A text that looks like it came straight from a courthouse is making the rounds across the U.S. And yes, I got it too.
First things first, that’s a scam. And to be clear: DON’T SCAN THAT QR CODE.
It’s the same playbook as last year’s toll road scams, just dressed up with a little more authority and a lot more pressure.
Before doing anything, our team ran it through McAfee’s Scam Detector. It immediately flagged the message as suspicious, and that’s exactly the kind of moment this tool is built for. When something feels just real enough to second guess, it gives you a clear signal before you click, scan, or spiral.
A screenshot showing Scam Detector in action.
How the scam works
The text claims you’ve missed a payment, violated a law, or have some kind of outstanding “case.” It then pushes you to scan a QR code or click a link to resolve it quickly.
From there, one of two things usually happens:
You’re taken to a fake payment page designed to steal your money, or
You’re prompted to download something that gives scammers access to your device or data
Either way, the goal is the same: get you to act fast before you have time to question it.
Here’s the scam text I got in California. You’ll notice it looks exactly like the others across the country.
The red flags in this message
Urgent, threatening language about fines, penalties, or legal action
Vague accusations with no real details about what you supposedly did
Official-looking formatting like case numbers, clerk signatures, and judge names
Copy-paste consistency across states: McAfee employees in New York and California received nearly identical messages with the same names
There are reports of this scam popping up nationwide, but the rule is simple: law enforcement does not text you to demand payment or resolve legal issues.
What to do if you scanned the QR code
First, don’t panic. Then:
Do not pay anything or enter personal information
Do not delete apps you were told to install (this can make it harder to detect what happened)
Run a device scan using a trusted security tool like McAfee’s free antivirus
Keep an eye on your financial accounts and logins for unusual activity
And that, my friends, is scam number one in this week’s This Week in Scams (new format, we’re experimenting a little).
Let’s get into what else is on our radar.
What to Know About an Alleged Crunchyroll Breach
Anime streaming platform Crunchyroll is investigating claims of a data breach involving customer support ticket data, potentially impacting millions of users.
According to TechCrunch, access appears to involve a third-party vendor system, a reminder that even strong security setups still rely on people and partners, which can introduce risk in everyday moments.
Even if you’ve never entered your credit card into a support form, these tickets can still include:
Email addresses
Usernames
Screenshots or account details
Conversations that reveal habits, subscriptions, or personal context
That’s more than enough for scammers to build highly believable follow-ups.
Why this matters right now
When breaches like this surface, scammers don’t wait. They use the moment to send emails and messages that feel timely, relevant, and legitimate.
For example, scammers might send messages pretending to be Crunchyroll and suggesting you “click this link to secure your account” after the breach. In reality, that “security check” exposes your information.
This is where tools like Scam Detector come back into play, flagging suspicious links and messages even when they reference real companies or real events.
What to do if you have a Crunchyroll account
Change your password, especially if you’ve reused it elsewhere
Turn on two-factor authentication
Be cautious of emails referencing the breach or asking you to “secure your account”
Avoid clicking links and go directly to the official site instead
How McAfee Helps You Stay Ahead of Scams and Breaches
McAfee+ Advanced gives you multiple layers working together so you’re not left figuring it out in the moment:
Scam Detector flags suspicious texts, emails, links, and even deepfake videos before you engage
Safe Browsing helps block risky sites if you do click or scan
Device Security helps detect and remove malicious apps or downloads
Identity Monitoring alerts you if your personal info shows up where it shouldn’t, so you can act fast
Personal Data Cleanup helps remove your information from data broker sites, making you a harder target in the first place
Secure VPN keeps your data private, especially on public Wi-Fi
Plus our instant QR code scam checks will flag suspicious QR codes before you scan them.
Safety tips to carry into next week
Slow down when a message creates urgency. That’s the hook
Don’t scan QR codes or click links from unexpected texts
Go directly to official websites instead of using links sent to you
Use tools that flag scams in real time so you don’t have to guess
The reality is, these scams are designed to look normal. You shouldn’t have to be an expert to spot them. That’s why McAfee’s here to help.
We’ll be back next week with more scams making headlines.
Experts say that an American ground operation targeting nuclear sites in Iran would be incredibly complicated, put troops’ lives at great risk—and might still fail.
