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Digital Surveillance Turns Everyday Devices Into Evidence

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Every time you unlock your smartphone or start your connected car, you are generating a trail of digital evidence that can be used to track your every move.

In Your Data Will Be Used Against You: Policing in the Age of Self-Surveillance, just published by NYU Press, law professor Andrew Guthrie Ferguson exposes how the Internet of Things has quietly transformed into a vast surveillance network, turning our most personal devices into digital informants. The following excerpt explores the concept of “sensorveillance,” detailing the specific mechanisms—such as Google’s Sensorvault, geofence warrants, and vehicle telemetry—that allow law enforcement to repurpose consumer technology into powerful tools for investigation and control.

A man walked into a bank in Midlothian, Va., his black bucket hat pulled low over dark sunglasses. He handed a note to the teller, brandished a gun, and walked away with US $195,000. Police had no leads—but they knew that the robber had been holding a smartphone when he entered the bank. Guessing that the smartphone, like most smartphones, had some Google-enabled service running, police ordered Google to turn over information about all the phones near the bank during the holdup. In response to a series of warrants, Google produced information about 19 phones that had been active near the bank at the time of the robbery. Further investigation directed the police to Okelle Chatrie, who was ultimately charged with the crime.

Cathy Bernstein had a tough time explaining why her own car reported an accident to police. Bernstein had been driving a Ford equipped with 911 Assist, which was automatically enabled when she struck another vehicle. Rather than stick around to trade insurance information, she sped away. But her smart car had registered the bump—and called the police dispatcher, leading to a fairly awkward conversation:

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Apparently, Bernstein did do something “like that.” She was soon caught and cited for leaving the scene of the accident. Her own car provided evidence of her guilt.

The Rise of “Sensorveillance”

Once upon a time, our things were just things. A bike was a tool for biking. It got you from one location to another, but it didn’t “know” more about your travels than any other inanimate object did. It was dumb in a comforting way, and we used it as intended. Today, a top-of-the-line bike can track your route and calculate your average speed along the way. Hop on an e-bike from a commercial bike share, and it will collect data for your trip, plus the trips of everyone else who used it that month.

These “smart” objects belong to what technologist Kevin Ashton named the Internet of Things. Ashton proposed adding radio-frequency identification (RFID) tags and sensors to everyday objects, allowing them to collect data that could be fed into networked systems without human intervention. A sensor in a river could monitor the cleanliness of the water. A tag on a bottle of shampoo could trace its journey throughout the supply chain. Add enough sensors to enough objects and you can model the health of an entire ecosystem—or learn whether you’re sending too much of your inventory to Massachusetts and too little to Texas.

Ashton first theorized the Internet of Things (IoT) in the late 1990s. Today, the IoT goes well beyond his initial vision, including not only RFID tags but also sensors with Wi-Fi, Bluetooth, cellular, and GPS connections. These small, low-cost sensors record data about movement, heat, pressure, or location and can engage in two-way communication.

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Of course, such a system is also, by necessity, a system of surveillance. “Sensorveillance”—a term I created to highlight the intersection of sensors and surveillance—is slowly becoming the default across the developed world.

Cellphone Surveillance Networks

Let’s start with phones. You’re probably not surprised that your cellphone company tracks your location; that’s how cellphones work. Both smartphones and “dumb” mobile phones use local cell towers, owned by cellphone companies, to connect you to your friends and family, which means those companies know which towers you are near at all times.

If you always carry your phone with you, your phone’s whereabouts—recorded as cell-site location information (CSLI)—reveal yours. One man, Timothy Carpenter, found this out the hard way after he and a group of associates set out to rob a series of electronics stores. Carpenter was the alleged ringleader, but he didn’t enter the stores himself. He served as the lookout, waiting in the car while his associates stuffed merchandise into bags.

It might have been hard for investigators to tie him to the crimes—if not for the fact that every minute he kept watch, his cellphone was pinging a local tower, logging his location. Using that information, the FBI was able to determine that he had been near each store during the exact moment of each robbery.

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Cell signals are the tip of the proverbial data iceberg. If you have a smartphone, you’re almost certainly using something created by Google. Google makes money off advertising. The more Google knows about users, the better it can target ads to them. Google’s location services are on all Android phones, which use the company’s operating system, but they’re also on Google apps, including Google Maps and Gmail.

For years, all that location information ended up in what the company called the Sensorvault. The Sensorvault, as the name suggests, combined data from GPS, Bluetooth, cell towers, IP addresses, and Wi-Fi signals to create a powerful tracking system that could identify a phone’s location with great precision. As you might imagine, police saw it as a digital evidence miracle. In 2020, Google received more than 11,500 warrants from law enforcement seeking information from the Sensorvault.

“Sensorveillance”—a term I created to highlight the intersection of sensors and surveillance—is slowly becoming the default across the developed world.

In 2024, Google announced that it would no longer retain all of this data in the cloud. Instead, the geolocation information would be stored on individual devices, requiring police to get a warrant for a specific device. The demise of the Sensorvault came about through a change in corporate policy, which could be reversed. But at least for now, Google has made it significantly harder for police to access its data.

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And while the Sensorvault was the biggest source of geolocational evidence, it is far from the only one. Even apps that have nothing to do with maps or navigation might nonetheless be collecting your location data. In one Pennsylvania case, prosecutors learned that a burglar used an iPhone flashlight app to search through a home, and they used the data from the app to prove he was in the home at the time of the break-in. These apps might be advertised as “free,” but they come with a hidden cost.

Cars, increasingly, collect almost as much information as phones. Mobile extraction devices can collect digital forensics about a car’s speed, when its airbags deployed, when its brakes were engaged, and where it was when all that happened. If you connect your phone to play Spotify or to read out your texts, then your call logs, contact lists, social media accounts, and entertainment selections can be downloaded directly from your vehicle. Because cars are involved in so many crimes (either as the instrument of the crime or as transportation), searches of this data are becoming more commonplace.

