It’s dispiriting to see that even after being made aware of the breach 2 weeks ago, IA has still not done the due diligence of rotating many of the API keys that were exposed in their gitlab secrets.

As demonstrated by this message, this includes a Zendesk token with perms to access 800K+ support tickets sent to info@archive.org since 2018.

Whether you were trying to ask a general question, or requesting the removal of your site from the Wayback Machine—your data is now in the hands of some random guy. If not me, it’d be someone else.

Here’s hoping that they’ll get their shit together now.

One of the constants in computing is the need for more storage. While 8TB SSDs offer both speed and capacity, they can be a little pricey, although there are deals available if you’re prepared to shop around. If you need more storage – nearly double, in fact – purchasing a 15.36TB SSD often provides better value on a per-terabyte basis.

For example, the Intel D5-P5316 2.5-inch 15.36TB SSD is available on Amazon for $1,650. It boasts write speeds of 3200 MB/s and read rates of 7000 MB/s. If you’re after a cheaper option, the Kioxia CD6-R KCD6XLUL15T3 is priced at a more affordable $1,397.63 on ServerPartDeals. This model offers 4000 MB/s write speeds and 5500 MB/s read rates.

Apple’s MacBook Air M3 represents the latest of the company’s very successful thin-and-light laptops built around Apple Silicon’s fast and highly efficient chipsets. It’s one of the best laptops made, and Windows machines have had a hard time keeping up.

Now, Intel has introduced a new chipset, the Core Ultra Series 2, also know as Lunar Lake, that aims to rectify things with much better efficiency. The Asus Zenbook S 14 is one of the first laptops introduced with the new chipset. Can it compete?

Specs and configurations

Design

The MacBook Air M3 is an incredibly thin laptop while still maintaining Apple’s usual excellent build quality and solid chassis. It’s CNC machined out of a single chunk of aluminum, and it’s an elegant aesthetic in one of four colors. The Zenbook S 14 is a pretty thin laptop as well, and it uses a “ceraluminum” (Asus’ word) material to be very light and yet sturdy. It’s a good-looking laptop as well, coming in either dark gray or white and with a geometric pattern on the lid.

Both laptops have the usual quality hinge that opens with one hand, and while the MacBook Air feels dense and cold in hand, the Zenbook has a warm texture. The bottom line is that nobody is likely to buy either laptop based solely on their look and feel.

The Zenbook S 14 has the very good Asus keyboard that you’ll find on the entire ZenBook line. It has plenty of spacing and large keycaps, as well as light and snappy switches. The MacBook Air uses Apple’s excellent Magic Keyboard, which is my favorite. It has a perfect layout, comfortable keys, and the most precise switches on a laptop today. The Zenbook’s mechanical touchpad feels Ok, but it’s almost too large, leaving a very small palm rest. The MacBook Air’s Force Touch haptic touchpad is perfectly sized and works great, with the Force Click function that adds additional features with a firmer “click.” The keyboard and touchpad are Apple strengths.

Connectivity favors the Zenbook S 14, which has a couple of legacy ports to go with the same two Thunderbolt 4 connections. And it has more up-to-date wireless connectivity. Both laptops have 1080p webcams, and the Zenbook uses an infrared camera with Windows 11 facial recognition compared to the MacBook Air’s Touch ID fingerprint reader. The Zenbook supports Studio Effects software that enhances videoconferencing.

Performance

Intel’s Lunar Lake chipsets are aimed at competing directly with Apple Silicon. We reviewed the Zenbook S 14 with the Core Ultra 7 258V, a 17-watt, 8-core (four Performance and four Low Power Efficient), 8-thread chipset. It uses the newest Intel Arc 140V integrated graphics. The MacBook Air uses Apple’s M3 chipset with eight CPU cores and eight or 10 GPU cores. We reviewed the faster version.

In our benchmarks, the MacBook Air M3 was faster in all but the Handbrake test. It was faster in both single-core and multi-core tests. And its GPU was more than twice as fast in the 3DMark Wild Life Extreme benchmark.

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It’s not that the Zenbook S 14 is a slow laptop. It’s just that the MacBook Air M3 is meaningfully faster.