The Telegram-based Xinbi Guarantee black market sells services that help prop up scam operations. British officials just hit the highly lucrative marketplace with sweeping sanctions.
US lawmakers are pressing Tulsi Gabbard to reveal whether using a VPN can strip Americans of their constitutional protections against warrantless surveillance.
As war reshapes the Gulf, the satellite infrastructure the world relies on to see conflict clearly is being delayed, spoofed, and privately controlled—and nobody is sure who is responsible.
The crowdsourced website and app Mahsa Alert provides citizens in Iran with crucial information amid the country’s ongoing war with the US and Israel—and an internet blackout.
Under a Homeland Security program, police departments around the US are signing up to assist in immigration enforcement. The cops of Carroll, New Hampshire, are going all in—and they’re likely not alone.
First heard as US and Israeli strikes on Iran began, the shortwave broadcast has since been traced to a US military base in Germany—but its purpose and its operator remain unclear.
A financially motivated data theft and extortion group is attempting to inject itself into the Iran war, unleashing a worm that spreads through poorly secured cloud services and wipes data on infected systems that use Iran’s time zone or have Farsi set as the default language.
Experts say the wiper campaign against Iran materialized this past weekend and came from a relatively new cybercrime group known as TeamPCP. In December 2025, the group began compromising corporate cloud environments using a self-propagating worm that went after exposed Docker APIs, Kubernetes clusters, Redis servers, and the React2Shell vulnerability. TeamPCP then attempted to move laterally through victim networks, siphoning authentication credentials and extorting victims over Telegram.
A snippet of the malicious CanisterWorm that seeks out and destroys data on systems that match Iran’s timezone or have Farsi as the default language. Image: Aikido.dev.
In a profile of TeamPCP published in January, the security firm Flare said the group weaponizes exposed control planes rather than exploiting endpoints, predominantly targeting cloud infrastructure over end-user devices, with Azure (61%) and AWS (36%) accounting for 97% of compromised servers.
“TeamPCP’s strength does not come from novel exploits or original malware, but from the large-scale automation and integration of well-known attack techniques,” Flare’s Assaf Moragwrote. “The group industrializes existing vulnerabilities, misconfigurations, and recycled tooling into a cloud-native exploitation platform that turns exposed infrastructure into a self-propagating criminal ecosystem.”
On March 19, TeamPCP executed a supply chain attack against the vulnerability scanner Trivy from Aqua Security, injecting credential-stealing malware into official releases on GitHub actions. Aqua Security said it has since removed the harmful files, but the security firm Wiz notes the attackers were able to publish malicious versions that snarfed SSH keys, cloud credentials, Kubernetes tokens and cryptocurrency wallets from users.
Over the weekend, the same technical infrastructure TeamPCP used in the Trivy attack was leveraged to deploy a new malicious payload which executes a wiper attack if the user’s timezone and locale are determined to correspond to Iran, said Charlie Eriksen, a security researcher at Aikido. In a blog post published on Sunday, Eriksen said if the wiper component detects that the victim is in Iran and has access to a Kubernetes cluster, it will destroy data on every node in that cluster.
“If it doesn’t it will just wipe the local machine,” Eriksen told KrebsOnSecurity.
Image: Aikido.dev.
Aikido refers to TeamPCP’s infrastructure as “CanisterWorm” because the group orchestrates their campaigns using an Internet Computer Protocol (ICP) canister — a system of tamperproof, blockchain-based “smart contracts” that combine both code and data. ICP canisters can serve Web content directly to visitors, and their distributed architecture makes them resistant to takedown attempts. These canisters will remain reachable so long as their operators continue to pay virtual currency fees to keep them online.
Eriksen said the people behind TeamPCP are bragging about their exploits in a group on Telegram and claim to have used the worm to steal vast amounts of sensitive data from major companies, including a large multinational pharmaceutical firm.
“When they compromised Aqua a second time, they took a lot of GitHub accounts and started spamming these with junk messages,” Eriksen said. “It was almost like they were just showing off how much access they had. Clearly, they have an entire stash of these credentials, and what we’ve seen so far is probably a small sample of what they have.”
