Defense (FTD) software is being actively exploited in attacks to remotely crash affected devices. [...]

source https://www.bleepingcomputer.com/news/security/cisco-warns-of-asa-and-ftd-vpn-flaw-exploited-to-crash-devices/

Microsoft August 2026 Patch Tuesday fixes 400 flaws, 3 zero-days

Today is Microsoft's August 2026 Patch Tuesday, and with it comes security updates for a massive 400 flaws, including one actively exploited and two publicly disclosed zero-day vulnerabilities. [...]

source https://www.bleepingcomputer.com/news/microsoft/microsoft-august-2026-patch-tuesday-fixes-400-flaws-3-zero-days/

Zuck rekindles open weights Llama drama with Muse Glimmer

After seemingly abandoning its open source AI roots this spring, Meta offered enterprises a glimmer of hope on Monday with the launch of its first open weights model in more than a year. Unveiled on Monday, Muse Glimmer is a 30 billion-parameter LLM distilled from the Social network's larger, and for now proprietary, Muse Spark model. Glimmer arrives as American tech companies grapple with a crisis over the proliferation of Chinese open weights models and a call for domestically-created alternatives. Meta built its reputation on the back of open weights model development beginning with the Llama herd back in 2023. But after Llama 4 flopped and the company restructured its AI group, critics questioned CEO Mark Zuckerberg's commitment to open source AI. With Muse Glimmer, Meta has returned to the open weights arena. The company describes the model as being ideally suited to local AI inference workloads, including local agents, code assistants, and applications requiring robust multi-modal tool use and function calling. Released under a highly permissive Apache 2.0 license, enterprises are also free to deploy, use, and modify the model however they see fit. We imagine it won't be long before Nous Research — one of the original Llama fine-tuners — emits another Hermes model based on Glimmer. Early support has begun to hit popular local AI inference platforms like Llama.cpp, Ollama, and Unsloth, with optimized implementations expected to hit over the next few weeks. But at 30 billion parameters, Muse Glimmer doesn't exactly move the needle much on reclaiming American open weights superiority. It's too small to compete with Moonshot AI's Kimi K3, Alibaba's Qwen 3.8-Max, DeepSeek V4 Flash, or any of the other Chinese models which have dominated the AI news cycle over the past few months. Instead, Muse Glimmer is positioned as a model for small-to-medium sized enterprises or enthusiasts, competing with similarly-sized LLMs from Alibaba and Google. This is reflected in Meta's benchmark figures, which pit the model against Alibaba's Qwen 3.6-27B and Google Gemma 4 31B. As usual, take these claims with a grain of salt, but Glimmer does appear to best Google's Gemma in most scenarios, and trades blows with Alibaba's equivalently sized model. Unfortunately for Meta, the comparison probably won't age well, with Qwen 3.8-27B due to be released any day now. Open and local Glimmer's relatively small parameter count means that its hardware requirements are rather modest compared to larger frontier-class models, like DeepSeek V4. At its native BF16 precision, the model should fit comfortably into a single Nvidia RTX Pro 6000 or AMD MI350P. Quantized to 4-bit precision and model's weights shrink from around 60 GB to just under 16 GB — small enough to fit in a 20 to 24 GB consumer graphics card, like an RTX 30/4090 or RX 7900 XT/XTX. Unfortunately for those with 16 GB cards, a lack of adequate working memory means dropping down to a smaller, less accurate 3-bit quant. Even if you can get the model to fit, it won't be as fast as some other recent models, like Qwen 3.6-35B-A3B or Gemma 4 26B-A4B, as Glimmer uses all 30 billion parameters to generate each token where the others use just 3 to 4 billion. Glimmer benefits heavily from memory bandwidth. On cards like the RTX 5090, which has 1.8 TB/s of it, Meta says users can expect between 75 and 233 tok/s. The higher end of that relies on a technique called speculative decoding. As a quick refresher, speculative decoding uses a small draft model, in this case one modeled after DeepSeek's DSpark drafter, to speed up inference by predicting the outputs of a larger model. If you're interested, we explore the concept in greater depth in this hands-on here. While 233 tok/s is plenty fast for most agentic workloads, most users won't see performance nearly that high. On an M5 Max MacBook Pro, Meta estimates that the systems' up to 614 GB/s of bandwidth will deliver a still-meaningful 26.2 to 57.8 tok/s, but it's also worth pointing out the M5 Max delivers 4x the memory bandwidth of the typical Windows notebook today. In other words, unless you've got a dedicated graphics card with enough memory to run the model, the best you can expect is around 6 to 14 tok/s. Testing on a DGX Spark in Unsloth Studio, we were getting around 12.2 tok/s, though DSpark support doesn't appear to have been implemented just yet. If you'd like to try the model out for yourself, its weights are currently available for download on Hugging Face as well as through local inference platforms like Ollama and LM Studio. Sparking joy Meta's return to the open weights arena doesn't stop with Glimmer. In an X post Monday, Meta's Superintelligence chief Alexandr Wang committed to releasing an open weights version of Muse Spark 1.2 "soon." Muse Spark 1.2 is Meta's most capable model, its first to compete in a meaningful way with rivals OpenAI, Anthropic, and Google. However, even this release won't close the gap with Chinese models. Both Kimi K3 and Qwen 3.8-Max outperform Spark, according to Artificial Analysis' intelligence index. Having said that, we still don't know how big Spark actually is. If Meta's next open weights model ends up delivering similar performance using fewer weights, this may end up being more competitive from a cost per token standpoint. ®

source https://www.theregister.com/ai-and-ml/2026/08/10/zuck-rekindles-open-weights-llama-drama-with-muse-glimmer/5285666

