• Hackers exploited Lenovo’s flawed email verification to hijack ~5,000 Dropbox accounts
• Attackers created Lenovo IDs with victims’ emails, bypassing login; 2FA absence worsened impact
• Dropbox ended Lenovo ID logins, expired sessions, and urged password changes plus 2FA setup

Around 5,000 Dropbox user accounts were compromised when hackers found a vulnerability in the Lenovo ID verification process. What does a Lenovo flaw have to do with people’s Dropbox accounts, you might ask? Here is what happened:

Earlier this week, Dropbox started notifying affected individuals about the incident. In the data breach notification email, the company explains:

Facepalm: Security experts recently uncovered a malicious campaign that had been active for years. Unknown cybercriminals abused Chrome’s extension system to infect tens of thousands of systems, and many victims may still be vulnerable if they haven’t manually changed their browser’s configuration.

Socket Inc. researchers have identified 19 malicious extensions targeting Chrome and Edge users. The cybercriminal campaign primarily targeted Google’s browser, but one extension gained significant popularity on both Chrome and Edge. In any case, the analysts believe a single “mind” is behind the campaign – and it’s determined to keep going even after the extensions have been removed from both browsers’ stores.

All of the malicious add-ons employed a similar strategy, Socket said. A majority of the extensions (14) were developed directly by the cybercriminals, while five others were purchased from legitimate developers and companies. Initially, the add-ons simply provided their advertised functionality. Over the past six months, however, the hackers updated the extensions with malicious code designed to compromise systems or start harvesting users’ data.

The list of add-ons included a particularly popular extension named “Enable Right Click & Copy – Smart Unlock + OCR.” It was ultimately installed on 70,000 Chrome browsers and another 10,000 Edge browsers. A total of 80,000 users were eventually exposed to the malicious extension, which primarily targeted crypto wallets and other cryptocurrency-related data.

The cybercriminals used some code-based attack patterns that were first identified in February 2024, Socket said. They injected malicious payloads after accumulating a considerable number of potential victims, managing the crypto-stealing campaign remotely through a flexible command-and-control domain infrastructure.

The malicious extensions were eventually removed from the Chrome and Edge stores. However, users might still be part of the C2 infrastructure if they haven’t checked for and manually removed all 19 add-ons listed by researchers.

In 2018, Google announced a major change to the extension technology used by the Chromium project. The Manifest V3 API was intended to improve the security architecture of add-ons across Chromium-based browsers, including Chrome and Microsoft Edge.

As the 19 malicious extensions retrofitted with malicious payloads clearly show, Google’s attempt to strengthen security might very well turn out to be wishful thinking. Cybercriminals are likely to continue targeting popular browser extensions even after Manifest V2 is gone.

The internet has a trust problem, and it’s not just because social media feeds are filling up with AI slop. AI-generated text and images are now making their way into job applications, product reviews, and even insurance claims, leaving platforms and users alike scrambling to figure out what’s real. 

A handful of startups have cropped up in the past couple of years to become the “trust layer” the internet needs — including Pangram. The startup recently snapped up $9 million for its AI detection system and landed a partnership with Substack, which is now using Pangram’s tech to show readers which of their favorite authors use AI to write their newsletters. Pangram also recently dropped a new AI image detection tool. 

Watch as Pangram co-founder and CEO Max Spero joins TechCrunch’s Equity podcast to dig into the promise of AI detection tools and where to draw the line between AI assisted and AI generated. 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

from the this-is-why-we-can’t-have-nice-things dept

Back in June, the Supreme Court ruled 6–3 in National Republican Senatorial Committee v. Federal Election Commission that federal limits on coordinated expenditures by political parties violate the First Amendment, opening the floodgates to a much broader array of political ads funded via no limit of rich assholes and their preferred dark money groups.

In preparation for the ruling, Trump FCC boss Brendan Carr revised FCC “Lowest Unit Charge Requirement” rules to try and make it much cheaper for the GOP to pummel the midterm elections with less-expensive TV ads carried via the nation’s soggy assortment of right wing broadcasters (which are currently petitioning the Trump FCC to approve massive new mergers).