Security experts say the spammed GitHub messages could be a way for TeamPCP to ensure that any code packages tainted with their malware will remain prominent in GitHub searches. In a newsletter published today titled GitHub is Starting to Have a Real Malware Problem, Risky Business reporter Catalin Cimpanu writes that attackers often are seen pushing meaningless commits to their repos or using online services that sell GitHub stars and “likes” to keep malicious packages at the top of the GitHub search page.
This weekend’s outbreak is the second major supply chain attack involving Trivy in as many months. At the end of February, Trivy was hit as part of an automated threat called HackerBot-Claw, which mass exploited misconfigured workflows in GitHub Actions to steal authentication tokens.
Eriksen said it appears TeamPCP used access gained in the first attack on Aqua Security to perpetrate this weekend’s mischief. But he said there is no reliable way to tell whether TeamPCP’s wiper actually succeeded in trashing any data from victim systems, and that the malicious payload was only active for a short time over the weekend.
“They’ve been taking [the malicious code] up and down, rapidly changing it adding new features,” Eriksen said, noting that when the malicious canister wasn’t serving up malware downloads it was pointing visitors to a Rick Roll video on YouTube.
“It’s a little all over the place, and there’s a chance this whole Iran thing is just their way of getting attention,” Eriksen said. “I feel like these people are really playing this Chaotic Evil role here.”
Cimpanu observed that supply chain attacks have increased in frequency of late as threat actors begin to grasp just how efficient they can be, and his post documents an alarming number of these incidents since 2024.
“While security firms appear to be doing a good job spotting this, we’re also gonna need GitHub’s security team to step up,” Cimpanu wrote. “Unfortunately, on a platform designed to copy (fork) a project and create new versions of it (clones), spotting malicious additions to clones of legitimate repos might be quite the engineering problem to fix.”
Update, 2:40 p.m. ET: Wiz is reporting that TeamPCP also pushed credential stealing malware to the KICS vulnerability scanner from Checkmarx, and that the scanner’s GitHub Action was compromised between 12:58 and 16:50 UTC today (March 23rd).
In a place denied access to basic forensic technology—and where people disappear into Israeli detention—the fate of thousands remains unknown. One of them is an autistic teenager.
For families of the missing, systemic obstacles to identifying remains and locating people in Israeli detention has created a kind of social and legal purgatory.
Congressman Jim Himes claims a sweeping surveillance authority should stay intact because he hasn't seen abuses by Kash Patel's FBI, according to internal messaging obtained by WIRED.
Meta blamed users for not opting into the privacy-protecting feature. Experts fear the move could be the first major domino to fall for end-to-end encryption tech worldwide.
The Aisuru, Kimwolf, JackSkid, and Mossad botnets had infected more than 3 million devices in total, many inside home networks, according to the US Justice Department.
Moxie Marlinspike says the technology powering his encrypted AI chatbot, Confer, will be integrated into Meta AI. The move could help protect the AI conversations of millions of people.
Today marks the start of Spring in the Northern Hemisphere, and with warmer weather setting in summer trips are vacation planning are starting to take shape.
But before you respond to that message about your hotel booking or payment confirmation, it’s worth asking: is it actually legit?
This week in scams, we’re breaking down a travel phishing scheme making the rounds through realistic booking messages, as well as new McAfee research on betting scams and AI-driven malware.
Scammers Who Know Your Exact Travel Reservation Details
A new phishing campaign targeting travelers is exploiting hotel booking platforms like Booking.com, and it’s convincing enough to fool even cautious users.
According to reporting from ITBrew and Cybernews, attackers are running a multi-stage scam:
How The Booking Scam Works
Scam Stage
How It Works
What You’ll Notice
How to Protect Yourself
Where McAfee Helps
Stage 1: Hotel account gets compromised
Attackers phish or hack hotel staff to access booking platforms and guest reservation data.
You won’t see this part — it happens behind the scenes.
Use strong, unique passwords and enable multi-factor authentication on your own accounts to reduce risk of similar breaches.
Identity Monitoring can alert you if your personal information appears in suspicious places or data leaks.
Stage 2: You receive a realistic message
Scammers use stolen booking data to send messages via WhatsApp, email, or even booking platforms.
The message includes your real name, hotel, and travel dates, making it feel legitimate.
