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US authorities are getting decidedly twitchy about frontier AI models. Just a couple of weeks after ordering Anthropic to prevent foreign companies from getting hold of its latest release, Mythos/Fable 5, it’s been putting the squeeze on another AI company..

Now, the Trump administration is asking OpenAI to hold back on the general release of GPT-5.6, according to a report from Bloomberg.

OpenAI CEO Sam Altman reportedly told employees that the government is asking that the model be released only to a short list of trusted partners, initially 20, before being more widely disseminated.

Altman reportedly told staffers that the administration was getting nervous about the capabilities of the latest AI tools. It didn’t go as far as forbidding access to foreign users but it’s clear that the White House is looking to act as the power of the new models becomes more apparent.

The administration’s actions will undoubtedly cause some anxiety among AI companies, particularly in light of OpenAI’s and Anthropic’s upcoming IPOs. There will be concerns that new software developments could be postponed or even halted. However, it should also be noted that the administration was already displeased with Anthropic over its moral stance on defense issues, so the action against Mythos should be placed in context.

Indeed, the government is trying to play down such fears. Bloomberg quoted a White House official as saying that the Trump administration continues to collaborate with frontier AI labs to develop shared approaches for addressing the challenges of scaling the technology.

Chinese tech giant Tencent is set to launch an AI assistant inside WeCom, its Slack-like collaboration tool for enterprises. The new tool, Dayuan, is built on the latest large language models from Chinese AI developer DeepSeek.

Tencent announced the news in a post on Chinese messaging platform Weibo by Tencent’s public relations manager Zhang Jun. Dayuan will automatically understand user requests and will respond according to the demands of the user, he wrote, according to a translation by Bloomberg. “At any time within WeCom, simply swipe left to summon Dayuan. It can intelligently recognize the interface you’re on, understand what you’re asking, and help you resolve issues more effectively,” he wrote, according to the report.

In addressing the Chinese enterprise market, Tencent has an advantage over other companies in the AI space because it has a vast reservoir of customers who use WeCom. Earlier this month, it announced a range of AI productivity agents to address the demand for more AI tools across enterprises.

Tencent has been intensifying its efforts in the AI space in an attempt to beat US competition. In April, it launched an updated version of its Hunyuan model to catch up with more established AI companies such as ByteDance, Alibaba and DeepSeek.

The launch of Dayuan with its vast supply of user data will provide a step-up for Tencent and will reinforce Chinese efforts to establish serious AI competition to US products.

Following a seven-month investigation, the European Commission has reached a preliminary decision that Amazon’s and Microsoft’s cloud platforms — AWS and Azure, respectively — should be classified as “gatekeepers” under the EU’s Digital Markets Act (DMA), Reuters reports.

The DMA, also known as the Digital Markets Regulation, aims to limit the market power of dominant players. For cloud services, this would entail, among other things, requirements for increased interoperability and data portability, as well as restrictions on how these services might favor their own products and services.

The Commission pointed, among other things, to AWS and Azure’s large market shares, extensive investments, large customer bases, and high costs for customers who wish to switch providers.

If the decision is approved, the companies would be subject to the same type of regulations that apply to several of the largest technology platforms. Both Amazon and Microsoft were critical of the assessment. Amazon argued that the EU already regulates the cloud market through the Data Act, while Microsoft believes the EU is underestimating the growing competition from Google Cloud.

Amazon and Microsoft will have the opportunity to respond to the European Commission’s preliminary conclusions before a final decision is expected later this year.

Australia’s Security Intelligence Organization (ASIO) has uncovered an attack on a critical infrastructure operator’s network. State-sponsored actors had compromised the network and were preparing to sabotage it, according to its director general, Mike Burgess.

Other countries face similar cyber-threats to critical infrastructure.

It’s impossible to exaggerate the danger that the country is facing from cyberattacks on its infrastructure, he said, presenting ASIO’s annual threat assessment this week. “We categorize them into ‘threats to life’ and ‘threats to our way of life,’” he said.

In this case, the hackers had gained access to login details and passwords for active users of the networks, including the IT professionals guarding it. ASIO had set up a specific team to deal with the issue of cyber sabotage.