OpenAI releases ChatGPT 5.6 Cyber, but it's only for approved users

OpenAI has developed a new model called "GPT 5.6 Cyber," designed for vulnerability research, penetration testing, incident response, and remediation. [...]

source https://www.bleepingcomputer.com/news/security/openai-releases-chatgpt-56-cyber-but-its-only-for-approved-users/

North Korean spies are running local LLMs to cause AI mischief

North Korean government snoops are operating LLMs locally and collecting technology to weave AI into their attack operations, according to South Korean security firm Genians. The researchers said they observed Kimsuky setting up and operating local LLM environments using Ollama, GPT4All, and Msty, experimenting with other AI tools such as Cursor, and using retrieval-augmented generation (RAG) for local document searches. This prevents the data from getting sucked into the cloud where enemies might see it and try to stop it. Kimsuky, a cyber-espionage crew that operates under North Korea's Reconnaissance General Bureau, has for years used phishing and decoy documents in attacks targeting government agencies, think tanks, academia and security research organizations. Genians’ findings “provide concrete evidence that the Kimsuky-affiliated threat actor is moving beyond one-off experimentation with AI and is continuously preparing to integrate the technology into actual attack capabilities, including malware development, data analysis, and the advancement of attack techniques,” the researchers said in a Monday report. The North Korean group’s recent phishing emails use ZIP archives containing malicious LNK files - Kimsuky typically disguises these as materials related to international events, research reports, or meeting requests. When the recipient opens the archive and executes the LNK file contained within it, the shortcut runs an embedded PowerShell loader. In some cases, the goon squad used AI to create lures related to virtual assets and finance, we’re told. These decoy documents “use natural language, a highly polished structure, and formats similar to actual business materials to increase user trust and induce the execution of malicious files,” the security analysts noted. Additionally, the Pyongyang spies use various obfuscation techniques, including Base64 encoding, string splitting, and custom decoding routines, to hide the files’ malicious behavior. The PowerShell script collects a ton of system information, including operating system version and architecture, system configuration, PC type, operating system installation and boot history, and a list of running processes. The attackers use this information to assess the infected environment and support follow-on attacks. As with earlier Kimsuky campaigns, these intrusions use Git repositories for command-and-control (C2) infrastructure. “During the analysis, Genians Security Center identified multiple public GitHub repositories operated by the threat actor,” the researchers wrote. “One repository contained not only configuration files and PowerShell scripts, but also various payloads used in subsequent attacks.” Additionally, the months-long investigation uncovered the spies also using the Git-based C2 infrastructure for malware development and testing, stolen data management, and AI technology research. This included setting up multiple local LLM environments using Ollama, GPT4All, and Msty on infrastructure it controlled. “Because the local approach prevents conversation data from being transmitted to external AI services, it reduces the risk of external exposure, making it a particularly attractive option for a state-sponsored threat actor,” Genians said. The miscreants also collected a “large number” of libraries, such as LLaMaSharp and Microsoft.Extensions.AI, plus packages including OpenAI and Azure.AI.OpenAI, which call and integrate commercial AI services into their own custom applications. “The fact that development components spanning 'local AI execution → document retrieval (RAG) → automated agents → external AI integration' were collected together strongly suggests that they were not gathered out of simple curiosity, but for the direct development of an AI-based tool designed for a specific purpose,” according to the threat hunters. Genians uncovered logs containing speech-to-text tools, such as OpenAI’s Whisper speech recognition models, and evidence that the spies used Cursor AI to edit code and tested RAG for document-based question answering. Using RAG on stolen files can help attackers more quickly and automatically identify valuable information within large volumes of data. While the researchers noted that they did not identify any evidence that the Norks have begun training their own models - but rather remain focused on applying AI to malware development and attack operations - the findings make a strong case for defenders needing to shift away from content-based assessment to behavior-based detection. Assessing threats based on the quality of fake documents, such as unnatural translated language, poor formatting, and spelling errors, is no longer effective because AI is really good at producing convincing decoys. In addition to using indicators of compromise (IoC) to detect attackers in their environments, organizations should look for anomalous behaviors following LNK execution - such as PowerShell execution, persistence establishment, and external communications - to hunt for threats.®

source https://www.theregister.com/security/2026/08/10/north-korean-spies-are-running-local-llms-to-cause-ai-mischief/5285632

