Technology

OpenAI is building an AI-powered smart speaker nobody wants. That is, if you believe the Bloomberg report from Mark Gurman and you've read his description of said rumored device.

According to the report:

"OpenAI believes the product’s defining feature will be its personality and ability to connect on a humanlike level with users. The speaker incorporates mechanical elements that can move on their own, creating a sense that it is alive and not just an object responding to commands. The machine also will draw on personal information such as emails to better understand its owner."

The news sources, it appears, come from an insider who decided to spill all the juicy details mere hours after Apple dropped a blockbuster trade-secrets lawsuit on OpenAI's head. OpenAI claims it's done nothing of the sort, and recent reports say that Apple's claim that the AI giant has not even responded to Apple's earliest concerns was based on it potentially incorrectly identifying the former Apple employees who left to join OpenAI (allegedly with Apple trade secrets in tow).

Apple's concerns here are twofold: First, these former employees had access to many of Apple's secretive product development details and may even have asked recruits to share fresh details when they approached them to interview for jobs at OpenAI. The other concern is that Apple is already far behind in the AI race, and if Apple's plans for Siri, AI, and a potential robotic desktop home assistant were also leaked, it could harm its ability to catch up in multiple market sectors.

This latest news, which may or may not be accurate, should put Apple's fears to rest.

OpenAI is apparently not building something that could ably compete with any of Apple's key hardware or future hardware initiatives.

First of all, there's the smart-speaker-ness of the whole rumored OpenAI concept. There are already too many smart speakers on the market, many of them with their own smart assistants. Amazon, for instance, is smack in the middle of trying to convince millions of customers that not only do they need Echo devices throughout the home, but they need the AI-powered Alexa+ to guide them through their smart home experiences and, to some extent, their lives.

Apple has its own HomePod, Siri-infused speakers, which may get considerably more powerful with the Gemini foundation model-backed version arriving this Fall.

Put another way, smart speakers are a known quantity in the home consumer electronics space, and I think what most tech companies are realizing is that people like and use them, but mostly in limited ways: they want music, occasional answers to simple questions, and voice control of their smart home devices. That's it.

Why does my speaker think it's alive?

(Image credit: Future)

OpenAI appears to be prepared to offer something different: a personality-filled speaker that can watch you, move to engage, seem alive, and generally make you feel uncomfortable.

Obviously, that would not be the objective, but it could be the result. Who needs a speaker that quietly watches you as you walk from your kitchen to the den, waiting and hoping for you to say, "hey ChatGPT, what's up with the Strait of Hormuz today?"

In my home, we have a Psync smart security webcam with one oddball feature: it has a motorized body that can turn almost 360 degrees on its base and lift its thin, rectangular face and camera to keep track of people and alert me to intruders. However, most of the time, it's just watching us move around the house, and I can tell you that my family hates it. Sometimes I come home and find its face forced down so it can't pop up and track anything.

Now, imagine a larger and far smarter OpenAI AI smart speaker in your home, watching, waiting, chiming in when you don't want it to, and generally making people feel uncomfortable.

This will not be the breakout hardware hit OpenAI is hoping for.

Look, I was under the impression that OpenAI (really Jony Ive and Sam Altman) were working on an AI wearable. I didn't love that idea either, but it was a lot less creepy than this.

So, Apple, chill out. OpenAI's plans are no threat to you, even if they do allegedly have a bunch of insidery Apple information.

• AI hallucination can be weaponized, new report warns
• HalluSquatting is short for “adversarial hallucination squatting”
• GitHub Copilot, Gemini CLI, and OpenClaw are all affected

Your favorite AI service could be subverted to deploy code that turns your phone or PC into a botnet, according to researchers at Intuit, Technion, and Tel Aviv University.

The technique has been given the name HalluSquatting, a portmanteau of adversarial hallucination squatting, and is similar to typosquatting in that it relies on a mistake in order to distribute malicious code. While typosquatting might occur with the incorrect input of a website URL, HalluSquatting pivots on an LLM being unable to identify a resource or repository with 100% accuracy.

Relying on an LLM’s tendency to hallucinate repository resource identifiers, this weakness could be scaled up to conduct massive ransomware campaigns, botnets, and more.

