For years, Google has been accused of harvesting data from Android phones without users’ consent. Following a California lawsuit that was settled for $314 million last year, a new settlement could mean payouts for another 100 million people.

A class action lawsuit alleging “Google caused Android mobile devices to transfer a variety of information to Google without users’ permission, consuming users’ cellular data,” is nearing its end. The two sides in Taylor v. Google LLC (PDF) have agreed to a settlement and have begun resolving it. 

Without admitting fault, Google agreed to a preliminary settlement in January, committing to pay $135 million in damages. The settlement website is now live. 

The final approval hearing won’t occur until June 23, when the court will hear objections and consider whether Google’s settlement is fair. After that, the court will decide whether to approve the $135 million settlement. 

In the meantime, if you qualify and want to be paid as part of the settlement, you can select your preferred payment method on the official website. There, you can find information on speaking at the June 23 court hearing and on how to exclude yourself or write to the court to object by May 29.

As part of the settlement, Google will update its Google Play terms of service to clarify that certain data transfers do occur passively even when you’re not using your Android device, and that cellular data may be relied upon when not connected to Wi-Fi. This can’t always be disabled, but users will be asked to consent to it when setting up their device. 

Google will also fully stop collecting data when its “allow background data usage” option is toggled off. 

Who can be part of the Google data settlement?

In order to join the Taylor v. Google LLC settlement, you must meet four qualifications:

1. Be a living, individual human being in the US.
2. Have used an Android mobile device with a cellular data plan.
3. Have used the aforementioned device at any time from Nov. 12, 2017, to the date when the settlement receives final approval.
4. You’re not a class member in the Csupo v. Google LLC lawsuit, which is similar but specifically for California residents.

To set your payment information on the official settlement website, you’ll need a Notice ID and Confirmation Code, which the settlement administrators mailed or emailed to eligible claimants.

The final approval hearing is on June 23, so you can add your payment method until then. The hearing’s date and time may change, and any updates will be posted on the settlement website. 

If you choose to do nothing and are eligible, you will still be issued a settlement payment, but not selecting a payment method might increase your risk of not getting paid.

Even if you didn’t receive a notification letter or email, you still might be eligible for a payout from Google. To find out, you can call the toll-free information number at 1-844-655-4255 or email info@FederalCellularClassAction.com. You can also mail a letter requesting more information to: Federal Cellular Class Action, 1650 Arch Street, Suite 2210, Philadelphia, PA 19103. 

Watch this: Your Phone is Disgusting: Let’s Fix That

05:07

How much could I get paid by Google?

It’s not currently known exactly how much each settlement class member will receive, but the maximum is $100. Payments will be distributed after final court approval and after the resolution of any appeals.

After all administrative, tax and attorney costs are paid, the settlement administrator will attempt to pay each member an equal amount. If any funds remain after payments are sent, and it’s economically feasible, they will be redistributed to members who were previously and successfully paid. If it’s not economically feasible, the funds will go to an organization approved by the court.

Photo credit: WSJ
Colin Angle, the co-founder who transformed the humble vacuum into a household staple, left iRobot in 2024 to pursue a new business, Familiar Machines & Magic. His most recent creation, Familiar, a four-legged companion, adds a unique element to living rooms. The prototypes, Daphne and Winston, are about the size of a bulldog. They have soft artificial fur to give them a cuddly appearance, and a touch sensitive layer underneath to detect how people interact with them. Their huge, round bear-cub ears and doe eyes draw them up for a conversation.

These things move using 23 separate joints, allowing them to bob their heads, tilt those little ears, adjust their gaze, and wag a small tail. They travel through the house at a slow pace, following you from room to room and plopping down when they think you’re close. People can touch them on the head or take them up for a squeeze, and the object will respond in a way that makes them feel alive, even if they do not say anything. They simply kind of… sound like they’re purring or emitting small chirps that change on the spot.