Be cautious of unexpected outreach, even if the details are correct. Don’t assume accuracy means authenticity.
Scam detection tools can help flag suspicious messages and identify potential phishing attempts.
Stage 3: Urgency is introduced
The message claims there’s an issue with your reservation and pushes you to act quickly.
Phrases like “confirm within 12 hours” or “risk cancellation” create pressure.
Pause before acting. Legitimate companies rarely require urgent payment changes without prior notice.
Scam detection can help identify high-risk messages designed to pressure you into quick decisions.
Stage 4: You’re sent to a fake payment page
A link leads to a convincing lookalike site designed to steal your payment details.
The page looks real but may have subtle URL differences or unusual formatting.
Always navigate directly to the official website or app instead of clicking links in messages.
Safe Browsing tools can help block risky or known malicious websites before you enter sensitive information.
March Madness Brackets, Bets, and Bad Actors
March Madness brings brackets, bets, and a flood of bad actors.
New McAfee research found that 1 in 3 Americans (32%) say they’ve experienced a betting or gambling scam, and nearly a quarter (24%) say they’ve lost money to one. On average, victims reported losing $547.
That’s not surprising when you look at the environment around the tournament. More than half of Americans are watching, more than half are participating in some form of betting, and 82% say they’ve seen betting promotions in the past year.
Some of the most common setups this season include:
“Guaranteed win” or “can’t lose” betting tips that require payment upfront
Fake sportsbook promotions offering bonus bets or free credits
Messages claiming you have winnings, but need to pay a fee to unlock them
Impersonation scams posing as sportsbook support or betting platforms
Invitations to private “VIP betting groups” on WhatsApp or Telegram
The takeaway: If a betting offer promises guaranteed results, demands the use of bizarre apps and sites, asks for money upfront, or pushes you to act quickly, it’s not an edge. It’s a scam.
“AI-Written” Malware Is Hiding in Everyday Downloads
Not all scams start with a message. Some start with a search.
443 malicious ZIP files disguised as legitimate software
1,700+ file names used to make those downloads look credible
48 variants of a malicious DLL file used to infect devices
These weren’t hosted on obscure corners of the internet either. The files were distributed through platforms people recognize, including Discord, SourceForge, and file-sharing sites.
Here’s how the attack typically works:
You search for a tool.
You download what looks like the right file.
It opens normally at first.
Then, behind the scenes, malware loads quietly and begins pulling in additional code. In some cases, victims are shown fake error messages while the real infection happens in the background.
From there, attackers can:
Turn your device into a cryptocurrency mining machine
Install additional malware like infostealers or remote access tools
Slow down your system while running hidden processes
What makes this campaign stand out is that some of the code appears to have been generated with help from AI tools.
That doesn’t mean AI is running the attack on its own. But it does suggest attackers are using AI to:
Generate code faster
Create more variations of malware
Scale campaigns more efficiently
In other words, the barrier to building malware is getting lower.
The takeaway: If a download is unofficial, hard to find, or feels like a shortcut, it’s worth slowing down. The file may look right, but that doesn’t mean it’s safe.
How McAfee+ Advanced Works in These Scam Moments
Whether it’s a message about your booking, a betting offer that looks legitimate, or a download that appears to be exactly what you were searching for, these scams all rely on the same thing: they blend into everyday moments.
That’s where having backup like McAfee+ Advanced comes in. It includes:
McAfee’s Scam Detector, which helps flag suspicious links in texts and messages like the ones used in these booking and betting scams, so you can spot something risky before you engage
Web protection and real-time device security, helping protect against risky links, malicious sites, and evolving threats if you do click, including fake betting platforms or malware hidden in downloads
Personal Data Cleanup, which helps remove your information from sites that sell it, making it harder for scammers to access the personal details that make messages and scams feel legitimate
Secure VPN, which helps keep your personal info safe and private anywhere you use public Wi-Fi, like hotels, airports, and cafés while traveling
Identity Monitoring and alerts, with 24/7 scans of the dark web to help ensure your personal and financial information isn’t being exposed or reused
Credit and transaction monitoring, so you can get alerts about suspicious financial activity if your information is ever compromised
Identity restoration support and up to $2 million in identity theft coverage, giving you access to US-based experts and added peace of mind if something does go wrong
Stay skeptical, verify before you click, and we’ll see you next week with more.
