Biz & IT – Page 3

Where hyperscale hardware goes to retire: Ars visits a very big ITAD site

Biz & IT, data centers, Features, it asset disposition, ITAD, sk tes / Shannon Garcia / May 26, 2025

Inside the laptop/desktop examination bay at SK TES’s Fredericksburg, Va. site. Credit: SK tes

The details of each unit—CPU, memory, HDD size—are taken down and added to the asset tag, and the device is sent on to be physically examined. This step is important because “many a concealed drive finds its way into this line,” Kent Green, manager of this site, told me. Inside the machines coming from big firms, there are sometimes little USB, SD, SATA, or M.2 drives hiding out. Some were make-do solutions installed by IT and not documented, and others were put there by employees tired of waiting for more storage. “Some managers have been pretty surprised when they learn what we found,” Green said.

With everything wiped and with some sense of what they’re made of, each device gets a rating. It’s a three-character system, like “A-3-6,” based on function, cosmetic condition, and component value. Based on needs, trends, and other data, devices that are cleared for resale go to either wholesale, retail, component harvesting, or scrap.

Full-body laptop skins

Wiping down and prepping a laptop, potentially for a full-cover adhesive skin. Credit: SK TES

If a device has retail value, it heads into a section of this giant facility where workers do further checks. Automated software plays sounds on the speakers, checks that every keyboard key is sending signals, and checks that laptop batteries are at 80 percent capacity or better. At the end of the line is my favorite discovery: full-body laptop skins.

Some laptops—certain Lenovo, Dell, and HP models—are so ubiquitous in corporate fleets that it’s worth buying an adhesive laminating sticker in their exact shape. They’re an uncanny match for the matte black, silver, and slightly less silver finishes of the laptops, covering up any blemishes and scratches. Watching one of the workers apply this made me jealous of their ability to essentially reset a laptop’s condition (so one could apply whole new layers of swag stickers, of course). Once rated, tested, and stickered, laptops go into a clever “cradle” box, get the UN 3481 “battery inside” sticker, and can be sold through retail.

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Feds charge 16 Russians allegedly tied to botnets used in cyberattacks and spying

Biz & IT, botnet, russian hacking, Security, syndication / Mike M. / May 24, 2025

The hacker ecosystem in Russia, more than perhaps anywhere else in the world, has long blurred the lines between cybercrime, state-sponsored cyberwarfare, and espionage. Now an indictment of a group of Russian nationals and the takedown of their sprawling botnet offers the clearest example in years of how a single malware operation allegedly enabled hacking operations as varied as ransomware, wartime cyberattacks in Ukraine, and spying against foreign governments.

The US Department of Justice today announced criminal charges today against 16 individuals law enforcement authorities have linked to a malware operation known as DanaBot, which according to a complaint infected at least 300,000 machines around the world. The DOJ’s announcement of the charges describes the group as “Russia-based,” and names two of the suspects, Aleksandr Stepanov and Artem Aleksandrovich Kalinkin, as living in Novosibirsk, Russia. Five other suspects are named in the indictment, while another nine are identified only by their pseudonyms. In addition to those charges, the Justice Department says the Defense Criminal Investigative Service (DCIS)—a criminal investigation arm of the Department of Defense—carried out seizures of DanaBot infrastructure around the world, including in the US.

Aside from alleging how DanaBot was used in for-profit criminal hacking, the indictment also makes a rarer claim—it describes how a second variant of the malware it says was used in espionage against military, government, and NGO targets. “Pervasive malware like DanaBot harms hundreds of thousands of victims around the world, including sensitive military, diplomatic, and government entities, and causes many millions of dollars in losses,” US attorney Bill Essayli wrote in a statement.

Since 2018, DanaBot—described in the criminal complaint as “incredibly invasive malware”—has infected millions of computers around the world, initially as a banking trojan designed to steal directly from those PCs’ owners with modular features designed for credit card and cryptocurrency theft. Because its creators allegedly sold it in an “affiliate” model that made it available to other hacker groups for $3,000 to $4,000 a month, however, it was soon used as a tool to install different forms of malware in a broad array of operations, including ransomware. Its targets, too, quickly spread from initial victims in Ukraine, Poland, Italy, Germany, Austria, and Australia to US and Canadian financial institutions, according to an analysis of the operation by cybersecurity firm Crowdstrike.

