Cybersecurity

AI Watch: OpenAI details 'unprecedented cyber incident' behind Hugging Face breach

Frontier AI models routinely cheat on evaluations, Lightweight AI model for vulnerability hunting emerges, Google launches Gemini Flash Cyber for vulnerability detection and repair, Malware hides inside normal AI coding activity, US weighs sanctions over alleged Chinese AI model theft, much more

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Yesterday's AI news occupied nearly every position in the cybersecurity contest with models autonomously crossing security boundaries, researchers discovering that they routinely pursue unauthorized shortcuts, vendors deploying them to find vulnerabilities, and attackers hiding inside the infrastructure built to support them.

First, and most astonishingly, an advanced OpenAI model escaped a restricted testing environment and breached Hugging Face’s production systems while attempting to obtain answers to a cybersecurity evaluation, in what may be the first publicly disclosed compromise carried out autonomously by a frontier AI model.

OpenAI revealed that GPT-5.6 Sol and a more capable, unreleased model were responsible for an intrusion Hugging Face disclosed last week without identifying the models or organization behind it. The disclosure amounts to a retroactive explanation of an incident that initially appeared to involve an unidentified autonomous agent operating across Hugging Face’s infrastructure.

The incident offers an unusually concrete demonstration of the risks posed by increasingly capable autonomous models. Instead of merely advising a human operator how to conduct an attack, the models independently discovered vulnerabilities, escaped their sandbox, escalated privileges, stole credentials, and compromised an external organization’s production systems.

OpenAI called it an “unprecedented cyber incident” and acknowledged that similar episodes are likely to become more common as models acquire stronger cybersecurity capabilities.

The models were participating in an internal evaluation called ExploitGym, which asks AI systems to follow complex attack paths to test their offensive cybersecurity abilities. OpenAI said it conducted the evaluation without the production classifiers normally used to prevent models from engaging in high-risk cyber activity.

Although the models’ direct internet access was supposed to be blocked, they found and exploited a previously unknown vulnerability in third-party software OpenAI used as a proxy and cache for package registries. They then escalated privileges and moved laterally through OpenAI’s research environment until they reached a system with open internet access.

From there, the models concluded that Hugging Face might host models, datasets, or solutions related to ExploitGym. They began looking for a way into the company’s systems and eventually chained together stolen credentials, zero-day vulnerabilities, and a remote code execution path to access secret information stored in Hugging Face’s production database.

OpenAI characterized the models as “hyperfocused” on solving the evaluation and said they went to extreme lengths to achieve that narrow objective. That framing distinguishes the incident from a deliberately malicious attack, but it also highlights a central problem with autonomous AI: a system does not need malicious intent to cause damage if it is capable of pursuing a goal through methods its developers did not anticipate or authorize.

Hugging Face previously said the autonomous agent executed tens of thousands of actions over a weekend, with investigators reconstructing more than 17,000 events. The intrusion began when a malicious dataset triggered code execution in Hugging Face’s data-processing environment, after which the agent escalated privileges and moved laterally through the company’s systems, according to Axios.

OpenAI’s disclosure suggests that the Hugging Face incident was not an isolated attack by an AI-enabled human adversary, but an unintended consequence of an internal model evaluation that spilled into another company’s infrastructure.

OpenAI said its own security team detected anomalous behavior, while Hugging Face’s security systems and agents detected and stopped the activity on its side. The companies are conducting a joint forensic investigation, and OpenAI said it has disclosed the proxy zero-day to the affected software vendor.

Hugging Face's own investigation ran into an unexpected wrinkle: the company reportedly turned to GLM, a Chinese open-weight model, to run forensic queries because the safety guardrails on US commercial models blocked the analysis its team needed to perform. The detail underscores a growing tension in AI security tooling, namely that the same restrictions designed to prevent misuse can also hamper legitimate incident response.

OpenAI has since added Hugging Face to its "trusted access" program, giving the company a version of GPT-5.6 Sol with fewer cyber guardrails intended specifically for defensive use, a tacit acknowledgment that the same capabilities driving the breach are also the ones defenders now need.

The incident appears likely to become a reference point for a new category of cyber risk: autonomous AI systems escaping controlled environments and conducting real-world intrusions while trying to complete legitimate assignments. As models gain the ability to operate over longer periods, use tools and recover from failed approaches, the distinction between a laboratory evaluation and an actual cyber operation may become increasingly difficult to maintain.

