"AI's decimation of call center jobs has begun," reports Bloomberg: Companies including the Commonwealth Bank of Australia, Microsoft Corp., Uber Technologies Inc. and Hyatt Hotels Corp. are using automated chat and phone systems to handle work that previously required humans. In some cases, they've already wiped out sizable chunks of their customer service operations, together representing thousands of workers.

The specter of automation has long loomed over the call center industry, which employs millions worldwide from the U,S, to India to the Philippines. But until recently, generative artificial intelligence wasn't good enough to move the needle. Now, AI advancements — and pressure on executives to show they're embracing the new technology — have prompted corporations to deploy the tools more widely. Customer service employment in the U.S. is declining and will likely continue to do so as more tasks are automated, Forrester analyst Kate Leggett wrote in a report earlier this year. While it's impossible to determine the future job losses, she estimated that almost half of customer service roles will be affected by 2030.

Globally, the steepest job cuts are expected to hit countries like the Philippines, where many Western companies have outsourced their most easily automated work. Salespeople at multiple tech companies told Bloomberg that they routinely pitch call center AI tools as a way of lowering labor costs, undercutting a common industry claim that AI is primarily a way to help workers become more productive rather than kill their jobs... Commonwealth Bank of Australia, the nation's largest lender, has shed hundreds of workers from its chat support line as it wove AI into the system, according to people familiar with the work. This amounted to tens of millions of dollars in savings per year, one of the people said...

Microsoft is both one of the largest vendors and adopters of customer service automation tools. This has helped the software giant trim its customer service workforce — a mix of contractors and full-time staff — from about 50,000 to 40,000 in recent years, according to a person familiar with the operations. "If something happened with little Johnny's Xbox in the middle of the night, we can now solve that with AI," Judson Althoff, who runs Microsoft's sales and service operations, said in an interview. Althoff said in April that AI is saving the company about $750 million per year in customer service costs. More complex problems still require human support, but the company is constantly expanding what can be fixed automatically, he said in the interview.
Two examples from the article:

• Last year Hyatt fired 30% of its in-house customer support staff for the Americas, according the hotel-industry news site Hotel Dive.

• Last week Bloomberg reported Uber had cut 10% of its customer service jobs as part of effort to "embrace artificial intelligence," according to the article. "Today, Uber pushes users to submit support requests through their apps, where they're met with an AI chatbot."

Slashdot reader prisoninmate shares this report from 9to5Linux: Coming ten days after the previous Linux kernel security update, which only fixed 12 vulnerabilities that may lead to a privilege escalation, denial of service, or information leaks, the new Debian 13 Linux kernel security update is a massive one, and it patches no less than 68 security vulnerabilities in the Linux 6.12 LTS kernel.

ebian 13 "Trixie" kernel security update are CVE-2026-64530, a use-after-free in the traffic-control subsystem leading to remote denial-of-service with potential for remote code execution, and CVE-2026-64531 (a.k.a. OVSwrap), a local-root vulnerability in the Open vSwitch datapath leading to local privilege escalation to root...

All Debian 13 "Trixie" users are urged to update their installations to Linux kernel 6.12.100-1 as soon as possible.

Researchers found enterprises are spending time troubleshooting cloud connectivity due to increased AI workloads, reports Computer Weekly. More than 400 IT and infrastructure decision-makers (US and UK) were surveyed for internet/cloud/AI exchange operator DE-CIX by market researchers Censuswide. But despite 96% of respondents claiming their enterprise networks are ready for cloud/AI loads, the average IT team still spends more than 11 hours each week resolving cloud connectivity problems Other leading concerns included downtime or reliability issues (26%), latency or slow performance (28%), and security vulnerabilities/DDoS attacks (27%). Cost of connectivity, staff expertise and lack of visibility/control over data flows were also cited as major challenges... As a result, as indicated in the study, many businesses are now turning to private interconnection, which enables enterprises to connect directly to cloud providers over dedicated infrastructure rather than routing traffic across the public Internet. Designed to deliver lower latency, greater resilience, enhanced security and more predictable performance, private interconnection has become an increasingly important way of supporting modern cloud and AI workloads. Specifically, the data showed that 61% of companies are already using private connectivity to clouds, while another 31% are actively considering it... [And 71% of enterprises with 1000 or more employees]