But it hasn’t all been easy going for the GOP, which believes its massive funding advantage ($125 million for the GOP versus a bunch of debt for the mismanaged DNC) would give them a real leg up during the midterms.

For one thing, the Richmond, Virginia-based 4th Circuit Court of Appeals recently sided 2-1 against the FCC, temporarily suspending the FCC’s attempt at discount TV agitprop, and ruling that neither political parties nor joint fundraising committees with non-candidate members are allowed the discounted rates.

But the GOP has already set the wheels in motion to get this all quickly overturned by the Trump-friendly Supreme Court:

“The committees submitted an emergency motion for a stay and asked the 4th Circuit to rule on that motion immediately so they can file a petition to the Supreme Court. “Intervenors respectfully request that the Court rule on this stay motion as soon as possible—whether by expediting or waiving response briefs—to permit Intervenors to seek emergency relief at the Supreme Court,” Republican committees told the court.

The court responded quickly, issuing an order today to deny the Republican committee’s motion and to immediately issue a mandate that can be appealed to the Supreme Court. Republicans will now seek swift action from the Supreme Court in an attempt to overturn the 4th Circuit ruling before the 60-day discount period starts on September 4.”

If the GOP wins, local broadcasters will be forced to offer dodgy dark money groups the same discounts previously reserved directly for candidates, something the FCC’s lone Democrat, Anna Gomez, states will be “unleashing a flood of coordinated campaign money into broadcast advertising, just as the Supreme Court has cleared the way for unlimited coordinated spending between parties and candidates.”

It’s another reminder (as if you needed one) that unless the U.S. Supreme court is radically expanded and reformed in the next few years, corruption is likely to strip the country down to parts and sell it for scrap off the back loading dock.

Filed Under: ads, appeal, brendan carr, fcc, midterms, propaganda, supreme court

Klipsch showed us quite a lot of hardware at CES 2026, but some of the most interesting products were sitting behind closed doors and came with the rather important disclaimer that we were looking at concepts.

The new Klipsch Reference Signature Series was one of them.

Eight months later, Klipsch is bringing Reference Signature to CEDIA Expo 2026 in Denver, and this time attendees will actually get to hear them. The company has also confirmed the six-model lineup, disclosed considerably more about the acoustic design, and provided an initial indication of what the speakers will cost when select models arrive this winter.

If Reference Signature sounds familiar, you have been paying attention.

We covered the early versions at CES in January, where Klipsch described Reference Signature as a more ambitious extension of its modern horn-loaded loudspeaker platform alongside the considerably more experimental Project Apollo.

What we did not see at Audio Advice Live 2026 was a Reference Signature launch. Klipsch used the Raleigh show in August for the global debut of its Reference Premiere III Series, including a rather substantial 7.4.4-channel home theater demonstration with Onkyo electronics.

Different speakers. Different series. There are already enough Klipsch model numbers in circulation without us helping create another family reunion nobody can follow.

Related Reviews:

Six Reference Signature Speakers

The new Reference Signature lineup consists of two floorstanding speakers, two monitor models, one center channel and a multipurpose Dolby Atmos, height and surround speaker.

Klipsch Reference Signature Series

• RS-8301F: Three-way 8-inch floorstanding loudspeaker
• RS-6301F: Three-way 6.5-inch floorstanding loudspeaker
• RS-8301M: Three-way 8-inch monitor loudspeaker
• RS-6301M: Three-way 6.5-inch monitor loudspeaker
• RS-6301C: Three-way 6.5-inch center-channel loudspeaker
• RS-6101SA: Two-way 6.5-inch Dolby Atmos, height and surround loudspeaker

The biggest departure from Reference Premiere is not the cabinetry or another variation on Klipsch’s familiar copper-colored drivers.

It is the dedicated midrange driver.