	Geekbench 6 (single/multi)	Cinebench R24 (single/multi/battery)	Handbrake	3DMark Wild Life Extreme
Asus Zenbook S 14 (Core Ultra 7 258V / Intel Arc 140V)	2,738 / 10,734	112 / 452	113	3,240
Apple MacBook Air M3 (M3 8/10)	3,102 / 12,078	141 / 601	109	8,098

Display

The Zenbook S 14 uses a 14-inch 2.8K OLED display running at up to 120Hz. It’s a lovely display with OLED’s usual bright, dynamic colors and inky blacks. That compares to the MacBook Air’s 13.6-inch 2560 x 1664 IPS display running at 60Hz.

While the MacBook Air’s display is a very good example of IPS technology, and it’s very bright and reasonably colorful, the Zenbook’s OLED panel has much wider colors and near-perfect blacks. Our review unit had oddly poor color accuracy, but that’s unusual and likely an outlier. The Zenbook’s display will be appreciated by creators and media consumers.

	Asus Zenbook S 14 (OLED)	Apple MacBook Air M3 (IPS)
Brightness (nits)	313	496
AdobeRGB gamut	95%	87%
sRGB gamut	100%	100%
DCI-P3 gamut	100%	99%
Accuracy (DeltaE, lower is better)	4.92	1.24
Contrast	28,310:1	1,480:1

Portability

The MacBook Air is the thinnest laptop you can buy, and the Zenbook S 14 is only a little thicker. In spite of having a larger display, the Zenbook is around the same width and depth, and it weighs about the same. These are both very portably laptops.

When it comes to battery life, the Zenbook S 14 comes about as close to the MacBook Air M3 as any recent Windows laptop has managed. It’s only three hours behind in our web-browsing test and an hour behind in our video-looping test. And the two laptops managed about the same in the demanding Cinebench R24 multi-core test.

	Web	Video	Cinebench R24
Asus Zenbook S 14 (Core Ultra 7 258V / Intel Arc 140V)	16 hours, 47 minutes	18 hours, 35 minutes	3 hour, 33 minutes
Apple MacBook Air M3 (M3 8/10)	19 hours, 38 minutes	19 hours, 39 minutes	3 hours, 27 minutes

Two very good laptops, but the MacBook Air wins a close one

The Snapdragon 8 Elite is set to be one of the best chips in Qualcomm’s history. Leaks about the formerly known Snapdragon 8 Gen 4 already suggested it, and benchmarks have been confirming it. Over the past few weeks, a few devices powered by the chip have been showing off their might on Geekbench. Now, the Snapdragon 8 Elite-powered realme GT7 Pro has gone through Antutu’s tests, showing massive improvements.

Smartprix got access to the realme GT7 Pro’s results on Antutu and put them side-by-side with those of the iPhone 16 Pro (Apple’s A18 Pro). That said, you should know that Antutu’s tests for Android and iOS devices use different APIs, so the results are not directly comparable. However, you can use them as a reference if you compare them with Antutu results from previous generations of devices.

Snapdragon 8 Elite scores over 3 million points in Antutu; surpasses Apple A18 Pro on Geekbench

The Snapdragon 8 Elite achieved an impressive overall score of 3,025,991 on Antutu. This represents a massive performance boost over the current Snapdragon 8 Gen 3. For reference, the latter scores around 2.1 million points in its best Antutu scores. These results are in line with what we’ve seen so far on other benchmark platforms. For example, in Geekbench, the chip scored 3,260 and 10,051 points on single-core and multi-core tests, respectively.

It’s notable that Geekbench results are comparable between Android and iOS devices. The Apple A18 Pro chip scores around 3,182 and 7,872 points in the single-core and multi-core tests on that platform. In GFXBench, a benchmark focused on graphics performance, the Snapdragon 8 Elite reached 125 FPS and 166 FPS in the DreamWorks Wild Life tests. So, the SoC is ready to take the tech industry by storm as soon as it is available.