Loona Robot Pet Dog ChatGPT-4o Smart AI-Powered Companion Voice & Gesture Control, Real-Time Interaction…

• 🌟V28 update 🚀 new features are now available! In response to Loona’s charging problem, we’ve upgraded the automatic recharge 2.0.The upgrade is…
• 🤖 Smart and Interactive Robot Pet🧠Loona is like no other pet you’ve seen. With a high-definition RGB camera, Loona sees and understands your…
• 🗣️ Voice Command Enabled AI robot 🎤Loona is not just a good listener; also a great conversationalist! Powered by Amazon Lex & ChatGPT, Loona…

All of this is thanks to onboard cameras and microphones that detect tone of voice, posture, and everyday routine. It everything happens on the device, thanks to a small AI that has been trained to understand social cues. They remember what you do every day, notice when you appear off, and change their behavior over time to maintain everything feeling natural and seamless. They’re doing all of this without sending any video or audio clips, unless you choose to provide a small clip or two to help the developers figure out what to fix.

Angle and his team drew on their extensive experience at Disney, Boston Dynamics, and MIT. They blended some of the low-cost strategies they discovered while working on the original Roomba with fresh motion and sound design ideas that have emerged since then. So, what do we get? A robot that does not attempt to walk like a person or do anything other than be a good pet. Familiar keeps low to the earth and simply existing.

In terms of money, expect to spend between $50 and $100 each month for the luxury of having one of these things around. When you consider the cost of food and vet visits for the real thing, it’s not much different than what you’d pay in pet expenditures. Sales aren’t expected to begin until 2027, so don’t get too excited just yet. For now the prototypes serve as proof that everyday homes can welcome a machine built first for company instead of chores.

Between 2000 and 2002 the Fisher Price Pixter was sold to children as an educational handheld toy with a touch screen that enabled drawing and listening to music in addition to cartridge-based games and more. It was followed up by multiple new iterations of the system, but as an ecosystem didn’t last beyond 2007. This has left much of the system in obscurity, with people like [Dmitry] doing their best to reverse-engineer, dump and document what they can, such as recently for the entire range of Pixter devices and most of the games.

One of the reasons why [Dmitri] got interested in the second-generation Pixter Color originally was as a potential PalmOS porting target, which gives somewhat of an idea of how these devices were meant to be used.

With absolutely no remaining known official documentation on how to develop software for the hardware reverse-engineering posed somewhat of a challenge. Fortunately this was made somewhat easier by the Pixter Color using the ARM-based LH7541, but worse by just how much of a minimal ARM7 implementation the SoC is. This was meant to go into a cheap-ish kid’s toy after all.

Where things got wild was that the firmware implements a 16-bit stack-based virtual machine, possibly due to initially having selected a completely different SoC. From here things get even crazier with how audio output is implemented, with [Dmitry] descending into a long-winded rant on this and all the weird things encountered during reverse-engineering.

After the Color Pixter its Multimedia sibling with slightly better SoC was also reverse-engineered, as well as the Classic device that started it all. This particular device uses an 8-bit VM, but a black-blob 6502 processor, which is rather astounding for a 2000-era device, but then again it was meant to be a toy.

In addition to getting a lot of reverse-engineering woes off his chest, [Dmitri] also details how he reverse-engineered and dumped the cartridges, as well as writing emulators to ensure that the Pixter legacy will endure, for better or worse.

Top image: Pixter with opened case. (Credit: Raimond Spekking, Wikimedia)

Wise began trading on Nasdaq on Monday under the ticker WSE. Shares opened at 15.96 dollars. The London-founded fintech, which went public on the London Stock Exchange in July 2021 via a direct listing that valued it at 11 billion dollars, has moved its primary listing to New York while keeping a secondary listing in London. Nearly 91 per cent of class A shareholders voted in favour of the move. The company will now report in US dollars under US GAAP. It is not just changing exchanges. It is changing countries.

The Nasdaq listing is the most visible part of a broader American migration. Wise has applied for a national trust bank charter from the Office of the Comptroller of the Currency, with the proposed entity, Wise National Trust, based in Austin, Texas. If approved, the company intends to seek a master account at the Federal Reserve Bank of Dallas, which would let Wise clear and settle US dollar payments directly through the Fed’s rails, including FedNow. A fintech that began by making international bank transfers cheaper is rebuilding itself as an American financial institution.

The numbers

For the fiscal year ended 31 March 2026, Wise processed 243 billion dollars in cross-border volume, an increase of 31 per cent year over year. Net revenue was 2.5 billion dollars, up 19 per cent. Transaction revenue grew 22 per cent to 1.9 billion dollars, split between 1.3 billion in cross-border revenue and 600 million in card and other revenue. Card revenue grew 34 per cent, the fastest-growing segment.