The floorstanding, monitor and center-channel models are true three-way designs with separate high-frequency, midrange and bass drivers. Klipsch says this allows each driver to handle a narrower portion of the audible spectrum and moves the crossover regions away from the frequencies where human hearing is particularly sensitive.

Paul W. Klipsch famously argued that “the midrange is where we live,” and apparently somebody in Indianapolis has been reading the old man’s notes.

A Different Kind of Klipsch Horn

Reference Signature still relies on horn loading and Klipsch’s titanium-diaphragm Linear Travel Suspension tweeter, but the more interesting development is its new phase-aligned horn architecture.

Klipsch positions the midrange directly within the tweeter horn so that the midrange and high frequencies originate from the same acoustic center. The objective is better coherence through the crossover region and more consistent tonal balance across a wider listening area.

That could prove particularly important in a home theater, where the person who paid for the system is rarely the only person sitting in front of it.

The larger Reference Signature models combine 8-inch Cerametallic bass drivers with a 6.5-inch midrange, while the smaller models pair 6.5-inch bass drivers with a 5.25-inch midrange. The floorstanding speakers use dual woofers, while the monitors use a single bass driver.

Klipsch’s spun-copper Cerametallic cones remain part of the recipe, maintaining some visual and technological continuity with Reference Premiere.

The Center Channel Might Be the Most Important Speaker Here

The RS-6301C deserves additional attention because Klipsch has moved away from the conventional horizontal MTM arrangement commonly used in center-channel loudspeakers.

Instead, Reference Signature uses a vertical driver array designed to reduce the horizontal lobing and comb-filtering issues that can make dialogue and tonal balance change as listeners move away from the center seat.

For a serious multichannel system, that is more than an engineering footnote.

The center channel carries an enormous percentage of movie dialogue and front-stage information, yet it is frequently the loudspeaker most compromised by furniture, screen placement and seating position. Klipsch’s approach is intended to provide clearer dialogue and more consistent timbre across multiple seats while maintaining a closer tonal match with the Reference Signature towers.

We want to hear this one from well off-axis before reaching any conclusions.

Atmos Without Locking Yourself Into Atmos

Klipsch has also avoided making the RS-6101SA a one-trick Dolby Atmos module.

The two-way speaker can sit on top of a Reference Signature tower or monitor and fire upward toward the ceiling, but it can also be wall-mounted for use as a direct-radiating height or rear surround channel.

A rear-panel switch changes the crossover configuration between Atmos and Surround operation.

That flexibility matters if somebody changes rooms, moves from reflected Atmos to direct-mounted height channels, or eventually realizes that drilling holes in drywall is less frightening than explaining another speaker upgrade to their spouse.

Klipsch Dresses Up

Reference Signature also represents a noticeable industrial-design upgrade over Reference Premiere.

Klipsch is using a one-piece BMC front baffle designed to provide a denser and more rigid mounting surface while reducing unwanted cabinet resonance. Rounded cabinet edges are intended to reduce diffraction and improve off-axis performance.

Ebony and Walnut finishes feature horizontal grain running along the curved cabinet profile, and Klipsch has added a decorative leather top panel along with metal carpet spikes and rubber feet.

All models will also provide adjustable tweeter output at +1 dB, 0 dB or -1 dB, giving owners a small degree of room or preference-based tonal adjustment without reaching for DSP.

Dual binding posts for bi-wiring and bi-amping will also be available on select models. None of that transforms loudspeaker performance by itself, but Reference Signature clearly needs to look and feel more expensive if Klipsch expects buyers to move beyond Reference Premiere.

The Bottom Line

Reference Signature should not be confused with the Reference Premiere III Series introduced at Audio Advice Live.

Reference Premiere III remains Klipsch’s broad modern passive loudspeaker platform for both two-channel and home theater systems. Reference Signature pushes further with dedicated three-way designs, more elaborate horn geometry, upgraded cabinetry and a considerably more premium presentation.

It is also not Project Apollo.