Even without physically extracting information from the car, police have other ways to get the data. After all, the car’s built-in telemetry system is sharing information with third parties. In addition to the usual personal information you give up when buying a car (name, address, phone number, email, Social Security number, driver’s license number), when you own a Stellantis-brand car, the company collects how often you use the car, your speed, and instances of acceleration or braking. Nissan asserts the right to collect information about “sexual activity, health diagnosis data, and genetic [data]” in addition to “preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes.” Nissan’s privacy policy specifically reserves the right to provide this information to both data brokers and law enforcement.

The Law of Smart Things

The fact that government agents can glean so much information from our things does not mean that they should be able to do so at any time or for any reason. The U.S. Fourth Amendment—drafted in an era without electricity—protects “persons, houses, papers, and effects” against unreasonable search and seizure, but is naturally silent on the question of location data.

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The first question is whether the data from our smart things should be constitutionally protected from police. In the language of the constitutional text, the smart device itself is an “effect”—a movable piece of personal property. But what about the data collected by the effect? Is the location data collected by your smartwatch considered part of the watch, or part of the person wearing the watch? Neither? Both?

To its credit, the U.S. Supreme Court has addressed some of the hard questions around digital tracking. In two cases, the first involving GPS tracking of a car and the second involving the CSLI tracking of Timothy Carpenter’s cellphone, the court has placed limits on the government’s ability to collect location data over the long term.

United States v. Jones involved GPS tracking of a car. Antoine Jones owned a nightclub in Washington, D.C. He also sold cocaine and found himself under criminal investigation for a large-scale drug distribution scheme. To prove Jones’s connection to “the stash house,” police placed a GPS device on his wife’s Jeep Cherokee. This was before GPS came standard in cars, so the device was physically attached to the undercarriage of the vehicle.

Data about Jones’s travels was recorded for 28 days, during which he visited the stash house multiple times. The prosecutors introduced the GPS data at trial, and Jones was found guilty. Jones appealed his conviction, arguing that the warrantless use of a GPS device to track his car violated his Fourth Amendment rights.

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“When the Government tracks the location of a cell phone it achieves near perfect surveillance.” — the Supreme Court

In 2012, the Supreme Court held that a warrant was required, based on the reasoning that the physical placement of the GPS device on the Jeep was itself a Fourth Amendment search requiring a warrant. Justice Sonia Sotomayor agreed regarding the physical search but went further, discussing the harms of long-term GPS tracking: “GPS monitoring generates a precise, comprehensive record of a person’s public movements that reflects a wealth of detail about her familial, political, professional, religious, and sexual associations.”

Timothy Carpenter’s ill-fated robbery spree gave the Supreme Court another chance to address the constitutional harms of long-term tracking. In their attempts to connect Carpenter to the six electronics stores that had been robbed, federal investigators requested 127 days of location data from two mobile phone carriers. The problem for the police, however, was that they had obtained the information on Carpenter without a judicial warrant.

Carpenter challenged the FBI’s acquisition of his CSLI, claiming that it violated his reasonable expectation of privacy. In a 5–4 opinion, the Supreme Court determined that the acquisition of long-term CSLI was a Fourth Amendment search, which required a warrant. As the Court stated in its 2018 ruling: “A cell phone faithfully follows its owner beyond public thoroughfares and into private residences, doctor’s offices, political headquarters, and other potentially revealing locales…. [W]hen the Government tracks the location of a cell phone it achieves near perfect surveillance.”

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Jones and Carpenter are helpful for setting the boundaries of location-based searches. But, in truth, the cases generate a lot more questions than answers. What about surveillance that is not long-term? At what point does the aggregation of details about a person’s location violate their reasonable expectation of privacy?

The Warrant According to Google

Okelle Chatrie’s case, in which police used Google’s location data to identify him as the mystery bank robber, offers a stark warning about the limits of Fourth Amendment protections under these circumstances. It’s also a terrific example of why “geofence” warrants, which request information within a certain geographic boundary, are appealing to police. From surveillance footage, detectives could see that the suspect had a phone to his ear when he walked into the bank. A geofence could identify who the suspect was, and likely where he came from and where he went. Google held the answer in its virtual vault. A warrant gave investigators the key.

The police cast a broad net. The geofence warrant asked for data on all the cellphones within a 150-meter radius, an area, as the court described it, “about three and a half times the footprint of a New York city block.” After receiving the police’s initial request for information on all the phones in the area, Google returned 19 anonymized numbers. Over the course of a three-step warrant process, the company narrowed those 19 phones down to three and then to one, which it revealed as belonging to Okelle Chatrie.

If the police wish to buy the data, just like an insurer or marketing firm might, how can you object? It’s not your data.

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The three-step warrant process is a unique innovation in the digital evidence space. Google’s lawyers developed a procedure whereby detectives seeking targeted geolocation data had to file three separate requests, first requesting identifying numbers in an area, then narrowing the request based on other information, and finally obtaining an order to unmask the anonymous number (or numbers) by providing a name.

To be clear, Google—a private company—required the government to jump through these hoops because Google considered it important to protect its customers’ data. It was the company’s lawyers—not the courts or the government—who demanded these warrants.

Buying Data

Warrants provide at least some procedural barrier to data collection by police. If government agencies want to avoid that minor hassle, they can simply buy the data instead. By contracting with data-location services, several federal agencies have already done so.

The logic for this Fourth Amendment loophole is straightforward: You gave your data to a third-party company, and the company can use it as it wishes. If you own a car that is smart enough to collect driving analytics, you clicked some agreement saying the car company could use the data—study it, analyze it, and, if it wants, sell it. If you don’t want to give them data in the first place, that is okay (although it will likely result in less optimal functionality), but you cannot rightly complain when they use the data you gave them in ways that benefit them. If the police wish to buy the data, just like an insurer or marketing firm might, how can you object? It’s not your data.

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Who Is to Blame?

Fears about the amount of personal information that could be revealed with long-term GPS surveillance have become reality. Today, police don’t need to plant a device to track your movements—they can rely on your car or phone to do it for them.