Australia isn’t alone in facing threats from the same state actors, Burgess said. “We struggle to find a single country in our region that has not been compromised by this state’s cyber apparatus.”

This meant that Australia is facing a persistent threat in the future, one that could have consequences for the way that the critical infrastructure is deployed and managed. “The biggest challenge is the cumulative one: in a degraded security environment defined by concurrent, cascading, compounding threats, when resources are limited, how and what do you prioritize?” he said.

This article first appeared on CSO.

AI won't replace GRC analysts, but it can eliminate much of the repetitive work they do. Anecdotes walks through building an agent that continuously monitors controls, identifies evidence gaps, and opens remediation tasks. [...]

A flaw in the Linux kernel's traffic-control subsystem can let a local unprivileged user gain root on affected systems. CVE-2026-46331, nicknamed "pedit COW," is an out-of-bounds write in the packet-editing action (act_pedit) that corrupts shared page-cache memory. A public, working exploit appeared within a day of the CVE assignment on June 16. Red Hat rates the flaw as Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

A high-severity flaw in Amazon Q Developer let a malicious repository run commands and steal a developer's cloud credentials. The path was short: a developer opens the repo, trusts the workspace, and Amazon Q does the rest. Amazon has patched it. Tracked as CVE-2026-12957 (CVSS 8.5), the bug sat in how Amazon's AI coding assistant handled Model Context Protocol (MCP) servers. Wiz Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

AI is beginning to reshape how penetration testing workflows are organized. For years, the penetration tester’s workflow has been a labor-intensive ritual: scan, enumerate, research, exploit, and report. But new frameworks like Dark Moon are attempting to codify that intuition, turning the "human-in-the-loop" process into a machine-coordinated workflow. But is this a genuine evolution in how we secure Linux environments, or just a sophisticated wrapper around the same old tools?

SSH persistence usually does not look malicious at first. The login succeeds normally, the session opens cleanly, and the account already exists on the server, which is exactly why attackers continue using SSH keys after gaining a foothold on Linux systems.

Apple’s decision to raise prices in response to memory cost increases is not unique to the company. If Apple has to do it, everyone else will as well. 

Apple announced stiff price increases Thursday — up to 25% in some cases — that extended across most products, including refurbished Macs and iPads (which saw prices increase up to $330). Apple might have left iPhones out of the mix for now, but they’ll likely see price increases when new models appear this fall. Omdia believes the memory price crisis spells the end of low-cost smartphones.

The price hikes begin

“We had assumed a price hike of $100 to Pro and ProMax iPhones, and $50 hike to base models,” wrote IDC Senior Director Nabila Popal. “However, seeing the price hikes to iPads and Macs going as high as $300 for some models, my personal instinct says the hike to iPhones may be even higher than what we assumed — perhaps even $200 to the Pro/Pro Max models. I think the days of $50 price increases are over.”

What’s driving all this? The answer, increasingly, is AI. The buildout of large language model (LLM) infrastructure requires vast quantities of high-bandwidth memory and that appetite is accelerating faster than manufacturers can respond.

Will Apple suffer? Maybe, though perhaps not too much. Popal notes that the introduction of Siri AI will give a large number of existing users a reason to upgrade. Given most of these devices are sold on installment plans, even a $200 price increase over 36-months might not pose a major barrier to sales. IDC expects iPhone sales to decline, but only by 5% — while the rest of the industry shrinks.

The worst is yet to come

This may not be the worst of it. Major players now warn that the supply-demand gap could continue to widen in the coming years. The higher costs that result will spread across all types of electronic devices, so anything with memory, a processor, or storage will become more expensive.  

Microsoft announced its own price increase, adding up to $150 to the cost of Xbox this week. And Lenovo made its own contribution when it warned that high memory prices will become the new normal into 2030, and prices might never return to early-2025 levels.

Micron, Samsung, and SK Hynix describe the situation as beyond their control, saying they’re having difficulty meeting demand even for their top customers. These companies are generating massive profits all the while. 

In Lenovo’s case, the company claims that while it is introducing additional manufacturing capacity, this is not making a dent in the supply-demand imbalance. SK Hynix is expected to expand its manufacturing capability by accelerating its original 2040 expansion plans to 2030, at which time it should have tripled output; even that might be insufficient to meet demand. 