Klipsch previewed Apollo alongside Reference Signature at CES as a separate, more ambitious exploration of high-performance two-channel audio. Reference Signature is the more recognizable Klipsch proposition: a complete modern speaker family capable of supporting both serious stereo listening and immersive home theater.

That distinction makes the new series potentially more important commercially.

Klipsch does not need another loudspeaker that exists primarily to prove what its engineers can build when cost and living-room diplomacy are removed from the equation. It already has Heritage products capable of occupying that territory rather convincingly.

Reference Signature has to work in actual homes.

Price & Availability

Klipsch is targeting $1,600 to $3,000 per pair, with final pricing and complete specifications to be announced at launch. Select Reference Signature models are expected to arrive in winter 2026.

With CEDIA now underway, we’ll have a chance to hear the new three-way horn architecture for ourselves in Denver and find out whether Reference Signature delivers on the promise of what Klipsch first showed us at CES.

For more information: Klipsch Reference Signature

Related Reading:

Presented by Zeta

Every forward-deployed engineering (FDE) pitch sounds identical for the first ten minutes: an engineer embedded on-site, a workflow encoded within weeks, a demo that finally works on the customer’s real data. What differs is what happens in the following months, and most vendors will not tell you until you ask directly.

FDE has become one of enterprise AI’s most consequential operating models. Vendors are building entire go-to-market motions around engineers who embed with customers, wire products into operating environments, and make the demo real. Investors often read FDE headcount as a growth signal and buyers read it as a promise of speed. Neither tells you whether the work is becoming a product advantage or simply accumulating as delivery labor.

The test is simple: after an FDE engagement, does the next customer start with more product and fewer unknowns — or just a new services team?

FDE is not one thing. At its weakest, it papers over a product that cannot yet stand on its own, translating by hand what the software should eventually understand. At its strongest, it is a disciplined product-learning function: it finds the edge cases of an AI-native architecture and turns them into reusable capability. The org chart looks the same, but the economics and trajectory do not.

FDE is valuable because it creates automation that powers a system of intelligence. A system of intelligence is more than software that executes workflows. It captures enterprise context, incorporates what it learns from every deployment, and improves the quality of future decisions. Forward-deployed engineers are how that context enters the system in the first place.

The engineers are the context layer

Model choice still matters in some domains. But in many enterprise workflows, the bigger constraint is not the model, it is what the enterprise knows about itself including business rules, exceptions, workflow logic, and definitions that took a decade of operating history to settle. Access to data is not the same as understanding the business.

In one large telecommunications deployment, an initial definition of a “high-intent” customer did not survive contact with the operating systems. The model’s signal said one thing while the retention team’s actual save-desk criteria said another. Those criteria were built from years of which offers actually worked, on which tenure bands, in which regions. No schema documented that logic; it lived in the judgment of people who’d been doing the job for a decade. An engineer had to sit with them, extract the knowledge, and encode it before the intelligence layer we were building could be trusted to trigger an action instead of just a score.

Once that logic was encoded into the intelligence layer, new acquisition and retention use cases could move from idea to execution in days rather than months. Rather than rebuilding the integration each time, teams were adding decisions to a shared foundation.

That kind of work produces more than an answer for one customer. Properly captured, it can become a semantic mapping, a policy module, a workflow template, a connector, or an evaluation that guards the decision in future deployments. The FDE is the context layer delivered first as a person, who then translates and delivers it as product.

Sandbox, mud, and what happens to the learning

The useful question in a diligence call or renewal conversation is not whether a vendor has FDEs. It’s whether an engineer touching your environment is playing in a sandbox of tools, or trying to dig you out of the mud.

In the sandbox, FDEs use a general-purpose engine in specific, gnarly environments. Their job is to find where the engine needs a new part, install it, and feed the learning back so that part can ship again. In the mud, the engineer manually constructs a missing capability one customer at a time, and there is no engine underneath waiting to receive the part; instead, it’s another custom build.

