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The Russian state-sponsored hacking group known as Turla has transformed its custom backdoor Kazuar into a modular peer-to-peer (P2P) botnet that's engineered for stealth and persistent access to compromised hosts. Turla, per the U.S. Cybersecurity and Infrastructure Security Agency (CISA), is assessed to be affiliated with Center 16 of Russia's Federal Security Service (FSB)

The Russian state-sponsored hacking group known as Turla has transformed its custom backdoor Kazuar into a modular peer-to-peer (P2P) botnet that's engineered for stealth and persistent access to compromised hosts. Turla, per the U.S. Cybersecurity and Infrastructure Security Agency (CISA), is assessed to be affiliated with Center 16 of Russia's Federal Security Service (FSB)Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

On Thursday, Google Cloud CEO Thomas Kurian issued a call for “forward-deployed engineers” to apply for jobs in the company’s go-to-market AI team. Their task: help non-tech organizations scale up their AI deployments.

That term — forward-deployed engineers, FDE for short — has been coming up a lot lately in conversations with CTOs, software engineers, and experts tracking the technology and job markets.

Google currently has 1,513 openings for that specific role and OpenAI, which just this week launched an organization called the Deployment Company, has 31. Microsoft is on board, too; in March, it partnered with Accenture to launch a forward-deployment partnership.

OpenAI’s new Deployment Company is, not surprisingly, designed to “help organizations build and deploy AI systems they can rely on every day across their most important work,” the company said in a blog post.

Forward-deployed engineering has seen the fastest growth in jobs created by AI, with the number of positions increasing 42-fold between 2023 and 2025, LinkedIn reported in a study earlier this year. (AI engineer jobs, by comparison, have grown 13-fold in that same time frame.)

Vendors and service providers created the FDE position to help clients install AI, said Jack Gold, principal analyst at J.Gold Associates.

Many non-tech firms have taken shots at deploying AI projects internally, without success or quick ROI. Some of the reasons those efforts haven’t worked out include poor vision, lack of talent, skimpy budgets, and underestimating the complexity of deploying AI.

That’s led to the arrival of FDEs — essentially hired guns for AI deployments. They focus on successful outcomes for customers instead of writing code. 

“They have skills that the organization may not have, and usually have done similar work with others before, so they bring expertise that companies need,” Gold said. 

FDEs analyze strategies, battle plan, discover applications, build agentic frameworks, and roll out AI systems with help from customers’ own domain experts and engineers. They also work with AI models, solve context and reasoning problems, evaluate models, and put security and governance guardrails in place. 

A good FDE can provide a much higher probability of successful implementations, Gold said.

Many software engineers have worried that AI would make their careers irrelevant. But the FDE role embodies where the role is going, analysts and IT experts said.

Code can now be written using human language, allowing software engineers to focus  more on outcomes than servicing code, said Alex Spinelli, senior vice president for AI and developer platforms at Arm.

“I think that’s where engineering is moving to…, much more blending of the sort of technical product management thinking, design thinking, and architecture thinking,” Spinelli said.

While AI can make engineering invisible, it also opens a toolbox to solve business problems, said Stephen Jones, CUDA architect at Nvidia. “You have more tools than you ever had before to solve problems that were previously completely unsolvable,” he said.

The FDE roll in the future might well entail reducing AI costs for customers, said Deepak Seth, senior director analyst at Gartner. “Some companies are moving towards outcome-based pricing…. [And] when people start realizing the real cost of tokens, then companies will start looking at token efficiency.”

Gold said the FDEs’ implementation efforts can help drive those token savings. “If the implementation is optimized, it can save on token costs for processing the workflows, …especially as companies move to agents,” he said.

If you think about it, it’s in the national interest for Apple to work with Intel to develop at least some capacity for silicon production outside of Taiwan. It’s also in Apple’s interest, as its continued growth means it needs more and more chips to put inside an ever-expanding product catalog.

During Apple’s Q2 26 fiscal call, CEO Tim Cook said the lack of what he called “high-end nodes” is affecting sales, particularly for Macs. He shared this news even as the company’s MacBook Neo is setting new sales records for the Mac.

