Apple’s India Evolution: Quarter of iPhones Now Crafted There

Apple is currently producing a quarter (25%) of its iPhones in India, fulfilling a significant benchmark that JPMorgan had forecasted as early as 2022. This move aligns with the tech giant’s enduring strategy to diminish its reliance upon manufacturing in China, as reported by Bloomberg.
The previous year, India was responsible for assembling 55 million iPhones out of the approximately 220…

Apple’s India Evolution: Quarter of iPhones Now Crafted There

Apple now makes one in four iPhones in India: report

Apple is now manufacturing 25% of its iPhones in India — hitting a milestone JPMorgan predicted back in 2022 — as part of its long-term plan to reduce its reliance on China, Bloomberg reported.
Last year, India accounted for 55 million iPhones of the roughly 220 million to 230 million produced worldwide, Bloomberg’s report said. Apple has also moved quickly to deepen that commitment: it began…

Apple now makes one in four iPhones in India: report

A suite of government hacking tools targeting iPhones is now being used by cybercriminals

Security researchers have identified a suite of powerful hacking tools capable of compromising iPhones running older software that they say has passed from a government customer into the hands of cybercriminals.
Google said Tuesday that it first identified the exploit kit, dubbed Coruna, in February 2025 during a surveillance vendor’s attempt to hack into someone’s phone with spyware on behalf of…

A suite of government hacking tools targeting iPhones is now being used by cybercriminals

Government’s iPhone Attack Kit Weaponized by Cybercriminals

Cybersecurity investigators have uncovered a collection of potent intrusion instruments, reportedly capable of breaching Apple iPhones running outmoded software. These tools, they contend, have transitioned from a state client into the hands of malicious digital actors.
On Tuesday, Google disclosed that it initially detected the exploitation suite, known as Coruna, in February 2025. This occurred…

Government’s iPhone Attack Kit Weaponized by Cybercriminals

A Possible US Government iPhone-Hacking Toolkit Is Now in the Hands of Foreign Spies and Criminals

An iPhone-hacking technique used in the wild to indiscriminately hijack the devices of any iOS user who merely visits a website represents a rare and shocking event in the cybersecurity world. Now one powerful hacking toolkit at the center of multiple mass iPhone exploitation campaigns has taken an even rarer and more disturbing path: It appears to have traveled from the hands of Russian spies who used it to target Ukrainians to a cybercriminal operation designed to steal cryptocurrency from Chinese-speaking victims—and some clues suggest it may have been originally created by a US contractor and sold to the American government.

Security researchers at Google on Tuesday released a report describing what they’re calling “Coruna,” a highly sophisticated iPhone hacking toolkit that includes five complete hacking techniques capable of bypassing all the defenses of an iPhone to silently install malware on a device when it visits a website containing the exploitation code. In total, Coruna takes advantage of 23 distinct vulnerabilities in iOS, a rare collection of hacking components that suggests it was created by a well-resourced, likely state-sponsored group of hackers.

In fact, Google traces components of Coruna to hacking techniques it spotted in use in February of last year and attributed to what it describes only as a “customer of a surveillance company.” Then, five months later, Google says a more complete version of Coruna reappeared in what appears to have been an espionage campaign carried out by a suspected Russian spy group, which hid the hacking code in a common visitor-counting component of Ukrainian websites. Finally, Google spotted Coruna in use yet again in what seems to have been a purely profit-focused hacking campaign, infecting Chinese-language crypto and gambling sites to deliver malware that steals victims’ cryptocurrency.

Conspicuously absent from Google’s report is any mention of who the original surveillance company “customer” that deployed Coruna may have been. But the mobile security company iVerify, which also analyzed a version of Coruna it obtained from one of the infected Chinese sites, suggests the code may well have started life as a hacking kit built for or purchased by the US government. Google and iVerify both note that Coruna contains multiple components previously used in a hacking operation known as “Triangulation” that was discovered targeting Russian cybersecurity firm Kaspersky in 2023, which the Russian government claimed was the work of the NSA. (The US government didn’t respond to Russia’s claim.)