Do not mistake these for a clean binary, though. Most companies live somewhere in the middle: reusable playbooks and connectors for the common cases, bespoke judgment for everything else. From the outside, sandbox, mud, and the middle can all look identical: a smart engineer, on-site, writing code against your data. The tell is what happens to what they learn. Either the next deployment begins with fewer unknowns, less custom code, and better tests, or it begins from zero with a prettier deck.

The strategic version of FDE treats every engagement as a disciplined learning loop. It starts with observing the exception in the field, codifying it into a reusable artifact, validating it with an evaluation and security review, releasing it into the product, then measuring whether the next deployment actually got easier. That last step is where most companies quietly fail. Not every field discovery belongs in the core product. Some customer logic is proprietary, temporary, or too idiosyncratic to generalize. Good teams know the difference between three things that get lumped together under “FDE”: product intelligence that compounds across every customer, configurable customer logic that’s reusable for one account but shouldn’t ship broadly, and one-off services work that is exactly what it looks like.

Customization is expected. The failure lies in not labeling which bucket the work is in, or in losing the learning from the parts that can compound.

This is the difference between a company that gets better at deploying and a product that gets better at understanding. The former can build a capable services business; its advantage lies in execution and relationships. The latter builds compounding product capability that persists after the engineer leaves.

The best FDE organization changes shape

The uncomfortable conclusion for teams building FDE functions is that human translation should shrink per unit of value delivered, even as absolute headcount grows. A fast-growing company may keep adding FDEs while still making each deployment materially lighter because more of the required logic already exists in the product. Each deployment should require less custom engineering than the last, with engineers spending more time extending reusable capabilities than rebuilding the same integrations, workflows, and decision logic.

Track four things:

• engineers per live workflow

• engineering hours per deployment

• time-to-value by vertical

• and the share of implementation work that gets reused rather than rebuilt.

Track one more that matters just as much and gets watched far less: the productization lag, the time between a field discovery, and a tested capability available to the next customer. Over time, that lag should fall, custom engineering should decline, and reuse should increase. If none of these are improving, the organization is delivering, without learning whatever the headcount chart says.

FDE is scaffolding only when it stays outside the building. The goal isn’t to eliminate the people doing the work; it’s to ensure more of what they learn becomes load-bearing product capability.

Three questions that get past the pitch

1. How is FDE priced?

Pricing is a signal rather than a verdict. A separate professional-services line may reflect honest transparency, bundled FDE may be a loss leader paid for by utilization. The more useful question is whether the contract, renewal, and margin story make clear which work is repeatable productization and which is bespoke delivery.

2. Where does field learning go?

Don’t infer this from résumés alone. Ask who owns the handoff from FDE to product, what artifacts are produced, and how quickly they become tested, supported capabilities. The organizational interface is what reveals whether learning compounds, not the job title.

3. What got faster on the last repeat deployment?

Ask for a specific vertical and a specific delta such as fewer engineering hours, fewer weeks to value, fewer custom integrations, or a higher reuse rate. A credible vendor can name what changed and how it was measured. General claims about “learnings” and “playbooks” are not enough.

Enterprise AI creates lasting advantage when every deployment leaves behind more than a satisfied customer. It leaves behind a deeper understanding of how enterprises operate. The goal isn’t simply to deploy AI. It’s to build a system of intelligence that captures enterprise context, converts customer learnings into reusable capability, and compounds over time.

Neej Gore is Chief Data Officer at Zeta.

Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.

A speed test measures three things in under a minute: how fast you can download data, how fast you can upload it, and how long a signal takes to reach a test server and come back. Run one for free at Speedtest by Ookla or Fast.com, ideally over a wired connection, and you’ll have a real answer before your coffee gets cold.

Quick Take

Before You Test

You don’t need to install anything to check your speed. A browser and about three minutes are enough. Close anything that’s actively downloading or streaming in the background first. Another device mid-download will drag your number down, and the test will show a falsely low reading.