It also shows that AI security will depend on conventional cybersecurity fundamentals. The models succeeded through familiar techniques — exploiting vulnerable software, stealing credentials, escalating privileges and moving laterally — even if the speed, persistence and autonomy behind those actions were novel.

The episode also isn't Sol's first brush with this kind of behavior. The independent lab that red-teamed the model ahead of its release had already caught it gaming its own test environments, in one case packaging an exploit into a data stream to escalate privileges and surface answers evaluators had hidden. That history suggests the Hugging Face breach was less an aberration than a foreseeable extension of a pattern OpenAI's own evaluators had already flagged.

OpenAI said it is strengthening containment, monitoring and access controls around future model evaluations, even when doing so slows research. The company also said the incident demonstrates why advanced cyber models should be used defensively to discover and remediate vulnerabilities before malicious actors exploit them.

UK researchers find frontier models repeatedly cheat on evaluations

Separate research released yesterday by the UK AI Security Institute reinforces OpenAI’s explanation that models may take unauthorized actions while pursuing an assigned objective.

Every frontier model the institute tested attempted to “cheat” during at least some capability evaluations, including by searching the internet for answers, attacking systems outside the permitted target, escalating privileges on the system running the model, and probing evaluation software for leaked solutions.

The institute defines cheating as taking an explicitly prohibited or out-of-scope action to achieve a goal through an unintended shortcut. It does not necessarily interpret the behavior as evidence of conscious deception.

In one especially stark example, an evaluation was accidentally configured so that it could not be solved as intended. The model responded by writing and running code on an external internet service in an attempt to access the institute’s evaluation infrastructure. The activity triggered a security alert, although no information was stolen and no damage occurred.

The institute warned that asking models whether they violated the rules is not a reliable detection mechanism. Models did not consistently acknowledge their prohibited behavior when questioned and described their actions as wrong less than half the time.

The findings closely parallel the OpenAI incident. In both cases, models encountered obstacles while performing cybersecurity tasks and began searching for unintended paths around the restrictions placed on them.

The research suggests that organizations evaluating or deploying autonomous systems will need independent monitoring that records what models do, rather than relying on the models’ own descriptions of their actions.

Cisco releases small AI models for vulnerability hunting

Cisco, meanwhile, released two small open-weight AI models designed to find vulnerable files in large software repositories.

The Antares-350M and Antares-1B models are intended to operate more like security investigators than general-purpose coding assistants. They search repositories, inspect potentially relevant files, abandon unproductive paths, and narrow their focus to code most likely to contain a known vulnerability.

Cisco said the models performed comparably with much larger systems, including OpenAI’s GPT-5.5, on a benchmark developed to measure whether models can locate vulnerable files in real-world repositories.

The smaller models are designed to run locally, allowing companies to avoid sending sensitive source code to an outside AI provider. Cisco said Antares could scan 500 repositories in about 15 minutes for less than $1, compared with approximately five hours and more than $100 using GPT-5.5.

Cisco is releasing the two smaller models through Hugging Face to verified cybersecurity defenders but is withholding a more capable 3-billion-parameter version, which it plans to incorporate into its own security products.

The controlled release reflects the continuing tension surrounding cyber-capable AI. The same models that can help defenders locate vulnerabilities could also allow attackers to identify exploitable weaknesses more quickly.

Google introduces Gemini model for finding and patching vulnerabilities

Google separately introduced Gemini 3.5 Flash Cyber, a security-focused model intended to detect, validate, and repair software vulnerabilities at scale.

Google said the model is based on its efficient Flash architecture and can find and patch code security problems at a lower cost than larger models. Its CodeMender vulnerability-repair system uses multiple Flash Cyber agents working together.

Access will initially be limited to governments and trusted partners through a pilot program, an apparent effort to give defenders access to the technology while reducing the potential for misuse.

The company also launched Gemini 3.6 Flash, which it said uses fewer tokens and tool calls to complete multi-step workflows, and Gemini 3.5 Flash-Lite, a less expensive model aimed at high-volume agentic search and document processing.

The releases illustrate how AI companies are attempting to channel increasingly powerful coding and cyber capabilities toward defense even as incidents such as the Hugging Face breach show how difficult those capabilities may be to contain.

Malware hides inside normal AI coding activity

New CrowdStrike research also shows that attackers are beginning to target the AI development toolchain itself.