Active customers reached 18.9 million, up 21 per cent. Customer holdings in Wise accounts climbed 40 per cent to 39 billion dollars. Seventy-five per cent of payments are now delivered instantly, up from 65 per cent a year ago. The company guided its income before tax margin toward the top of its 13 to 16 per cent target range, including the costs of the Nasdaq listing itself. Wise saved its customers more than 3.3 billion dollars in fees during the year, a figure the company uses to illustrate the pricing gap between its service and traditional bank transfers.

The market capitalisation is approximately 14 billion dollars. That is a premium to its 2021 direct listing price but below the levels implied by comparable US-listed fintechs. The move to Nasdaq is, in part, a bet that American investors will pay more for a company growing revenue at 19 per cent, processing a quarter of a trillion dollars annually, and expanding into banking.

The migration

CEO and co-founder Kristo Kaarmann was blunt about why Wise left London. “We have current shareholders who would like to own more, but they can’t, because there is not enough trading volume for them in our shares,” he said.

Major investors including Peter Thiel, Andreessen Horowitz, and Baillie Gifford had shown interest since the 2021 listing but were constrained by London’s liquidity. The US has the world’s deepest and most liquid capital markets. London does not.

The national trust bank charter application, filed in June 2025, is the more consequential move. A charter gives Wise a single federal regulator and federal legitimacy.

A Fed master account would give it direct access to the payment rails through which money actually moves in the American financial system, eliminating the need to route transactions through intermediary banks. Fed Governor Chris Waller has said publicly that he is exploring a streamlined account structure for newly chartered entities, but no formal framework exists. The charter is not guaranteed. The master account is even less so.

If both are approved, Wise would become one of the few fintechs with direct Fed access, a position that would fundamentally alter its cost structure for US dollar transactions and position it as a competitor not just to other fintechs but to the correspondent banking network that currently intermediates cross-border payments. The Austin hub is not a regional office. It is the foundation of a US banking operation.

The exodus

Tech companies have been snubbing the London Stock Exchange for years, but the pace has accelerated. Arm opted for a New York IPO in 2023. CRH, the building materials group, delisted from London entirely after switching its primary listing to New York. Flutter moved its primary listing to New York in 2024 and is now considering dropping London altogether. Darktrace left the London market after a 4.3 billion pound sale to Thoma Bravo. Just Eat quit for Amsterdam. Tui moved to Frankfurt. Ashtead and Indivior are gone or going.

More than 100 billion dollars in market capitalisation has migrated away from the LSE in the past five years. The pattern is consistent: companies list in London, grow, discover that London cannot provide the liquidity, analyst coverage, or valuation multiples they need, and leave. Wise is the latest. It will not be the last. Revolut, valued at 75 billion dollars after a 2025 secondary share sale, has confirmed that its IPO will be on Nasdaq, targeting a valuation of 150 to 200 billion dollars. Klarna listed on the NYSE last year.

McKinsey has warned that Europe’s software sector is at a critical inflection point, with the continent producing more than 280 software companies generating over 100 million euros in annual recurring revenue but struggling to retain them as public companies. The talent, the capital, and the customers are in the United States. The companies follow.

The counterargument

Monzo quit the US to focus on Europe ahead of a London IPO, a decision that suggests not every fintech concludes the American market is worth the cost of entry. Monzo’s board calculated that European expansion offered better unit economics than competing in a US market where customer acquisition costs are higher and regulatory complexity is deeper. The company is preparing to list in London, not New York, betting that a home-market focus is what investors will reward.

Wise is making the opposite bet. Its US business is its largest growth opportunity. The American cross-border payments market is the biggest in the world by volume. A banking charter and Fed access would give Wise structural advantages that no amount of London liquidity could replicate. The question is whether the regulatory path is as clear as the commercial one. Eleven companies filed for or received OCC national trust bank charter approvals in 83 days earlier this year, a wave that includes Circle and Ripple alongside Wise. The Fed’s master account process is slower, more discretionary, and less predictable.

The position

The argument that European startups need their own Nasdaq has been made for years. It has not happened. Instead, the companies that would anchor such an exchange keep leaving for the real one. Wise is now a Nasdaq-listed, Austin-headquartered, US GAAP-reporting company that happens to have been founded in London by two Estonians who were frustrated by the cost of sending money between the UK and Estonia.