This happened because companies sold convenience and consumers bought it. So it might be tempting to blame ourselves. We’re the ones buying this technology. If we don’t want to be tracked, we can always go back to using paper maps and writing down directions by hand. If few of us are willing to make that trade, that’s on us.

But it’s not that easy. You may still be able to choose a dumb bike over a smart one, but a car that tracks you will soon be the only type of car you can buy. And while cars and data can, in theory, be separated, that’s not true for all our smart things. Without cell-signal tracking capabilities, a cellphone is just a paperweight. And in today’s world, living without a phone or a car is simply not practical for many people.

There are technological steps we can take toward protecting privacy. Companies can localize the data the sensors generate within the devices themselves, rather than in a central location like the Sensorvault. Similarly, the information that allows you to unlock your Apple iPhone via facial recognition stays localized on the phone. These are technological fixes, and positive ones. But even localized data is available to police with a warrant.

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This is the puzzle of the digital age. We can’t—or don’t want to—avoid creating data, but that data, once created, becomes available for legal ends. The power to track every person is the perfect tool for authoritarianism. For every wondrous story about catching a criminal, there will be a terrifying story of tracking a political enemy or suppressing dissent. Such immense power can and will be abused.

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Google’s quantum warning suggests Bitcoin encryption may fail sooner as reduced qubit requirements shift assumptions about future cybersecurity risks

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  • Quantum resource estimates suggest encryption barriers may fall faster than expected
  • Reduced qubit requirements bring theoretical attacks closer to practical reality
  • Bitcoin’s cryptographic foundations face pressure from advancing quantum algorithm efficiency

Google researchers have revised expectations around the computational requirements needed to break widely used cryptographic systems protecting cryptocurrencies.

The company’s latest whitepaper claims a future quantum machine could solve the elliptic curve discrete logarithm problem using significantly fewer resources than previously assumed.

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New Jersey has no right to ban Kalshi’s prediction market, US appeals court rules

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Kalshi can’t be stopped in New Jersey. A 3rd US Circuit Court of Appeals panel ruled on Monday that New Jersey has no authority to regulate Kalshi’s prediction market allowing people to bet on the outcome of sports events. That power rests with the Commodity Futures Trading Commission, the panel ruled 2-1.

The CFTC is headed by President Donald Trump appointee Michael Selig, who vocally and actively supports prediction markets like Kalshi and Polymarket, calling them “exciting products.” The Trump family agrees: Donald Trump Jr. is a paid adviser to Kalshi and an unpaid adviser to Polymarket, and Truth Social, which is run by the Trump Media and Technology Group, is set to start a prediction market of its own.

Online prediction markets are an emerging phenomenon that allow users to bet on the outcome of basically anything, from local athletic competitions to lethal military invasions. Though they’re new, these marketplaces have already shown evidence of insider trading on an extreme scale, with suspicious bets and big payouts tied to the US and Israel’s military strikes in Iran, and also the US’ brief invasion in Venezuela. According to blockchain analyst DeFi Oasis, fewer than 0.04 percent of Polymarket accounts captured more than 70 percent of profits, totaling $3.7 billion.

Multiple state gaming regulators have filed legal challenges against Kalshi and Polymarket in recent months, and just last week the CFTC sued Arizona, Connecticut and Illinois over their attempts to regulate prediction markets. While each state has its own angle of attack, from election issues to underage betting, they’re all broadly claiming that prediction markets are just illegal gambling businesses. Today’s ruling marks the first federal-level decision in one of these cases and it’s in favor of the prediction markets.

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New Jersey sent Kalshi a cease and desist letter in 2025, claiming the service violated the state’s ban on collegiate sports betting. Kalshi escalated the situation and sued New Jersey, arguing that its sports contracts are actually swaps, a type of financial investment that’s (conveniently) regulated by the CFTC. A lower-court judge previously sided with Kalshi, prompting New Jersey to appeal. Two of the three judges in that appeal ruled that Kalshi’s sports-related event contracts were indeed swaps. Kalshi CEO Tarek Mansour called Monday’s ruling “a big win for the industry.”

US Circuit Judge Jane Richards Roth dissented, writing that Kalshi’s “offerings were virtually indistinguishable from the ​betting products available on online sportsbooks, such as DraftKings and FanDuel.”

New Jersey Attorney General Jennifer Davenport has the option to ask the full 3rd Circuit to rehear the case, and the issue is also pending in several other courts.

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New GPUBreach attack enables system takeover via GPU rowhammer

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New GPUBreach attack enables system takeover via GPU rowhammer

A new attack, dubbed GPUBreach, can induce Rowhammer bit-flips on GPU GDDR6 memories to escalate privileges and lead to a full system compromise.

GPUBreach was developed by a team of researchers at the University of Toronto, and full details will be presented at the upcoming IEEE Symposium on Security & Privacy on April 13 in Oakland.

The researchers demonstrated that Rowhammer-induced bit flips in GDDR6 can corrupt GPU page tables (PTEs) and grant arbitrary GPU memory read/write access to an unprivileged CUDA kernel.

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An attacker may then chain this into a CPU-side escalation by exploiting memory-safety bugs in the NVIDIA driver, potentially leading to complete system compromise without the need to disable Input-Output Memory Management Unit (IOMMU) protection.

GPUBreach attack steps
GPUBreach attack steps
Source: University of Toronto

IOMMU is a hardware unit that protects against direct memory attacks. It controls and restricts how devices access memory by managing which memory regions are accessible to each device.

Despite being an effective measure against most direct memory access (DMA) attacks, IOMMU does not stop GPUBreach.

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“GPUBreach shows that GPU Rowhammer attacks can move beyond data corruption to real privilege escalation,” the researchers explain.

“By corrupting GPU page tables, an unprivileged CUDA kernel can gain arbitrary GPU memory read/write, and then chain that capability into CPU-side escalation by exploiting newly discovered memory-safety bugs in the NVIDIA driver.”

