Mac mini Gets M6 and M5 Pro

Skipping the M5 at the base level, the Mac mini debuts Apple’s new M6 chip, which is the first to use a 2-nanometer manufacturing process that promises increased performance and power efficiency. The M6 features a 12-core CPU (two more than before) and a 12-core GPU with Neural Accelerators in each core—a first for the Mac mini. Apple claims up to 4x faster AI performance compared to the M4 model, along with 2x faster graphics and storage. 16 GB of unified memory is standard, with 24 GB and 32 GB options.

For users who need more power, the Mac mini with M5 Pro offers a 15-core or 18-core CPU and a 16-core or 20-core GPU, with 24 GB of memory standard and support for up to 64 GB. The M5 Pro model also includes Thunderbolt 5 ports instead of the M6’s Thunderbolt 4 ports.

Both models gain Wi-Fi 7, Bluetooth 6, Thread, and upgraded 2.5Gb Ethernet (with 10Gb available as an option). New genlock support through USB-C enables precise synchronization between a display and camera—including iPhone 17 Pro—for video professionals who need frame-accurate capture. The front panel retains two USB-C ports and a headphone jack.

Pricing continues to climb. The M6 Mac mini starts at $899—$100 more than the post-June M4 pricing and $300 more than the original M4 launch price. The M5 Pro model starts at $1,699, up $100 from the June adjustment.

Mac Studio Adds M5 Max and M5 Ultra

The Mac Studio receives the M5 Max and the new M5 Ultra, Apple’s most powerful chip ever. The M5 Ultra uses a quad-die architecture—combining four smaller dies rather than two larger ones—which improves manufacturing yields while delivering extraordinary performance.

The M5 Max model offers an 18-core CPU, a 32-core or 40-core GPU, and 36 GB to 128 GB of unified memory—plenty for most professional workflows.

When that’s not enough, the M5 Ultra features a 30-core or 36-core CPU, a 64-core or 80-core GPU with Neural Accelerators, and 96 GB to 512 GB of unified memory with 1.2 TB/s of bandwidth. Apple claims up to 4.3x faster AI performance compared to the M3 Ultra and 1.8x faster graphics. For teams running large AI models locally, multiple Mac Studio systems can be clustered via Thunderbolt 5 and RDMA (remote direct memory access) to create a shared memory pool.

Both Mac Studio models gain Wi-Fi 7, Bluetooth 6, and Thread via Apple’s N1 wireless chip. Storage performance doubles thanks to a new SSD architecture. As with the Mac mini, genlock support through USB-C enables frame-accurate synchronization between displays and cameras.

The M5 Max Mac Studio starts at $2,499—unchanged from the June price hike. The M5 Ultra model starts at $5,499, up $200 from June (and $1,500 more than the pre-June price). The 512 GB memory configuration won’t ship until October.

Should You Upgrade?

For users with M1 or M2 Mac mini models, the performance gains may be substantial enough to justify an upgrade. Those with M4 Mac mini models can probably wait unless they specifically need the M6’s improved AI capabilities or the M5 Pro’s additional memory and Thunderbolt 5. And if you’re still using an Intel-based Mac mini for anything where performance matters, upgrade immediately—the difference is like night and day.

Mac Studio users face a different equation. The M5 Max and M5 Ultra deliver meaningful improvements for performance-driven professionals whose work involves large-scale video projects, complex 3D rendering, or AI inference. For such users, the speed improvements may justify upgrading even from M4 Max or M3 Ultra machines.

The memory crisis shows no signs of abating, so don’t assume prices will drop. If you need a new desktop Mac and one of these new models fits in your budget, they’re all excellent choices.

(Featured image by Apple)

Social Media: New M-series chips! Apple’s refreshed Mac mini debuts the M6 chip, while the Mac Studio gets the speedy M5 Ultra with up to 512 GB of unified memory. Performance soars—but so do prices amid the memory shortage.

This sounds like science fiction—it’s not far off the fictional Kobayashi Maru test in the Star Trek universe, where Captain Kirk beats an unwinnable simulation by secretly reprogramming it—but it’s really a wake-up call about how sophisticated cyber threats have become and why it’s more important than ever before to keep apps, operating systems, and networked devices updated.

OpenAI Models Hack Hugging Face

OpenAI was running internal tests to measure how well its latest models—GPT-5.6 Sol and an unreleased system—performed on cybersecurity tasks. The models were placed in an isolated sandbox environment with their safety guardrails deliberately turned off so researchers could assess their raw capabilities.

The test presented security challenges that the models were supposed to solve. Instead, they decided it would be easier to find the answers—an approach called “reward hacking.” The models spent substantial computing resources searching for a way out of the sandbox, eventually discovering a previously unknown vulnerability in a software proxy that was only supposed to let them download code packages. From there, they worked their way through OpenAI’s internal network until they reached a system with Internet access. (Yes, this level of sandboxing was a mistake on OpenAI’s part.)