NEC tests parking tech that only starts charging once you exit your car

ASIA IN BRIEF Japan’s NEC has started tests of parking technology that will start charging once a driver leaves their car. Most car parks record the time a driver enters the facility and start charging, or depleting a free parking period, at that moment. That means drivers pay for time spent driving around looking for a spot and for the time it takes to exit a car park. NEC, in concert with another Japanese company called UrbanChain, will next month test a system that detects when a driver pulls up in a parking spot and exits their car – and starts charging for parking at that moment. That’s only possible using cameras and AI analysis of real-time video, and the tests NEC will conduct in September will investigate how many cameras are needed to make its plans feasible. NEC’s announcement also mentions “data utilization services targeting commercial facilities that can be used for monitoring vehicle occupant exit counts, analyzing facility visitor trends, and more” plus “new possibilities for data utilization.” Which sounds like a new form of surveillance capitalism, brought to car parks. The two companies also think there’s a safety benefit to their proposal, as it can spot drivers who haven’t left their cars for an extended period – a potential sign of illness. They also hypothesize that if drivers know they won’t be charged while searching for a spot or exiting a center, they may drive more safely. Fujifilm may join Japan’s printer exodus Fujifilm last week informed investors [PDF] that it is investigating a partial spin-off of its printer business. The company wants to float the business and retain up to 20 percent of its shares; an idea it thinks will mean Fujifilm can focus on its other businesses. If the plan goes ahead, Fujifilm will join fellow Japanese printer-makers Epson. Toshiba, and Ricoh in reducing its exposure to the biz. It’s not hard to see why Fujifilm is eyeing the exit: Analyst firm IDC recently said “a confluence of structural transformation and cyclical pressure” has brought uncertainty and sharply falling sales to the printer market. 2GW-plus datacenter opens in western China Chinese company Envision last week announced the commissioning of a two-gigawatt-plus datacenter in Ulana, Inner Mongolia. The company said the 120,000-square-meter facility can house up to one million GPUs and deliver one million PFLOPS of AI computing power. Renewable energy powers the facility, which is located in China’s west – making it an expression of Beijing’s Data East, Compute West plan that calls for construction of large datacenters closer to sources of clean energy and away from large population centers. Cable operator calls for police probe after faults follow “suspicious” activity Australian submarine cable operator and entrepreneur Bevan Slattery on Sunday claimed “some suspicious/coincidental activity” took place at the time two of his cables experienced a fault. “This is a concerning development. Partially because submarine cables are the digital lifeblood of our nation, but also because this could very well turn out to be the second such incidence in a Federally declared cable protection zone,” Slattery wrote. His post includes a marine chart that shows a vessel called the GEM Sapphire, which ship-tracking site VesselFinder lists as a 183-meter long tanker, repeatedly crossing the path of two cables. Infosys to wear Crocs for ten years Indian tech services giant will spend the next decade making sure the world’s ugliest shoes can be produced efficiently, after scoring a deal to help Crocs modernize its systems. Infosys says it will “unify data across the organization and aim to empower Crocs, Inc. with real-time, insight-driven decision-making – accelerating innovation while enhancing efficiency, responsiveness and customer experience.” Apparently, the deal “help Crocs, Inc. address key industry challenges, including rising costs, inconsistent processes and the need for increased agility. The transformation will standardize operations and aim to enable the business to better respond to evolving consumer and market demands.” There’s no mention if the deal will mean anyone looks cool wearing Crocs. Maybe even a decade of help from Infosys can’t make that possible. Australia urges smart glasses privacy probe Australian discount department store Kmart last week started selling low-end smart glasses for just AU$89 ($62/£46). The Guardian reported they sold out swiftly, sparking a privacy debate that quickly saw Australia’s Attorney-General write to the nation’s Privacy Commissioner to ask “that this issue be given priority consideration.” “Privacy is an essential part of all our lives,” said Attorney-General Michelle Rowland, before citing “widespread community concerns about the potential impacts of ‘smart glasses’, particularly for women and children.” ®

source https://www.theregister.com/software/2026/08/10/nec-tests-parking-tech-that-only-starts-charging-once-you-exit-your-car/5285245