“The result is system-wide compromise up to a root shell, without disabling IOMMU, unlike contemporary works, making GPUBreach a more potent threat.”

Overview of how GPUBreach works
Overview of how GPUBreach works
Source: University of Toronto

The same researchers previously demonstrated GPUHammer, the first attack showing that Rowhammer attacks on GPUs are practical, prompting NVIDIA to issue a warning to users and suggesting the activation of the System Level Error-Correcting Code mitigation to block such attempts on GDDR6 memory.

However, GPUBreach is taking the threat to the next level, showing that it is possible not only to corrupt data but also to gain root privileges with IOMMU enabled.

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The researchers exemplified the results with an NVIDIA RTX A6000 GPU with GDDR6. This model is widely used in AI development and training workloads.

Comparison to other attacks
Comparison to other GPU attacks
Source: University of Toronto

Disclosure and mitigations

The University of Toronto researchers reported their findings to NVIDIA, Google, AWS, and Microsoft on November 11, 2025.

Google acknowledged the report and awarded the researchers a $600 bug bounty.

NVIDIA stated that it may update its existing security notice from July 2025 to include the newly discovered attack possibilities.

As demonstrated by the researchers, IOMMU alone is insufficient if GPU-controlled memory can corrupt trusted driver state, so users at risk should rely solely on that security measure.

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Error Correcting Code (ECC) memory helps correct single-bit flips and detect double-bit flips, but it is not reliable against multi-bit flips.

Ultimately, the researchers underlined that GPUBreach is completely unmitigated for consumer GPUs without ECC.

The researchers will publish the full details of their work, including a technical paper and a GitHub repository with the reproduction package and scripts, on April 13.

Automated pentesting proves the path exists. BAS proves whether your controls stop it. Most teams run one without the other.

This whitepaper maps six validation surfaces, shows where coverage ends, and provides practitioners with three diagnostic questions for any tool evaluation.

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Spain’s Xoople raises $130m to build the data infrastructure AI needs to understand Earth

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In short: Xoople, a Madrid-based geospatial data company founded in 2019, has raised a $130 million Series B led by Nazca Capital, bringing its total funding to $225 million and pushing its valuation into unicorn territory. The round was co-invested by MCH Private Equity, CDTI (the Spanish government’s technology development fund), Buenavista Equity Partners, and Endeavor Catalyst. Alongside the raise, Xoople announced a partnership with US space and defence contractor L3Harris Technologies to build sensors for its own satellite constellation, designed to produce Earth surface data it says will be “two orders of magnitude better than existing monitoring systems.” The company’s EarthAI platform, built on Microsoft Azure and distributed through Microsoft and Esri, delivers continuous surface intelligence for insurers, farmers, governments, and infrastructure operators.

Xoople has spent seven years building something that did not previously exist in a commercially deployable form: a continuous, AI-native data layer for the Earth’s surface. The Madrid startup, founded in 2019, emerged from that development period with a €115 million in prior funding, a platform embedded in the two most widely used enterprise geospatial ecosystems in the world, and a thesis that the AI era will require a fundamentally different approach to Earth observation — one designed from the ground up for machine learning rather than adapted from satellite imagery workflows built for human analysts. The $130 million Series B, led by Nazca Capital, confirms that investors believe that thesis is credible enough to back at scale.

CEO and co-founder Fabrizio Pirondini told TechCrunch the raise brings Xoople’s total funding to $225 million and puts the company in unicorn territory on valuation. The round was joined by MCH Private Equity, CDTI, the Spanish government-backed technology development fund that has also backed Nazca Capital’s aerospace and defence fund, Buenavista Equity Partners, and Endeavor Catalyst.

What EarthAI actually does

Xoople’s core product, EarthAI, is an end-to-end Earth intelligence system. It ingests continuous surface data, currently sourced from government spacecraft and third-party satellite networks, and processes it into AI-ready datasets that can be queried for change detection, risk prediction, and environmental monitoring. The key design choice is continuity: rather than producing point-in-time images for human review, EarthAI is built to stream a persistent, structured view of the planet’s surface into AI models that need regular, reliable ground truth.

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The use cases span industries that share a dependence on understanding what is happening on the physical surface of the Earth. For agriculture, EarthAI provides early detection of crop stress, monitors soil health and water conditions, and generates data that enables farmers to participate in carbon credit markets. For insurance, it enables more precise climate risk pricing and real-time verification of natural disaster claims, removing the delay and subjectivity of ground-based assessments. For infrastructure operators, it monitors physical assets for signs of stress or degradation before failures occur. For governments, it supports emergency planning, environmental enforcement, and humanitarian response. Capital flowing into specialised AI applications at the intersection of science, data, and infrastructure has accelerated considerably over the past year, and Xoople sits precisely at that intersection.

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The satellite play

The $130 million will fund Xoople’s transition from a platform built on others’ data to one powered by its own. Alongside the Series B, the company announced a partnership with L3Harris Technologies, a US space and defence contractor, to design and manufacture sensors for Xoople’s own satellite constellation. The sensors will collect optical data. Pirondini told TechCrunch that the constellation is designed to produce “a stream of data that is going to be two orders of magnitude better than existing monitoring systems“, a claim that, if borne out, would represent a substantial leap over the imagery quality currently available from commercial earth observation operators.

That claim is where Xoople meets its competitive reality. The company is entering a market that includes Vantor (formerly Maxar Intelligence, rebranded in October 2025), Planet Labs, BlackSky, Airbus Defence and Space, ICEYE, and Capella Space — all of which have satellites already in orbit and established AI-focused data processing pipelines. Companies building the hardware and data layers that AI depends on face a lengthy gap between the announcement of a new approach and its delivery in deployable form, and Xoople’s constellation is not yet in orbit. For now, EarthAI runs on data it did not produce. The L3Harris partnership signals that the proprietary data supply is the next phase.