How you test depends on what you’re actually trying to find out:

Run the Test

Once you’ve picked your path above, the actual test takes four short steps.

1. Pick a real test tool. Speedtest by Ookla and Fast.com are both free and need no account. Fast.com pulls its test data from Netflix’s own streaming servers, so it doubles as a check on your real Netflix performance, not just a lab number. Running both catches the rare case where one tool’s test server is having a bad day.
2. Connect the way your path calls for. Plugging in with an Ethernet cable gives the cleanest read on your plan’s real ceiling, according to T-Mobile’s testing guide. If you’re testing Wi-Fi, sit close to the router with as few walls in between as you can manage. Testing cellular means switching Wi-Fi off first.
3. Run the test and let it finish on its own. Tap or click Go. Most tests take 20 to 40 seconds and stop automatically once the numbers stabilize.
4. Repeat it three times, at different times of day. Try once in the morning, once during peak evening hours, and once more the next day. Write down all three sets of numbers before you draw any conclusions.

Reading Your Results

Your result screen shows four numbers, and each one tells you something different about your connection.

Download speed is how fast data moves from the internet to your device. It’s the number that decides how fast a video buffers or a webpage loads.

Upload speed is the reverse: how fast your device sends data out. It matters most for video calls, uploading files to cloud storage, and live streaming to an audience.

Ping, also called latency, is how many milliseconds a signal takes to reach the test server and return. Lower is better. High ping doesn’t slow down downloads, but it makes anything real-time feel laggy even on a fast connection. For online gaming specifically, ping usually matters more than download speed, and switching to a faster DNS server can shave off extra milliseconds.

Jitter is how much your ping bounces around from moment to moment. A connection with low average ping but high jitter still feels choppy on calls, because the delay keeps changing instead of holding steady.

What Speed Do You Actually Need?

The FCC’s household broadband guide sorts household needs into three rough bands, based on how many things you’re doing at once rather than any single app.

These tiers come from the FCC’s household broadband guide, and the agency is upfront that they’re rough estimates, not lab-tested numbers. The bottom row reflects a separate, more recent change: in 2024, the FCC raised its official broadband speed benchmark to 100 Mbps down and 20 Mbps up, four times higher than the old 25/3 Mbps standard.

Verify Your Result Against Your Plan

Compare your download number to what you’re actually paying for. Real-world speeds often run a bit below the advertised number, especially during peak hours when your neighbors are all streaming at once. A gap of 10 to 20% below your plan’s rating is normal and not worth worrying about.

A gap of 50% or more, especially across multiple tests at different times, points to a real problem. It could sit with your equipment, your home wiring, or your provider’s network.

If you run a small business or work from home full time and you keep landing short of what you’re paying for, it may be worth comparing a broadband service built for business use, since those plans are usually built for steadier, more simultaneous demand than a typical home plan.

Troubleshooting Slow or Inconsistent Results

Most bad speed test readings trace back to one of a handful of causes. Work through these in order before you call your provider.

Where This Approach Has Limits

A speed test is a snapshot, not an average. It tells you what your connection did for those 20 to 40 seconds, not what it does at 11pm on a Friday when your whole household is home and active.

It also can’t tell you where a problem actually lives. A low reading could point to your provider’s network, your own router, bad wiring in the walls, or a damaged cable. The test alone won’t say which.

A mesh Wi-Fi system or a set of powerline adapters complicates a clean reading further, since each hop between units adds its own small loss. Satellite and fixed wireless home internet behave differently than cable or fiber, too: higher and more variable ping is normal for those connections, even when the download number looks perfectly fine.

Key Takeaways

FAQ

AI AND ML

Predictive text remains available, but users will have to invite it into their workflow

Microsoft is switching off text predictions by default in Word and Outlook after acknowledging that unwanted suggestions can interrupt rather than assist some users.

The change is coming to Word for Windows, the web, iOS, and Android, as well as classic Outlook for Windows and Outlook for Mac. The feature will remain available but will no longer be enabled by default.