I've gone from writing about SD-WAN to depending on it

This spring, my wife and I moved from the Denver suburbs into the Colorado Rockies. The high-altitude retreat presented a welcome reprieve from our otherwise tech-dominated lives. As remote workers, however, we faced certain challenges, and technology was the only reason our move was possible in the first place. Prior to my time at El Reg, I, among other things, breathlessly covered a subset of the networking industry, which as it happens had become big business following the COVID-19 outbreak and the pandemic that followed. I’m speaking, of course, about software defined wide-area-networking (SD-WAN). Little did I know, a mere six years later, this technology would become essential to my wife and me. Had it not been for 5G and Starlink, the move might as well have been time travel. To put it into perspective just how far into the foothills we’d ventured, the fastest wired connection at our disposal was DSL. CenturyLink promised, but notably did not guarantee, up to 20 Mbps down and a staggering 1.5 Mbps up. Compared to the symmetrical gigabit fiber line we’d enjoyed in the Denver suburbs for the past six years, relying on DSL alone felt positively medieval. To those, including many of my neighbors, living this reality, you have my sympathies. Thankfully, DSL wasn’t our only option. For better or worse, 5G and Starlink are helping to close the digital divide in a meaningful way — but individually they’re still far from perfect. Where we live, T-Mobile’s 5G internet service delivers near-gigabit download speeds and uplink speeds ranging from 30–40 Mbps. Meanwhile, Starlink promised between 100 and 400 Mbps downlink depending on the plan, with uplinks that, at least for us, capped out at around 30 Mbps. Either would be fast enough for our needs, but reliable? Turns out there’s still some room for improvement. In the past two months we’ve experienced no fewer than a dozen dropped connections lasting anywhere from a minute all the way to five. Making matters worse, the majority of these drops took place during working hours. With a relatively clear view of the sky, we’ve found Starlink to be more reliable, but even SpaceX isn’t immune to the occasional outage. That’s not to mention the threat of space junk kicking off a Kessler syndrome-like event. SD-WAN to the rescue The easy way to approach multi-WAN would have been to set up two networks, each with its own SSID. In the event one went down, we’d switch to the other. While simple, it’s far from perfect, and does nothing to mitigate disruptions to the voice and video calls on which my wife and I spend a considerable amount of our week. With two WiFi access points, we’d also have to contend with interference from overlapping channels. Wrangling multiple LANs, wireless SSIDs, and firewall rules isn’t exactly ideal. Thankfully, there’s a better way, and we just so happened to have all the equipment we needed. SD-WAN was developed in the early 2010s to solve a very specific problem: as SaaS apps like Office 365, Salesforce, and Google Apps took off, more and more enterprise traffic was going out to the internet. This was a problem for a lot of enterprise WANs, which often relied on expensive MPLS links designed to connect satellite offices to servers running back at headquarters or regional datacenters. In many cases, these WANs were built to prioritize reliability over bandwidth, and due to their topology required backhauling traffic tens or hundreds of miles just to access the internet. SD-WAN gateways offered an alternative. These devices could route internal traffic over the private WAN while SaaS and other internet-bound traffic could be piped over whatever local ISP served businesses in that area. SD-WAN is an entire can of worms in itself, but for my purposes two key capabilities stood out: multi-WAN and policy-based routing support. Our router, a Ubiquiti UniFi Dream Machine SE (UDM-SE), already supported both. The hardware The UDM-SE is not Ubiquiti’s newest nor even its most capable gateway. Introduced in 2022, the all-in-one appliance combines a 3.5 Gbps router (with IPS/IDS enabled) with an 8-port gigabit PoE switch, an integrated network video recorder, and critically two WAN ports, one good for 2.5 Gbps and another capable of 10 Gbps. Ubiquiti’s SD-WAN implementation is somewhat basic compared to gateways from HPE, Cisco, or Extreme. However, of the bevy of networking and security features SD-WAN encompasses, we only really needed a handful – multi-WAN and policy-based routing were the main ones – and Ubiquiti is kind enough not to gate this functionality behind an enterprise license. The setup itself was about as simple as it gets: plug each ISP-provided gateway into one of UDM-SE’s WAN ports and tell it whether you want to load-balance traffic across the two, or failover in the event of an outage or dropped connection. In practice there were a few extra steps, including disabling the 5G and Starlink gateways' onboard routing and WiFi functionality. Starlink supports a bypass mode, but the T-Mobile modem+router combo didn’t. We were able to disable the onboard WiFi, but only using an onboard utility. Putting it to the test With everything connected, we opted to configure the UDM-SE for WAN failover with T-Mobile as the primary and Starlink as the backup, rather than load-balancing traffic across the two, in part because the 5G link was so much faster. The first few days after setting everything up, my wife and I were questioning whether we even needed Starlink. But then we saw the notification: “Internet connection WAN1 (T-Mobile USA) on port 9 is down and WAN2 (Starlink) is now active,” and then a few minutes later, “Internet connection WAN1 (T-Mobile USA) on port 9 is restored after failing over to WAN2 (Starlink).” Both notifications were dated two hours earlier. We just hadn’t noticed. In fact, despite at least a dozen dropped connections over the past two months, the UDM-SE failed over fast enough that it was never an issue. No dropped calls, no buffering video, no timed-out web pages. Perhaps the most surprising discovery was that while Starlink didn’t offer the fastest or lowest-latency connectivity, it was remarkably reliable. Despite less than perfect alignment and view of the sky, the logs show just two dropped connections in the past month, one of which happened in the middle of the night when no one was awake to notice. While WAN failover kept us online, it didn’t do anything to guard against network congestion. The UDM-SE offers a preconfigured quality-of-service (QoS) policy that in theory should detect Zoom or MS Teams traffic and prioritize it over something like Windows Update or YouTube. But since we had two WANs, we could go one better and take advantage of another SD-WAN favorite: policy-based routing. This allowed us to force certain devices or services to prioritize one ISP over the other. For example, because Starlink had proven to be the more reliable of the two links, I wrote a policy to route traffic from my wife’s work laptop over the satellite link first and fail over to T-Mobile in the event of an outage. This also had the benefit of ensuring that if I happened to kick off a large game or AI model download while she was in the middle of a meeting, I wouldn’t get myself in trouble for turning her Zoom call into a pixelated mess. The digital divide is narrowing, not closed In the more rural parts of the US where wired connectivity isn’t a given, cellular home internet and low-Earth orbit (LEO) satellite communications, like Starlink, have gone a long way toward closing the digital divide — particularly for those working from home. However, individually they’re still far from perfect. Dropped connections weren’t a daily occurrence, but they still occurred more frequently and for longer than we would have liked. Five minutes is a long time to wait wondering whether the person on the other end of the Zoom call will be there when you eventually get back online. Technologies like SD-WAN can help to mitigate the problem by allowing multi-WAN failover, load balancing, and policy based routing, but to take advantage of them also requires paying for two ISPs and hundreds of dollars of equipment, which may or may not require monthly subscriptions or annual licenses. We were fortunate that the hardware we already owned supported these features and didn’t lock them behind a pricy enterprise license. Even still, we’re paying more for internet than we’d like. Between T-Mobile and Starlink, we’re spending around $125 a month to get online. Along with the higher price, network latency is also a lot higher than we’d like. Compared to our old fiber line, which routinely achieved latencies under 5 ms, T-Mobile and Starlink ranged from 15 ms at best to as much as 80 ms at worst. The only online game I play regularly is a real-time strategy that’s old enough to drink. I’m not playing CS:GO or whatever twitch shooter is popular these days, so the higher latency wasn’t that big of a deal, but if you're a competitive gamer, a wired connection is still a must. The good news is T-Mobile and Starlink may not be our only options for high-speed internet for much longer. There are numerous ongoing efforts across the US and other nations to improve access to fiber connectivity, including one slowly working its way down the highway in our general direction. On a personal note, while it’s neat to experience a technology firsthand that I dedicated years of my life to writing about, the moment fiber-to-the-home comes, both our Starlink and 5G home internet subscriptions are getting the boot. ®

source https://www.theregister.com/networks/2026/08/09/ive-gone-from-writing-about-sd-wan-to-depending-on-it/5285130