Coruna’s code also appears to have been originally written by English-speaking coders, notes iVerify’s cofounder Rocky Cole. “It’s highly sophisticated, took millions of dollars to develop, and it bears the hallmarks of other modules that have been publicly attributed to the US government,“ Cole tells WIRED. “This is the first example we’ve seen of very likely US government tools—based on what the code is telling us—spinning out of control and being used by both our adversaries and cybercriminal groups.”
An “EternalBlue Moment”

Regardless of Coruna’s origin, Google warns that a highly valuable and rare hacking toolkit appears to have traveled through a series of unlikely hands, and now exists in the wild where it could still be adopted—or adapted—by any hacker group seeking to target iPhone users.

“How this proliferation occurred is unclear, but suggests an active market for ‘second hand’ zero-day exploits,” Google’s report reads, using the term zero-day to refer to secret hacking techniques that exploit unpatched vulnerabilities. “Beyond these identified exploits, multiple threat actors have now acquired advanced exploitation techniques that can be reused and modified with newly identified vulnerabilities.”

iVerify’s Cole notes that if Coruna actually began life as a tool intended for the US government, though, it also raises questions about the security of mobile devices in a world where highly sophisticated hacking tools created for or sold to the American government can leak to adversaries. “This is the EternalBlue moment for mobile malware,” says Cole. EternalBlue is the Windows-hacking tool stolen from the National Security Agency and leaked in 2017, leading to its use in catastrophic cyberattacks, including North Korea’s WannaCry worm and Russia’s NotPetya attack.
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Google notes that Apple patched vulnerabilities used by Coruna in the latest versions of its mobile operating system, iOS 26, so its exploitation techniques are only confirmed to work against iOS 13 through 17.2.1. It targets vulnerabilities in Apple’s Webkit framework for browsers, so Safari users on those older versions of iOS would be vulnerable, but there’s no confirmed techniques in the toolkit for targeting Chrome users. Google also notes that Coruna checks if an iOS devices has Apple’s most stringent security setting, known as Lockdown Mode, enabled, and doesn’t attempt to hack it if so.

Despite those limitations, iVerify says Coruna likely infected tens of thousands of phones. The company consulted with a partner that has access to network traffic and counted visits to a command-and-control server for the cybercriminal version of Coruna infecting Chinese-language websites. The volume of those connections suggest, iVerify says, that roughly 42,000 devices may have already been hacked with the toolkit in the for-profit campaign alone.

Just how many other victims Coruna may have hit, including Ukrainians who visited websites infected with the code by the suspected Russian espionage operation, remains unclear. Google declined to comment beyond its published report. Apple did not immediately provide comment on Google or iVerify’s findings.
A Single, Very Professional Author

In iVerify’s analysis of the cybercriminal version of Coruna—it didn’t have access to any of the earlier versions—the company found that the code appeared to have been altered to plant malware on target devices designed to drain cryptocurrency from crypto wallets as well as steal photos and, in some cases, emails. Those additions, however, were “poorly written” compared to the underlying Coruna toolkit, according to iVerify chief product officer Spencer Parker, which he found to be impressively polished and modular.

“My God, these things are very professionally written,” Parker says of the exploits included in Coruna, suggesting that the cruder malware was added by the cybercriminals who later obtained that code.

As for the code modules that suggest Coruna’s origins as a US government toolkit, iVerify’s Cole notes one alternative explanation: It’s possible that the overlaps between Coruna’s code and the Operation Triangulation malware, which Russia pinned on US hackers, could have resulted from Triangulation’s components being picked up and repurposed after they were discovered. But Cole argues that’s unlikely. Many components of Coruna have never been seen before, he points out, and the whole toolkit appears to have been created by a “single author,” as he puts it.