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Researchers cause GitLab AI developer assistant to turn safe code malicious

AI, Artificial Intelligence, Biz & IT, chatbots, large language models, Security / Beth Washington / May 24, 2025

Marketers promote AI-assisted developer tools as workhorses that are essential for today’s software engineer. Developer platform GitLab, for instance, claims its Duo chatbot can “instantly generate a to-do list” that eliminates the burden of “wading through weeks of commits.” What these companies don’t say is that these tools are, by temperament if not default, easily tricked by malicious actors into performing hostile actions against their users.

Researchers from security firm Legit on Thursday demonstrated an attack that induced Duo into inserting malicious code into a script it had been instructed to write. The attack could also leak private code and confidential issue data, such as zero-day vulnerability details. All that’s required is for the user to instruct the chatbot to interact with a merge request or similar content from an outside source.

AI assistants’ double-edged blade

The mechanism for triggering the attacks is, of course, prompt injections. Among the most common forms of chatbot exploits, prompt injections are embedded into content a chatbot is asked to work with, such as an email to be answered, a calendar to consult, or a webpage to summarize. Large language model-based assistants are so eager to follow instructions that they’ll take orders from just about anywhere, including sources that can be controlled by malicious actors.

The attacks targeting Duo came from various resources that are commonly used by developers. Examples include merge requests, commits, bug descriptions and comments, and source code. The researchers demonstrated how instructions embedded inside these sources can lead Duo astray.

“This vulnerability highlights the double-edged nature of AI assistants like GitLab Duo: when deeply integrated into development workflows, they inherit not just context—but risk,” Legit researcher Omer Mayraz wrote. “By embedding hidden instructions in seemingly harmless project content, we were able to manipulate Duo’s behavior, exfiltrate private source code, and demonstrate how AI responses can be leveraged for unintended and harmful outcomes.”

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Google’s Will Smith double is better at eating AI spaghetti … but it’s crunchy?

AI, Ai video generator, Biz & IT, Deepfakes, Google, Google Veo, machine learning, Spaghetti, Veo, Veo 3, video synthesis, will smith / 9u50fv / May 24, 2025

On Tuesday, Google launched Veo 3, a new AI video synthesis model that can do something no major AI video generator has been able to do before: create a synchronized audio track. While from 2022 to 2024, we saw early steps in AI video generation, each video was silent and usually very short in duration. Now you can hear voices, dialog, and sound effects in eight-second high-definition video clips.

Shortly after the new launch, people began asking the most obvious benchmarking question: How good is Veo 3 at faking Oscar-winning actor Will Smith at eating spaghetti?

First, a brief recap. The spaghetti benchmark in AI video traces its origins back to March 2023, when we first covered an early example of horrific AI-generated video using an open source video synthesis model called ModelScope. The spaghetti example later became well-known enough that Smith parodied it almost a year later in February 2024.

Here’s what the original viral video looked like:

One thing people forget is that at the time, the Smith example wasn’t the best AI video generator out there—a video synthesis model called Gen-2 from Runway had already achieved superior results (though it was not yet publicly accessible). But the ModelScope result was funny and weird enough to stick in people’s memories as an early poor example of video synthesis, handy for future comparisons as AI models progressed.

AI app developer Javi Lopez first came to the rescue for curious spaghetti fans earlier this week with Veo 3, performing the Smith test and posting the results on X. But as you’ll notice below when you watch, the soundtrack has a curious quality: The faux Smith appears to be crunching on the spaghetti.

On X, Javi Lopez ran “Will Smith eating spaghetti” in Google’s Veo 3 AI video generator and received this result.

It’s a glitch in Veo 3’s experimental ability to apply sound effects to video, likely because the training data used to create Google’s AI models featured many examples of chewing mouths with crunching sound effects. Generative AI models are pattern-matching prediction machines, and they need to be shown enough examples of various types of media to generate convincing new outputs. If a concept is over-represented or under-represented in the training data, you’ll see unusual generation results, such as jabberwockies.

Google’s Will Smith double is better at eating AI spaghetti … but it’s crunchy? Read More »

New Claude 4 AI model refactored code for 7 hours straight

agentic AI, AI, AI assistants, Alex Albert, Anthropic, Anthropic Claude, Biz & IT, chatgpt, chatgtp, Claude, Claude 4, Claude 4 Opus, Claude 4 Sonnet, large language models, machine learning, openai / 9u50fv / May 22, 2025

Anthropic says Claude 4 beats Gemini on coding benchmarks; works autonomously for hours.