Ransomware gangs skip the CEO, head straight for the 40-something IT manager

Turns out the fastest way to get a company to consider paying a ransom isn't calling the CEO – it's targeting the 46-year-old IT manager. That's according to Zscaler, whose ThreatLabz researchers tracked 351 victims across 334 organizations caught up in a single ransomware campaign over the course of a month. The data suggests today's ransomware crews have become oddly specific about their preferred victim profile: nearly two-thirds of victims held manager-level titles or above, the average victim was a 46-year-old Gen Xer, and three-quarters worked in accounting and finance, sales, operations, HR, or marketing. Half worked in the industrial or IT sectors. Rather than blasting the same extortion email across an organization, attackers are doing their homework first. Zscaler says they combine information from compromised systems with publicly available data to map reporting lines and identify the employees most likely to influence a company's response. "The ransomware landscape has shifted from indiscriminate attacks to highly targeted extortion campaigns," the security outfit wrote. "Rather than targeting executives directly, attackers are increasingly focusing on managers and other key personnel with the authority or influence to accelerate payment decisions." That shift reflects what Zscaler calls "business privilege" rather than technical privilege. Security teams have traditionally focused on privileged users with administrator rights. Attackers, meanwhile, are after employees whose day jobs give them access to invoices, payment approvals, budgets, supplier contracts, customer accounts, HR records, or other sensitive business processes. "The value of a compromised managerial account lies in the breadth of business access associated with the position," the researchers wrote. "Managers may approve payments, oversee budgets and vendors, review contracts, access sensitive records, or coordinate work across business units." The Gen X skew is probably no coincidence either. Zscaler says many workers in their forties and fifties have reached established management positions, giving attackers access to valuable systems, sensitive information, and people with decision-making authority without needing to compromise the executive suite. It also found more than a dozen organizations said multiple employees were compromised during the campaign, suggesting attackers weren't content with a single foothold once inside a network. Instead, they appeared to work their way through different business functions to increase the chances of reaching valuable data and the people capable of influencing a ransom payment. The wider report points to a ransomware ecosystem that is becoming increasingly focused on extortion rather than encryption alone. Zscaler said ransomware attempts blocked across its cloud platform increased 146 percent over the past year, while public extortion cases rose 70 percent and the volume of data stolen from victims climbed 92 percent. By the time the ransom note lands, the crooks may already know who approves invoices, who signs contracts, who runs HR, and who reports to whom. The encryption is just the bit that victims notice. ®

source https://www.theregister.com/security/2026/08/09/ransomware-gangs-skip-the-ceo-head-straight-for-the-40-something-it-manager/5284499

IceWM 4.1.0 released

IceWM, the venerable X11 window manager, has put up a new maintenance release, version 4.1.0. It’s got a small number of fixes, two very minor new features, as well a few updated translations. That’s it.

source https://www.osnews.com/story/145703/icewm-4-1-0-released/

Brit boffins boast of beating barriers to building fusion power

Scientists at the UK Atomic Energy Authority (UKAEA) say that they have overcome plasma instability issues standing in the way of commercial fusion power plants. The boffins overseeing the MAST (Mega Amp Spherical Tokamak) Upgrade installation at UKAEA's Culham Campus in Oxfordshire conducted a fifth series of experiments on it during 2025 and 2026 and produced more than 1,100 fusion plasmas. During these experiments, the team demonstrated the highest pressure ever achieved with the MAST Upgrade machine, without the super-hot plasma destabilizing, they say. One of the challenges they set out to address is to figure out how to suppress instabilities known as Edge Localised Modes or ELMs. These are described as “sudden bursts at the plasma’s outer edge” that can cause a loss of plasma pressure and also lose up to a tenth of its stored energy in a single event. Over time, these occurrences will damage the tokamak’s inner wall and exhaust components, and were therefore seen as a serious obstacle to commercial viability. To cure this, the team adopted two techniques already previously tested to avoid these damaging heat bursts; Quasi-Continuous Exhaust mode (QCE-mode) and Resonant Magnetic Perturbations (RMP). With QCE, the plasma edge experiences high-frequency, low-amplitude filaments that act to bleed off pressure before it can build to a destructive level. Likewise, RMPs use a magnetic field to induce small perturbations at the edge of the plasma that bleed off the pressure leading to ELMs. The team also accessed two additional stable operating regimes known as Quiescent H-mode (QH-mode) and I-mode (Intermediate-mode), improved plasma confinement techniques that deliver better energy confinement while mitigating issues associated with large ELMs. QH-mode is understood to tackle ELM using an edge electromagnetic instability called the Edge Harmonic Oscillation (EHO) to steadily remove excess heat, while I-mode is a confinement technique that features a steep thermal barrier at the edge that allows particles to escape, again preventing the buildup of pressure. The Culham scientists also claim to have developed a technique for controlling the plasma’s position. This involves measuring visible light created by deuterium emitted from the machine’s upper and lower outer divertors (the exhaust system), allowing minute positional imbalances to be detected in real-time. Detecting changes in position is a step towards automated, real-time control systems that future commercial power plants will need to operate without constant manual intervention, according to the team. The series of experiments also explored “negative triangularity” plasma shapes that allow high-power operations without ELMs. This is said to be an approach being closely watched by the international fusion community. This MAST Upgrade installation is set to get further enhancements this year. These will include two new neutral beam injectors, doubling the machine’s heating capacity, and the installation of an Electron Bernstein Wave (EBW) system that will provide an additional 1.6 MW of heating power. Following this further upgrade, a sixth series of experiments is planned for 2028. EBW systems use high-frequency, electrostatic plasma waves to heat and drive currents in dense fusion plasmas, and the technology is planned for use in STEP, (Spherical Tokamak for Energy Production), the UK’s pilot fusion power plant to be built at the site of a former coal power station in Nottinghamshire. “These findings take us another step closer to practical fusion energy,” claimed James Harrison, head of MAST Upgrade science at UKAEA. “The results genuinely shape the design of future fusion power plants. Accessing four stable high-performance plasma regimes demonstrates that MAST Upgrade is producing science at the leading edge of what is possible.” Earlier this year, the UKAEA published a roadmap of targets it wants scientists to hit before the end of the decade, in order to drive forward development of working commercial fusion reactors. Reg readers will no doubt be aware of the old chestnut that working fusion power is perpetually 30 years away, but there have been developments in recent years, such as “ignition” being achieved at the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory (LLNL) in California, while UK fusion firm Tokamak Energy said it expected to deliver commercial fusion energy in the next decade. ®

source https://www.theregister.com/science/2026/08/07/brit-boffins-boast-of-beating-barriers-to-building-fusion-power/5284882