The company processes a quarter of a trillion dollars a year. It has 18.9 million active customers. It is applying for a US banking charter. Its co-founder told investors that London could not provide enough liquidity for the shareholders who wanted to buy more. The Nasdaq listing is not the story. The banking charter is not the story. The story is that London built a fintech ecosystem, celebrated it, and is now watching it leave, one listing at a time, for markets that can price it properly.

General Motors has laid off more than 10% of its IT department, or about 600 salaried employees — in a deliberate skills swap: clearing out workers whose expertise no longer fits and making room for some with AI-focused backgrounds.

GM confirmed to TechCrunch that it had conducted layoffs; they were first reported by Bloomberg News.

In an emailed statement, the automaker framed the layoffs as a means to prepare it for the future, without providing specifics. “GM is transforming its Information Technology organization to better position the company for the future,” the company said.

These layoffs are not all permanent headcount reductions. A person familiar with the layoffs told TechCrunch that the company is still hiring people for roles in its IT department, but for different skills. The most sought-after capabilities are AI-native development, data engineering and analytics, cloud-based engineering, and agent and model development, prompt engineering, and new AI workflows. In practical terms, GM is looking for people who know how to build with AI from the ground up — designing the systems, training the models, and engineering the pipelines — not just use AI as a productivity tool.

GM has laid off white-collar employees in several departments over the past 18 months, as it focuses its resources on high-priority initiatives, including AI. In August 2024, for example, the company cut about 1,000 software workers.

The software workforce has undergone significant change since Sterling Anderson — co-founder of the autonomous trucking startup Aurora and a veteran of the autonomous vehicle industry — was hired in May 2025 as chief product officer. Last November, three top executives left the company’s software team as Anderson pushed to consolidate GM’s disparate technology businesses into one organization: Baris Cetinok, senior vice president of software and services product management; Dave Richardson, senior vice president of software and services engineering; and Barak Turovsky, a former VP at Cisco who spent just nine months as GM’s chief AI officer.

GM has since moved to fill the gap with new AI-focused hires. It hired Behrad Toghi, who previously worked at Apple, in October as AI lead. The company also brought on Rashed Haq as its vice president of autonomous vehicles. Haq spent five years at Cruise — the self-driving vehicle company acquired and later shuttered by GM — as its head of AI and robotics.

For the industry, GM’s restructuring is a signal of what enterprise AI adoption actually looks like in practice — not just adding AI tools on top of existing teams, but deliberately rebuilding the workforce from the ground up. The specific capabilities it’s hiring for — agent development, model engineering, AI-native workflows — point directly at where large-enterprise demand is heading.

GitLab is cutting jobs to invest in AI agents. The company announced on Monday that it will flatten management layers, reorganise its research and development teams into roughly 60 smaller autonomous units, reduce its country footprint by approximately 30 per cent, and use AI agents to automate internal reviews, approvals, and handoffs. CEO Bill Staples said the restructuring is “not an AI optimization or cost cutting exercise” and that the company intends to “reinvest the vast majority of savings back into the business to accelerate our unique opportunity in the agentic era.”

The stock fell more than eight per cent in after-hours trading. GitLab reaffirmed its guidance for the first quarter and full fiscal year 2027. Staples does not yet know how many roles the process will eliminate. The scope and financial impact will be disclosed on 2 June, when the company reports quarterly earnings.

The framing is now familiar. A software company announces layoffs. It says the cuts are about investment, not austerity. It promises to redirect savings into AI. The stock drops anyway. The question, as it is every time, is whether the restructuring represents a genuine strategic pivot or whether AI has become the vocabulary companies use to describe cost cuts they would be making regardless.

The company

GitLab makes a DevSecOps platform that manages the entire software development lifecycle, from planning and coding through testing, security scanning, and deployment. The company went public on Nasdaq in October 2021 at 77 dollars per share, closed its first day of trading at 103.89 dollars, and reached an all-time high of 137 dollars the following month. It now trades at approximately 25 dollars. The market capitalisation has fallen from roughly 15 billion dollars at its peak to 4.1 billion.

For fiscal year 2026, which ended in January, GitLab reported 955 million dollars in revenue, up 26 per cent year over year. Annual recurring revenue surpassed one billion dollars. Free cash flow was 220 million dollars, up more than 80 per cent. The company authorised a 400 million dollar share buyback. Fiscal year 2027 revenue guidance is 1.099 to 1.118 billion dollars, implying 15 to 17 per cent growth. The deceleration from 26 per cent to 16 per cent is the context for the restructuring.