Apple’s success is creating a chip problem

The need to source all those chips might have prompted Apple to reach out to Intel on how the two firms could work together on processor production once again. Supply chain analyst Ming-Chi Kuo now believes Apple is evaluating Intel’s advanced node technologies with a view to processor supply. “Apple’s wafer plans at Intel reflect the technology lifecycle of the [Intel] 18A-P series: small-scale testing in 2026, ramp in 2027, continued growth in 2028, and decline in 2029,” he said.

If it comes to fruition, the arrangement is a probable lifeline for Intel, which the US government feels is strategically important enough it acquired an $8.9 billion stake in the company to secure domestic advanced chip manufacturing capacity.

Intel could be TSMC’s +1

While the arrangement with Intel could end TSMC’s exclusive hold on chip production for Apple, it doesn’t seem to be a huge threat. The Taiwan-based company will continue to manufacture roughly 90% of Apple’s most powerful chips, even as the number of processors required to satiate Cupertino’s voracious appetite grows. For Intel, the promise of even 10% of Apple’s global processor demand is a lifeline for company revenue. TSMC, meanwhile, continues to invest in US chip manufacturing facilities.

Apple’s relationship with the US government suggests it also recognizes the government’s position on the national significance of Intel, which is why diverting at least some of its orders back to its old Mac processor supplier makes sense. It’s good business for Apple to maintain supplier flexibility, while it’s also good citizenship to support the government in its attempt to protect domestic chip manufacturing. 

Entry-range Apple, with a small touch of Intel

Industry and media speculation in recent months suggests that Intel will not be making the most advanced Apple Silicon chips, concentrating instead on older chip designs used in entry-level iPads, iPhones, and Macs. 

Speculation also suggests Apple intends to split up the iPhone launch cycle soon, offering advanced devices (bearing chips made by TSMC) in September, with lower-end product refresh events such as for the iPhone ‘e’ series each spring.  This is what Apple did this year, when it also introduced the MacBook Neo, a system also powered by an older processor. 

It’s plausible to think that Intel will eventually manufacture the Apple Silicon chip used inside the entry-level Mac. Of course, this would still be Apple Silicon — Intel would just make them in America. 

Could Apple’s entry-level Macs one day be made in America?

Of course, the decision to widen chip manufacturing in the US leans into Apple’s ongoing move to make more of its hardware in America, too. Apple already makes servers for Private Cloud Compute in the US and has confirmed it will begin manufacturing some Mac mini models later this year.

>“Apple is deeply committed to the future of American manufacturing, and we’re proud to significantly expand our footprint in Houston with the production of Mac mini starting later this year,” said Cook when this was announced.

>But with Intel expected to begin churning out processors for use across Apple’s entry-level devices, how likely is it that the company will begin to make more of the hardware that runs those chips in the USA as well? Does the decision to manufacture chips in the US make a future in which the MacBook Neo is “Made in the USA” possible?

>Even if it did, to what extent would the cost of manufacturing in the US make it difficult for Apple to maintain the $599 starting price on those Macs, unless the factories churning them out were almost totally automated? 

>You can follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Two vulnerabilities in the Avada Builder plugin for WordPress, with an estimated one million active installations, allow hackers to read arbitrary files and extract sensitive information from the database. [...]

Microsoft is updating the Edge web browser to ensure it no longer loads saved passwords into process memory in clear text at startup after previously stating it was "by design." [...]

Stolen browser sessions and authentication tokens are becoming more valuable than stolen passwords. Flare explains how the REMUS infostealer evolved around session theft and operational scalability. [...]

Cybersecurity researchers have disclosed a set of four security flaws in OpenClaw that could be chained to achieve data theft, privilege escalation, and persistence. The vulnerabilities, collectively dubbed Claw Chain by Cyera, can permit an attacker to establish a foothold, expose sensitive data, and plant backdoors. A brief description of the flaws is below -

Cybersecurity researchers have disclosed a set of four security flaws in OpenClaw that could be chained to achieve data theft, privilege escalation, and persistence. The vulnerabilities, collectively dubbed Claw Chain by Cyera, can permit an attacker to establish a foothold, expose sensitive data, and plant backdoors. A brief description of the flaws is below - Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

The UK’s competition regulator has launched a broad antitrust investigation into Microsoft’s business software ecosystem, opening a new front in growing regulatory scrutiny of how cloud platforms, productivity software, and embedded AI capabilities may affect competition in enterprise technology markets.