Distribution before data

Xoople’s strategic sequencing is unusual for an Earth observation company. Most competitors in the space led with hardware — launching satellites, then figuring out distribution. Xoople did the reverse: it spent its first seven years embedding its platform into Microsoft and Esri, the two dominant environments where enterprise buyers, governments, and GIS professionals already live. Neither Microsoft nor Esri has its own proprietary satellite data. Xoople positioned itself to supply that gap from inside the platforms where the purchasing decisions are made.

The Microsoft relationship is structural: Xoople’s platform runs on Azure, and the company is integrated with Microsoft’s Planetary Computer Pro, which delivers AI-powered geospatial insights for enterprise use. Esri, the world’s largest geospatial software company, is a partner distributor. The implication is that when Xoople’s own constellation is operational and its data quality delivers on the “two orders of magnitude” promise, it will have distribution in place that its newer competitors would need years to replicate. The investment flowing into cloud-based AI data infrastructure has made the ability to process and deliver petabytes of Earth surface data at low latency a tractable problem; the scarcity is in the quality and continuity of the underlying data itself.

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A Spanish unicorn in a European context

Xoople’s raise is one of the larger deep tech rounds to come out of Spain in recent years, and it lands in a moment that the European space and defence investment community has been accelerating. Nazca Capital, which led the Series B, runs Spain’s largest private equity fund specialised in aerospace and defence, a fund that also received a €294 million commitment from CDTI and a €40 million investment from the European Investment Fund. The investor composition of the Xoople round,government-backed funds, European private equity, and Endeavor Catalyst, which focuses on high-impact technology entrepreneurs, reflects the persistent tension in European technology between deep technical ambition and the capital required to realise it: the funding is patient, multi-source, and has a public interest dimension that pure venture rounds often lack.

The earth observation market was valued at $7.04 billion in 2025 and is projected to reach $14.55 billion by 2034, growing at just over 8% annually. Xoople is betting that as AI models grow more capable and more dependent on real-world data, the market for continuous, structured Earth surface intelligence, rather than periodic imagery, will grow faster than that aggregate. A year in which the appetite for AI applications in climate, infrastructure, and environmental risk grew considerably provided the validation Xoople needed; the $130 million is the bet that the second half of the decade will prove it right at scale.

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Closing the data security maturity gap: Embedding protection into enterprise workflows

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Presented by Capital One


Data security remains one of the least mature domains in enterprise cybersecurity. According to IBM, 35% of breaches in 2025 involved unmanaged data source or “shadow data.” This reveals a systemic lack of basic data awareness. It’s not because of a lack of tooling or investment. It’s because many organizations still struggle with the most fundamental questions: What data do we have? Where does it live? How does it move? And who is responsible for it?

In an increasingly complex ecosystem of data sources, cloud platforms, SaaS applications, APIs, and AI models, those questions are only becoming more difficult to answer. Closing the maturity gap in data security demands a cultural shift where security is no longer treated as an afterthought. Instead, protection is embedded throughout the full data lifecycle, grounded in a robust inventory, clear classification, and scalable mechanisms that translate policy into automated guardrails.

Visibility as the foundation

The most persistent barrier to data security maturity is basic visibility. Organizations often focus on how much data they hold, but not on what that data is made up of. Does it contain personally identifiable information (PII)? Financial data? Health information? Intellectual property? Without this level of understanding and inventory, it’s a lot tougher to implement meaningful protection.

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This can be avoided, however, by prioritizing enterprise capabilities that can detect sensitive data at scale across a large and varied footprint. Detection must be paired with action, deleting data where it’s no longer needed, and securing data where it is by aligning enforcement to a well-defined policy.

Mature organizations should start by treating data security as an “understanding your environment” problem. Maintain an inventory, classify what’s in the ecosystem, and align protections with the classification rather than solely relying on perimeter controls or point solutions to scale.

Securing chaotic data

One reason data security has lagged behind other security domains is that data itself is inherently chaotic. Unlike perimeter security, which relies on explicit ports and defined boundaries, data is largely unpredictable. That is to say, the same underlying information may appear across very different formats: structured databases, unstructured documents, chat transcripts, or analytics pipelines. Each may have slightly different encodings or transformations that introduce unforeseen, and often undetected, changes to the data itself.

Human behavior compounds the challenge, with different actions introducing risks in ways that perimeter controls simply can’t anticipate. This could be anything from a credit card number copied into a free-form comment field, a spreadsheet emailed outside its intended audience, or a dataset repurposed for a new workflow.

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When protection is bolted on at the end of a workflow, organizations create blind spots. They rely on downstream checks to catch upstream design flaws. Over time, complexity accumulates and the risk of exposure becomes a question of when, not if.

A more resilient model assumes that sensitive data will surface in unexpected places and formats, so protection is embedded from the moment data is captured. Defense-in-depth becomes a design principle: segmentation, encryption at rest and in transit, tokenization, and layered access controls.

Critically, these safeguards travel with the data lifecycle, from ingestion to processing, analytics and publishing. Instead of retrofitting controls, organizations design for chaos. They accept variability as a given and build systems that remain secure even when data diverges from expectations.

Scaling governance with automation

Data security becomes operationally sustainable when governance is enforced through automation from its genesis. When coupled with clear expectations to create bounded contexts: teams understand what is permitted, under what conditions, and with what protections data can be used effectively.

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This matters more than ever today. AI systems often require access to huge volumes of data, across domains. This makes policy implementation particularly challenging. To do so effectively and safely requires deep understanding, strong governance policies, and automated protection.

Security techniques such as synthetic data and token replacement enable organizations to preserve analytical context while making sensitive values harder to read. Policy-as-code patterns, APIs, and automation can handle tokenization, deletion, retention constraints, and dynamic access controls. With guardrails built into the platforms they use, engineers can focus more on innovating with data and elevating business outcomes securely.

AI systems must also operate within the same governance and monitoring expectations as human workflows. Permissions, telemetry, and controls around what models can access, along with the information they can publish, are essential. Governance will always introduce a degree of friction. The goal is to make that friction well understood, navigable and increasingly automated. Confirming purpose, registering a use case, and provisioning access dynamically based on role and need should be clear, repeatable processes.