The U.S. Justice Department joined authorities in Canada and Germany in dismantling the online infrastructure behind four highly disruptive botnets that compromised more than three million Internet of Things (IoT) devices, such as routers and web cameras. The feds say the four botnets — named Aisuru, Kimwolf, JackSkid and Mossad — are responsible for a series of recent record-smashing distributed denial-of-service (DDoS) attacks capable of knocking nearly any target offline.
Image: Shutterstock, @Elzicon.
The Justice Department said the Department of Defense Office of Inspector General’s (DoDIG) Defense Criminal Investigative Service (DCIS) executed seizure warrants targeting multiple U.S.-registered domains, virtual servers, and other infrastructure involved in DDoS attacks against Internet addresses owned by the DoD.
The government alleges the unnamed people in control of the four botnets used their crime machines to launch hundreds of thousands of DDoS attacks, often demanding extortion payments from victims. Some victims reported tens of thousands of dollars in losses and remediation expenses.
The oldest of the botnets — Aisuru — issued more than 200,000 attacks commands, while JackSkid hurled at least 90,000 attacks. Kimwolf issued more than 25,000 attack commands, the government said, while Mossad was blamed for roughy 1,000 digital sieges.
The DOJ said the law enforcement action was designed to prevent further infection to victim devices and to limit or eliminate the ability of the botnets to launch future attacks. The case is being investigated by the DCIS with help from the FBI’s field office in Anchorage, Alaska, and the DOJ’s statement credits nearly two dozen technology companies with assisting in the operation.
“By working closely with DCIS and our international law enforcement partners, we collectively identified and disrupted criminal infrastructure used to carry out large-scale DDoS attacks,” said Special Agent in Charge Rebecca Day of the FBI Anchorage Field Office.
Aisuru emerged in late 2024, and by mid-2025 it was launching record-breaking DDoS attacks as it rapidly infected new IoT devices. In October 2025, Aisuru was used to seed Kimwolf, an Aisuru variant which introduced a novel spreading mechanism that allowed the botnet to infect devices hidden behind the protection of the user’s internal network.
On January 2, 2026, the security firm Synthientpublicly disclosed the vulnerability Kimwolf was using to propagate so quickly. That disclosure helped curtail Kimwolf’s spread somewhat, but since then several other IoT botnets have emerged that effectively copy Kimwolf’s spreading methods while competing for the same pool of vulnerable devices. According to the DOJ, the JackSkid botnet also sought out systems on internal networks just like Kimwolf.
The DOJ said its disruption of the four botnets coincided with “law enforcement actions” conducted in Canada and Germany targeting individuals who allegedly operated those botnets, although no further details were available on the suspected operators.
In late February, KrebsOnSecurity identified a 22-year-old Canadian man as a core operator of the Kimwolf botnet. Multiple sources familiar with the investigation told KrebsOnSecurity the other prime suspect is a 15-year-old living in Germany.
McAfee Labs has uncovered a widespread malware campaign hiding inside fake downloads for things like game mods, AI tools, drivers, and trading utilities.
What makes this campaign especially notable is that some parts of it appear to have been built with help from large language models (LLMs). McAfee researchers found signs that certain scripts likely used AI-generated code, which may have helped the attackers create and scale the campaign faster.
That does not mean AI created the whole operation on its own. But it does suggest AI may be helping cybercriminals lower the effort needed to build malware and launch attacks.
Attackers created many different fake downloads to reach more victims
48 malicious DLL variants
The campaign used multiple versions of the malware, not just one file
1,700+ file names observed
The same threat was repackaged under many different names to look convincing
17 distinct kill chains
Researchers found multiple attack flows, but they followed a similar overall pattern
Hosted on familiar platforms
The malware was distributed through services users may recognize, including Discord and SourceForge
AI-assisted code suspected
Some scripts contained explanatory comments and patterns that strongly suggest LLM assistance
Cryptomining and additional malware observed
Infected devices could be used to mine cryptocurrency or receive more malicious payloads
What Is “AI-Written Malware”?
In this case, “AI-written malware” does not meanan AI system independently invented and launched the attack.