Push-me-pull-you

Previous LLM-based malware operations have relied on pull-based attacks. In this scenario, a prompt designed to jailbreak or otherwise subvert the AI is (for example) placed on a website and the LLM encouraged to gather the information, thereby reducing its internal security.

What the researchers have shared in their paper, is that pull techniques are being combined with push attacks, which are traditionally executed as code injection.

The paper’s introduction summary states: “By preemptively registering hallucinated resources—a technique we call adversarial hallucination squatting (HalluSquatting)—we demonstrate remote tool execution and remote code execution at scale across a range of popular agentic LLM applications, which could be exploited to the establishment of a botnet.”

Once an attacker has identified the resource likely to be misnamed by an LLM, and squatted on it (to embed adversarial prompts), the work is done. All that remains is for a user to trigger the resource, the AI chatbot or agent to initiate the response, and the squatted resource will be accessed.

Promptware attack

Following this, the adversarial content held within the squatted resource is activated, triggering the tool invocation stage. This is the promptware attack, where attacker-controlled instructions are executed, with results potentially including turning the device you’re using into a botnet zombie.

LLMs such as the Cursor, Cursor CLI, Windsurf, GitHub Copilot, Cline coding assistants have been used in the testing of this avenue of attack along with Gemini CLI, and the OpenClaw, ZeroClaw, and NanoClaw AI assistants. The researchers successfully achieved remote tool execution (essentially remotely accessing and controlling the LLMs) and remote code execution (RCE, where malicious code is executed remotely).

Some mitigation is available, including LLM developers blocking fetch operations in favor of a search tool, and resource owners enforcing strict naming, perhaps in favor of globally unique resource names. However, these are will require collaboration by disparate parties, and may take a while to implement.

The risk of LLM-based malware is increasing, and some has already been spotted in the wild. Of these, the JADEPUFFER attack is perhaps the most notable, as it isn’t simply AI-based malware – it is a full ransomware attack run entirely by an LLM.

Here are hints and answers for the NYT Strands puzzle for July 16, No. 865.

Here are some hints and the answers for the NYT Connections puzzle for July 16, No. 1,131.

Leaked Pixel Watch 5 renders reveal every color, both case sizes, and Google's familiar design ahead of the Made by Google event on August 12.

The post Google Pixel Watch 5 Renders Leak Ahead of Launch appeared first on TechRepublic.

Here are hints and the answer for today's Wordle for July 16, No. 1,853.

Microsoft is redesigning Windows Search with improved local results, fewer promotional elements, better file previews, and more control over web-based search.

The post Windows Search Gets a Major Revamp Focused on Usability appeared first on TechRepublic.

Looking to buy 3D printer filament? Skip the confusion with our top options for all experience levels, picked by CNET's experts.

The hack allegedly confirms the suspicions of record labels and artists that their music is used in the creation of AI music.

• The three man team is known as “Slopfix”
• It claims to be able to reduce AI generated codebases by up to 65% in size
• They aim to "refactor vibecoded codebases back to maintainability"

Vibecoding has a lot to answer for, not least some excessively large codebases. A new team of software engineers are collaborating to reduce the size of these cumbersome projects… with a $10,000 per week bill.

Slopfix is the name of the team (comprising a trio: Maciej, Kuba, and Krzysztof), but its aim is efficiency and functionality, rather than code golf, where code is reduced to the shortest possible length.

However, while this might seem like a noble task and a service worth paying for, Slopfix isn’t taking a stand against the use of AI. In fact, it is employing AI tools to detect the AI flab in your codebases.

Use an AI to catch an AI

Challenges around vibecoded projects have increased in recent months, as the limitations of the technology become apparent.

While using an AI to program based on your prompts and requirements is straightforward, agents habitually begin to lose context and logic once the project reaches a certain size or age. Once that happens, you’re looking at duplication, features breaking, and of course, the dreaded hallucination.

Slopfix is targeting companies that have adopted vibecoding, built huge codebases, and found that they’re running into issues. To find the problematic AI code, however, Slopfix is employing AI.

They state that a full “screen by screen, endpoint by endpoint” evaluation of the vibecoded app is made, which aims to find the duplicated functions, broken logic, and other issues. There’s also the promise of a two-week warranty for anything they break.

All of this is aided by Claude Code “on a very short leash” which Slopfix uses find problems. They clearly state that “the agent doesn’t get a vote.” Instead, they’re relying on their experience as developers to improve your code.