Metabase SQLi zero-day exploited in customer data-theft attacks

A critical Metabase SQL injection vulnerability was exploited in zero-day attacks to breach customer instances in data theft attacks, known to impact Framework and Tally. [...]

source https://www.bleepingcomputer.com/news/security/framework-tally-disclose-metabase-data-theft-attacks/

Unlimited Technology Systems breach impacts 3.8 million people

Healthcare software company Unlimited Technology Systems reported that more than 3.8 million people were impacted by a data breach incident that occurred in October 2025. [...]

source https://www.bleepingcomputer.com/news/security/unlimited-technology-systems-breach-impacts-38-million-people/

Uncle Sam aims to help nuclear energy find its sea legs

Not content with nuclear reactors on land, the US is backing an international push to put atomic power plants aboard civilian ships and floating platforms. The US will host the launch of the International Atomic Energy Agency's (IAEA) Atomic Technologies Licensed for Applications at Sea (ATLAS) initiative in Washington, DC, on August 26 and 27. ATLAS aims to tackle the legal, regulatory, safety, security, and liability problems that stand between maritime reactors and commercial deployment. Ahead of the launch, the US will hold an "Industry Day" on August 25 to showcase technology from American nuclear and maritime companies hoping to take a share of any future market. US Secretary of Energy Chris Wright linked the event to the Department of Energy's broader drive to deliver oodles of extra atomic power for AI datacenters and other industries. "DoE remains focused on unleashing American energy dominance, accelerating innovation, and advancing sources of energy that are affordable, reliable, and secure for the American people," he said. "Hosting the launch of ATLAS supports this critical mission, positioning the US nuclear and maritime sectors at the forefront of advanced energy innovation, while promoting safety and security for the United States and the world." The initiative covers civilian nuclear-powered ships and floating power plants, with the latter potentially supplying coastal communities or energy-hungry industrial processes such as desalination. The DoE is pinning its hopes on small modular reactors (SMRs), whose high energy density and long operating cycles could suit ships and offshore power installations. America is no stranger to reactors afloat. Every active US Navy aircraft carrier is nuclear-powered, giving it almost unlimited range without frequent refueling. The US Navy also used to operate nuclear-powered cruisers, such as the Virginia class, but these were retired after the end of the Cold War because they were costly to run. Civilian nuclear ships are also not entirely new. NS Savannah was the first nuclear-powered merchant ship when it was launched back in 1959, but again proved costly to run. Perhaps the IAEA hopes that SMRs will make atom-driven civilian ships more economical. Russia operates the world's only floating nuclear power plant. The Akademik Lomonosov is a barge-like vessel whose two KLT-40S reactors can generate a combined 70 MW of electricity. Putting a reactor on water changes the risks rather than making them disappear. The surrounding sea provides a vast heat sink for cooling, but a plant moored in a remote location may have limited access to emergency backup power, according to one assessment. However, any accident might also see radioactive contamination of the marine environment near the damaged reactor, which could seriously affect the coastal community the nuke was meant to be serving. "The global maritime sector is at a critical turning point, facing urgent pressure to sustain long-distance, high-speed operations while ensuring reliability and energy security," said IAEA Director General Rafael Mariano Grossi. "Small modular reactors offer a safe and viable option for maritime transport and offshore energy systems – delivering high energy density and long operating cycles that eliminate the need for frequent refueling." ®

source https://www.theregister.com/science/2026/08/06/uncle-sam-aims-to-help-nuclear-energy-find-its-sea-legs/5284179

New TONTOU CPU attack bypasses Spectre v2 fixes, leaks Linux password hashes

Researchers found a way to bypass recent mitigations for Spectre v2 speculative execution side-channel attacks and developed an exploit to leak secrets from Linux machines. [...]

source https://www.bleepingcomputer.com/news/security/new-tontou-cpu-attack-bypasses-spectre-v2-fixes-leaks-linux-password-hashes/