Only 8.62% of the smaller companies were spending 21 to 40 hours per week dealing with connectivity issues, while just 2.53% of the largest companies in the sample do. Summing up these findings, DE-CIX said that together they suggest direct interconnection is rapidly becoming a core component of enterprise cloud and AI infrastructure and a competitive advantage for companies, though optimising interconnection strategies clearly remains a pressing challenge for small and medium-sized enterprises... "Every AI application depends on data moving quickly, securely and predictably between users, clouds and AI infrastructure. Our research suggests that far too many enterprises are still spending valuable time trying to maintain that kind of connectivity, with more than a third spending between 11 and 20 hours per week, and just under one in 10 spending between 21 to 40 hours per week. This confirms what we already knew — that that network architecture can make or break AI adoption."
Elsewhere The Register reports that cloud infrastructure services "grew at their fastest for eight years during the second quarter of 2026, thanks to the AI craze and continued demand for flexible and scalable IT infrastructure." According to the latest figures from Synergy Research, enterprise spending on cloud infrastructure passed $143 billion in Q2, a year-on-year growth rate of 43 percent. This followed 11 successive quarters of increasing growth rates, during which the market has now doubled in size... "AI has, of course, driven most of that incremental growth, and we now see year-on-year growth rates of 165 percent for AI-specific cloud services...." And the top three global players continue to dominate the market, with Amazon Web Services (AWS), Microsoft Azure and Google Cloud together accounting for 67 percent of all the cloud revenue during the quarter. That percentage has increased since the third quarter of last year, when the triumvirate made up 63 percent of enterprise cloud infra spending.

The Hill published the thoughts of Gleb Tsipursky, Ph.D., who serves as the CEO of the future-of-work consultancy Disaster Avoidance Experts: A recent EnhancV survey of 1,000 full-time U.S. workers subject to new or stricter return-to-office policies found that 72% suspect these mandates are really a voluntary attrition strategy — a strategy by their own employers to make them quit their jobs. A full 46% admit to the practice of coffee-badging. Thirty-six percent have applied for a new job while sitting at their current office desk. Thirty-six percent have started a side hustle since the mandate was announced, in anticipation of being let go or quitting. Those numbers do not prove that employees reject collaboration. They show that many employees no longer trust the official story...

The central mistake in many in-office mandates is the assumption that proximity automatically produces commitment. It does not. A worker who spends two hours commuting to sit on video calls with colleagues in other cities is not experiencing culture. That worker is experiencing theater. When executives describe the office as a cure-all, many employees experience lost time, higher costs and lower autonomy. The policy's defining feature becomes its credibility gap. Research keeps undercutting the belief that more office time automatically means better performance. A University of Pittsburgh analysis of S&P 500 firms found that return-to-office mandates reduced employee satisfaction without improving firm performance or firm value....

Baylor University's reporting on office mandates and brain drain found that firms with mandates faced greater turnover among women, senior employees, managers and high-skilled workers, while job vacancy duration increased and hiring rates declined. In other words, the people with the most options are often the first to leave. The employees who remain may not be the most committed — they may simply be the least mobile... Attendance can be mandated, but commitment cannot. When leaders confuse the two, they do not rebuild workplace culture. They create a room full of people planning their exit.

"A hardware wallet is supposed to be the safest place to keep Bitcoin," writes The Street, since it never connects to the internet, its keys never leave the device, and "the whole point is that an attacker would need to physically hold it to steal anything."

The problem is that anyone who can reproduce the recovery seed doesn't need to possess the COLDCARD, Nerds.xyz points out. More from The Street: [The recovery seed] is supposed to come from a hardware random number generator producing 128 bits of entropy, a number so large that guessing it is computationally impossible. It wasn't. According to Block's engineering team a single code change on March 1, 2021 caused the firmware to silently fall back to a software-based generator instead of the hardware one. On Mk3 devices the effective search space collapsed to roughly 40 bits. Coinkite has confirmed that figure and called it preliminary. The gap between 128 bits and 40 bits is not a matter of degree. It is the difference between a lock that cannot be picked and one that can be brute-forced by anyone with rented cloud computing....