$10,000 seem a bit steep?

While the price might seem high, $10,000 for one successful week’s work for three seasoned developers shouldn’t really be a budget breaker.

The fee covers successful work only, and as the Slopfix website states, payment is in proportion to how much of the reduction target the team hits, with $10,000 being the price for hitting the target – it’s not the default fee.

However, there is a lot of preparation involved, and the analysis of your codebase is conducted free of charge. If they can't fix your project's issues, they'll let you know and refuse the contract.

As software consultancies go, Slopfix is an unusual case. But as the problems with vibecoded projects begin to become apparent, competing consultancies may begin offering similar services.

The UK plans a midnight-to-6 a.m. social media curfew for 16- and 17-year-olds, with autoplay and personalised feeds switched off by default from spring 2027.

The post UK to Introduce Midnight Social Media Curfew for Older Teens appeared first on TechRepublic.

New Jalisco and OmegaLord phishing kits target Microsoft 365 accounts by abusing device code flows, OAuth tokens, and MFA prompts to maintain access.

The post Jalisco, OmegaLord Phishing Kits Target Microsoft 365 Accounts appeared first on TechRepublic.

A new system could create patient-specific lenses for those with irregular corneas who struggle with traditional contact lenses.

New York paused new hyperscale data center permits for up to one year while it studies grid, water, ratepayer, and community impacts.

The post New York Imposes One-Year Moratorium on New Hyperscale Data Centers appeared first on TechRepublic.

Netflix brings the '80s nostalgia with this 10th-anniversary special edition of season 1.

• Vyriy 15 FPV with The Fourth Law's TFL-1 AI guidance reportedly struck Russian logistics 68 miles (110 KM) away
• Ever-innovating Ukrainian drone industry continues to achieve economies of scale even as it becomes a growing threat to Russian advances
• With a payload capacity of 8kg and the ability to be equipped with a thermal imaging module as well as electronic warfare deterrence, it offers an interesting alternative to comparable fixed-wing drones that cost thousands of dollars

Basic FPV drones are hardly a new thing in a market flooded with hundreds, if not thousands of options that can cost as little as $100 to 200, but the Russia-Ukraine conflict might have upped the ante on affordability for a different kind of UAV that leverages the same tech: attack drones.

The Vyriy 15 is a self-styled "kamikaze drone" by the company that offers a stated strike range of 40-70km with up to a 8kg payload in tow which can be retrofitted with a thermal imaging module as well as an extended band VTX module to make jamming it harder.

With a control range of up to 30KM and a flight duration of 20 minutes (with a payload) and a cruising speed of 60-100 km/h, its not the most technologically advanced drone out there, but at its purported price tag of $500, it doesn't need to be.

An FPV strike record backed by AI

On the 10th of July, Yaroslav Azhnyuk, the CEO of Ukrainian autonomy developer The Fourth Law, announced on X what he called "a new FPV strike record": a Vyriy 15 quadcopter, flown by Ukraine's 5th Border Guard Detachment and fitted with his company's AI terminal-guidance module, had flown 110 km (68 miles) to strike a Russian logistics target.

This is both a significant achievement for Ukraine's domestic drone industry and a key indicator of how fast the Russia-Ukraine war has turned into one of attrition, with supply lines becoming increasingly targeted to prevent significant advances in either direction.

It also showcases how AI on the battlefield is shaping the conflict: the Vyriy 15 is, by default, a manually controlled drone that would otherwise need an operator or a relay to be closer to the theater of war.

The competition is American-made Hornets, fixed-wing drones that can cost upwards of $5,000, a 10-fold increase in cost for an already cash-strapped Ukrainian military that is increasingly looking towards localized solutions.

The optional AI module used to set the record is The Fourth Law's TFL-1, a machine-vision terminal-guidance module that operates on a fire-and-forget principle: once the operator visually designates a target, an onboard computer takes over the final approach, essentially countering Russian jammers that would otherwise disrupt a video link.

If Ukraine manages to mainstream such warfare in the future while cutting costs down to a tenth of what they do right now, reliably striking as deep as 100km into enemy territory while proving difficult to jam or costly to intercept, drones like the Vyriy 15 could signal an evolution in the modern battlefield even as aggression with low-cost drone swarms is already being rewarded in other conflicts such as the US-Iran war.