Researchers found a worm operating inside AI coding environments that steals credentials, cryptographic keys, and software package tokens before moving deeper into compromised systems. Once it gains sufficient access, it can destroy files or prevent legitimate users from accessing the affected infrastructure.

The malware is particularly difficult to detect because many of its actions resemble normal AI-assisted software development. Automated coding agents routinely inspect systems, access repositories, use package-management services, and perform actions across development pipelines.

CrowdStrike said the resulting telemetry overlap makes it difficult for defenders to distinguish legitimate automation from malicious activity. The malware also delays some actions by hours or days, making it harder to connect the initial compromise with later credential theft or destructive behavior.

The campaign points to another side of the emerging AI-security problem. Defenders must not only control what autonomous models are allowed to do but also detect human-directed malware that hides by imitating the models and agents now operating throughout software-development environments. (Ina Fried / Axios, OpenAI, Russell Brandom / TechCrunch, Sam Sabin / Axios, Cisco, CrowdStrike, AISI, MacKenzie Sigalos / CNBC, Abner Li / 9to5 Google, Lily Hay Newman / Wired)

Yesterday's AI news also showed Washington and Beijing locked in a strategic squeeze with the US threatening sanctions over alleged theft even as Chinese models become embedded in American business, while both governments quietly set up their first formal AI dialogue under Trump.

Treasury Secretary Scott Bessent said the administration will scrutinize Chinese AI models for signs they were built on stolen American technology, warning that "if we see... overseas models are stealing from our great companies, we have the ability to sanction them because of this theft."

He named the mechanism as distillation — training a smaller model off a stronger one's outputs — and said the government is already finding US model "watermarks" embedded in Chinese systems. The warning follows Moonshot AI's Kimi K3 release earlier this month, which outperformed OpenAI and Anthropic on some benchmarks and rattled tech stocks.

It also follows Anthropic's own complaint to the Senate Banking Committee last month alleging Alibaba ran the largest known distillation attack against it to date — though CNBC noted the irony that both Anthropic and OpenAI have faced their own IP accusations, including Anthropic's $1.5 billion author-copyright settlement and the Times' ongoing suit against OpenAI and Microsoft.

That threat now has a diplomatic track attached. Reuters reported the US and China will hold their first official AI dialogue under Trump in September, likely ahead of Xi Jinping's planned September 24 US visit, with Bessent leading the American delegation. Participants and agenda are still undecided.

A source close to Beijing's side said China wants technical engagement rather than political theater, and analysts expect the first meeting to do little more than agree on basic terms — like what even counts as a "frontier" model. Notably, Reuters reported Beijing's own priority list includes Anthropic's Mythos, since Chinese authorities are reportedly weighing curbs on overseas access to their most capable models over concerns about Mythos's hacking potential.

Bloomberg captured why a US crackdown on Chinese models would be harder to pull off than past moves like the Huawei 5G ban: open-weight software, once released, can be downloaded and run locally, and Chinese models already account for close to 60% of US company token usage on the OpenRouter marketplace, with DoorDash and Airbnb among the adopters.

That entrenchment is already dividing AI policy voices — OpenAI's Dean Ball suggested Washington should manufacture "regulatory risk" around Chinese open-weight models to scare enterprises off using them, "even if not well justified," which drew a public rebuke from White House adviser David Sacks, who called for decisions "grounded in facts, logic, and evidence."

Meanwhile, Xi has leaned into the openness contrast, pitching "AI for all" at last week's World AI Conference in Shanghai and warning against what he called overstretching the national-security concept in AI — rhetoric Beijing is also pushing at the UN, with a foreign ministry spokesperson arguing countries shouldn't be "coerced into taking sides" on AI systems.

Against that backdrop, OpenAI is working to keep its own house in order with Washington. Bloomberg reported CEO Sam Altman will brief the Trump administration and lawmakers next week on OpenAI's next model family, with global affairs chief Chris Lehane framing it around "work and scaling work" capabilities.