Chainalysis found the attacker went after the largest balances first, pulling more than $30 million in the opening ten minutes. Within about 25 minutes, roughly 594 BTC had moved out of some 500 single-signature wallets. One victim lost around $1.8 million... Coinkite has shipped fixed firmware, but with a warning that matters more than the patch itself. Updating does not repair an existing seed. A seed created with weak entropy stays weak forever. Affected users have to generate an entirely new wallet on updated hardware and move their coins to it.
By Saturday morning Galaxy research was tracking 1,158.66 BTC, worth roughly $75.1 million, taken from 2,673 addresses, according to the article. And "The Coldcard exploit is ONGOING," Galaxy Research posted an hour ago on X.com. "Move Coldcard single-sig funds to safe locations immediately!" We have reported ~600 addresses we believe to be hackers holding funds stolen from Coldcard-generated weak entropy addresses to federal investigators, industry compliance firms, and cross-industry cyber investigators.
Thanks to Slashdot reader BrianFagioli for sharing the news.

"GitHub and the Python Package Index (PyPI) have introduced new policies meant to boost supply chain security," reports SecurityWeek, "by preventing the fast propagation of poisoned package versions and the poisoning of old and long-stable releases." To prevent the fast delivery of malicious code through the immediate fetching of brand-new releases, GitHub has introduced a Dependabot cooldown, where the automation tool waits for at least three days after a release has been published before opening a pull request. "Waiting a few days before adopting a new release gives maintainers, security researchers, and automated scanners time to spot a malicious version and get it pulled before it ever reaches your pull requests," GitHub explains.

The three-day cooldown only applies to non-security version bumps, and the behavior can be modified through the configuration option in the dependabot.yml. "Three days as the default balances two goals: it pushes you past the window where most of these attacks live, and it doesn't hold your dependencies back longer than necessary," GitHub notes.
And the Python Package Index (PyPI) "now rejects new files being uploaded to releases that are older than 14 days," according to a recernt blog post from the Python Software Foundation's security developer-in-residence Seth Larson: This restriction was put in place to prevent old and long-stable releases from being poisoned in case publishing tokens or workflows of PyPI projects were compromised... The discussion of this behavior began during PEP 740 (Digital Attestations) back in January 2024. The discussion was restarted in March 2026 after the popular packages LiteLLM and Telnyx were compromised. These packages were compromised due to a "mutable reference" in these projects' usage of the Trivy GitHub Action...

To quantify how disruptive this change would be to existing workflows, the PyPI database was queried for projects that have published new files to old releases... [O]nly 56 projects of 15,000 had published a [Python] 3.14-compatible wheel more than 14 days after a release was available. This topic was brought to the Packaging Summit at PyCon US 2026 by PyPI Safety & Security Engineer, Mike Fiedler. The rough consensus of the discussion was that the summit attendees thought it was "acceptable to require users to bump to the next version" to support new Python versions. With the data and consensus in hand, Seth moved forward with a patch to reject new files on old releases which was merged July 8th, 2026.

An anonymous reader quotes a report from Reuters: OpenAI has discovered other instances in which autonomous agents have escaped containment as the company expands its investigation of the hacking incident at tech firm Hugging Face that drew global attention this month, two people familiar with the matter said on Friday. The new breakouts were uncovered during the company's publicly announced investigation into how one of its agents escaped what was meant to be a contained testing environment this month, the two people said, and OpenAI is now looking into those instances as well. One of the sources said that the escapes were limited in nature and that none of the agents were thought to have left OpenAI's network.

An OpenAI spokesperson referred to a statement issued by the company on Tuesday that said it was reviewing "broader activity from our models" in addition to the Hugging Face intrusion. The discovery of additional rogue behavior at OpenAI, even if limited in nature, could feed growing appetite for regulation coming out of the White House and elsewhere. The expanded investigation by OpenAI was launched shortly before its primary rival, Anthropic, disclosed that its models were also responsible for a series of break-ins that led to breaches at three other companies dating back to April, according to the two sources and a third source familiar with the matter. The recent discovery of other past breakouts at OpenAI has not previously been reported.