Prompt injection isn't the bug, AI agent frameworks are

Nearly a dozen flaws, some critical, in major AI agent frameworks that enterprises use to build apps reveal a security failure that extends beyond prompt injection - or any single model - according to Check Point researchers. “Our research shows a deeper failure: in many agentic frameworks, prompt-controlled content can cross the boundary into trusted framework logic itself,” Yarden Porat and Shahar Tal note in a write-up about a Wednesday Black Hat talk on post-injection exploitation across AI agent frameworks, which they also discussed with The Register. “A bug in an agent framework isn't a bug in one product - it's a bug in the layer a whole category of AI apps runs on,” Tal told us. “And the agent needs no dangerous tools to be turned against you: reading the wrong document is enough. We’re building this layer faster than we know how to defend it.”  The researchers spent a year trying to break various frameworks that enterprises use including LangChain, LangGraph, CrewAI, AutoGen, Microsoft Agent Framework, and Google ADK. And across these frameworks, the team found and disclosed 11 vulnerabilities. “Almost none of it was a completely new bug class,” Tal said. “That's insecure deserialization, server-side request forgeries, path traversals, use-after-free. These are bugs that we learned to fix 20 years ago, and they're sitting underneath agents that now read your inbox, or update your database.” These are old types of threats, and the model isn’t the weak link, he added. The failure exists in the “plumbing around the model, and we think this has been overlooked,” Tal told us. “There’s a lot of research going into prompt injection and defenses, which are important, but that’s just the beginning.” Defenders should assume prompt injection, according to the researchers. The bug is what the framework does with the injection - and in these cases, the threat hunters found that the frameworks often fail to keep attacker-controlled content in the data plane. This allows it to influence trusted orchestration, memory, state, routing, and system instructions. For example, the duo found a critical checkpoint deserialization bug in Microsoft Agent Framework that led to remote code execution. “Agents have checkpoints, which are a way for them to save their state or rewind to an earlier point,” Tal explained. These checkpoints are saved snapshots of an agent's state, or task progress at a specific moment, and they serialize data - such as conversation history - into persistent storage, so if an error occurs, the system reloads this saved state instead of starting from scratch. In this case, Check Point’s team found an insecure deserialization issue where, via prompt injection, the agent loaded untrusted checkpoint data, and this could allow attackers to execute malicious code on the system. “One person's message plants the payload, and then a different person rewinds their own session, which triggers the payload, and now the attacker has a shell on that server,” Tal said. Microsoft recognized the researchers’ findings, paid a $10,000 bug bounty and fixed the issue. But because the framework wasn’t a generally available product when Check Point found the flaw, Microsoft did not issue a CVE. Microsoft told us that it appreciated the researchers reporting the vulnerability. “We have released protections to harden the Agent Framework and prevent the concrete exploitation path demonstrated in the proof of concept,” a spokesperson told The Register. “In addition, we updated the specific checkpoint file with additional language to define the security boundary.” The duo also found flaws in Google ADK (agent development kit). However, Google responded differently, the researchers told us, and did not completely fix the vulnerability or issue a CVE. “ADK ships a built-in development assistant that can write files, and it stays reachable over the HTTP API even though it is hidden from the app listing,” Porat told us. To break this trust boundary, an attacker opens a session, asks ADK to write an agent whose Python code runs at import time, and then asks the server to run the agent, he explained. The server then imports the file and executes the attacker’s code. “There is no authentication on that API by default, and adk deploy cloud_run publishes the same API, so on a default Cloud Run deployment it is reachable without credentials,” Porat said. “From there it reaches the environment's API keys and the container's Google Cloud service account." Google did not respond to The Register’s inquiries. But according to Check Point, Google initially deemed the issue not a bug. “We argued the consequence rather than the mechanism: code execution on that container reaches the environment's API keys and the container's Google Cloud service account, which is secret theft, not a developer inconvenience,” Porat said. Google ultimately paid a $3,133.70 bounty and issued a partial fix, we’re told. In total, the bug hunters received $17,133.70 in rewards for their efforts. And this isn’t a story about one vendor or framework doing a “particularly bad job,” Tal said. “If one was an outlier, this would be a story about that one vendor,” he added. “Our finding is that the same bug classes turn up in all of them.” ®

source https://www.theregister.com/security/2026/08/05/prompt-injection-isnt-the-bug-ai-agent-frameworks-are/5283585

Time Magazine has a separate version of its website with ads only AI can see

AI webpage crawlers are now being served their very own ads that ordinary visitors never see, with one firm's boss openly describing a strategy to influence what chatbots say about brands. The next time you ask Claude about where to bank, its answer may have been influenced by this bot-targeted content. We only have one documented example so far, and that's Time serving AI-only ads to selected AI crawlers, as spotted by Germany-based freelance software developer Vincent Schmalbach. In a Wednesday blog post, Schmalbach detailed how he found sponsored content embedded in markdown versions of some Time pages that are served to AI crawlers but not ordinary browsers. Those pages also contained advertising tags from adtech vendor Mobian ahead of extensive FAQs for online-only bank Ally. The FAQs include brand "facts," such as the number of fee-free ATMs associated with the branchless bank, alongside claims that Ally is "the only bank built for life today," putting it in "a category of one." Key “brand fact” statements that make for great regurgitable facts are also included in the AI-only advertisement, as are answers to questions like “is Ally good for everyday banking,” “can you deposit cash at Ally Bank,” and the like. The FAQ is flagged as sponsored content on the markdown page, but it doesn’t change the fact that the entire thing is written like it was designed to be spit back out by a chatbot in response to specific questions. Not all web crawlers are getting these markdown ads either. Per Schmalbach, Google’s standard search indexing bot doesn't see the ads, as it just gets the same HTML that a human gets. “Only the [chatbot] assistant crawlers get the forked version,” he wrote. That means user-agents including ClaudeBot, OAI-SearchBot, and PerplexityBot receive the sponsored markdown, while Google's standard search crawler gets the same HTML served to ordinary browsers. GPTBot and ChatGPT-User, which OpenAI uses for model training and user-initiated retrieval respectively, return HTTP 406 errors in Schmalbach's tests, while OAI-SearchBot receives the markdown version used to support ChatGPT Search. These AI ad-infused markdown versions of stories should be viewable by humans who change the User-Agent header sent as part of HTTP requests, which is how Schmalbach said he spotted them. The Register tested several articles from Time to see for ourselves, and we were able to replicate the results using the crawler simulator provided by search engine optimization firm Encited. When viewed as ClaudeBot, Time’s Best Inventions of 2025 list includes the Ally Bank ad, as do stories about Time’s top content creators of 2026, as does a gallery of photos from a creators' party held in New York recently to honor the list. The markdown ads don’t appear on newsier stories that we checked, suggesting the ads may be part of more evergreen content rather than articles with a shorter shelf life. As Schmalbach points out in his writeup, this could be “the first clear look at what the web starts to become when the main audience is AI models,” which is a threshold we’ve already crossed. Why advertise to humans when you can make AI do it for you? It’s not clear whether Time’s strategy of advertising to AI crawlers has been adopted by other publishers, but it’d be a shock if others weren’t at least considering it. As noted above, AI crawler traffic has already begun to surpass human visits to webpages, making it potentially more lucrative for advertisers to target those crawlers than the humans who made them. With half of the US consumers surveyed saying they use AI to search the web, the potential to reach consumers by influencing AI responses is incredibly powerful, and that is what Time and its advertising partner Mobian appear to be banking on. When we asked the publication to verify Schmalbach’s report and the results we found, they didn’t answer questions, instead pointing us to a story in media and marketing outlet Digiday from last week that verified not only what we saw but our fears about the scheme, too. Per Digiday, Time started converting its web pages to markdown in order to make them more appealing to AI crawlers in June, and a partnership with Mobian was included in that rework. Time COO Mark Howard told Digiday that the publication’s sales team is pitching agent ads to brands that have also converted their websites to markdown, as it suggests those brands are thinking about reaching AI bots. It’s a quote from Mobian CEO and co-founder Jonah Goodhart that makes the objective clear, however: The company's aim is to shape what AI assistants say about the brands paying for the service. “When you influence ChatGPT, you’re influencing potentially all of ChatGPT. If ChatGPT changes what it says about [a brand], it’s massive and it’s more than any one campaign could ever do,” Goodhart told Digiday. “With a human you influence one person.” So far, the pair confirmed to Digiday that Ally Bank and the Project Management Institute were the first brands trying to influence AI search results, matching the ads Schmalbach and The Register found in AI crawler versions of Time's pages. Time and Mobian told Digiday that the partnership marks the first time a publisher has served ads directly targeting AI crawlers, but that “more are already being lined up.” In other words, you soon may not be able to tell which results in an AI powered search are legitimately being surfaced because of being good products, and which are just gaming the system. It’s the early days of the SEO race all over again, only this time fooling the indexers is as easy as handing any old idiot the same pamphlet over and over again until its content becomes truth. ®