At enterprise scale, this requires centralized capabilities that implement cyber security policy in the data domain. This includes detection and classification engines, tokenization and detokenization services, retention enforcement, and ownership and taxonomy mechanisms that cascade risk management expectations into daily execution.

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When done well, governance becomes an enablement layer rather than a bottleneck. Metadata and classification drive protection decisions automatically while accelerating business discovery and usage. Data is protected across its lifecycle by strong defenses like tokenization and deleted when required by regulation or internal policy. There should be no need for teams to “touch the data” manually for every control decision, with policy enforced by design.

Building for the future

Put simply, closing the data security maturity gap is less about adopting a single breakthrough technology and more about operational discipline. Build the map. Classify what you have. Embed protection into workflows so that security is repeatable at scale.

For business leaders seeking measurable progress over the next 18–24 months, three priorities stand out.

First, establish a robust inventory and metadata-rich map of the data ecosystem. Visibility is non-negotiable. Second, implement classification tied to clear, actionable policy expectations. Make it obvious what protections each category demands. And finally, invest in scalable, automated protection schemes that integrate directly into development and data workflows.

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When protection shifts from reactive bolt-on controls to proactive built-in guardrails, compliance becomes simpler, governance becomes stronger, and AI readiness becomes achievable, without compromising rigor.

Learn more how Capital One Databolt, the enterprise data security solution from Capital One Software, can help your business become AI-ready by securing sensitive data at scale.


Andrew Seaton is Vice President, Data Engineering – Enterprise Data Detection & Protection, Capital One.


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UK Politicians Continue To Miss The Point In Latest Social Media Ban Proposal

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from the does-no-one-remember-being-a-teen? dept

The UK is moving forward with its efforts to ban social media for young people. Ahead of this week’s House of Lords debate on the topic, we’re getting you situated with a primer on what’s been happening and what it all means.

What was the last vote about? 

On 9 March, the House of Commons discussed amendments tabled by the House of Lords in the government’s flagship legislation, the Children’s Wellbeing and Schools Bill. 

The House of Lords previously tabled an amendment to “prevent children under the age of 16 from becoming or being users” of “all regulated user-to-user services,” to be implemented by “highly-effective age assurance measures,” which effectively banned under-16s from social media. When this proposal came before the House of Commons, MPs defeated it by 307 votes to 173. 

Instead, the Commons proposed its own amendment: enabling the Secretary of State to introduce provisions “requiring providers of specified internet services” to prevent access by children, under age 18 rather than 16, to specified internet services or to specified features; and to restrict access by children to specified internet services which ministers provide. 

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Who does this give powers to?

The Commons proposal redirects power from the UK Parliament and the UK’s independent telecom regulator Ofcom to the Secretary of State for Science, Innovation and Technology, currently Liz Kendall, who will be able to restrict internet access for young people and determine what content is considered harmful…just because she can. The amendment also empowers the Secretary of State to limit VPN use for under 18s, as well as restrict access to addictive features and change the age of digital consent in the country; for example, preventing under-18s from playing games online after a certain time.  

Why is this a problem? 

This process is devoid of checks or accountability mechanisms as ministers will not be required to demonstrate specific harms to young people, which essentially unravels years-long efforts by Ofcom to assess online services according to their risks. And given the moment the UK is currently in, such as refusing to protect trans and LGBTQ+ communities and flaming hostile and racist discourses, it is not unlikely that we’ll see ministers start restricting content that they ideologically or morally feel opposed to, rather than because the content is harmful based, as established by evidence and assessed pursuant to established human rights principles. 

We know from other jurisdictions like the United States that legislation seeking to protect young people typically sweeps up a slew of broadly-defined topics. Some block access to websites that contain some “sexual material harmful to minors,” which has historically meant explicit sexual content. But some states are now defining the term more broadly so that “sexual material harmful to minors” could encompass anything like sex education; others simply list a variety of vaguely-defined harms. In either instance, this bill would enable ministers to target LGBTQ+ content online by pushing this behind an under-18s age gate, and this risk is especially clear given what we already know about platform content policies. 

How will this impact young people? 

The internet is an essential resource for young people (and adults) to access information, explore community, and find themselves. Beyond being spaces where people can share funny videos and engage with enjoyable content, social media enables young people to engage with the world in a way that transcends their in-person realm, as well as find information they may not feel safe to access offline, such as about family abuse or their sexuality. In severing this connection to people and information by banning social media, politicians are forcing millions of young people into a dark and censored world. 

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How did each party vote? 

The initial push to ban under-16s from social media came from the Conservative Party, who have since accused the UK’s Prime Minister Keir Starmer of “dither and delay” for not committing to the ban. The Liberal Democrats have also called this “not good enough.” The Labour Party itself is split, with 107 Labour Party MPs abstaining in the vote on the House of Lords amendment. 

But we know that the issue of young people’s online safety is a polarizing topic that politicians have—and will continue to—weaponize for public support, regardless of their actual intentions. This is why we will continue to urge policymakers and regulators to protect people’s rights and freedoms online at all moments, and not just take the easy route for a quick boost in the polls.

How does this bill connect to the Online Safety Act?

The draft Children’s Wellbeing and Schools Bill that came from the Lords provided that any regulation pertaining to the well-being of young people on social media “must be treated as an enforceable requirement” with the Online Safety Act. The Commons amendment, however, starts out by inserting a new clause that amends the Online Safety Act. 

For more than six years, we’ve been calling on the UK government to pass better legislation around regulating the internet, and when the Online Safety Act passed we continued to advocate for the rights of people on the internet—including young people—as Ofcom implemented the legislation. This has been a protracted effort by civil society groupstechnologiststech companies, and others participating in Ofcom’s consultation process and urging the regulator to protect internet users in the UK.