AI safety experts said the new disclosures paint a portrait of a group of cutting-edge labs whose ability to develop dangerous autonomous hacking agents outstrips their ability to keep them under control. "We have a whole industry where the people designing, developing and putting out these tools aren't keeping up themselves to responsibly develop these things and keep them safe," said Maurice Chiodo, a mathematician who works at Cambridge University's Center for the Study of Existential Risk. Reuters could not establish exactly how many incidents OpenAI investigators found or the timings or circumstances under which they occurred. The three sources said OpenAI and outside experts were examining log data from earlier in the year in a bid to understand what took place.

An anonymous reader quotes a report from NBC News: Cyberattacks targeting municipal water systems have been reported in at least seven states this week, prompting the FBI and the Environmental Protection Agency to warn utilities nationwide that hackers are trying to disrupt critical water infrastructure. In a public service announcement Thursday, the agencies said water and wastewater utilities have reported incidents to the FBI, with some malicious activity degrading water operations. The announcement does not name the states.

The warning comes after hackers targeted more than 30 municipal water facilities in Minnesota in an attack that had hallmarks of Iranian meddling, according to a law enforcement official. It is still under investigation. A spokesperson for Minnesota's information technology services agency said Thursday there was no indication the breaches contaminated any municipal water supplies. The federal Cybersecurity and Infrastructure Security Agency said in a separate alert that some larger attacks on water infrastructure had "resulted in boil water notices and sustained manual operations," though it did not say where.

[...] The federal advisory said the malicious cyber actors, or MCAs, targeted specific brands of control systems used by municipal water utilities, though the FBI and the EPA urged operators of all systems to take precautions. [...] The agencies said the hackers remotely accessed internet-facing devices, changed IP addresses and passwords, and caused utilities to lose monitoring and control capabilities. The federal advisory calls on system operators to remove programmable logical controllers, or PLCs, from direct internet exposure by putting them behind secure gateways and firewalls; use strong passwords; and limit communications between authorized control system devices through access control lists.

Google says AI-assisted workflows helped Chrome fix 1,072 security bugs across versions 149 and 150, more than the previous 23 releases combined. The company is also testing twice-weekly security updates and "dynamic patching," which could apply most fixes without requiring users to restart the entire browser. "By leveraging Chrome's multi-process architecture, dynamic patching sequentially replaces background child processes (like the Renderer and GPU) with updated binaries on the fly," says Google in a blog post. PiunikaWeb reports: Alongside dynamic patching, Google is rolling out smarter background updates during periods of minimal user disruption. Starting with Chrome 150 on macOS, the browser takes advantage of the operating system's windowless state. If all Chrome windows are closed but the app remains running in the background, the browser will quietly auto-restart to apply pending updates.

For enterprise environments, IT admins can continue to manage fleet-wide deployments through Chrome Enterprise Core or enforce update prompts using the RelaunchNotification policy. Google's long-term vision is a browser that remains continuously protected in the background without interrupting your daily browsing session. In the meantime, you can manually trigger pending updates by clicking the update prompt in the top-right corner of Chrome.

Anthropic found that Claude models breached three outside organizations during cybersecurity tests because misconfigured environments accidentally gave them access to the internet. The company notified those affected and urged other AI labs to audit their own testing systems. The BBC reports: Anthropic said in a statement that it reviewed more than 140,000 tests to find evidence that Claude - its family of AI models - could access the internet from testing environments that were designed to be sealed off. The tests include so-called "capture-the-flag" evaluations in which Claude was tasked with obtaining information by breaching other systems - a common way that experts assess a model's hacking capabilities.

A "misconfiguration" on systems run by Anthropic and its testing partner left the models with live internet access, allowing them to breach other systems, the San Francisco-based firm said. Anthropic said the earliest incidents date back to April and that it is "approaching the fixes as if the responsibility were ours alone." Neither Anthropic nor the organizations that were breached had noticed the intrusions at the time.