The Claude 4 logo, created by Anthropic. Credit: Anthropic

On Thursday, Anthropic released Claude Opus 4 and Claude Sonnet 4, marking the company’s return to larger model releases after primarily focusing on mid-range Sonnet variants since June of last year. The new models represent what the company calls its most capable coding models yet, with Opus 4 designed for complex, long-running tasks that can operate autonomously for hours.

Alex Albert, Anthropic’s head of Claude Relations, told Ars Technica that the company chose to revive the Opus line because of growing demand for agentic AI applications. “Across all the companies out there that are building things, there’s a really large wave of these agentic applications springing up, and a very high demand and premium being placed on intelligence,” Albert said. “I think Opus is going to fit that groove perfectly.”

Before we go further, a brief refresher on Claude’s three AI model “size” names (first introduced in March 2024) is probably warranted. Haiku, Sonnet, and Opus offer a tradeoff between price (in the API), speed, and capability.

Haiku models are the smallest, least expensive to run, and least capable in terms of what you might call “context depth” (considering conceptual relationships in the prompt) and encoded knowledge. Owing to the small size in parameter count, Haiku models retain fewer concrete facts and thus tend to confabulate more frequently (plausibly answering questions based on lack of data) than larger models, but they are much faster at basic tasks than larger models. Sonnet is traditionally a mid-range model that hits a balance between cost and capability, and Opus models have always been the largest and slowest to run. However, Opus models process context more deeply and are hypothetically better suited for running deep logical tasks.

A screenshot of the Claude web interface with Opus 4 and Sonnet 4 options shown. Credit: Anthropic

There is no Claude 4 Haiku just yet, but the new Sonnet and Opus models can reportedly handle tasks that previous versions could not. In our interview with Albert, he described testing scenarios where Opus 4 worked coherently for up to 24 hours on tasks like playing Pokémon while coding refactoring tasks in Claude Code ran for seven hours without interruption. Earlier Claude models typically lasted only one to two hours before losing coherence, Albert said, meaning that the models could only produce useful self-referencing outputs for that long before beginning to output too many errors.

In particular, that marathon refactoring claim reportedly comes from Rakuten, a Japanese tech services conglomerate that “validated [Claude’s] capabilities with a demanding open-source refactor running independently for 7 hours with sustained performance,” Anthropic said in a news release.

Whether you’d want to leave an AI model unsupervised for that long is another question entirely because even the most capable AI models can introduce subtle bugs, go down unproductive rabbit holes, or make choices that seem logical to the model but miss important context that a human developer would catch. While many people now use Claude for easy-going vibe coding, as we covered in March, the human-powered (and ironically-named) “vibe debugging” that often results from long AI coding sessions is also a very real thing. More on that below.

To shore up some of those shortcomings, Anthropic built memory capabilities into both new Claude 4 models, allowing them to maintain external files for storing key information across long sessions. When developers provide access to local files, the models can create and update “memory files” to track progress and things they deem important over time. Albert compared this to how humans take notes during extended work sessions.

Extended thinking meets tool use

Both Claude 4 models introduce what Anthropic calls “extended thinking with tool use,” a new beta feature allowing the models to alternate between simulated reasoning and using external tools like web search, similar to what OpenAI’s o3 and 04-mini-high AI models currently do in ChatGPT. While Claude 3.7 Sonnet already had strong tool use capabilities, the new models can now interleave simulated reasoning and tool calling in a single response.

“So now we can actually think, call a tool process, the results, think some more, call another tool, and repeat until it gets to a final answer,” Albert explained to Ars. The models self-determine when they have reached a useful conclusion, a capability picked up through training rather than governed by explicit human programming.

General Claude 4 benchmark results, provided by Anthropic. Credit: Anthropic

In practice, we’ve anecdotally found parallel tool use capability very useful in AI assistants like OpenAI o3, since they don’t have to rely on what is trained in their neural network to provide accurate answers. Instead, these more agentic models can iteratively search the web, parse the results, analyze images, and spin up coding tasks for analysis in ways that can avoid falling into a confabulation trap by relying solely on pure LLM outputs.

“The world’s best coding model”

Anthropic says Opus 4 leads industry benchmarks for coding tasks, achieving 72.5 percent on SWE-bench and 43.2 percent on Terminal-bench, calling it “the world’s best coding model.” According to Anthropic, companies using early versions report improvements. Cursor described it as “state-of-the-art for coding and a leap forward in complex codebase understanding,” while Replit noted “improved precision and dramatic advancements for complex changes across multiple files.”