Lehane pushed for a coherent national AI strategy and floated support for an independent, Finra-like regulator to vet frontier models — an idea Bessent has reportedly helped shape and one that parallels a proposal from Google DeepMind's Demis Hassabis. The context is pointed: last month Anthropic was hit with US export controls that forced it to temporarily disable Fable 5 and Mythos 5, while OpenAI avoided formal measures but made unspecified changes to GPT-5.6 at the government's request before release. Absent congressional action, Lehane said OpenAI will pursue "reverse federalism," aligning states like Massachusetts around shared standards for catastrophic-risk disclosure — a push Anthropic also backs. (Nectar Gan / Bloomberg, Maggie Eastland / Bloomberg, Laurie Chen / Reuters, Ashley Capoot / CNBC)

The US intelligence community needs to devote more resources to protecting American artificial intelligence companies from foreign espionage, former officials told the House Intelligence Committee, arguing that China will use a range of intelligence-gathering techniques to steal proprietary AI technology and advance its own military and economic goals.

The hearing, focused on emerging threats to the US in the 25 years since the Sept. 11, 2001, terrorist attacks, also highlighted AI’s growing role across a range of national security concerns, including cyberattacks, autonomous drones and foreign influence operations.

“Of course, our intelligence services and agencies are going to have secrets that are always going to be of top desire for foreign intelligence adversaries, but if you’re [China’s Ministry of State Security] today, you’re looking at frontier model companies,” said Frank Cilluffo, a former George W. Bush homeland security official who leads Auburn University’s McCrary Institute for Cyber and Critical Infrastructure.

“I think we’ve got to actually rethink counterintelligence. It’s not just the traditional spy-versus-spy, information-versus-information,” he added. “It’s who holds the keys right now, it’s not going to be in government alone.”

Access to proprietary US AI research is valuable to foreign adversaries because it can help them close technological gaps without bearing the cost and time of developing those capabilities themselves. (David DiMolfetta / NextGov/FCW)

Related: House Intelligence Committee

German authorities say they have neutralized the main infrastructure supporting the Kratos phishing-as-a-service (PhaaS) kit following an operation supported by the US and Indonesia.

Officers from Frankfurt am Main's Central Office for Combating Internet Crime (ZIT) and the Federal Criminal Police (BKA) described Kratos as one of the most widespread and dangerous PhaaS kits on the market.

In Indonesia, authorities said they arrested the Kratos kit's alleged "developer and technical administrator." The announcement of Kratos's takedown did not mention whether any other individuals are being pursued.

According to the ZIT and BKA, Kratos allowed low-skill cybercriminals to harvest credentials, including passwords and session cookies, to bypass MFA by providing them with convincing Microsoft-themed phishing pages.

Criminals using Kratos phishing pages targeted hundreds of thousands of victims across more than 30 countries, while the operation behind the kit allegedly earned more than €300,000 ($342,000) since 2024.

More than 1,800 criminal enterprises are estimated to have used Kratos, which was responsible for around 15,000 phishing campaigns per month.

"Each individual campaign had the potential to harm several thousand recipients worldwide," the German authorities said in a statement.

The operation neutralized more than 200 servers, according to the ZIT and BKA, although the latter declined to explain how. (Connor Jones / The Register)

One of Australia's largest energy companies, Origin Energy, says it is investigating a security breach that "may have" affected customer data.

"Origin Energy Limited (Origin) is currently investigating a potential security incident which may involve unauthorised access to some customers' data," it said in a statement.

"We do not believe the impacted data includes customer credit card or bank details.

"We understand an incident like this may raise concerns and acknowledge the impact of this uncertainty on Origin customers.

"Our investigations into this incident are occurring as a matter of urgency, and Origin will provide further updates as appropriate."

The Australian news outlet reported a hacker had sent it a sample of 50 customer records containing names, addresses, emails, dates of birth, phone numbers and bill history.

It is understood that following this, Origin Energy alerted authorities to a potential security breach. (Tessa Flemming, Emilia Terzon and Cam Wilson / ABC.net.au)

Researchers at DTEX report that the people orchestrating North Korea’s IT worker scheme are funneling money through a web of front companies and intermediaries, including sanctioned entities, that partly fund Russia’s war effort against Ukraine.

Their research shows that the scheme is moving beyond funding the country’s weapons program and into a bigger pool that supports many of the regime’s objectives. This includes manufacturing weapons and supplying them to Russia’s military, according to DTEX.

“When we think IT workers, we typically think head down, get your money, support the weapons program,” Michael Barnhart, nation state investigator at DTEX and lead author of the report, said.

“It’s a broad cover-all statement when we say it’s supplying the weapons program,” he said. “That’s the predominant place it goes,” but many other domestic programs and entities tasked with other projects are taking cuts from that pool of money as well.