Introduced several years ago, the feature is the computing equivalent of Microsoft  peering over users’ shoulders and suggesting what they might type next. Depending on the user and their workflow, it can be a boon, an irritation, or simply something to ignore. The irksome part was that it was turned on by default.

According to Microsoft, “text predictions helps you write documents and emails more efficiently by suggesting words and phrases as you type. While some people find these suggestions useful, others prefer to write without predictive text. This update gives you more flexibility, allowing you to customize your editing experience and create a workflow that best suits your needs.

“This update helps ensure that predictive text remains available for people who find it helpful, while reducing unwanted interruptions for those who prefer to write without suggestions appearing automatically.”

The Windows behemoth did not explain whether the change will disable text predictions for users who have already enabled them or apply only to new installations and profiles. Users who want the suggestions will still be able to switch them on through the applications’ settings.

Microsoft is not the only company to suggest text as users type. Google, for example, introduced Smart Compose in Gmail in 2018.

Microsoft did not say whether telemetry or user feedback prompted the reversal, but it has elected to make the feature opt-in rather than opt-out.

It is a small change, but perhaps a sign that Microsoft is listening to customers who would rather decide for themselves whether AI belongs in their workflow. ®

Original Nintendo DS handhelds from late 2004 keep showing up in repair piles with hinges that snap and shells that powder at the slightest pressure. Owners who stored one in a drawer for two decades often discover the damage only when they try to swap a dead screen or tighten a loose screw. Metallic paint Nintendo laid over the ABS plastic appears to be reacting with the case itself. Yellow or greenish stains leak out around edges, button wells, and hinge roots. Force the clamshell open and the plastic flakes instead of flexing.

Gold Plastic Syndrome was named after a particular annoyance among Transformers collectors who noticed that gold and bronze swirl components began to shatter from the late 1980s onwards, frequently falling apart without any visible stress. The initial wave of successes comprised late Generation 1 figures, Generation 2 combiners, and Beast Wars toys. This state was differentiated not only by the stress-free manner in which the parts dissolved, but also by the shards’ appearance to leave microscopic fine residue for the collectors to clean up.

Nintendo Switch 2 System

• The next evolution of Nintendo Switch
• One system, three play modes: TV, Tabletop, and Handheld
• Larger, vivid, 7.9” LCD touch screen with support for HDR and up to 120 fps

Hasbro later said that the main reason for this was the large number of metallic flecks mixed into the plastic, which simply did not adhere properly, leaving microscopic gaps that accumulated and grew until the part failed with very no force. Sqwerks noticed the same thing on multiple original DS units and Game Boy Advance SP shells with the same gold finish.

Sqwerks spent years dealing with dozens of original DS consoles and only lately began documenting the awful state of the situation late last August, and the results are telling. A sky blue one still has some flexibility in the hinge, but another identical one that has the syndrome is showing signs of deterioration from the lid being pushed around. The paint appears to be a thin layer over a yellow green cast on the graphite black ones. The worst of them just completely break apart, with sides missing and a shredded ribbon cable as a bonus. The board and screen are usually still functional. The case, not so much. It only takes seconds to figure out why; take a screwdriver to a mid panel on an affected case, and it snaps with light pressure. Repeat the process with an unaffected unit, and everything should be OK.

As far as he can tell, no lab study has ever been able to pinpoint exactly what kind of chemistry is at work here, but it’s clear that the additives used to give off that metal sheen and nice swirl finish don’t work well with ABS plastic in the long run, leaving it brittle and prone to shattering. What accelerates the process even more? Age. Combine that with some heat and a layer of paint, and watch it break. No, Retrobrite won’t assist much because it only changes the colors of the old yellowed plastics. Oils that soften old rubber will also be of little use in this situation.

He believes that purchasing an aftermarket shell and getting rid of the factory one before it chooses to disintegrate on its own would be a better choice for people who own an original Nintendo DS in the same state. Save the original board, displays, digitizer, buttons, and other useful components.
[Source]