In fact, GitHub announced it will use Sonnet 4 as the base model for its new coding agent in GitHub Copilot, citing the model’s performance in “agentic scenarios” in Anthropic’s news release. Sonnet 4 scored 72.7 percent on SWE-bench while maintaining faster response times than Opus 4. The fact that GitHub is betting on Claude rather than a model from its parent company Microsoft (which has close ties to OpenAI) suggests Anthropic has built something genuinely competitive.

Software engineering benchmark results, provided by Anthropic. Credit: Anthropic

Anthropic says it has addressed a persistent issue with Claude 3.7 Sonnet in which users complained that the model would take unauthorized actions or provide excessive output. Albert said the company reduced this “reward hacking behavior” by approximately 80 percent in the new models through training adjustments. An 80 percent reduction in unwanted behavior sounds impressive, but that also suggests that 20 percent of the problem behavior remains—a big concern when we’re talking about AI models that might be performing autonomous tasks for hours.

When we asked about code accuracy, Albert said that human code review is still an important part of shipping any production code. “There’s a human parallel, right? So this is just a problem we’ve had to deal with throughout the whole nature of software engineering. And this is why the code review process exists, so that you can catch these things. We don’t anticipate that going away with models either,” Albert said. “If anything, the human review will become more important, and more of your job as developer will be in this review than it will be in the generation part.”

Pricing and availability

Both Claude 4 models maintain the same pricing structure as their predecessors: Opus 4 costs $15 per million tokens for input and $75 per million for output, while Sonnet 4 remains at $3 and $15. The models offer two response modes: traditional LLM and simulated reasoning (“extended thinking”) for complex problems. Given that some Claude Code sessions can apparently run for hours, those per-token costs will likely add up very quickly for users who let the models run wild.

Anthropic made both models available through its API, Amazon Bedrock, and Google Cloud Vertex AI. Sonnet 4 remains accessible to free users, while Opus 4 requires a paid subscription.

The Claude 4 models also debut Claude Code (first introduced in February) as a generally available product after months of preview testing. Anthropic says the coding environment now integrates with VS Code and JetBrains IDEs, showing proposed edits directly in files. A new SDK allows developers to build custom agents using the same framework.

A screenshot of “Claude Plays Pokemon,” a custom application where Claude 4 attempts to beat the classic Game Boy game. Credit: Anthropic

Even with Anthropic’s future riding on the capability of these new models, when we asked about how they guide Claude’s behavior by fine-tuning, Albert acknowledged that the inherent unpredictability of these systems presents ongoing challenges for both them and developers. “In the realm and the world of software for the past 40, 50 years, we’ve been running on deterministic systems, and now all of a sudden, it’s non-deterministic, and that changes how we build,” he said.

“I empathize with a lot of people out there trying to use our APIs and language models generally because they have to almost shift their perspective on what it means for reliability, what it means for powering a core of your application in a non-deterministic way,” Albert added. “These are general oddities that have kind of just been flipped, and it definitely makes things more difficult, but I think it opens up a lot of possibilities as well.”

Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.

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Authorities carry out global takedown of infostealer used by cybercriminals

Biz & IT, CISA, infostealer, infostealers, Security, syndication / 9u50fv / May 22, 2025

Authorities, along with tech companies including Microsoft and Cloudflare, say they’ve disrupted Lumma.

A consortium of global law enforcement agencies and tech companies announced on Wednesday that they have disrupted the infostealer malware known as Lumma. One of the most popular infostealers worldwide, Lumma has been used by hundreds of what Microsoft calls “cyber threat actors” to steal passwords, credit card and banking information, and cryptocurrency wallet details. The tool, which officials say is developed in Russia, has provided cybercriminals with the information and credentials they needed to drain bank accounts, disrupt services, and carry out data extortion attacks against schools, among other things.

Microsoft’s Digital Crimes Unit (DCU) obtained an order from a United States district court last week to seize and take down about 2,300 domains underpinning Lumma’s infrastructure. At the same time, the US Department of Justice seized Lumma’s command and control infrastructure and disrupted cybercriminal marketplaces that sold the Lumma malware. All of this was coordinated, too, with the disruption of regional Lumma infrastructure by Europol’s European Cybercrime Center and Japan’s Cybercrime Control Center.

Microsoft lawyers wrote on Wednesday that Lumma, which is also known as LummaC2, has spread so broadly because it is “easy to distribute, difficult to detect, and can be programmed to bypass certain security defenses.” Steven Masada, assistant general counsel at Microsoft’s DCU, says in a blog post that Lumma is a “go-to tool,” including for the notorious Scattered Spider cybercriminal gang. Attackers distribute the malware using targeted phishing attacks that typically impersonate established companies and services, like Microsoft itself, to trick victims.