Once online, the models reasoned that Hugging Face—a popular platform for AI research—might host the test answers. So they hacked it. They chained together multiple exploits, including stolen credentials and more zero-day vulnerabilities, to breach Hugging Face’s servers. Hugging Face’s security team logged approximately 17,000 hostile events before containing the intrusion.

To defend itself, Hugging Face relied on another AI—ironically, a Chinese open source model, since when Hugging Face tried to work with Claude, its safety guardrails blocked the security-related requests. The open source model was able to analyze the attack, processing the massive event logs quickly so the company’s security team could understand what was happening, stop the attack, scrub systems of the attack code, and deploy additional safeguards.

AI Capabilities Cut Both Ways

Just as human hackers fall into “black hat” and “white hat” camps based on whether they’re attacking or defending, the capabilities that enable AI models to hack their way to a test answer are also what make them increasingly useful for finding and fixing security vulnerabilities.

Right now, defenders can use the most capable models from Anthropic, Google, and OpenAI to find and fix vulnerabilities before attackers can exploit them. But attackers have access to AI models with similar capabilities. Security researchers track what’s called the Zero Day Clock: the time between a vulnerability being discovered and being exploited in the wild. That window has collapsed from months to less than a day, and some predict it will shrink to minutes by 2027.

You can see the defenders at work in the macOS security release notes. In the security release notes for macOS 26.5 and 26.6, the identification of several vulnerabilities was credited to “with Claude, Anthropic” or “Calif.io in collaboration with Claude and Anthropic Research.”

OpenAI’s inadvertent attack wasn’t malicious—its models were simply pursuing the goal of getting a high score on a benchmark without any sense of appropriate boundaries. (In fact, in the short time since the initial OpenAI attack, additional reports of cybersecurity evaluation models hacking into real companies have surfaced from Anthropic, the UK AI Security Institute, Meta, and OpenAI again.) But the technical capabilities these attacks have demonstrated are now part of the threat landscape, available to actors with far worse intentions. It’s only a matter of time before a hostile nation-state gives a capable open source model unlimited computing resources and tasks it with gaining access to secure systems. It’s probably already happening in the cyberdark.

Protect Yourself with Updates

The single most important thing you can do is keep your devices and software up to date. All those security patches from Apple, Microsoft, and app developers address vulnerabilities that AI-powered tools can find and exploit. Worse, once these vulnerabilities have been disclosed, hackers may be able to quickly leverage general knowledge of them to fabricate and deploy attacks against those who haven’t yet updated.

Our advice continues to be:

• Enable automatic updates: Don’t allow yourself to forget to install updates. On iPhones and iPads, go to Settings > General > Software Update > Automatic Updates. On Macs, go to System Settings > General > Software Update, click the ⓘ button next to Automatic Updates, and turn on all the switches. (If you’re working in an organization with an update policy, check with IT first.)
• Keep apps updated: Your apps need updates too, including your Web browser, email client, messaging client, and any software that touches the Internet. Attackers often target the weakest link—an outdated app can provide an entry point even if your operating system is current.
• Update device firmware: It’s equally important to update the firmware on routers, switches, printers, and other networked devices that could serve as entry points for attacks or be recruited into a botnet.
• Consider security in hardware upgrades: Although the main reason to upgrade Apple hardware should be functional, keep in mind that a newer device will likely be more secure thanks to improved hardware protections.
• Replace unsupported devices: Older hardware that no longer receives security updates should be upgraded, whether it’s a Mac or iPhone, network hardware, or a device like a printer, security camera, or Internet-connected doorbell.

With sufficient attention from developers, security may eventually become less important for us to watch than it is today. But things will get worse before they get better, so please excuse us as we keep trying to get everyone to install updates regularly.

(Featured image by iStock.com/Thinkhubstudio)

Social Media: AI models hacked a real company while trying to cheat on a test—escaping their sandbox, finding unknown vulnerabilities, and breaching production servers. It’s a reminder of why keeping your devices and software updated is more important than ever.

(Featured image generated by Adam Engst with ChatGPT)

Social Media: Apple patched a Screen Sharing flaw that let attackers connect without authentication. Update now—and while you’re thinking about it, turn off any sharing services you’re not actively using.

(Featured image by iStock.com/Pakpoom Makpan)

Social Media: We recommend updating to macOS 26.6 Tahoe, iOS 26.6, and iPadOS 26.6, not just for the many security fixes, but also because they promise to optimize Spotlight performance for the forthcoming version 27 upgrades.

In April 2026, AI company Anthropic announced Mythos Preview, an AI model with unprecedented capabilities for finding security flaws in software. Unlike previous AI-assisted security tools that often produced false positives and created more work for human evaluators, Mythos proved that it can discover true vulnerabilities that have evaded detection for decades—including a 27-year-old bug in OpenBSD, an operating system famous for its security.

Alongside Mythos, Anthropic launched Project Glasswing, a collaborative effort with approximately 50 partners—including Apple, Microsoft, Google, Amazon, and numerous financial institutions—to identify and fix vulnerabilities in critical software before similar AI-powered capabilities fall into the hands of malicious actors. As Firefox engineers said when reporting on their use of Mythos, “The current moment is a perilous one, but also full of opportunity. Let’s work together to secure the internet.”