A long journey ahead

“We currently do not have line of sight as to when memory supply will be able to catch up with increasing demand,” Micron CEO Sanjay Mehrotra said this week.

With no end in sight, Wedbush Securities analyst Dan Ives says he believes Apple is attempting to get ahead of the inflationary spiral, speculating that the latest price increases bake future increases into their model. 

Memory prices began to spiral out of control last fall, with prices today reaching levels no one anticipated. They rose as much as 98% in the first quarter of 2026 and are set to jump by another 58% to ​63% in the current quarter, according to TrendForce.

This consequential uncertainty is affecting tech stocks. Asian stock markets fell sharply on Friday, led by a sell-off in technology firms. Trading on South Korea’s Kospi was temporarily suspended as a result — for the third time this week. Apple shares are down again, and the sell-off is expected to continue.

So, who’s winning?

The beneficiaries of this memory squeeze are not hard to identify. While consumers face higher prices for phones, laptops and games consoles, the companies driving memory demand — the hyperscalers and AI firms building out server farms at extraordinary scale — are posting record revenues. The costs flow down; the profits flow up.

Some, including Naomi Klein, see it as a kind of strip mining of human intellect and ingenuity, a cultural wealth transfer in which human innovation is packaged and resold as competing chatbots, for a fee. 

There are signs this may not be sustainable. A UBS Group survey finds approximately 60% of companies have started curbing AI spending because of token costs, shifting to low-cost and open-source models. But even if AI-driven memory demand softens, there is little reason to expect consumer tech prices to follow. History suggests they rarely do.

Truncated dreaming

For Apple watchers, it was pleasant enjoying a few months in which the dream of a sub-$500 Mac was realized, only for that happy reverie to be dashed by the VC-funded race to deploy AI server farms for the benefit of those with pockets deep enough for the tokens to feed them. 

Please join me on social media at BlueSky,  LinkedIn, or Mastodon, even better, please subscribe to The Core for your daily collection of human-curated Apple News.

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Thursday added a critical remote code execution vulnerability impacting PTC Windchill PDMlink and PTC FlexPLM enterprise Product Data Management (PDM) and Product Lifecycle Management (PLM) software to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation. The vulnerability in question is Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

DirtyClone is a new Linux kernel privilege escalation in the DirtyFrag family. JFrog Security Research published a working exploit walkthrough for the flaw on June 25, the first public demonstration for this variant. Tracked as CVE-2026-43503 (CVSS 8.8), it lets a local user corrupt file-backed memory through a cloned network packet and gain root. The patch landed in Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

AI agents are moving through enterprise environments, inheriting permissions, traversing systems, and executing decisions at machine speed with minimal oversight. The identity infrastructure built to govern human access wasn't designed for autonomous actors, and the gap between what enterprises are deploying and what their governance programs actually cover is widening fast. This guide breaks [email protected]

Cybersecurity researchers have flagged yet another evolution of the supply chain attack linked to the Mini Shai-Hulud, Miasma, and Hades malware family that has compromised a new set of npm packages, even as it has propagated to the Go ecosystem. "The latest activity includes malicious npm releases affecting LeoPlatform and RStreams packages, GitHub Actions workflow abuse, and a related Go Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

For years, Microsoft has hyped Windows 11 cas an OS with AI, and the company is finally putting the building blocks in place for that transformation.

Microsoft execs shared examples of how the company is integrating AI in Windows 11 at its Build event earlier this month, highlighting how AI models and agents will make the OS smarter, allowing users to interact with it using natural language and intent.

Specifically, Windows 11 PCs will provide unmetered intelligence so users can run AI for free without a network connection. “No token cost. No sensitive data leaves the device. It also reduces latency,” Anastasiya Tarnouskaya, product manager for Windows ML, said during a Build session.

Hardware makers introduced AI-capable hardware before the applications were available. But Tarnouskaya said more than 500 million PCs are already running local AI workloads. “Thanks to recent advancements in AI models, hardware, and the software stacks that run them, today, every Windows PC is becoming increasingly AI-capable,” she said. 