Even if you don't use AI, I found some useful features in the iOS 27 beta. But most of them are smaller, quality-of-life changes.

Geopolitical tensions are mounting, and nation states are employing new types of strategies to gain intelligence. A recent Five Eyes warning, for example, accused Chinese military intelligence officers of using professional networking sites and online job platforms to target individuals of interest.

In this specific case, the agents pose as recruiters advertising seemingly legitimate work to build relationships and, ultimately, get their hands on non-public information. Popular sites like LinkedIn, Indeed and Upwork have all seen this new type of attack take place.

At the same time, a parallel threat sees operatives applying for jobs within trusted organizations with access to intelligence, creating insider threats that experts warn AI might be mostly responsible for.

Generative AI, for example, can create documents, write applications and even supply live answers during real-time remote interviews, meaning that a small group of fake applicants can extend their reach much more quickly.

Rather than attacking existing workers, nation states are creating their own job candidates

Once inside an organization and with access to company tools like PCs, emails and other internal systems, nation state spies can then move laterally to acquire the information they sought.

Security experts at Exabeam warn that, because this technique is still evolving, it might not always be so easy to spot. Additionally, motives can differ, with Chinese intelligence operations typically seeking military, political or economic information. North Korean agents, on the other hand, tend to be tied to stealing money, which could also come with the side effect of data and intelligence theft.

Exabeam even observed this type of attack first-hand, when a North Korean-affiliated applicant used a false identity to apply for a job at the company. After passing technical tests, a video interview and other standard checks, the suspect’s laptop was quickly flagged for unusual activity.

In the following Q&A with AI Strategy and Security Research VP Steve Povolny, I discuss these new types of attacks, who’s responsible for stamping them out and what we can do to prevent similar incidents from happening more commonly.

• The Five Eyes alliance recently warned that foreign intelligence groups are using job platforms to recruit insiders. How significant is this threat, and what is driving its growth?

This is among the most serious access-driven threats facing cleared workers, and it keeps growing because the economics now favor the attacker.

Foreign intelligence services no longer need handlers and dead drops when they can post a job ad on LinkedIn or Upwork and let candidates self-select based on the access listed in their own resumes. Generative AI lets them run thousands of these conversations at once, drafting outreach and scoring which applicants sit closest to sensitive information without a trained officer.

The Five Eyes alert describes a scaled, automated funnel, and that scale is what makes it dangerous.

• A parallel risk runs alongside that warning: adversaries who secure employment directly rather than recruiting an existing employee. Which scenario presents the greater defensive challenge, and why?

The infiltration model gives defenders less to work with, which makes it the harder problem. When an adversary recruits someone already on staff, most of the suspicious behavior happens outside the company on platforms the employer never sees, yet the insider remains a known person with a verified identity and a real history.

When the adversary becomes the employee, the company has onboarded a fabricated person and handed them a laptop and standing network access on day one. No behavioral baseline exists, since everything that account does counts as a first. The deception also clears the controls most organizations trust, so the failure lands before any security tool gets a vote.

• Exabeam identified a North Korea-affiliated individual who gained employment at the company. How did the operative clear Exabeam's hiring process, and what first signaled that something was wrong?

He cleared it by performing well on the parts we test and forging the parts we verify. Applying under the alias Trevor Rothluebber, he aced the technical interview and take-home assessment, passed the video interview and cleared our standard pre-employment process including the background check and I-9 validation.

Our hiring team flagged a suspicion that he leaned on generative AI for live help during the video call, the first soft signal. The hard signal arrived the moment he logged into his corporate account. Our threat intelligence feed matched his username to activity previously associated with North Korean operatives and rated it high risk, and that single match reframed how the team read everything that followed.

Simultaneously, Exabeam’s platform detected a number of anomalies inconsistent with a brand new employee’s first day, and escalating in severity within hours. Incident response quietly isolated and reimaged his laptop before any real damage could be done.

• The candidate completed applications, interviews and assigned work without raising alarm. In retrospect, what indicators were present, and why did standard screening miss them?

The indicators existed, but they lived in places our screening was never built to read. The driver's license he submitted was either AI-generated or very badly manually modified, and the tell was physical. The image had unique aberrations, such as the ears in the photo which had an unnatural and pixelated modification an artifact that image generators still produce, and a reviewer skims past.