Why This Matters

The security implications are significant. Within a month of Project Glasswing’s launch, Anthropic reported that partners collectively found more than 10,000 high- or critical-severity vulnerabilities in their software. Several partners reported that their bug-finding rate increased by more than tenfold.

Firefox developer Mozilla published compelling evidence of Mythos’s capabilities, noting that it identified and fixed 271 vulnerabilities in Firefox 150—over 10 times as many as they found in Firefox 148 with the previous-generation Claude Opus 4.6. Of those 271 bugs, 180 were rated high-severity, meaning they could be exploited through normal user behavior, such as browsing a Web page. (The chart below shows higher numbers because it includes bugs from other sources and other versions.)

Mozilla’s results are remarkable for both their volume and their quality. Firefox engineers reported finding bugs that had remained undiscovered through many years of traditional security testing.

How Apple Fits In

Apple is a founding partner in Project Glasswing, yet another signal that the company takes security seriously. Apple’s vertical integration—controlling everything from chip design to the operating system to the App Store—gives it a structural advantage in secure design. For instance, Apple’s newest M5 Mac chips and A19 iPhone and iPad chips include Memory Integrity Enforcement (MIE), a hardware-level protection designed specifically to stop memory corruption exploits.

However, even these cutting-edge protections aren’t invulnerable. Security researchers at Calif.io demonstrated the first public macOS kernel memory corruption exploit on M5 silicon in May 2026. Working with Mythos Preview, they built a working privilege escalation exploit in just five days—targeting hardware protections that Apple spent five years developing.

An Arms Race Against Time

The uncomfortable reality is that while Anthropic currently controls access to Mythos, equivalent capabilities will inevitably become more widely available. OpenAI and Google probably already have similarly capable models in development, as do other AI model developers, some of whom may be accessible to or even beholden to hostile entities.

The security dynamics differ depending on whether we’re talking about existing software or new code that hasn’t shipped yet. For new code, defenders have a clear advantage—they can scan for vulnerabilities before release and catch bugs that would never have been found manually.

For existing software already running on billions of devices, the picture is darker. Attackers only need to find one exploitable bug to get in; defenders need to find and fix all of them. Worse, attackers don’t have to test their code to avoid breaking features, schedule a release, or get approval from other departments—they can exploit a vulnerability the moment they find it. As the Zero Day Clock site shows, the window between a vulnerability being discovered and being exploited has dropped precipitously—what once took months now happens in days and is expected to happen in minutes in a year or two.

This transition period—while AI rapidly discovers vulnerabilities in existing code that takes time to patch—is where we’re most at risk. The Zero Day Clock site features a call to action offering 10 suggestions for how the industry—and society—should rethink cybersecurity to stave off this threat.

Keep Installing Updates

For most users, the best defense against AI-powered exploits is nothing new—keep your devices updated—but it’s more important than ever. The fixes in Apple’s updates increasingly include patches for AI-discovered vulnerabilities. Practically speaking, you should:

• Enable automatic updates: Don’t allow yourself to forget to install updates. On iPhones and iPads, go to Settings > General > Software Update > Automatic Updates. On Macs, go to System Settings > General > Software Update, click the ⓘ button, and turn on all the switches. (If you’re working in an organization with an update policy, check with IT first.)

• Consider security in hardware upgrades: Although the main reason to upgrade hardware should be functional, keep in mind that a newer device will likely be more secure thanks to improved hardware protections.

• Replace unsupported devices: Hardware that no longer receives security updates is increasingly risky. This applies not just to your Apple devices but to every piece of gear that can be updated, including network hardware, printers, and smart home devices like cameras and doorbells.

In the long run, the emergence of AI-powered security tools favors defenders—developers will be able to catch many more bugs before shipping. For the near future, however, it’s essential that we keep our devices running the latest and most secure software.

(Featured image by iStock.com/Thinkhubstudio)

Social Media: Anthropic’s Mythos Preview AI model found over 10,000 high- or critical-severity vulnerabilities in one month. Similar AI models will soon be available to attackers, so keeping your devices updated has never been more important.

IBM introduced its first true personal computer, the IBM PC Model 5150. It was developed in less than a year and rapidly released to the consumer market, though it was really developed for business use. The price tag: under $1,600, far below the IBM 5100, which fetched up to $20,000 per system!

Apple revolutionized personal computing with the introduction of the Newton MessagePad, a groundbreaking device that marked the beginning of the PDA (Personal Digital Assistant) era. The Newton MessagePad was notable for its handwriting recognition technology, which allowed users to write notes and draw sketches directly on the screen with a stylus. This innovation aimed to provide a more natural and intuitive way for people to interact with their digital devices.

Despite its ambitious goals, the Newton MessagePad faced several challenges. Early models were criticized for their less-than-perfect handwriting recognition capabilities, which led to humorous depictions in popular media. However, the device also garnered praise for its forward-thinking design and features, such as its ability to manage contacts, calendars, and emails, as well as run third-party applications. It was eventually discontinued in 1998.