GitLab operates as one of the world’s largest all-remote companies, with approximately 2,500 employees across more than 65 countries. The 30 per cent reduction in country footprint will consolidate that presence. Staples, who became CEO in December 2024 after co-founder Sid Sijbrandij stepped down for health reasons, previously ran New Relic and held executive roles at Microsoft Azure and Adobe Experience Cloud, where he oversaw three billion dollars in annual revenue.

The product shift

GitLab’s AI strategy centres on Duo, an agent platform that adds usage-based pricing alongside traditional per-seat subscriptions. The company introduced GitLab Credits, a virtual currency priced at one dollar per credit, to meter AI agent usage. Premium tier customers receive 12 credits per user per month. Ultimate tier customers receive 24. Automated code reviews cost 25 cents each, a flat rate that GitLab says undercuts competitors charging 15 to 25 dollars per review using token-based models.

The shift from pure per-seat pricing to a hybrid model that includes usage-based AI credits is an acknowledgment that the economics of developer tools are changing. When an AI agent can review code, set up pipelines, and remediate security vulnerabilities autonomously, the value of the platform shifts from enabling human collaboration to orchestrating machine workflows. The seat is no longer the natural unit of value. The task is.

GitHub froze new Copilot sign-ups after agentic AI broke the economics of its unlimited-use pricing. Agent-driven coding sessions run for hours, spawn parallel threads, and generate token volumes that dwarf traditional autocomplete interactions. The cost structures built for lightweight AI assistance no longer hold. GitHub’s response, pausing new individual subscriptions and tightening usage caps, signals that the era of unlimited AI coding assistance at fixed prices is ending. GitLab’s credit-based model is an attempt to get ahead of the same problem.

The competition

The AI coding tools market reached an estimated 12.8 billion dollars in 2026, up from 5.1 billion in 2024. GitHub Copilot holds approximately 37 per cent market share. Cursor has become the most widely adopted AI coding tool among individual developers. Amazon Q Developer, Google Gemini Code Assist, and JetBrains’ Junie agent are all competing for enterprise adoption.

GitLab’s position is different from most of these competitors. It is not primarily an AI coding assistant. It is a platform that manages the entire development lifecycle, and it is adding AI capabilities across that lifecycle rather than building a standalone AI product. The risk is that the platform becomes the substrate on top of which AI agents operate, essential but invisible, while the agent layer captures the margin. The opportunity is that enterprises want a single platform that governs the full workflow, including the AI agents running inside it, and GitLab is one of the few companies positioned to offer that.

Atlassian cut 1,600 jobs in March, approximately 10 per cent of its workforce, framed as an adaptation to the AI era. One month later, Atlassian launched AI visual tools and partner agents in Confluence. The pattern is identical to GitLab’s: cut staff, announce AI investment, ship AI features. The developer tools sector is restructuring around a thesis that fewer humans and more agents will produce better software faster. Whether that thesis is correct is an empirical question that the companies are answering with headcount reductions before the evidence is in.

The pattern

Meta and Microsoft announced 23,000 combined job reductions in the same week, with the same underlying logic: the companies are not cutting because they cannot afford their workforces but because they have decided to redirect that capital to AI infrastructure. Meta’s 135 billion dollar AI spending programme and Microsoft’s first-ever buyout offers represent the extreme end of a spectrum on which GitLab’s restructuring sits. The common thread is companies converting payroll into AI capital expenditure.

OpenAI CEO Sam Altman has called the practice of using AI as justification for cuts made for other reasons “AI washing.” Fewer than one per cent of 2025 job losses could be directly attributed to artificial intelligence, he said in February. The label matters because it determines whether investors should treat AI-justified restructurings as forward-looking investments or backward-looking cost cuts dressed in new language.

The human cost of tech layoffs is not captured in restructuring charges. The tech industry has shed more than 95,000 jobs across 247 layoff events in 2026, an average of 882 per day. GitLab’s contribution to that number will not be known until June. Staples wrote that “in some cases AI can augment and accelerate what team members have been doing, in other places we need to expand certain roles to go faster.” The sentence contains both a euphemism for job elimination and a promise of job creation. The ratio between the two is the number that matters, and it has not been disclosed.