“In 2025, probably following Redline’s disruption and Lumma’s own development, it has ranked as the most active module, indicating its growing popularity and widespread adoption among cybercriminals,” says Victoria Kivilevich, director of threat research at security firm Kela.

Microsoft says that more than 394,000 Windows computers were infected with the Lumma malware between March 16 and May 16 this year. And Lumma was mentioned in more than 21,000 listings on cybercrime forums in the spring of 2024, according to figures cited in a notice published today by the Federal Bureau of Investigation (FBI) and Cybersecurity and Infrastructure Security Agency (CISA). The malware has been spotted bundled in fake AI video generators, fake “deepfake” generation websites, and distributed by fake CAPTCHA pages.

Law enforcement’s collaboration with Microsoft’s DCU and other tech companies like Cloudflare focused on disrupting Lumma’s infrastructure in multiple ways, so its developers could not simply hire new providers or create parallel systems to rebuild.

“Cloudflare’s role in the disruption included blocking the command and control server domains, Lumma’s Marketplace domains, and banning the accounts that were used to configure the domains,” the company wrote in a blog post on Wednesday. “Microsoft coordinated the takedown of Lumma’s domains with multiple relevant registries in order to ensure that the criminals could not simply change the name servers and recover their control.”

While infostealing malware has been around for years, its use by cybercriminals and nation-state hackers has surged since 2020. Typically, infostealers find their way onto people’s computers through downloads of pirated software or through targeted phishing attacks that impersonate established companies and services, like Microsoft itself, to trick victims. Once on a computer it is able to grab sensitive information—such as usernames and passwords, financial information, browser extensions, multifactor authentication details and more—and send it back to the malware’s operators.

Some infostealer operators bundle and sell this stolen data. But increasingly the compromised details have acted as a gateway for hackers to launch further attacks, providing them with the details needed to access online accounts and the networks of multi-billion dollar corporations.

“It’s clear that infostealers have become more than just grab-and-go malware,” says Patrick Wardle, CEO of the Apple device-focused security firm DoubleYou. “In many campaigns they really act as the first stage, collecting credentials, access tokens, and other foothold-enabling data, which is then used to launch more traditional, high-impact attacks such as lateral movement, espionage, or ransomware.”

The Lumma infostealer first emerged on Russian-language cybercrime forums in 2022, according to the FBI and CISA. Since then its developers have upgraded its capabilities and released multiple different versions of the software.

Since 2023, for example, they have been working to integrate AI into the malware platform, according to findings from the security firm Trellix. Attackers want to add these capabilities to automate some of the work involved in cleaning up the massive amounts of raw data collected by infostealers, including identifying and separating “bot” accounts that are less valuable for most attackers.

One administrator of Lumma told 404Media and WIRED last year that they encouraged both seasoned hackers and new cybercriminals to use their software. “This brings us good income,” the administrator said, referring to the resale of stolen login data.

Microsoft says that the main developer behind Lumma goes by the online handle “Shamel” and is based in Russia.

“Shamel markets different tiers of service for Lumma via Telegram and other Russian-language chat forums,” Microsoft’s Masada wrote on Wednesday. “Depending on what service a cybercriminal purchases, they can create their own versions of the malware, add tools to conceal and distribute it, and track stolen information through an online portal.”

Kela’s Kivilevich says that in the days leading up to the takedown, some cybercriminals started to complain on forums that there had been problems with Lumma. They even speculated that the malware platform had been targeted in a law enforcement operation.

“Based on what we see, there is a wide range of cybercriminals admitting they are using Lumma, such as actors involved in credit card fraud, initial access sales, cryptocurrency theft, and more,” Kivilevich says.

Among other tools, the Scattered Spider hacking group—which has attacked Caesars Entertainment, MGM Resorts International, and other victims—has been spotted using the Lumma stealer. Meanwhile, according to a report from TechCrunch, the Lumma malware was allegedly used in the build-up to the December 2024 hack of education tech firm PowerSchool, in which more than 70 million records were stolen.

“We’re now seeing infostealers not just evolve technically, but also play a more central role operationally,” says DoubleYou’s Wardle. “Even nation-state actors are developing and deploying them.”