UK’s Competition and Markets Authority (CMA) said in a statement that it had opened a Strategic Market Status (SMS) investigation into Microsoft’s business software operations under the country’s new digital markets regime.

The regulator said it will assess whether Microsoft has “substantial and entrenched market power” and a “position of strategic significance” in business software markets.

“The investigation will assess whether Microsoft is using its position in business software to limit competition in cloud services, cybersecurity, communications, and AI,” the regulator said in a statement.

The case is the fourth strategic market status (SMS) investigation the regulator has opened since the UK’s digital markets competition regime came into force in January 2025, following earlier SMS cases into Google search, Apple’s mobile platform, and Google’s mobile platform.

A designation decision is due by February 2027, the statement added.

“Our aim is to understand how these markets are developing, Microsoft’s position within them and to consider what, if any, targeted action may be needed to ensure UK organisations can benefit from choice, innovation and competitive prices,” CMA chief executive Sarah Cardell said in the statement.

The scope covers productivity software, PC and server operating systems, database management, and security software, the CMA said, naming Windows, Word, Excel, Teams, and Copilot. Microsoft has more than 15 million commercial users across its UK ecosystem.

AI integration central to the case

The CMA will examine how AI competitors integrate with Microsoft’s business software and whether customers can mix AI tools from rival suppliers within Microsoft environments, the regulator said, citing the rapid embedding of AI functionality and a shift towards agentic AI in workplace tools.

Microsoft has pushed Copilot across Microsoft 365 tiers and expanded agentic features inside Office and Teams over the past year.

That AI overlay has not yet reset the lock-in question, but soon will, said Dario Maisto, senior analyst at Forrester. “Copilots have the potential to make employees and organizations more dependent on existing vendors, as any other feature embedded in the suites,” Maisto said. “At this stage, they do not change the enterprise lock-in conversation but will in the near future as adoption scales.”

For CIOs, switching away is no easier than swapping any other layer of the stack, Maisto added, describing diversification as as difficult as finding enterprise-grade alternatives to other Microsoft products.

What the CMA will examine

The investigation will assess whether Microsoft has SMS in business software and whether it uses that position to limit customer choice, the CMA statement added. It will look at product bundling, interoperability limits, and default settings that may stop customers from switching or weaken competitive pressure from rivals.

UK customers may not always be able to combine Microsoft software with products from other providers, the regulator said, limiting access to the best products at competitive prices.

An SMS finding would also let the CMA act on an unresolved concern from its earlier cloud market investigation, which found that Microsoft’s software licensing was reducing competition in cloud services. AWS previously told the regulator that Microsoft’s 2019 and 2022 licensing changes made it harder to run Microsoft products on Google Cloud, AWS, and Alibaba.

Wider scope than previous SMS cases

The case is wider in scope than any previous SMS investigation, covering productivity tools, operating systems, database management, and security software in a single ecosystem-level review. The previous three designations each targeted a narrower set of activities.

The SMS status does not assume wrongdoing, the CMA said. If Microsoft is designated, the regulator can impose conduct requirements or pro-competition interventions, subject to the relevant legal tests.

The probe runs alongside the CMA’s ongoing engagement with AWS and Microsoft on cloud egress fees and product interoperability, announced in March after the regulator decided not to pursue SMS designation on cloud services.

Sovereignty push runs in parallel

For enterprise customers, the investigation comes as many organizations pursue multi-cloud strategies while simultaneously consolidating technology stacks around a smaller number of strategic vendors.

Maisto said interoperability is likely to become an increasingly important — and difficult issue for regulators and enterprise buyers.

“Interoperability is a big topic these days, but it is easier said than done,” he said. “What works on paper in a policy may not work in reality.”

Maisto also pointed to growing European discussions around “tech sovereignty”.

“The European Commission is considering rules to restrict use of US cloud platforms to process sensitive government data,” he said. “The Commission is expected to present its ‘Tech Sovereignty Package’ on May 27 to define sectors that have to be hosted on European cloud capacity.”

At the same time, Maisto said he does not expect regulatory intervention alone to significantly alter market concentration trends.

“We do not foresee a massive decrease in market concentration,” he said.

Microsoft did not immediately respond to a request for comment.

Microsoft is introducing a new capability that will allow it to remotely roll back problematic Windows drivers delivered through Windows Update. [...]