The chip could be available in two variants

Leaks about Qualcomm’s upcoming flagship mobile SoC claim that it will use a 2+6 core architecture. The chip would be available in two variants, where the main difference would be the clock speed of the two most powerful cores. The “standard” version would reach 4.09 GHz, while the “Pro” variant would boast 4.32 GHz. The other six cores would have a clock speed of 2.78 GHz in both models.

In addition to the realme GT7 Pro, the iQOO 13, OnePlus 13, and Xiaomi 15 series will be the first devices to boast the Snapdragon 8 Elite. All (or most) of these phones are expected to arrive before 2025.

Apple Pay debuted almost 10 years ago to the day, and Apple is marking the occasion by rolling out some features it revealed at WWDC. If you have iOS 18 or iPadOS 18 installed on your iPhone or iPad, you’ll now be able to use the payment service on third-party browsers on those devices, as well as desktop computers. In the latter case, you’ll be asked to scan a QR code with your iPhone or iPad to complete the payment. However, Apple says the feature is only available in select markets.

It’ll be easier than ever to add supported cards to Apple Wallet on your iPhone. Thanks to the Tap to Provision feature, you can simply tap an eligible NFC-enabled card to the back of your phone, though you may have to enter the security code manually. Again, though, Tap to Provision isn’t available everywhere.

Apple is bringing more third-party buy now, pay later (BNPL) services to Apple Pay. This starts with the ability to check out with Klarna in the US and UK. The company will add more installment payment options in the future, including Citi, Synchrony and eligible Apple Pay issuers via Fiserv in the US. Klarna will also be available as an option in Canada at a later date. Apple discontinued its own Pay Later option earlier this year and it added Affirm as a BNPL option in the US last month.

Meanwhile, US Apple Pay users can redeem rewards on eligible Discover credit cards at checkout. Support for rewards from other issuers and in more countries is on the way.

Update October 18, 8:48AM ET: This story previously indicated that Apple was starting to add third-party BNPL services with the integration of Klarna, but Affirm support was added last month.

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Modern cybersecurity professionals require advanced technologies to deter, detect and expel hackers, and the predictive benefits of AI can mean the difference between data protection and ruin.

The average cost of a data breach in the U.S. hit a high-water mark of $9.48 million in 2023. Losses have ticked up every year since 2013, even during the global health emergency of Covid-19 when many businesses shuttered. An analysis in IBM’s 2024 data breach report indicates that organizations that employed extensive AI security automation saved $2.22 million, while also lowering cybersecurity insurance.

Industry leaders would be well-served to think about cyberattacks outside the financial implications, as well. Should your organization pay a ransomware demand or right the ship after a crushing malware attack, the reputational damage can far outweigh the dollars. When hackers steal confidential, sensitive and personal identity information, those in your orbit are negatively impacted. Employees, customers and industry partners may file civil actions. 

And, when word gets out that your enterprise cannot protect personal data, business can get eerily quiet. It’s not uncommon for an institution to file for bankruptcy within one year of a significant breach of trust. Fortunately, AI cybersecurity can harden your defenses and make cybercriminals look elsewhere for low-hanging fruit.

What role does AI play in cybersecurity?

There are wide-reaching benefits to integrating AI into an operation’s cybersecurity posture. The lengthy list, which we’ll briefly cover here, does have one central theme — reaction time. The bedrock of the thought leadership behind using AI in the data protection sector involves reducing how long it would otherwise take to detect and expel hackers.

The role AI plays in today’s lightning-quick hacking landscape can determine whether companies suffer stinging losses and hiccups or walk away unscathed. When you consider how fast a sophisticated cybercriminal can work, it’s abundantly clear why time is on the bad guys’ side unless we do something about it.

• Ransomware attacks: These hacks usually take 4 hours, but advanced persistent threats can take over a business network in 45 minutes. Ransomware attacks occur every 11 seconds.
• Phishing emails: Almost 30% of all phishing emails are opened by their recipients. These malware-laced communications account for 91% of all cyberattacks.
• Malware deployment: Hackers deploy malware at a rate of 11.5 attacks per minute.