Ian Gray, director of analysis and research at the security firm Flashpoint, says that while infostealers are only one tool that cybercriminals will use, their prevalence may make it easier for cybercriminals to hide their tracks. “Even advanced threat actor groups are leveraging infostealer logs, or they risk burning sophisticated tactics, techniques, and procedures (TTPs),” Gray says.

Lumma isn’t the first infostealer to be targeted by law enforcement. In October last year, the Dutch National Police, along with international partners, took down the infrastructure linked to the RedLine and MetaStealer malware, and the US Department of Justice unsealed charges against Maxim Rudometov, one of the alleged developers and administrators of the RedLine infostealer.

Despite the international crackdown, infostealers have proven too useful and effective for attackers to abandon. As Flashpoint’s Gray puts it, “Even if the landscape ultimately shifts due to the evolution of defenses, the growing prominence of infostealers over the past few years suggests they are likely here to stay for the foreseeable future. Usage of them has exploded.”

This story originally appeared at wired.com.

Wired.com is your essential daily guide to what’s next, delivering the most original and complete take you’ll find anywhere on innovation’s impact on technology, science, business and culture.

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“Microsoft has simply given us no other option,” Signal says as it blocks Windows Recall

Biz & IT, microsoft, privacy, recall, Security, signal messenger, Windows / Mike M. / May 22, 2025

But the changes go only so far in limiting the risks Recall poses. As I pointed out, when Recall is turned on, it indexes Zoom meetings, emails, photos, medical conditions, and—yes—Signal conversations, not just with the user, but anyone interacting with that user, without their knowledge or consent.

Researcher Kevin Beaumont performed his own deep-dive analysis that also found that some of the new controls were lacking. For instance, Recall continued to screenshot his payment card details. It also decrypted the database with a simple fingerprint scan or PIN. And it’s unclear whether the type of sophisticated malware that routinely infects consumer and enterprise Windows users will be able to decrypt encrypted database contents.

And as Cunningham also noted, Beaumont found that Microsoft still provided no means for developers to prevent content displayed in their apps from being indexed. That left Signal developers at a disadvantage, so they had to get creative.

With no API for blocking Recall in the Windows Desktop version, Signal is instead invoking an API Microsoft provides for protecting copyrighted material. App developers can turn on the DRM setting to prevent Windows from taking screenshots of copyrighted content displayed in the app. Signal is now repurposing the API to add an extra layer of privacy.

“We hope that the AI teams building systems like Recall will think through these implications more carefully in the future,” Signal wrote Wednesday. “Apps like Signal shouldn’t have to implement ‘one weird trick’ in order to maintain the privacy and integrity of their services without proper developer tools. People who care about privacy shouldn’t be forced to sacrifice accessibility upon the altar of AI aspirations either.”

Signal’s move will lessen the chances of Recall permanently indexing private messages, but it also has its limits. The measure only provides protection when all parties to a chat—at least those using the Windows Desktop version—haven’t changed the default settings.

Microsoft officials didn’t immediately respond to an email asking why Windows provides developers with no granular control over Recall and whether the company has plans to add any.

“Microsoft has simply given us no other option,” Signal says as it blocks Windows Recall Read More »

Chicago Sun-Times prints summer reading list full of fake books

AI, Biz & IT, Chicago Sun-Times, confabulations, machine learning / Kelly Newman / May 20, 2025

Photo of the Chicago Sun-Times “Summer reading list for 2025” supplement. Credit: Rachel King / Bluesky

Novelist Rachael King initially called attention to the error on Bluesky Tuesday morning. “The Chicago Sun-Times obviously gets ChatGPT to write a ‘summer reads’ feature almost entirely made up of real authors but completely fake books. What are we coming to?” King wrote.

So far, community reaction to the list has been largely negative online, but others have expressed sympathy for the publication. Freelance journalist Joshua J. Friedman noted on Bluesky that the reading list was “part of a ~60-page summer supplement” published on May 18, suggesting it might be “transparent filler” possibly created by “the lone freelancer apparently saddled with producing it.”

The staffing connection

The reading list appeared in a 64-page supplement called “Heat Index,” which was a promotional section not specific to Chicago. Buscaglia told 404 Media the content was meant to be “generic and national” and would be inserted into newspapers around the country. “We never get a list of where things ran,” he said.

The publication error comes two months after the Chicago Sun-Times lost 20 percent of its staff through a buyout program. In March, the newspaper’s nonprofit owner, Chicago Public Media, announced that 30 Sun-Times employees—including 23 from the newsroom—had accepted buyout offers amid financial struggles.