The question

The argument that AI is not coming for your job but for your justification captures the dynamic playing out at GitLab and across the industry. The company is not replacing developers with AI agents. It is restructuring the organisation around a world in which AI agents handle an increasing share of the development workflow, and the humans who remain are expected to be more productive, faster, and focused on the work that agents cannot yet do.

GitLab’s revenue is growing at 16 per cent. Its free cash flow is 220 million dollars. It is not in distress. It is a profitable, growing company that has decided its current structure is built for an era that is ending. The company that pioneered all-remote work, that built a platform on the assumption that geographically distributed human developers need tools to collaborate, is now rebuilding around the assumption that many of those developers will be replaced by agents that do not need collaboration tools at all. The restructuring will be detailed on 2 June. The thesis, that the agentic era demands fewer people and more credits, is already priced in.

Security

UPDATED: Sorry, kids, everything’s back up so get to work on your new assignment – An essay on the ethics of paying ransoms, because it looks like that’s what happened here 

Ed-tech giant Instructure confirmed two rounds of unauthorized activity affecting its online learning platform Canvas within two weeks as data-theft-and-extortion crew ShinyHunters threatened to leak data it claims belongs to more than 275 million students, teachers, and staff tied to nearly 9,000 schools worldwide.

In a security incident update, Instructure apologized for the disruption when Canvas went offline last Thursday, leaving thousands of colleges, universities, and K-12 schools without access to course materials, grades, and due dates during final exams and Advanced Placement testing for many. 

As of Saturday, the parent company claimed, “Canvas is fully back online and available for use.”

And it finally broke its silence on Monday about what happened, admitting not one but two intrusions after criminals exploited a security vulnerability in its Free-for-Teacher learning system, and saying the data thieves stole information including usernames, email addresses, course names, enrollment information, and messages. 

“Core learning data (course content, submissions, credentials) was not compromised,” the Monday disclosure said. “We’re still validating all findings, but we want to be clear about what we understand was and wasn’t affected.”

On April 29, the online education firm “detected unauthorized activity in Canvas,” immediately revoked the intruder’s access, and initiated a probe into the breach, according to Instructure’s notice posted on its website. 

On May 7, the company “identified additional unauthorized activity tied to the same incident.” ShinyHunters defaced about 330 Canvas school login portals, also exploiting the same Free-for-Teacher vulnerability, and that caused the ed-tech firm to take Canvas offline and “into maintenance mode to contain the activity.”

ShinyHunters claims it stole 3.65 TB of data, including about 275 million records from about 8,800 schools including Harvard, Columbia, Rutgers, Georgetown, and Stanford universities. After moving the pay-or-leak deadline multiple times, ShinyHunters set a final deadline of end-of-day May 12 for individual institutions to contact them directly to negotiate payment – or the group will publish the full dataset.

In response, Instructure said it temporarily shut down its Free-for-Teacher accounts. It also revoked privileged credentials and access tokens tied to compromised systems, rotated internal keys, restricted token creation pathways, and added monitoring across all platforms. 

The education platform hired CrowdStrike to assist with its forensic analysis and incident response, and said it also notified the FBI – which published its own alert on social media – and the US Cybersecurity and Infrastructure Security Agency.

This is Instructure’s second breach in less than a year. ShinyHunters claimed to have breached Instructure’s Salesforce environment in September 2025, and while Instructure didn’t name the crew in its latest disclosure, it did address the intrusion. “The prior Salesforce-related incident and this Canvas security incident are distinct events involving different systems and circumstances,” the company said. ®

UPDATED AT 01:10 UTC MAY 12 Instructure At 10:21 UTC on May 11, Instructure updated its incident report to state “All Canvas environments are available.”

The company also admitted it “reached an agreement with the unauthorized actor involved in this incident” and secured stolen data.“

“We received digital confirmation of data destruction (shred logs),” the company said, adding “We have been informed that no Instructure customers will be extorted as a result of this incident, publicly or otherwise.”

Further: “This agreement covers all impacted Instructure customers, and there is no need for individual customers to attempt to engage with the unauthorized actor.”

The statement makes it hard not to conclude that Instructure took the controversial decision to pay a ransom.

“While there is never complete certainty when dealing with cyber criminals, we believe it was important to take every step within our control to give customers additional peace of mind, to the extent possible,” the statement adds.

There is no honor among thieves.