The live AI assistance during the interview was another, since his answers carried a fluency that did not match the natural hesitation you expect when someone reasons through an unfamiliar problem. Standard screening missed all of it because background checks and identity validation confirm whether documents are internally consistent and whether a record exists, and they never ask whether the human attached to those documents is real.

Further fabrication of documents such as I-9 were missed by a 3rd party identity verification company, and validation of (fake) job references was not properly identified.

• How did AI contribute to the deception? What did the fraudulent documentation involve, and what capabilities does AI introduce that traditional forgery methods lack?

AI showed up at nearly every stage. The fraudulent documentation centered on a forged driver's license we believe was generated rather than physically produced, paired with a stolen identity that gave the paperwork a real history to rest on.

During the interview the candidate appeared to have run an AI copilot feeding him answers in real time, and many of these tools now stay invisible to everyone else on the call even while the candidate shares a screen. What AI adds over traditional forgery is volume and believability together. A skilled forger could always produce one convincing passport, but the craft capped how many operations could run at once.

Generative tools remove that ceiling, so a single actor can fabricate convincing documents and coach themselves through a live technical interview across dozens of applications at once, and the forgery stopped being the bottleneck it used to be.

• The Five Eyes warning focused on China, while the Exabeam case involved North Korea. Do these actors share tactics and objectives, or do they represent distinct operational models that overlap on method?

They overlap heavily on method while running on different motives, which defenders should sit with. The Chinese operation the Five Eyes described aims at intelligence collection, pulling government and military insight out of people who already hold access.

The North Korean program that hit us and so many others in this industry is funded differently, since much of its purpose is revenue for a sanctioned regime, with intrusion and theft riding alongside the paycheck. The objectives diverge, yet the tradecraft has converged on one toolkit of fabricated identities, AI-assisted documents, manufactured professional histories and the patient relationship-building that lets an operative stay quiet.

When two adversaries with separate goals reach the same playbook, that tells you the playbook works and other actors are already watching.

• Conventional insider threat programs are built to detect employees who become compromised over time. How should organizations identify a candidate who was an adversary from the point of hire?

Our mindset must shift toward treating the moment of hire as the start of the highest-risk window rather than the end of vetting. Traditional insider programs watch for drift, the employee who gradually turns after a financial shock or a grievance, so they depend on a baseline built over months.

A candidate who was hostile from day one never produces that baseline, which forces you to scrutinize the earliest behavior most closely. In our case, the catch came from putting new accounts under enhanced monitoring and letting an AI agent correlate scattered signals that no single alert would have justified escalating.

The working principle is to give hiring workflows and new-hire activity the same suspicion you already apply to production access.

• Where should accountability for this threat reside within an organization? Is it a security function, an HR function, or a gap that persists because ownership is unclear?

Accountability most often lives in the gap right now, and that gap is exactly why the threat works. Hiring sits with HR and talent acquisition, who are measured on filling roles quickly and are not equipped to run identity verification at an intelligence-grade level.

Detection sits with security, which usually gains no visibility into a candidate until that person already holds a badge and a laptop, and the adversary exploits the seam between the two.

The workable answer is shared ownership with a clean handoff, where security sets the identity and behavioral standards hiring must meet and stays involved through the first weeks of employment rather than inheriting the problem once onboarding closes.

• Many mid-sized companies lack dedicated threat intelligence resources. What practical measures can such organizations implement to reduce their exposure?

Useful defense does not require a dedicated threat intelligence team. The interview itself is the cheapest control available, and small changes make it far more revealing.

Underspecifying a problem on purpose shows whether a candidate asks clarifying questions like a real engineer or simply produces a confident answer and switching the problem partway through tests whether they adapt or whether something is feeding them responses.

Asking for an external webcam that shows the workspace instead of a shared screen removes one of the easiest hiding spots for an interview copilot. Beyond hiring, the highest-leverage move is placing every new employee on a watchlist for closer monitoring through their first weeks, which costs configuration time rather than budget.

Even a basic, low-cost threat intelligence feed would have surfaced the username match that broke our case open.

• What is the most contested prediction on this issue, one that many security leaders would currently dispute?

My contested prediction is that within a couple of years the verified human interview, run live and in person for any role with meaningful access, returns as a security requirement. Many security leaders will fight that because it breaks the remote-first hiring model they spent years optimizing.