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The MPs amendment essentially rips this up. Technology Secretary Liz Kendall recently said that ministers intended to go further than the existing Online Safety Act because it was “never meant to be the end point, and we know parents still have serious concerns. That is why I am prepared to take further action.” But when this further action is empowering herself to make arbitrary decisions on content and access, and banning under-18s from social media, this causes much more harm than it solves. 

Is the UK alone in pushing legislation like this? 

Sadly, no. Calls to ban social media access for young people have gained traction since Australia became the first country in the world to enforce one back in December. On 5 March, Indonesia announced a ban on social media and other “high-risk” online platforms for users under 16. A few days later, new measures came into effect in Brazil that restricts social media access for under-16s, who must now have their accounts linked to a legal guardian. Other countries like Spain and the Philippines have this year announced plans to ban social media for under-16s, with legislation currently pending to implement this.

What are the next steps?

The Children’s Wellbeing and Schools Bill returns to the House of Lords on 25 March for consideration of the new Commons amendments. The bill will only become law if both Houses agree to the final draft. 

We will continue to stand up against these proposals—not only to young people’ free expression rights, but also to safeguard the free flow of information that is vital to a democratic society. The issue of online safety is not solved through technology alone, especially not through a ban, and young people deserve a more intentional approach to protecting their safety and privacy online, not this lazy strategy that causes more harm than it solves. 

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We encourage politicians in the UK to look into what is best, not what is easy, and explore less invasive approaches to protect all people from online harms. 

Republished from the EFF’s Deeplinks blog.

Filed Under: social media, social media ban, teens, uk

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AI data centers are cooking the planet, creating extreme heat islands that affect millions in cities and rural regions alike

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  • AI data centers are producing extreme heat islands that extend miles beyond facilities
  • Over 340 million people experience elevated temperatures due to hyperscale AI facilities
  • Extreme temperature spikes of up to 16.4 °F have been recorded near data centers

The expansion of AI-driven data centers is having a more immediate environmental impact than previously understood, experts have warned.

A research team led by Andrea Marinoni at the University of Cambridge claims these facilities, often sprawling over a million square feet, are not only consuming massive amounts of energy but also generate extreme local heating effects, known as heat islands.

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Netflix is expanding into kids’ games with a new standalone app

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Netflix is launching a new standalone app for kids’ games called Netflix Playground, the company announced on Monday. Netflix Playground is available as part of a Netflix subscription, and doesn’t have any ads or in-app purchases.

Netflix says the app gives children access to an “ever-growing” library of games for kids. Netflix Playground is launching with titles featuring characters from popular kids’ shows.

The app, which is designed for children ages eight and under, is now available in the U.S., Canada, the U.K., Australia, the Philippines, and New Zealand. It will roll out worldwide on April 28. The app is available on both iOS and Android.

It can be accessed offline without a mobile or Wi-Fi connection, which the company says makes it the “perfect companion for long airplane rides or grocery trips.”

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Image Credits:Netflix

For example, one game is titled “Playtime With Peppa Pig,” and sees players “jump into Peppa’s world with a collection of playful activities.” There’s also a “Sesame Street” game where players practice matching with memory cards or coordination with connect-the-dots. Other titles include “Let’s Color,” “Storybots,” “Bad Dinosaurs,” and more.

“We’re building a world where kids can not only watch their favorite stories, they can step inside them and interact with their favorite characters,” said John Derderian, Netflix Vice President of Animation Series + Kids & Family TV, in a press release. “We’re creating a seamless destination for discovery, learning, and play. Whether it’s reuniting with Hank and the ‘Trash Truck’ crew for new adventures or making a smoothie with ‘Peppa Pig,’ watching and playing on Netflix can be the fun and easiest part of every family’s day.”

Netflix first launched games in 2021 and had ambitious plans for the space, but has since dialed them back after its titles failed to gain traction. The streaming giant has also shut down several video game studios like Boss Fight, Spry Fox, and an AAA studio.

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Late last year, Netflix forayed into TV gaming with a slate of new party titles meant to be played in groups, including TV versions of Tetris and Pictionary. The company has also said it will prioritize cloud gaming, but has noted that it’s still in the early stages of these plans.

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Playing DVDs On The Sega Dreamcast

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Although the Sega Dreamcast had many good qualities that made it beloved by the thousands of people who bought the console, one glaring omission was the lack of DVD video capabilities. Despite its optical drive being theoretically capable of such a feat, Sega had opted to use the GD-ROM disc format to not have to cough up DVD licensing fees, while the PlayStation 2 could play DVD movies. Fortunately it’s possible to hack DVD capability into the Dreamcast if you aren’t too fussy about the details, as [Throaty Mumbo] recently demonstrated.

For the Tl;dw folk among us, there’s a GitHub repository that contains the basic summary and all needed files. Suffice it to say that it is a bit of a kludge, but on the bright side it does not require one to modify the Dreamcast. Instead it uses a Pico 2 board that emulates a Sega DreamEye camera on the Dreamcast’s Maple bus via the controller port. The Dreamcast then requests image data as if from said camera.

On the DVD side of things there’s a Raspberry Pi 5 that connects to an external USB DVD drive and which encodes the video for transmission via USB to the Pico 2 board. Although somewhat sketchy, it totally serves to get DVDs playing on the Dreamcast. If only Sega had not skimped on those license fees, perhaps.

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5 Niche Craftsman Tools You Probably Shouldn’t Waste Your Money On

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The workshop has become a place with specialized gadgets for just about every task you can imagine. However, all this niche inventory often makes your workspace more complicated. It leaves you with a cluttered toolbox packed with pricey, single-purpose items that rarely get used. For many hobbyists and pros, that high-tech solution or a really specific manual tool can be tough to pass up when you’re browsing the hardware store aisles.

If you take a closer look at how useful these items actually are, you’ll see that the classic, versatile tools that have helped tradespeople for generations are often superior to modern, specialized versions. Many of these niche items aren’t good investments because they lack the adaptability of standard equipment.