In Your Biggest Security Risk Isn't Malware — It's What You Already Trust, we made a simple argument: the most dangerous activity inside most organizations no longer looks like an attack. It looks like administration. PowerShell, WMIC, netsh, Certutil, MSBuild — the same trusted utilities your IT team uses every day are also the preferred toolkit of modern threat actors. Bitdefender's analysis

In Your Biggest Security Risk Isn't Malware — It's What You Already Trust, we made a simple argument: the most dangerous activity inside most organizations no longer looks like an attack. It looks like administration. PowerShell, WMIC, netsh, Certutil, MSBuild — the same trusted utilities your IT team uses every day are also the preferred toolkit of modern threat actors. Bitdefender's analysis [email protected]

OpenAI has disclosed that two of its employee devices in its corporate environment were impacted via the Mini Shai-Hulud supply chain attack on TanStack, but noted that no user data, production systems, or intellectual property were compromised or modified in an unauthorized manner. "Upon identification of the malicious activity, we worked quickly to investigate, contain, and take steps to

OpenAI has disclosed that two of its employee devices in its corporate environment were impacted via the Mini Shai-Hulud supply chain attack on TanStack, but noted that no user data, production systems, or intellectual property were compromised or modified in an unauthorized manner. "Upon identification of the malicious activity, we worked quickly to investigate, contain, and take steps to Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

On Thursday, Microsoft shared mitigations for a high-severity Exchange Server vulnerability exploited in attacks that allow threat actors to execute arbitrary code via cross-site scripting (XSS) while targeting Outlook on the web users. [...]

“If you can’t measure it, you can’t fix it.” 

That’s a common saying in business, and it tends to be true. But what if the thing you want to fix is your employees’ attitudes? 

The AI revolution makes it possible to measure emotions and mental states. So why not use it widely and fix what’s broken? 

That’s the idea behind emotion AI, which is also called “affective computing,” “sentiment analysis,” or “algorithmic affect management.” The idea is to use sensors and AI to detect, interpret, classify, and act upon human emotions in the workplace. 

Thanks to improvements and breakthroughs in a wide range of technologies (including computer vision, natural language processing, speech and voice analysis, biometrics, machine learning and deep learning, and edge computing hardware) emotion AI is now possible. 

Many companies have come forward to provide ready-to-use solutions for emotional AI apps, including Cogito, Affectiva, Hume AI, Entropik, and HireVue.

The idea is simple: Collect data from employees, process it through AI, and get a result that shows how an employee feels. Depending on the solution, the data comes from: 

• Vocal features — pitch, tone, cadence, micro-pauses, vocal stress
• Facial expression — video analysis of video calls and through desktop cameras
• Text — mass sentiment analysis on emails, Slack/Teams messages, survey responses, and performance reviews
• Physiological biosignals — heart rate variability, galvanic skin response (via wearables)
• Behavioral telemetry — keystroke cadence, mouse dynamics, app-switching patterns
• Posture and gaze — computer vision analysis from cameras installed in workplaces

Despite the progress and variety of solutions, this whole area is problematic for businesses. 

Why companies want to use emotion AI

The range of business goals driving emotion AI is vast. The most defensible reason is safety. Workers in risky jobs, such as factory workers and truck drivers, could be protected with AI tools that help avoid injury and death. A common example is technology that detects when a truck driver is dozing off and either sounds an alarm or switches to autopilot to take control of the truck and pull over. 

Another goal is better customer service. Companies like MetLife use software that monitors call center agents’ voice, tone, and pitch to make sure they don’t get snippy or express frustration with customers. 

HR departments could use AI to understand the workplace mood by analyzing company communications and employee surveys. Companies can also check for employee burnout and use the technology for hiring. By applying emotion AI to a video job interview, companies might make better hires. 

Emotion AI in the workplace can offer other benefits such as lowering employee turnover, healthcare expenses, and safety risks while boosting customer satisfaction, worker productivity, and insight into team or managerial dysfunction.

What’s wrong with emotion AI

While measuring, then acting upon, the emotions and mental states of employees sounds like a powerful idea, it’s often based on bad science. 

Emotion AI systems that lean on facial expressions, for example, are based on a theory by Paul Ekman, an American psychologist at the University of California, San Francisco. He theorized back in the late 1960s that a small set of basic human emotions produces universal, reliably readable facial expressions across cultures. 