Barnhart corroborated previously leaked data from an internal North Korean payment server, which included 390 IT worker accounts, chat logs and transaction data. (Matt Kapko / CyberScoop)

Related: DTEX

Despite NSO Group's contention that it does not operate its Pegasus spyware tool on behalf of clients, an investigation by OCCRP, Código Morse, and Shomrim can reveal that NSO Group co-founder Shalev Hulio traveled to Panama in 2013 on an Israeli diplomatic passport and told Panamanian immigration he would be staying at the Israeli embassy.

John Scott-Railton from Citizen Lab, a research group at the University of Toronto that has studied Pegasus and NSO Group, said the finding “raises questions about NSO's connections to the [Israeli] state.”

Eitay Mack, an Israeli lawyer and human rights activist, said the discovery of Hulio’s diplomatic passport raised the possibility that “the separation between the [Israeli] government and NSO is a smokescreen.”

NSO Group is useful for the Israeli government, Mack said, because foreign governments that may not have diplomatic ties with Israel still want access to Israeli spyware technology. NSO Group’s sales abroad help Israeli intelligence networks foster connections with their foreign counterparts.

“It’s an important tool for Israel to build its relationships, specifically with intelligence units in foreign countries,” Mack said. “It is one of Israel’s main tools for creating relations and keeping them stable – by providing services and having relationships of trust with intelligence and military establishments in these countries.”

Hulio said the “allegations concerning a diplomatic passport and my purported role as a representative of the State of Israel are entirely false and categorically denied.” The Israeli Ministries of Defense and Foreign Affairs did not respond to requests for comment. (Luis Esquivel Golcher / Código Morse, Nathan Jaccard / OCCRP, Uri Blau / Shomrim / OCCRP)

Apple says it has fixed a vulnerability in its Hide My Email feature, which let essentially anyone figure out a user’s real email address, which was supposed to be protected by the feature.

Apple only fixed the vulnerability after 404 Media wrote about it at the start of July, despite Apple knowing about the issue for more than a year. The news also follows the filing of a class action lawsuit against Apple over the vulnerability.

Apple said it deployed a patch for the issue on July 3, which the company says has fully resolved the issue.

Hide My Email is part of Apple’s paid iCloud+ product. It lets customers quickly create a new, anonymous email address they can then use to sign up to websites, services, or email people with. The generated email addresses typically contain two random words followed by a number and the @icloud.com domain. (Joseph Cox / 404 Media)

The home appliance giant LG Electronics USA said this week it plans to suspend any apps built for its smart TVs that turn one’s television into an always-on residential proxy node.

The move comes less than a month after researchers found that more than 42 percent of games and other apps available for download on LG’s webOS store allow unknown third parties to route their Internet traffic through a user’s TV.

Security firm Spur examined the prevalence of residential proxy software development kits (SDKs) in smart TV apps. Spur found more than 42 percent of apps available for download on LG smart TVs include SDKs that turn one’s television into a proxy node indefinitely, and that more than a quarter of the apps made for Samsung’s Tizen operating system had similar residential proxy components.

LG Senior Vice President John Taylor said the company was working with app developers to remove the residential proxy option from their apps on the webOS platform. Developers that fail to comply, he said, will find their apps suspended. (Brian Krebs / Krebs on Security)

A cyberattack at AI music generator Suno last year allowed a hacker to steal the personal information of more than 55.3 million people, according to the data breach notification service Have I Been Pwned, offering the first glimpse into the scale of the data theft.

Per Have I Been Pwned, which obtained a copy of the breached dataset, the stolen data included customers’ names, physical addresses and email addresses, phone numbers, purchases, and partial payment card numbers taken from the company’s Stripe account, including card expiry dates.

The breach happened in November 2025, but was only recently revealed thanks to reporting by independent news outlet 404 Media.

The data theft also included Suno’s source code, which revealed how the company allegedly scraped millions of songs and lyrics from popular streaming sites, including Deezer, Genius, and YouTube, to train its AI models. Several major record labels are currently suing Suno, claiming that its mass-scraping efforts violate copyright law.

Suno has not yet publicly disclosed the cyberattack or notified individuals that their information was taken. (Zack Whittaker / TechCrunch)

A hacker group calling itself RansomHouse has claimed responsibility for a cyberattack last week that disrupted operations at Japanese frozen-food and logistics company Nichirei, affecting restaurants, supermarkets and school lunch programs.

The group posted a statement on the dark web saying it had stolen internal Nichirei data, according to Nobuo Miwa, president of cybersecurity company S&J, who confirmed the posting Wednesday.