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By taking a close look at these pricey novelties, you can better appreciate the value of a streamlined, multipurpose tool kit. Tools like speed squares, bungee cords, and extraction sockets can handle a wide range of problems across different projects and have many uses, unlike tools designed for a single use. Even with professional marketing and shiny finishes, you’re probably better off leaving these on the shelf.

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Digital Angle Gauge

The Craftsman Digital Angle Gauge is impressive, but it’s a lot more than you probably need. It’s built as a four-function tool, so it works as an angle finder, a compound cut calculator, a protractor, and a standard level. It can measure angles from 0 to 220 degrees and stays accurate to the nearest 0.1 degree. It’s made from durable aluminum, but is still pretty heavy at 2.7 pounds.

This is the kind of tool you could get from Home Depot that you wouldn’t realize existed. Digital gauges are great if you need decimal-point precision, but you don’t really need it for framing walls or building furniture. A standard speed square or a sliding T-bevel will give you plenty of accuracy for almost any project. Bringing a device with two delicate LCD screens onto a dusty, rough job site is just asking for problems.

One dropped board or a misplaced hammer swing can shatter those screens, turning your expensive tool into useless aluminum. You’re also going to get tired of dealing with batteries and electronic quirks. Even though the tool is built to be tough, an analog version will never run out of power in the middle of a measurement.

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Universal Nut Cracker

The Craftsman Auto Universal Nut Cracker is meant to save you when a nut is stuck and just won’t budge. It uses a hardened steel cutter to split the hardware, working on sizes from 5/16-inch to 7/8-inch across the flats. It’s designed to break rusted or frozen nuts without messing up the threads on the bolt underneath. While that sounds pretty good, it’s often tough to use in real-world situations, like in a cramped engine bay where the frame just won’t fit.

Even though it looks small, it measures 8.35 inches long, 3.35 inches wide, and 1.34 inches high. The maker says you can’t use power tools with it, so you’re stuck using your hands in tight spots where you probably can’t get much leverage anyway. A good set of extraction sockets is usually a better pick for rounded or stuck nuts, since those work on many sizes and aren’t hard to find. Instead of fighting with this tricky gadget, you could just grab a hacksaw or a torch to get that hardware off.

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Even the few people who bought it from Craftsman have left it an average of 1 star out of 5 possible stars. Store reviews, like these bad ones from Ace Hardware, often offer valuable insight from buyers. 

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Auto Caliper Hanger Set

The Craftsman Auto Caliper Hanger Set is a classic example of a tool you just don’t need to pick up. This universal kit works for cars with disc brakes, and it’s supposed to hold the calipers securely while you’re doing brake work. It’s designed to keep the heavy caliper from hanging on your rubber brake lines, which could really damage them. It’s basically a heavy-duty S-hook with a tough coating, so you can reuse it.

Even with all that in mind, it’s really just a single-purpose item that’ll mostly just clutter up your toolbox, which shouldn’t have tools you never use anyway. You can get the same result with things you probably already have in your garage. A basic bungee cord from Tractor Supply, or even a piece of scrap wire from an old coat hanger works just as well. You just bend the wire into an S-shape, and you’re good to go.

This is basically just a simple piece of bent metal made in China. The set does come with a limited lifetime warranty, and the company says it’ll replace it for any reason, even without a receipt. Still, there’s really no reason to spend your money on a dedicated hanger when alternatives you probably have will work similarly.

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Auto LED Inspection Mirror

The Craftsman Auto LED Inspection Mirror might seem like a smart way to check dark engine corners or behind walls, but it’s mostly a gimmick. It comes with a telescoping wand that has a rubber handle, a 2-inch mirror, and a swivel joint to help you get into tricky spots. The shaft begins at 6-1/4 inches and can stretch out to 37-1/2 inches.

The big selling point is its built-in LED light, which is meant to help you spot leaks or dropped bolts. However, that light is actually its main problem. Since it has an LED, the mirror needs a CR2032 battery to operate. These batteries last a while in a key fob, but drain relatively quickly with larger devices.

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For daily work, a standard telescoping mirror along with a basic headlamp or flashlight is plenty. When you separate the light from the mirror, you actually get better lighting angles. You can bounce the light off the glass to see what you’re checking out without the glare from the built-in LED messing up the reflection. You could even just put a separate light source in the engine bay to light up the whole area instead of counting on one tiny light on a stick.

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3-Jaw Oil Filter Wench

The Craftsman 3-jaw Oil Filter Wrench is another niche item that most people can live without. It’s marketed as a universal way to handle oil changes on different vehicles, promising to make the job simpler for anyone, regardless of their skill level. The tool uses metal jaws made from heat-treated steel. It’s designed to handle filters from 2 inches to 4-1/2 inches in diameter. It’s a low-profile item that’s 1.61 inches high and about 6.85 inches long, weighing in at 0.82 pounds.

Even with those specs and a lifetime warranty, this gadget isn’t a necessary purchase. It uses a gear mechanism to grip the filter while you turn it with a 3/8-inch or 1/2-inch drive ratchet. While it technically works, it’s not as versatile as some options. You likely already have many of the basic oil change tools from a store like Harbor Freight. A pair of filter pliers can handle the same job and will fit a much wider range of filter sizes.

This wrench is a heavy chunk of metal that takes up space. Sticking to a reliable strap wrench or standard pliers will save you money and keep your collection uncomplicated. Those tools also work for basic plumbing repairs, whereas this wrench does only one thing.

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Why these were picked

The hardware aisle is filled with specialized gadgets, like those in the Craftsman catalog, that solve singular problems rather than being multi-function tools. While these get marketed as revolutionary solutions to common mechanical hurdles, they can be a poor investment. These niche items tend to prioritize flashy, single-purpose engineering over the rugged adaptability that has defined the trades for generations.

Standard equipment like speed squares, extraction sockets, bungee cords, and basic strap wrenches gives you a level of durability and broad utility that specialized gear can’t match. These classic alternatives aren’t just way more affordable; they also do the same job without electronic glitches or taking up too much space. Being smart in the workshop is often about being clever, not about buying the fanciest gadgets.

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