The objection I expect is that it does not scale and shrinks the talent pool, and those concerns are legitimate. My counter is that the economics have already flipped for high-access roles, since the cost of onboarding a single fabricated adversary now dwarfs the friction of one in-person verification step.

The deeper claim underneath it is that remote identity verification as we practice it today is no longer reliable for sensitive positions, and AI is what made it unreliable. Most security leaders are not ready to say that out loud yet.

In the past year I've spent tens of hours streaming with VPNs, and one thing is consistently problematic for even the best VPNs — live events.

So, if you're traveling and keen to catch BBC's coverage of England vs Argentina later this evening instead, you might think you're stuck. Thankfully, NordVPN proved to be the one streaming VPN I tested that consistently performed well in these scenarios.

Over the past year, I've used NordVPN with Peacock, BBC iPlayer, TNT Sports, ITVX, and 7Plus. And compared to any other VPN, it's proved the most effective.

I experienced the least delayed streams, the least buffering, and, most importantly, the fewest complete connection dropouts when using NordVPN. So, while cheaper alternatives such as Norton VPN and Surfshark exist, if you want the most reliable performance, this is where I'd put my money.

If you don't want a long term commitment, you could always choose to pick a monthly plan. For $15, you can watch the rest of the tournament and gain all the additional security benefits that come with a VPN.

NordVPN: from $3.49/month or $15 for one month
It might not be the cheapest but NordVPN's price is more than worth it considering its performance. It's the most reliable VPN I've streamed with and it's packed with added security features to keep you secure once you've watched the big game. Unsure? Either pick up a monthly plan for only $15 or make use of NordVPN's 30-day money-back guarantee.View Deal

You don't need NordVPN's most advanced features to watch England with a VPN. That's a good thing, as right now its premium plans are considerably more expensive than many other providers.

With long term plans, Surfshark plans start at $2.49/month, a full dollar cheaper per month; the same goes for Norton VPN. If you're really budget-focused, both PIA and Cyberghost are less than $1.60 per month right now, too.

But, should you choose a NordVPN Plus plan or above, you do get some great perks. NordPass, the best password manager we've tested, cloud storage, dark web monitoring, and more are on offer.

It's worth mentioning that buying the more premium plans monthly will set you back at least $20, so I'd recommend signing up for a longer duration if you prefer these extra features.

• Group‑IB warns of scams exploiting Celine Dion’s concert comeback, with fraudsters selling duplicate Ticketmaster tickets and spoofing sites like AXS and Paris La Défense Arena
• Scammers embed themselves in Facebook fan groups and marketplaces, even using voice messages to build trust and make fake offers seem legitimate
• Fans are advised to only buy from official distributors, verify tickets in person if using resellers, and contact banks to dispute charges if scammed

Celine Dion is back, and hackers are already trying to exploit the fact for their own financial gain, experts have warned.

A report from security researchers Group-IB has claimed there are numerous scam campaigns all across the internet and social media, looking to exploit gullible fans and steal their money.

Its aptly named “The Scam Will Go On” report said it saw scammers lurking in Facebook Groups, Facebook Marketplace, and other fan-centric spaces, offering concert tickets for sale. The tickets themselves, hosted on Ticketmaster, are valid. However, the scammers only have a few tickets which can be redeemed by the first person who reaches the venue. Everyone else will be denied entry, since their tickets will already have been used.

How to avoid getting scammed

But that’s not the only scam. Some people don’t want to pay an unknown third person via wire, and would prefer to purchase the tickets directly from a service.

For those people, the scammers created entire websites, spoofing ticketing distributors such as AXS and Ticketmaster. Group-IB also saw fake websites spoofing Celine Dion and Paris La Défense Arena, the stadium where the concert will take place.

“We see that such an event generates excitement and provides scammers with another opportunity to make a fortune at the expense of unsuspecting fans,” Group-IB warned.

“Scammers are using increasingly sophisticated techniques, such as embedding themselves into social networking fan groups and speaking directly to their victims via voice messages to make the interaction more personal and gain their victims’ trust more easily. Furthermore, official ticketing platforms are being misused to make scams seem legitimate.”

The researchers recommend fans only visit official websites and those of official distributors, and if they absolutely must buy from a reseller, to make sure they’re purchasing a physical ticket, in person. Those that fell for the scam should call their bank and lodge an objection on their credit card.