source https://www.theregister.com/ai-and-ml/2026/08/05/time-magazine-has-a-separate-version-of-its-website-with-ads-only-ai-can-see/5283640

Elon pledges to give Nvidia a virtual monopoly over the stars

Nvidia commands about 85 percent of the datacenter GPU market today, and if Elon Musk has his way, the AI infrastructure giant will have a virtual monopoly over the stars. On Tuesday, Musk wrote on the social media network he owns that “SpaceX has committed to using Nvidia GPUs exclusively because they are the best.” The collab should surprise absolutely no one. It’s not like AMD or anyone else out there is making hardened versions of their GPUs for orbital datacenters. Why, you might ask? Well, to quote one Gartner analyst, the idea that space-based datacenters will ever be economically viable is “peak insanity.” Nvidia just happens to have $13.2 billion in cash to burn on pipe dreams like these. Specifically, SpaceX says that it will be deploying Nvidia’s Space-1, a specialized version of its upcoming Vera Rubin compute platform designed to operate high above the Earth’s atmosphere where no one can hear you scream because the LLM is hallucinating again. In a separate X post Tuesday, SpaceX announced it was “partnering with Nvidia to design the Starmind AI1 satellite compute payload,” and that “Each of the Starmind satellites will include Nvidia Rubin GPUs and Vera CPUs for datacenter class space compute.” According to SpaceX’s website, when fully deployed, the Starmind AI1 will measure 30 meters tall, have a wingspan of 75 meters from solar array to solar array, and support a compute payload of 250 kW. That might sound like a lot of power, but to put that in perspective, that’s only enough power for roughly a single Vera Rubin NVL72 rack. So, if you thought Nvidia’s rack systems were expensive, just wait till you have to loft them into orbit. Speaking of orbit, before any of this can happen, SpaceX needs to get its super heavy rocket, Starship, into orbit, which still hasn’t happened. An even bigger challenge is making it cost-effective to lob the 3.33 ton satellites into orbit. It currently costs about $7,000 to put a kilogram into orbit aboard a Falcon 9 rocket. That puts the current price of launching the AI1 at north of $23 million, assuming you manage to pack the thing into a Falcon 9 in the first place. For orbital datacenters to be cost-effective, Starship is going to need to get the cost per kilogram down to Elon’s stated goal of $10, Ortibal CEO told El Reg earlier this year. That would bring the cost to orbit to about $33,300, assuming the target is anything more than aspirational. Now is probably about the time we remind folks that Elon doesn’t exactly have the greatest track record of following through on his “commitments.” Remember how SpaceX was going to put humans on Mars by 2022 or how Tesla would field a million robo-taxis by 2020? But even if they don't go to space, Musk still might get something valuable out of Starmind AI1’s development. In yet another X post, Elon opined that the satellite's architecture was so efficient that SpaceX properties would be deploying them, sans solar and thermal management systems, in their terrestrial datacenters. “It’s a major improvement in data center efficiency,” he wrote. The notes came on the heels of SpaceX's first earnings report as a public company, during which it said that capital expenditures grew by a factor of 6x versus a year ago to $18.4 billion as the company goes into overdrive building out xAI, the company's artificial intelligence offering. The company posted a quarterly net loss of $541 million on revenues of $7.81 billion. The stock was down more than 10% in mid-day trading on Wednesday, and is down 17% from its listing price of $135 in June. ®

source https://www.theregister.com/systems/2026/08/05/elon-pledges-to-give-nvidia-a-virtual-monopoly-over-the-stars/5283605

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