The AI experiences are blended into apps and the Windows UI, not working only as chatbots such as those offered by ChatGPT or Gemini. 

Microsoft Office, Photos and Teams already use on-device AI capabilities, with Outlook, for instance, summarizing emails using Microsoft’s Phi Silica model and a GPU on the PC.

“And it’s not just developers that are betting on local AI…, [companies] from Adobe to WhatsApp are building some incredible local AI-powered experiences.” Tarnouskaya said. Other early adopters include Canva, Affinity, and Speechify.

AI apps for Windows 11 proliferated after Microsoft shipped Windows ML last fall, she said. (Windows ML helps developers create offline AI applications without accessing cloud models. It maps applications, localized AI models and hardware such as GPUs and neural processors.)

Windows ML is part of Microsoft’s “Foundry” portfolio of products, which includes Foundry Local for running open-source models on Windows devices, and Windows AI APIs that automate tasks such as conversation summarization, speech recognition, and video upscaling.

Microsoft is also turning to AI agents to change how users interact with Windows 11. Users can describe a task through natural language, and a long-running agent will get to work and complete the action. “Windows is evolving into a platform where natural language can map to real system outcomes,” said Samantha Song, product manager for Windows at Microsoft.

Song demonstrated how users could just tell or type how they want to personalize colors, wallpaper, or menus, and the agent will do it. “There is no manual set up against themes, setting or lighting. The system treats it as one coherent action,” Song said.

For the effort to succeed, developers will need to create a skills file that maps how an agent behaves. That skill can then be reused over and over again, Song said.

“At the enterprise level, you could imagine a world where a user switches into a secure finance mode, and the system aligns apps, access boundaries and environment automatically,” Song said.

Microsoft also demonstrated how OpenClaw can be used to create personalized agents to run Windows functions.

At Build, LLMware.ai demonstrated an agent on a Qualcomm laptop that collects Jira issues in real-time, summarizes them locally, and emails daily summaries of top issues to the team. The agent runs automatically without prompting.

“You can get optimized performance on the NPU [neural processing unit] by running the model locally…and you also implement a scheduled run of your automated agents,” said Darren Oberst, co-founder of LLMWare.ai.

Samsung, Lenovo and others are rolling out — albeit slowly and carefully — agentic AI features under the moniker of ‘personal AI,’” said Leonard Lee, principal analyst at Next Curve. “The problem is ensuring safe deployment,” he said.

Microsoft’s efforts to embed AI in Windows will force enterprises to rethink hardware strategies, said Jack Gold, principal analyst at J. Gold Associates. And since AI chips excel at different tasks, Microsoft will have to support multiple chips to offer choice to enterprises, he said.

“We recommend — and others do, too — that any new PC purchases, especially for enterprise, be done with this in mind and purchase AI PCs during any upgrade cycle,” Gold said.

AI is here, and we must help workers adapt: That’s the response of a new non-profit organization to the ongoing debate about whether AI will destroy jobs and cause catastrophe or take the economy to new heights.

Launched Thursday, Raise Us is a nonpartisan national organization that says it will partner with state governors, employers, workers, and training organizations to help the US workforce make a successful transition to an AI economy. It says it will design and pilot new corporate incentives to retrain and redeploy workers, develop new approaches to support people through job transitions, and create new training models tied to changing employer demand.

It has already raised more than $500 million and hopes to bring that up to $1 billion in multi-year commitments from philanthropists and industry sources. Anchor partners include Amazon, Microsoft, Anthropic, and the OpenAI Foundation, and more than two dozen other organizations including Cisco, IBM, ADP, AMD, and Deloitte have also signed on.

The organization is led by two former US state governors, Gina Raimondo, who will serve as CEO and co-chair, and Eric Holcomb, co-chair, and its initial government partnerships are with the states of Arkansas, Connecticut, Maryland, and Utah, which, it said, “will serve as the first proving grounds for outcome-driven pilots.”

However, analysts are skeptical that the initiative is anything other than a public-relations effort for the AI industry.

Jason Andersen, VP and principal analyst at Moor Insights & Strategy, said the organization’s initial communications are more marketing and posturing than strategy and action. “It also does not help that there are many CEOs involved who have already displaced thousands of workers due to AI,” he said.