A March report on the buyout in the Sun-Times described the staff reduction as “the most drastic the oft-imperiled Sun-Times has faced in several years.” The departures included columnists, editorial writers, and editors with decades of experience.

Melissa Bell, CEO of Chicago Public Media, stated at the time that the exits would save the company $4.2 million annually. The company offered buyouts as it prepared for an expected expiration of grant support at the end of 2026.

Even with those pressures in the media, one Reddit user expressed disapproval of the apparent use of AI in the newspaper, even in a supplement that might not have been produced by staff. “As a subscriber, I am livid! What is the point of subscribing to a hard copy paper if they are just going to include AI slop too!?” wrote Reddit user xxxlovelit, who shared the reading list. “The Sun Times needs to answer for this, and there should be a reporter fired.”

This article was updated on May 20, 2025 at 11: 02 AM to include information on Marco Buscaglia from 404 Media.

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The empire strikes back with F-bombs: AI Darth Vader goes rogue with profanity, slurs

AI, Biz & IT, Darth Vader, Disney, epic games, fortnite, gaming, James Earl Jones, machine learning / Shannon Garcia / May 17, 2025

In that sense, the vulgar Vader situation creates a touchy dilemma for Epic Games and Disney, which likely invested substantially in this high-profile collaboration. While Epic acted swiftly in response, maintaining the feature while preventing further Jedi mind tricks from players presents ongoing technical challenges for interactive AI speech of any kind.

An AI language model like the one used for constructing responses for Vader (Google’s Gemini 2.0 Flash in this case, according to Epic) are fairly easy to trick with exploits like prompt injections and jailbreaks, and that has limited their usefulness in some applications. Imagine a truly ChatGPT-like Siri or Alexa, for example, that could be tricked into saying racist things on behalf of Apple or Amazon.

David Prowse as Darth Vader and Carrie Fisher as Princess Leia filming the original *Star Wars.* Credit: Sunset Boulevard/Corbis via Getty Images

Beyond language models, the AI voice technology behind the AI Darth Vader voice in Fortnite comes from ElevenLabs’ Flash v2.5 model, trained on examples of speech from James Earl Jones so it can synthesize new speech in the same style.

Previously, Lucasfilm worked with a Ukrainian startup we covered in 2022 on Obi-Wan Kenobi to recreate Darth Vader’s voice performance using a different AI voice model called Respeecher, which isn’t used in Fortnite.

According to Variety, Jones’ family supported the new Fortnite collaboration, stating: “James Earl felt that the voice of Darth Vader was inseparable from the story of Star Wars, and he always wanted fans of all ages to continue to experience it. We hope that this collaboration with Fortnite will allow both longtime fans of Darth Vader and newer generations to share in the enjoyment of this iconic character.”

This article was updated on May 16, 2025 at 4: 25 PM to include information about an email sent out from Epic Games to parents. This Article was updated again on May 17, 2025 at 10: 10 AM to correctly attribute ElevenLabs Flash v2.5 as the source of the Darth Vader audio model in Fortnite. The article previously incorrectly stated that Respeecher had been used for the game.

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Spies hack high-value mail servers using an exploit from yesteryear

Biz & IT, cross-site scripting, Security, sednit, webmail, xss / Shannon Garcia / May 15, 2025

Threat actors, likely supported by the Russian government, hacked multiple high-value mail servers around the world by exploiting XSS vulnerabilities, a class of bug that was among the most commonly exploited in decades past.

XSS is short for cross-site scripting. Vulnerabilities result from programming errors found in webserver software that, when exploited, allow attackers to execute malicious code in the browsers of people visiting an affected website. XSS first got attention in 2005, with the creation of the Samy Worm, which knocked MySpace out of commission when it added more than one million MySpace friends to a user named Samy. XSS exploits abounded for the next decade and have gradually fizzled more recently, although this class of attacks continues now.

Just add JavaScript

On Thursday, security firm ESET reported that Sednit, a Kremlin-backed hacking group also tracked as APT28, Fancy Bear, Forest Blizzard, and Sofacy—gained access to high-value email accounts by exploiting XSS vulnerabilities in mail server software from four different makers. Those packages are: Roundcube, MDaemon, Horde, and Zimbra.

The hacks most recently targeted mail servers used by defense contractors in Bulgaria and Romania, some of which are producing Soviet-era weapons for use in Ukraine as it fends off an invasion from Russia. Governmental organizations in those countries were also targeted. Other targets have included governments in Africa, the European Union, and South America.