Anthropic said it could have reviewed its records more thoroughly and added that the findings gave the firm "cautious optimism" that such risks can be overcome with more investment and tighter measures. "The broader lesson is not necessarily that AI has developed a fundamentally new attack capability," cyber security expert David Allott told the BBC. "Instead, it is that AI agents can combine capabilities, obtain credentials and system access to take actions autonomously, while adapting scope and scale at machine speed," he added. The announcement comes just days after OpenAI said that its models had breached the systems of other companies, including AI tools platform Hugging Face.

An anonymous reader quotes a report from Wired: OpenAI said Tuesday that the rogue AI agent that breached Hugging Face's platform also hacked multiple third-party accounts and services as part of the attack. It's now clear that the unprecedented security incident, which arose during an internal test of OpenAI's latest AI models, was more extensive than the company initially disclosed. In an updated blog post, OpenAI said that an ongoing review of the incident revealed that "four accounts" tied to "publicly available services" were used by the AI agent as part of a larger effort to hack Hugging Face. The rogue agent apparently found credentials that had been exposed on the open web and used them to break into the accounts.

OpenAI did not disclose what companies or organizations the accounts belonged to, but noted that they were not impacted at "the level of severity or scale of what we've shared related to Hugging Face." One of the additional accounts compromised by OpenAI's agent was used as an "outbound relay and staging path," potentially to obscure where the attack on Hugging Face was coming from, the company said. OpenAI's rogue agent also used another account for data storage to assist with the hack.

Reuters reported on Tuesday that a customer of Modal, a company that offers software infrastructure for training and running AI services, was one of the entities compromised by OpenAI's agent. In a statement to WIRED, Modal's chief technology officer Akshat Bubna confirmed that OpenAI's agent exploited a vulnerability in one of its customer's codebases, which was running on Modal's infrastructure. However, Bubna says, "Modal's platform was not compromised in any way." The identity of the customer could not be determined.

jrnvk shares a report from KMSP: Minnesota IT Services reports that a "coordinated cyberattack" targeted technology at more than 30 community water systems between Sunday, July 26 and Monday, July 27. The state has activated its cybersecurity incident response capabilities to respond to the attacks.

On Monday and Tuesday, FOX 9 reported on notices from four cities that had disclosed the attacks: Plymouth, South St. Paul, Maple Plain, and Braham. All four cities said the impacts of the attacks were limited or mitigated and residents could continue normal water use. The Minnesota Department of Health is not aware of any municipality asking residents to alter their drinking water use as a result of the attacks.

State officials are working with federal and private-sector partners to investigate the attacks, support the affected communities, and strengthen the security of Minnesota's critical infrastructure.

AI-assisted vulnerability discovery has yet to produce the expected surge in real-world attacks: VulnCheck found that only 14 of 1,061 attributed discoveries, or 1.3 percent, had been exploited, which is "almost identical to the rate across all vulnerabilities in VulnCheck's dataset," reports The Register. "That's a far cry from the narrative that frontier AI is dramatically tilting the balance in attackers' favor by churning out instantly weaponizable bugs." The findings suggest AI is currently better at increasing the volume of bugs found than making them easier to weaponize. From the report: The report takes particular aim at Anthropic's much-publicized Project Glasswing, unveiled in April with warnings that AI-assisted vulnerability discovery could allow attackers to hijack systems, disrupt operations, or steal data. Claude Mythos may have identified 23,019 vulnerability candidates, but there's remarkably little public evidence showing what became of most of them. VulnCheck notes that only 126 have been published as CVEs, that just one has been confirmed exploited in the wild, and that Anthropic's public disclosure record has seen little movement since Project Glasswing launched.

But that doesn't mean AI-assisted vulnerability research has failed, according to Patrick Garrity, security researcher at VulnCheck. "AI-assisted vulnerability discovery clearly has value for both attackers and defenders," Garrity wrote. "The data does not suggest that AI-discovered vulnerabilities are inherently more likely to be exploited than those found through traditional methods." Instead, he argues, AI is simply helping researchers discover more flaws, giving defenders an opportunity to patch them before criminals get there.