“The framework holds together very well,” says Cole, who previously worked at the NSA, but notes that he’s been out of the government for more than a decade and isn’t basing any findings on his own outdated knowledge of US hacking tools. “It looks like it was written as a whole. It doesn’t look like it was pieced together.”

If Coruna is, in fact, a US hacking toolkit gone rogue, just how it got into foreign and criminal hands remains a mystery. But Cole points to the industry of brokers that may pay tens of millions of dollars for zero-day hacking techniques that they can resell for espionage, cybercrime, or cyberwar. Notably, Peter Williams, an executive of US government contractor Trenchant, was sentenced this month to seven years in prison for selling hacking tools to the Russian zero-day broker Operation Zero from 2022 to 2025. Williams’ sentencing memo notes that Trenchant sold hacking tools to the US intelligence community as well as others in the “Five Eyes” group of English-speaking governments—the US, UK, Australia, Canada and New Zealand—though it’s not clear what specific tools he sold or what devices they targeted.

“These zero-day and exploit brokers tend to be unscrupulous,” says Cole. “They sell to the highest bidder and they double dip. Many don’t have exclusivity arrangements. That’s very likely what happened here.”

“One of these tools ended up in the hands of a non-Western exploit broker, and they sold it to whoever was willing to pay,” Cole concludes. “The genie is out of the bottle.”

ALT

From 2009 - 2026 (might put my SIM card in the Nokia and go back in time)

NATO says iPhones are secure enough to handle classified data

The NATO-restricted designation is the lowest level of classified information, and it applies to information that would be “disadvantageous to the interests of NATO” if disclosed, according to a security document posted by the Marines. BlackBerry 10 phones similarly received approval to hold this level of classified information in 2013.

Following an “extensive evaluation” by Germany’s Federal…

NATO says iPhones are secure enough to handle classified data

KombackBlog | How to Spot a Fake iPhone in Nigeria (2026 Buyer Guide)

How to Spot a Fake iPhone: A Complete Buyer’s Guide (2026)

Buying an iPhone is a big investment. Whether you’re purchasing a brand-new device, UK-used, or a Nigerian-used iPhone, the fear is the same: “What if this iPhone is fake?”

Unfortunately, fake iPhones have become more convincing over the years. Some clones look almost identical to the original, come in iPhone-like boxes, and even run on modified Android software that mimics iOS. Many buyers only realize they’ve been scammed days—or weeks—later.

This detailed guide will walk you through every reliable method to spot a fake iPhone, even if you’re not tech-savvy. If you follow these steps carefully, you’ll drastically reduce your chances of buying a cloned or refurbished-as-new device in Computer Village.

My thousand dollar iPhone can’t do math

TL;DR:

My iPhone 16 Pro Max produces garbage output when running MLX LLMs. An iPhone 15 Pro runs the same code perfectly. A MacBook Pro also runs the same code perfectly. The tensor outputs on the 16 show numerical values an order of magnitude wrong. I suspect it points to a hardware defect in the Neural Engine or some other ML-needed system.

It was a PITA to debug, but at least I got a blog post out of it.

How did I get there?

This was supposed to be a simple, unwinding-time project.

For the past few months I’ve been working on a Clawdbot Moltbot clone that I’ve been calling Schmidt. It basically does the same kind of thing but with a custom chat UI instead of using Telegram, WhatsApp or other “I-can’t-afford-to-be-banned-from” Service. This project has been consuming early days and late nights, so, to unwind, I decided that it may be a good idea to do something simpler. Since I recently subscribed to MiniMax M2.1, I thought I would do what many do and build a simple expense tracking app to test out the model.

The core functionality is simple:

• Automatically, upon each payment, add the expense to my app
• Update an Apple Watch complication with the % of my monthly budget spent
• Categorize the purchase for later analysis

This all comes from being basically orphaned by Nubank’s amazing native app (since replaced by a less-full-featured Flutter version).

Something like that, I can’t find the original complication itself. Apparently, this was designed by Guilherme Neumann (according to their Dribbble)

Integrating with Shortcuts is manual, but reliable. Within 15 minutes I had a version of the app that could register purchases. The Apple Watch complication, the main goal, can come later. I’d rather get the classification feature, which should be easy, done quickly – so I figured.