But Ekman’s theory was shown to be problematic by a 2019 meta-analysis led by Lisa Feldman Barrett, in an article published in Psychological Science in the Public Interest. She looked at more than 1,000 studies and concluded that you can’t always reliably infer people’s emotional states from facial movements alone. 

Most emotion AI solutions are based on the assumption that everyone’s emotions can be interpreted the same way, and that’s almost certainly wrong, given how different people can be in appearance, voice, personality and physiology. 

Like many areas of business and leadership in recent years, AI is often seen as a solution to the challenges of managing a lot of employees. 

Emotion AI holds out the promise that leaders can bypass the need to inspire, motivate and educate employees so that their actions are aligned with company goals, and instead try to achieve this alignment through hyper-surveillance. 

But that’s unfair, say some emotion AI supporters. Many organizations use emotion AI systems claiming to help employees in some way. Research suggests that this might backfire. 

A 2024 Finnish case study found that workplace emotion-tracking technology tends to undermine wellbeing more than support it and has a bunch of problems. First, the technology often fails to work. Specifically, it claims to identify mental states like “stressed” or “engaged,” which turn out not to faithfully reveal actual internal moods. 

Second, the quality of emotional AI output often varies by race. The study found that the faces of black people were wrongly labeled as “angry” or “contemptuous” more often, even when showing the same facial expressions as white participants. That’s just one example of bias that might come from treating employees differently based on an AI’s flawed ability to interpret human emotional expression. 

Third, they found that claims of “anonymous aggregation” turn out to be false in practice with smaller teams. The data can unintentionally reveal identities, leading to privacy violations. 

Fourth, emotion AI may have the practical effect of requiring “emotional labor,” which means mustering up and conveying the right emotions as part of the job, on an ever-growing range of professions. 

And finally, emotion AI is prone to mission creep. Companies often deploy it for one purpose then drift toward increasing worker surveillance. 

Emotion AI may have no future

While emotion AI is growing in some sectors of the economy, it’s being forcibly shrunk through growing regulatory action. The European Union last year banned emotion AI in the workplace and in educational settings, with narrow exceptions for medical or safety reasons. Multinational corporations are gravitating to the European standard. 

There’s even been limited legal or regulatory action against the technologyin a few states, including California, New York, and Illinois.

Some companies have voluntarily rejected emotion AI. Microsoft, for example, announced in June 2022 that it would retire the Azure Face API’s emotion-recognition capabilities (along with inference of gender, age, smile, facial hair, hair, and makeup) as part of an overhaul of its Responsible AI Standard. 

The company’s Chief Responsible AI Officer, Natasha Crampton, explained the change by citing “the lack of scientific consensus on the definition of ’emotions,’ the challenges in how inferences generalize across use cases, regions, and demographics, and the heightened privacy concerns around this type of capability.” Microsoft also worried that such technology “can subject people to stereotyping, discrimination, or unfair denial of services.”

So while there are real and helpful uses for emotion AI in some cases, the science behind it is weak, the results are often misleading, employees generally dislike it and find it stressful, bias is likely built in, privacy violations are likely — and it might not even be legal internationally or even across all American states. 

Tempting as it is, emotion AI is too problematic to deploy. 

AI disclosures: I don’t use AI for writing. The words you see here are mine. I used a few AI tools via Kagi Assistant (disclosure: my son works at Kagi) as well as both Kagi Search and Google Search as one part of my fact-checking for this column. I used a word processing product called Lex, which has AI tools, and after writing the column, I used Lex’s grammar checking tools to hunt for typos and errors and suggest word changes.

Microsoft has disclosed a new security vulnerability impacting on-premise versions of Exchange Server that it said has come under active exploitation in the wild. The vulnerability, tracked as CVE-2026-42897 (CVSS score: 8.1), has been described as a spoofing bug stemming from a cross-site scripting flaw. An anonymous researcher has been credited with discovering and reporting the issue. "

Microsoft has disclosed a new security vulnerability impacting on-premise versions of Exchange Server that it said has come under active exploitation in the wild. The vulnerability, tracked as CVE-2026-42897 (CVSS score: 8.1), has been described as a spoofing bug stemming from a cross-site scripting flaw. An anonymous researcher has been credited with discovering and reporting the issue. "Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]