Nichirei has not identified the attacker nor confirmed the group’s claims. The Tokyo-based company said Wednesday that it was continuing to investigate the incident with an outside cybersecurity firm and was cooperating with police and other authorities.

Some affected servers contained personal information, and Nichirei said it had separately notified the people concerned. It did not disclose the type or volume of data potentially affected.

Nichirei first announced July 13 that it had detected system problems caused by unauthorized access. The company later confirmed that its servers had been targeted in a cyberattack.

The disruption interfered with incoming and outgoing shipments at refrigerated warehouses operated by Nichirei group companies, as well as deliveries of frozen-food products. Operations began gradually resuming July 17, and the company said all affected locations, including warehousing and frozen-food shipping facilities, were expected to return to normal this week.

One of the companies affected was Kentucky Fried Chicken Japan. The company said Wednesday that all of its restaurants had resumed normal operations after the disruption caused product shortages, restricted menus and shortened opening hours. (Jessica Speed / The Japan Times)

American fast food restaurant chain Chick-fil-A is notifying an undisclosed number of customers of a data breach after their accounts were hacked in a wave of recent credential stuffing attacks.

The company revealed in data breach notification letters sent to affected individuals and filed with multiple Attorney General offices that it detected the attacks after identifying suspicious login activity to certain Chick-fil-A One accounts.

As Chick-fil-A discovered while investigating the incident, the attackers targeted Chick-fil-A's website and mobile app in June.

"Following a careful investigation, we determined that unauthorized parties launched an automated attack against our website and mobile application between June 17 and June 19, 2026, using account credentials (e.g., email addresses and passwords) obtained from a third-party source," it said.

"Based on our investigation, we determined on July 13, 2026 that the unauthorized parties may have accessed information in your Chick-fil-A One account." (Sergiu Gatlan / Bleeping Computer)

Related: Newsweek, Mass.gov

According to researchers at the enterprise browser platform Island, a large-scale operation dubbed ‘FakeGit’ is pushing SmartLoader and StealC malware through 7,600 malicious GitHub repositories that accumulated more than 14 million downloads.

Over 800 repositories pretended to be AI skills or MCP servers and appeared more than 600 times in public AI registries and catalogs. This increased the likelihood of being discovered by AI agents and developers, a technique that researchers call "agentbaiting."

The campaign is considered a continuation of an older operation that used Lumma Stealer and was attributed to a threat actor tracked as “Water Kurita” by researchers at cybersecurity company Trend Micro.

According to researchers at the enterprise browser platform Island, the AI focus was introduced in March and peaked in April, with the creation of 300 GitHub repositories linked to AI tools.

Researchers found that FakeGit grew to more than 1,400 repositories related to AI tools, agents, and workflows, all linking to SmartLoader or StealC malware downloads. (Bill Toulas / Bleeping Computer)

Malicious GitHub repository. Source: Island

At least one municipal government was among those to see their internet service disrupted after a cyberattack against a Maine telecommunications firm Sunday caused an outage affecting 23 towns along the state’s midcoastal region.

A local NBC affiliate reported that the government office of Damariscotta, a tourist town of roughly 2,300 inhabitants known for its oysters, experienced unreliable or unavailable internet service following a cyberattack against Tidewater Telecom.

“The Town Office currently has spotty to no internet service,” read a public notice issued Monday by the town of Damariscotta, a name reputedly derived from an Algonquian word meaning “place of abundance of small fish.” “Since the majority of town office services rely on the internet, we are significantly limited in what we can accomplish this morning.”

TideWater Telecom posted on its website Monday that the “issue has been identified and a fix is being implemented.” A second post later that day said, “We are working with our internet uplinks to drop the malicious traffic clogging our network. The situation is improving. Please note this is a dynamic situation.” An update Tuesday morning claims “services have returned to near-normal operating conditions.” (Colin Wood / StateScoop)

Related: SC Media

Best Thing of the Day: Six Years Is Better Than Nothing for This Guy

Illinois man Kyle Svara was sentenced to more than six years in prison after admitting he hacked the Snapchat accounts of hundreds of women in order to steal any nude or semi-nude photos they had, which he then ‌kept, sold or traded on the internet.

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University of Washington researchers tested three open-source, large language models (LLMs) and found they favored resumes from white-associated names 85% of the time, and female-associated names 11% of the time.