Garrity stopped well short of declaring the threat overblown forever, but he did suggest some of the rhetoric has outpaced reality. "The data so far, including Anthropic's own stalled disclosure ledger, suggests that AI-assisted vulnerability discovery and frontier capabilities have been overhyped relative to the evidence available today," he wrote. "That doesn't mean the risk is imaginary. It means the impact has been real but modest."

Anthropic's Claude Mythos Preview has "found flaws in a weakened version of a digital encryption standard that is in pervasive use throughout the internet," reports The New York Times. Researchers said the model discovered novel attacks against weakened versions of AES and the experimental post-quantum HAWK system, including one that was 200 to 1,000 times faster than previous human-developed methods. From the report: The flaws identified do not concern a cryptographic standard currently in use today, which means that modern banking and communication systems are not subject to immediate potential intrusions from A.I. Instead, Anthropic's technology cracked a watered-down version of an algorithm for Advanced Encryption Standard, or A.E.S., a ubiquitous protocol that safeguards web traffic, wireless networks, data storage and more. It is common to perform tests on weaker versions of encryption algorithms to understand whether more powerful computers could someday crack the actual standards, akin to solving a simpler math problem to identify whether patterns may exist for a more complicated one. In the testing, Mythos was able to break the weaker version of Advanced Encryption Standard in a way that Anthropic said made an assault 200 to 1,000 times faster than what previous human research had managed to do. While the immediate ramifications are minimal, the long-term implications could be significant. In previous tests, large-language models seemingly could not match or best what humans can do in the mathematically dense field of cryptographic research, but their rapid advances could suggest a future in which top models can surmount traditional internet security protections that are foundational to just about everything that takes place on the internet.

[...] In addition to the attack on the encryption standard, Mythos also orchestrated another improved attack against a different digital cryptographic system known as HAWK that is designed to be bulletproof against both traditional and quantum computers. HAWK is not currently in use, but under consideration by the National Institute of Standards and Technology to become a new standard. The HAWK attack was validated by its authors, and independent cryptographers reviewed the Advanced Encryption Standard attack, Anthropic said, adding that it had shared its findings with the U.S. government and industry partners ahead of publication. Mythos devised the cryptographic attack on A.E.S. almost entirely autonomously, Anthropic said, but only after first refusing to contemplate the problem because it believed it was impossible to improve on existing methods of analysis. But after some coaxing, the chatbot sat with the puzzle for about a week before engineering its novel attack. Two human researchers then worked for nearly a month to verify that the method appeared correct. "Given that we are constantly underestimating the power and time of availability of future models, are we really comfortable that two years from now strong encryption won't be threatened?" said Glenn S. Gerstell, the former general counsel at the National Security Agency.

"Mathematicians would tell you that it shouldn't be possible given current computing powers to break strong encryption in any meaningful time," added Mr. Gerstell, who helped write a report on cryptology in 2022. "But I don't think the capabilities of future models in the medium term -- before quantum computing or quantum-proof cryptography -- should be dismissed as trivial in this context."

wiredmikey shares a report from SecurityWeek: Nvidia and a large group of technology, cybersecurity, and enterprise software companies have launched new initiative aimed at developing and sharing open source tools, models, and techniques for securing AI systems and agents. The new Open Secure AI Alliance aims to give defenders more open tools for testing, auditing and protecting AI models and agents. Nvidia points to the recent security incident involving OpenAI and Hugging Face, noting that when closed AI tools could not differentiate between attackers and defenders and blocked forensic work, Hugging Face used the open-weight GLM 5.2 model on its own systems to review over 17,000 actions and contain the breach. "The right response is not to deny defenders access to capable open systems. It is to pair openness with strong safeguards, clear rules against malicious misuse, rigorous evaluation and rapid remediation. In cybersecurity, the safer path is the one that gives more defenders the ability to test, verify and strengthen the systems on which society relies," Nvidia said.

Thanks to longtime Slashdot reader SphericalCrusher for also sharing the news.