Apple Intelligence

Given the new LLM-bonanza we’ve been living through, it’s no surprise that Apple has their own set of APIs developers such as me can use. Reading up on the documentation, it’s a matter of checking for the availability of the feature and then asking the model to either reply to a textual query or, in my case, categorize a request.

MiniMax raced through it in a single prompt and then I ran it on my iPhone. First expense was a purchase at a shop called “Kasai Kitchin”, classified as… unknown.
Weird.

Checking the logs, it was clear: the model support was downloading. The feature hadn’t been enabled. Again, weird. I should have it on. Anyway, I go into settings, do the weird dance of toggling it on and off – sadly, that’s not surprising on Apple’s services. Maybe my Settings.app got stuck in a weird state, who knows? – and wait for it to download.

After 4h I realized it was not going anywhere. Looking it up, it seems that many have the same issue (this thread shows 12 pages of frustrated users). Again, not a surprise for Apple’s services recently.

Oh well, time to give up on the Apple Intelligence approach. Let’s move on to the next one.

MLX LLM

Well, the iOS framework engineers don’t seem to be the only engineers at Apple capable of coming up with Machine Learning APIs in Swift. Apparently, there’s a whole separate way of doing it – with models downloaded to your app. Not great for the user’s storage, but great for me!

Again, MiniMax does it in a heartbeat, specially after being given documentation and one or two Medium posts. Time to run on my iPhone and… gibberish.

The CPU spins to 100% and the model starts generating. But it’s all gibberish. And no “stop” token is generated, so this goes on for long.

“What is 2+2?” apparently “Applied…..*_dAK[…]” according to my iPhone

At this point, the only explanation is: I’m completely incompetent and can’t even get a simple “ready made” framework to execute what I want. Or, rather, MiniMax is! The good thing about offloading your work to an LLM is that you can blame it for your shortcomings. Time to get my hands dirty and do it myself, typing code on my keyboard, like the ancient Mayan and Aztec programmers probably did.

My own MLX implementation

I went back to the documentation, to the Medium posts and, much to my surprise: MiniMax had followed it to the letter. Even went back to some deprecated methods of generation and it also was gibberish. And now there’s no one to blame, but myself. I go to work everyday and this impostor-syndrome inducing problem silently consumes me.

After 3 days of trying to get it to work, I’m ready to give up…
…until, on a Tuesday morning, at 7-8 AM, I have an idea: let me, just in case, run this on my old iPhone 15 Pro. Up to this point, I was running it on my daily driver, an iPhone 16 Pro Max that was a replacement phone sent by Apple Care after a small clubbing mishap (in which my iPhone was irreparably crashed). I rush to get everything ready before it’s time to go to work and: it works! Gemma, Qwen, and all other models generate coherent responses!

I stop and think: this cannot be a hardware issue, right? Of course not. The iPhone 15 is still running iOS 18. The iPhone 16 is running 26. It must be an OS issue. Well, time to be late for my work standup and update the old phone. The curiosity is too much. Many minutes later… same results, now on iOS 26. The plot is thickening.

Finding the smoking gun: breakpoints in MLX’s implementations of Gemma

After that work day, and after many lunch and coffee discussions with coworkers about the sources of my troubles, I get home and immediately set myself on debugging MLX as it runs, if possible. The game plan is:

• Use a known-to-be-reliable model, that fits in RAM (I went with quantized Gemma)
• Use a simple prompt, in my case “What is 2+2?”
• To be really pedantic: the prompt was <start_of_turn>user\nWhat is 2+2?<end_of_turn>\n<start_of_turn>model
• Run everything with temperature set to 0.0 – maybe that’s enough to remove variability
• Find the model implementation
• Find where the model iterates through the layers and
• Print out the MLXArray/Tensor with the values on each layer as the input goes through

A few moments later and I find where I need to be. Added the breakpoints, added the logs and off to the races.