The organization has chosen to work with state governments rather than the US federal government but even partnering at the state level may be too broad, he said, given that the industry makeup varies from state to state, with some leaning towards knowledge workers, while others are more manufacturing-focused.

AI-washing

Technology analyst Carmi Levy said Raise Us’s mission is laudable, but, “Unfortunately, for all its slick website and optimistic-sounding copy, Raise Us is possibly the highest-profile example of AI-washing thus far, a well-intentioned but ultimately futile attempt to illustrate that something is being done to cut through the uncertainty and empower the workforce of tomorrow. In reality, it’s a convenient vehicle for a diverse range of stakeholders, including state governments, educators, financial institutions, and companies like Amazon, Anthropic, Microsoft, and the OpenAI Foundation, to virtue-signal that they’re doing their utmost to solve the AI employment crisis and mitigate the impact of this generational technology deployment on everyday workers.”

Like Andersen, he noted that since many of those same companies have already had multiple rounds of tech-driven layoffs, “It’s more than a little rich for them to be joining an initiative whose mission revolves around protecting workers from the worst risks associated with AI.”

But, he said, “If Raise Us can deliver on its lofty promises, it could be an important first step in the great AI workforce transition. Otherwise, it could end up being little more than a high-profile exercise in creating plans and reports and conference panels with little on-the-ground execution to show for it. I’ll believe in its mission when middle-aged, mid-level administrative workers are realistically redirected into new AI-enabled career paths without a massive pay cut.”

Andersen, too, said he’s keeping an open mind, “but something more measurable and specific is in order, or this just looks like a public relations effort.”

Have you seen “The Founder”?

It’s the story of McDonald’s and how Ray Kroc (played by Michael Keaton) transformed the company from a local burger joint to a global landlord. According to the movie, Kroc’s accountant gave him the revelation: “You’re not in the burger business. You’re in the real estate business.”

When brothers Richard and Maurice McDonald transformed their San Bernardino, CA barbecue restaurant into a fast-food burger joint in 1948, their model was to make and sell their own burgers. They would succeed or fail based on making better food products than other restaurants. 

By the time Kroc bought out the McDonald brothers in 1961, the new model was leasing real estate to other people, and those other people would make the food. Whether the original San Bernardino McDonald’s succeeded or failed became irrelevant to the success of the McDonald’s corporation. 

SpaceX has done the same thing. Its San Bernardino location, i.e. xAI, can now succeed or fail without affecting the success of the parent company, which is SpaceX. 

The company this week signed a compute lease with Reflection AI, a pre-revenue startup founded by former Google DeepMind researchers. Under the agreement, Reflection pays $150 million per month for use of the Nvidia GB300 chips housed at Colossus 2, SpaceX’s expansion facility in Memphis, TN. If the lease runs for the full term, SpaceX as a landlord stands to make around $6.3 billion. (Reflection AI has shipped open-weight models, but has no widely adopted frontier model yet, and was reportedly raising capital at a $25 billion valuation.) 

Earlier this month, an S-1 filing revealed that Google agreed to pay SpaceX approximately $920 million per month for 32 months. SpaceX stands to make around $30 billion. And last month, SpaceX disclosed that xAI made a big deal with Anthropic that could bring in to SpaceX as much as $45 billion in revenue.

Regardless of whether xAI — or, for that matter, Reflection, Google, or Anthropic — succeeds or fails, SpaceX still wins. 

Like McDonald’s (which developed its super efficient burger-building system in order to succeed with its San Bernardino location and ended up using that system to succeed as a landlord), SpaceX is using the Colossus infrastructure it built for xAI’s Grok to succeed as an AI landlord.

Grok might succeed, or it might fail. But SpaceX makes bank if Grok’s competitors pay their rent. 

That makes Elon Musk, who is the CEO of SpaceX, the Ray Kroc of AI. 

Nvidia is Mayor McCheese

Colossus originally went online in July 2024, powered by 100,000 Nvidia H100 Hopper GPUs housed in a Supermicro liquid-cooled HGX H100 chassis. The company doubled that to 200,000 GPUs within a short time and it now comprises more than 220,000 Nvidia GPUs including H100, H200, and next-generation Blackwell-class accelerators. The entire fabric runs on Nvidia’s Spectrum-X Ethernet platform, specifically the Spectrum SN5600 switch built on the Spectrum-4 ASIC. 