RoundPress, as ESET has named the operation, delivered XSS exploits through spearphishing emails. Hidden inside some of the HTML in the emails was an XSS exploit. In 2023, ESET observed Sednit exploiting CVE-2020-43770, a vulnerability that has since been patched in Roundcube. A year later, ESET watched Sednit exploit different XSS vulnerabilities in Horde, MDaemon, and Zimbra. One of the now-patched vulnerabilities, from MDaemon, was a zero-day at the time Sednit exploited it.

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OpenAI adds GPT-4.1 to ChatGPT amid complaints over confusing model lineup

AI, Biz & IT, chatgpt, chatgtp, GPT-4, GPT-4.1, large language models, machine learning, openai / Shannon Garcia / May 15, 2025

The release comes just two weeks after OpenAI made GPT-4 unavailable in ChatGPT on April 30. That earlier model, which launched in March 2023, once sparked widespread hype about AI capabilities. Compared to that hyperbolic launch, GPT-4.1’s rollout has been a fairly understated affair—probably because it’s tricky to convey the subtle differences between all of the available OpenAI models.

As if 4.1’s launch wasn’t confusing enough, the release also roughly coincides with OpenAI’s July 2025 deadline for retiring the GPT-4.5 Preview from the API, a model one AI expert called a “lemon.” Developers must migrate to other options, OpenAI says, although GPT-4.5 will remain available in ChatGPT for now.

A confusing addition to OpenAI’s model lineup

In February, OpenAI CEO Sam Altman acknowledged on X his company’s confusing AI model naming practices, writing, “We realize how complicated our model and product offerings have gotten.” He promised that a forthcoming “GPT-5” model would consolidate the o-series and GPT-series models into a unified branding structure. But the addition of GPT-4.1 to ChatGPT appears to contradict that simplification goal.

So, if you use ChatGPT, which model should you use? If you’re a developer using the models through the API, the consideration is more of a trade-off between capability, speed, and cost. But in ChatGPT, your choice might be limited more by personal taste in behavioral style and what you’d like to accomplish. Some of the “more capable” models have lower usage limits as well because they cost more for OpenAI to run.

For now, OpenAI is keeping GPT-4o as the default ChatGPT model, likely due to its general versatility, balance between speed and capability, and personable style (conditioned using reinforcement learning and a specialized system prompt). The simulated reasoning models like 03 and 04-mini-high are slower to execute but can consider analytical-style problems more systematically and perform comprehensive web research that sometimes feels genuinely useful when it surfaces relevant (non-confabulated) web links. Compared to those, OpenAI is largely positioning GPT-4.1 as a speedier AI model for coding assistance.

Just remember that all of the AI models are prone to confabulations, meaning that they tend to make up authoritative-sounding information when they encounter gaps in their trained “knowledge.” So you’ll need to double-check all of the outputs with other sources of information if you’re hoping to use these AI models to assist with an important task.

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Google introduces Advanced Protection mode for its most at-risk Android users

advanced protection mode, android, Biz & IT, Google, hacking, Security / Shannon Garcia / May 14, 2025

Google is adding a new security setting to Android to provide an extra layer of resistance against attacks that infect devices, tap calls traveling through insecure carrier networks, and deliver scams through messaging services.

On Tuesday, the company unveiled the Advanced Protection mode, most of which will be rolled out in the upcoming release of Android 16. The setting comes as mercenary malware sold by NSO Group and a cottage industry of other exploit sellers continues to thrive. These players provide attacks-as-a-service through end-to-end platforms that exploit zero-day vulnerabilities on targeted devices, infect them with advanced spyware, and then capture contacts, message histories, locations, and other sensitive information. Over the past decade, phones running fully updated versions of Android and iOS have routinely been hacked through these services.

A core suite of enhanced security features

Advanced Protection is Google’s latest answer to this type of attack. By flipping a single button in device settings, users can enable a host of protections that can thwart some of the most common techniques used in sophisticated hacks. In some cases, the protections hamper performance and capabilities of the device, so Google is recommending the new mode mainly for journalists, elected officials, and other groups who are most often targeted or have the most to lose when infected.

“With the release of Android 16, users who choose to activate Advanced Protection will gain immediate access to a core suite of enhanced security features,” Google’s product manager for Android Security, Il-Sung Lee, wrote. “Additional Advanced Protection features like Intrusion Logging, USB protection, the option to disable auto-reconnect to insecure networks, and integration with Scam Detection for Phone by Google will become available later this year.”

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