These ones were the ones I added

I run it on my iPhone 16 Pro Max. The model loads and the prompt is “What is 2+2?”. The tensors start printing out, line after line after line. For once, the logs aren’t complete gibberish – they’re numbers. Floating point values representing the model’s internal state as it processes the input. I save the output to a file and do the same on my iPhone 15 Pro. Same model, same prompt, same code. Time to compare.

Welp, now it’s definitely out of my expertise

I grep for a pattern I know should be consistent – an array at log-line 58, right before the values get normalized/softmaxed. On a working device, I hypothesize this should be the same every time.

On the iPhone 15 Pro:
3: “[[[[53.875, 62.5625, -187.75, …, 42.625, 6.25, -21.5625]]]]”
On the iPhone 16 Pro Max:
3: “[[[[191.5, 23.625, 173.75, …, 1298, -147.25, -162.5]]]]”

Huh. Not close. Not at all. These values are orders of magnitude off. I double check the start of the logs and both phones show the same:

1: “array([[[0.162842, -0.162842, -0.48877, …, -0.176636, 0.0001297, 0.088501],\n [-0.348633, -2.78906, 0, …, 0.84668, 0, -1.69336],\n [-1.30957, 1.57324, -1.30957, …, -0.0010376, -0.0010376, 1.12305],\n …,\n [-0.348633, -2.78906, 0, …, 0.84668, 0, -1.69336],\n [0.296875, 0.59375, 0.890625, …, -0.59375, 0.296875, -0.890137],\n [1.02734, -0.616211, -0.616211, …, -0.275879, -0.551758, 0.275879]]], dtype=float16)”

OK, so the model receives the same thing as input, but at some point, the values start to go off. Like, way off. In order to make sure I’m not crazy, I do one last thing: run the same thing on my Mac. Make the app run on iPad compatibility mode and…
3: “[[[[53.875, 62.5625, -187.75, …, 42.625, 6.25, -21.5625]]]]”

Bingo! Same as iPhone 15!

The model isn’t broken. The code isn’t broken. Most importantly, I’m not broken*. My phone is broken.
*arguable, but besides the point here

What’s going on?

Let me explain what I think it’s going on here: the iPhone 16 Pro Max contains Apple’s A18 chip with its Neural Engine—a specialized accelerator for machine learning operations. MLX uses Metal to compile tensor operations for this accelerator. Somewhere in that stack, the computations are going very wrong. I don’t think it’s a widespread issue but, I do get disappointed that a relatively newly replaced iPhone from Apple Care came with such an issue.

However, if my Apple Intelligence troubles are related – and they might as well be, I’d assume that code and MLX are not dissimilar in operations being done –, it could be that all the 12 pages of users are users in a similar dillema, but without the means of debugging it.

What now?

I spent 3 days thinking I was incompetent. I blamed MiniMax. I blamed myself. The entire time, my $1,400 phone had a broken hardware. I could lose more time figuring out exactly what is wrong with it but it’s literally not worth my time.

I guess I can at least take a lesson that, when debugging, I should always consider the physical layer. I spent three days assuming this was a software problem – my code, the library, the framework, my skills as a developer. The breakthrough was basically: “What if I’m not dumb and it’s not my code?”

As for my phone: it’ll probably go back to Apple, as a trade in for a new iPhone 17 Pro Max that hopefully 🤞 can do math.

Update on Feb. 1st:

Well, now it’s Feb. 1st and I have an iPhone 17 Pro Max to test with and… everything works as expected. So it’s pretty safe to say that THAT specific instance of iPhone 16 Pro Max was hardware-defective.

idk how romantic screwing in one screw for 10 hours a day is tbh…….

most people quit after a month or two here

Heavy user or content creator? iPhone 16 Pro Max 512GB Kuwait handles it all. Shop today.