Also: Nvidia is also heavily invested in companies that are renting compute power on Colossus. The company invests in Anthropic and Reflection AI — and, for that matter, xAI itself and, therefore, SpaceX. 

Nvidia has positioned itself as the Mayor McCheese of the AI industry, collecting taxes at every node of the AI economy. It supplies the GPUs and networking fabric that every frontier lab must train on and collects hardware revenue from the winner’s rivals, even as it profits from the winner’s success. 

So whether Anthropic, Google, Reflection AI, xAI, or some yet-unformed lab produces the dominant model, the computing power was bought from Nvidia and the landlord’s machine was built from Nvidia silicon. 

And Apple is the Hamburglar

Apple’s AI strategy is even more brilliant than Nvidia’s. 

It’s built on a three-tier routing system. When you ask Siri to do something, a built-in orchestrator in the operating system decides how complex the task is. According to third-party estimates, around 85% of requests are handled on your Apple device by Apple’s own small, efficient models. (It does things like summarizing text, prioritizing notifications, cleaning up photos, or suggesting replies.) Roughly 12% of all queries get sent to Private Cloud Compute, Apple’s own server infrastructure running Apple’s larger models on Apple silicon in Apple-owned data centers. Only the hardest 3% of queries get routed to an external partner model.

This design lets Apple avoid the ruinous cost of training a frontier model from scratch. Microsoft, Google, Meta, and Amazon each spend tens of billions of dollars per year on GPU clusters, energy, and research teams to build and run trillion-parameter models. Apple doesn’t. Its own models are deliberately small and run on chips Apple already sells you, so the inference cost is basically absorbed into the device. It only needs a frontier model for that tiny sliver of hard queries, which is where the partnership strategy kicks in.

While frontier labs are collectively spending trillions to build AI infrastructure, Apple is paying Google a mere $1 billion per year to license a custom Gemini model that powers the rebuilt Siri and Apple Intelligence’s complex-query path.

The reason Apple can swap partners is the Foundation Models framework, a native Swift API with a published LanguageModel protocol that any provider can implement. Google’s Gemini conforms to it. Anthropic’s Claude probably conforms to it. Any future model can theoretically conform to it. Apple’s orchestrator routes to whatever model fits the interface, so switching providers means changing routing logic, not rebuilding the whole system. 

Apple profits through several channels. Apple Intelligence requires recent hardware, driving upgrade cycles. Advanced features push users toward higher iCloud storage tiers. 

And so while everyone else is investing trillions, creating what is essentially debt that has to be repaid somehow, Apple is mainly just collecting billions without the massive investments needed by the frontier model companies. 

The AI industry has been telling itself a story: that the companies building the best models will win, that intelligence is the product, that the chatbot with the most capabilities and the cleverest training run will capture the market. That story is wrong. Some of the companies building the best models are tenants. The companies that rent out the compute are landlords. 

Ray Kroc would recognize SpaceX’s strategy immediately. The burger doesn’t matter; the land does. Right now, the most valuable land in the world isn’t in Silicon Valley. It’s a data center complex in Memphis full of hundreds of thousands of GPUs. 

The man who owns it just realized that he’s not in the AI business at all. He’s in the real estate business. (And he’s probably lovin’ it.)

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. Why I disclose my AI use and encourage you to do the same. 

An active phishing campaign has been targeting hotel and other hospitality organizations across Europe and Asia since April 2026, using photo-themed ZIP files to drop a Node.js implant and dig into front-desk machines, Microsoft says. The company has not attributed the activity to a known threat actor, and the operators' end goal is still unclear. The lure plays to how hotels work. Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

Russian authorities used Cellebrite's UFED forensic tools to break into the iPhone of detained opposition activist Andrey Pivovarov in June 2021, three months after Cellebrite said it would stop selling its tools and services to Russia and Belarus. The finding, published June 25 by the Citizen Lab, rests on two things that rarely line up: traces on the phone itself and an official Russian Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

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