The average hacker needs only 9.5 hours to pilfer off valuable and sensitive digital assets. Cybercriminals can operate with impunity if no one is monitoring activity while the business is closed and staff are fast asleep. Operations without AI, machine learning (ML) and other advanced technologies typically average 197 days to notice a breach and another 67 days to contain it. Hackers are more than happy to hide in plain sight and copy incoming data until you expel them.

The benefits of using predictive AI technology

The fundamental element of AI in cybersecurity may be its time management effectiveness. It’s important to understand how this forward-looking technology benefits an organization’s overall cyber hygiene. Here are some ways AI delivers quantitative and qualitative data security benefits.

Advanced threat detection

The ability of AI to sift through massive amounts of data seemingly at light speed cannot be matched by human beings. Programmed to learn and identify even subtle anomalies in network traffic, user activity and system logs can make it difficult for hackers to go undetected. Generating a real-time and ongoing analysis of wide-reaching movement, anything that deviates from predictive patterns gets flagged. A cybercriminal or deployed malicious software triggers an immediate threat detection alert. The most skilled perpetrator could not get the 45 minutes needed to effectively insert a ransomware file.

Behavioral analytics

To say that AI exceeds expectations in terms of behavioral analytics would be something of an understatement. ML, largely a sub-category of AI, involves following and understanding consistent patterns. For example, a legitimate network user enters a username, password, then a two-factor authentication code. Once inside the system, staff members carry out relatively consistent tasks. That means they open the same programs, access similar data and perform these duties in a uniform manner.

When a hacker orchestrates an attack, the digital burglar isn’t interested in filing incident reports or tabulating inventory. Cybercriminals head for valuable and confidential information that can be sold on the dark web. Because AI and ML follow the behaviors of users — sometimes down to keyboard strokes — alarms are triggered, and prompt actions are taken to confine and expel the threat.

Reduce fault threat alerst

Before organizations started adopting AI and ML, responding to false alarms seemed like the cost of doing business. That’s largely because the alternative was not knowing when a genuine threat was in progress. In terms of efficiency, pre-AI threat detection was a lot like a fire department responding to dozens of alarms being set off by overly sensitive heat detectors.

The rise of AI has been a game changer in terms of decreasing false alarms and reducing the time managed IT and security officers spend vetting each and every one. As technology adapts to common false positives and learns to distinguish between low-level and heightened irregularities, cybersecurity professionals spend fewer wasted hours.

Non-stop threat monitoring and learning

Although people and most machines require downtime, AI works relentlessly to identify abnormalities. During this never-ending process, technology continues to accumulate actionable information. It can adapt to changes in the digital landscape and be reconfigured to assess new norms. The alternative to AI would be hiring a full-time staff and checking systems activities 24 hours a day, 7 days a week. For many organizations, the cost of non-stop threat monitoring can prove prohibitive.

Getting comfortable with AI automated incident response

One of the processes that AI delivers involves automated threat responses. Not every business director feels comfortable allowing technology to push back on threats, be they malware, ransomware or a human attempting a blunt-force attack. There’s a certain loss of control that accompanies letting the so-called “machines take over.” But automated incident responses may actually be in your best interest.

Industry leaders can choose their comfort level regarding which threats are handled by the technology and which get elevated for a real person’s attention. Low-level threats are typically managed by AI, and it’s commonplace to have AI start the threat containment efforts while security professionals respond to an alert. These rank among the benefits companies gain from automating varying incident responses.

• Speed and efficiency: Pre-determined responses to emerging threats happen immediately. The speed at which AI can address these issues helps efficiently mitigate risk.
• Minimize human error: The majority of successful data breaches can be traced back to human error. Technologies such as AI and others carry out the procedures and duties assigned to them. You can’t trick AI into allowing users to access data deemed off-limits.

Integrating AI and ML may be one of the most cost-effective ways to harden your cybersecurity position. It does the work of dozens of humans faster and more efficiently without logging overtime hours. Adaptable to wide-reaching networks and architectures such as zero trust, its ability to sift through massive amounts of data, identify patterns and constantly learn makes it invaluable in risk management. When a threat actor finds a way into your network or an insider attempts to steal a trade secret, they cannot escape AI’s watchful eye.

John Funk is a creative consultant at SevenAtoms.