Apple update on my phone. Everything should be set on fire now actually

How to Spot a Fake iPhone in Nigeria (2026 Buyer Guide)

How to Spot a Fake iPhone: A Complete Buyer’s Guide (2026)

Buying an iPhone is a big investment. Whether you’re purchasing a brand-new device, UK-used, or a Nigerian-used iPhone, the fear is the same: “What if this iPhone is fake?”
Unfortunately, fake iPhones have become more convincing over the years. Some clones look almost identical to the original, come in iPhone-like boxes, and even run on…

How to Spot a Fake iPhone in Nigeria (2026 Buyer Guide)

Please help me signal boost!

I got two review surveys because I got passed to another support person, so I’ve made it very clear how this is unacceptable, and

I invite anyone else who’ve had this data transfer issue, whether or not you’ve personally had a hard time, to contact support in order to get that review option and make it clear that that isn’t fucking acceptable. That’s the only way of *complaining* that I know of.

I got gifted a new phone. The iPhone 17 and it’s been a NIGHTMARE.

Tried 8 times for that automatic data transfer (via the two phones being close) which should take less than an hour, and come to find out after looking up wtf that it’s a known issue for the model!

This is apple, basically the top of the phone and computer market, at least in the west, and a nearly two-decade old device, this is entirely unnacceptable!

The other way to transfer? iCloud and all that extra labor for other apps and such. Also, I have a brain disease, all this extra monkeybusiness is difficult for me especially when the “ease of use” is fucking rotting.

Well, I lost ALL my notes AND calendar data because the new phone and iCloud couldn’t do it’s literal fucking jobs (no, it doesn’t make sense). Notes does NOT have any feature to save notes in phone and not in iCloud despite literally all sense.

I don’t even know how all that happened, and I’m terrified I’ve lost other data without knowing!

I spent three hours with support just to be told all my notes data is lost (discovered calendar issue hours later), and making it seem like a me problem when the notes aren’t in fact part of the fucking phone AND I shouldn’t have even had to go through iCloud!

They’re all “protecting your data” except for the obvious places.

I like looking at my own archives using my own smartphone

Tell me the truth?

What smartphone are you using now?

I am using an iPhone 📲

Is this the folding apple iphone’s creaseless display?

Samsung Program showcased a brand-new retractable OLED panel at CES that does not have a noticeable fold– something that currently blights every collapsible phone on the marketplace. This might be our first have a look at the panel utilized in the future generation of Samsung’s Galaxy foldables and additionally the folding apple iphone, considered that Samsung Existing is a veteran company for…

Is this the folding apple iphone’s creaseless display?

So I got another one of those iPhone vs Android reels about the green text phenomenon that reminded me of something I realized a while back:

Transcript below the cut:

Blue text: So I used to think that Apple users were just being extremely shallow about the whole green text thing, and they definitely are, but there’s a more nefarious aspect to it that us android users don’t really notice:

Green text: The green texts are harder to read.

Blue text: I only realized after my friend was showing me long text chains in green and in blue but there’s something about the shades of green and blue that iMessage uses that make a stark difference in readability between them. You’re straining your eyes more when you read the green texts which is why you feel an aversion to them that you can’t explain.

Blue text: Entire User Interface Design teams work on every aspect of your phone’s presented interface so this is no mistake. Apple limits your phone’s usability for the sake of profiteering (not the first time they’ve been called out for this kind of thing).

Foxconn’s Karnataka iPhone Plant Aims for 50,000 Jobs by 2026

Foxconn’s Devanahalli iPhone assembly plant is rapidly scaling up, already hiring 30,000 workers and planning to reach 50,000 by 2026. The facility is a major boost for India’s tech manufacturing and global supply chain role.

Redmi Note 15 and 5G make their global debut

What’s Next for Apple in 2026: iPhones, Wearables, Smart Devices & More

Explore every new Apple product expected in 2026, including iPhone 18, a foldable iPhone, new Macs, iPads, smart home devices, and major AI upgrades.

https://ifixscreens.com/upcoming-apple-products-2026/