Instead, McAfee Labs found evidence that the attackers very likely used AI tools to help generate some of the code used in the campaign, especially in certain PowerShell scripts.
Put simply:
Term
Plain-English meaning
Large language model (LLM)
An AI system that can generate text and code based on prompts
AI-assisted malware
Malware where attackers appear to have used AI tools to help write or structure parts of the code
Vibe coding
A style of coding where someone describes what they want and an AI does much of the writing
This matters because it can make malware development faster, easier, and more scalable for attackers.
Figure 1: Attack Vector
How The Fake Download Attack Works
The attack begins when someone searches for software online and downloads what looks like the tool they wanted.
That tool might appear to be a game mod, AI voice changer, emulator, trading utility, VPN, or driver. But behind the scenes, the ZIP archive includes malicious components that start the infection.
Step
What happens
1. A user downloads a fake file
The ZIP archive is disguised as something useful or desirable, such as a mod menu, AI tool, or driver
2. The file appears normal at first
In some cases, the package includes a legitimate executable so it feels more convincing
3. A malicious DLL is loaded
A hidden malicious file, often WinUpdateHelper.dll, starts the real attack
4. The user is distracted
The malware may display a fake “missing dependency” message and redirect the user to install unrelated software
5. A PowerShell script is pulled from a remote server
While the user is distracted, the malware contacts a command-and-control server and runs additional code
6. More malware is installed
Depending on the sample, the device may receive coin miners, infostealers, or remote access tools
7. The infected device is abused for profit
In many cases, attackers use the victim’s system resources to mine cryptocurrency in the background
What Kinds of Files Were Used as Bait
McAfee found that the attackers cast a very wide net. The malicious ZIP files impersonated many types of software, including:
Bait category
Examples
Gaming tools
game mods, cheats, executors, Roblox-related tools
AI-themed tools
AI image generators, AI voice changers, AI-branded downloads
System utilities
graphics drivers, USB drivers, emulators, VPNs
Trading or finance tools
stock-market utilities and related downloads
Fake security or malware tools
fake stealers, decryptors, and other risky-looking utilities
That broad range is part of what made the campaign effective. It was designed to catch people already looking for shortcuts, unofficial tools, or hard-to-find software.
Why McAfee Researchers Believe AI Was Used
One of the strongest clues came from the comments inside some of the attack scripts.
McAfee researchers found explanatory comments that looked more like AI-generated instructions than the kind of shorthand attackers usually leave for themselves. In one example, a comment referred to downloading a file from “your GitHub URL,” which suggests the code may have come from a generated template and was not fully cleaned up before use.
These details do not prove every part of the campaign was AI-made. But they do support McAfee’s assessment that certain components were likely generated with help from large language models.
What Happens on an Infected Device
In many cases, the malware was used to turn victims’ computers into quiet crypto-mining machines.
McAfee observed mining activity involving several cryptocurrencies, including:
Ravencoin
Zephyr
Monero
Bitcoin Gold
Ergo
Clore
Some samples also downloaded additional payloads such as SalatStealer or Mesh Agent.
For victims, that can mean:
Possible effect
What it may look like
Slower performance
apps lag, games stutter, system feels unusually sluggish
High CPU or GPU usage
fans run constantly, laptop gets hot, battery drains faster
if an infostealer or remote access tool is installed
McAfee was also able to trace several Bitcoin wallets tied to the campaign. At the time of the report, those wallets held about $4,536 in Bitcoin, while total funds received were approximately $11,497.70. Researchers note the real total could be higher because some of the currencies involved are harder to trace.
Who Was Targeted Most
This campaign was observed most heavily in:
United States
United Kingdom
India
Brazil
France
Canada
Australia
That does not mean users elsewhere were unaffected. These were simply the countries where researchers saw the highest prevalence.
Figure 2: Geographical Prevalence
Red Flags To Watch For
Even though the campaign used advanced techniques, the warning signs for users were often familiar.
Red flag
Why it matters
You found the file through a random link
Unofficial forums, Discord links, and file-hosting pages are common malware delivery paths
The download is a ZIP for something sketchy or unofficial
Cheats, cracks, mod tools, and unofficial utilities carry higher risk
You get a “missing dependency” message
Attackers may use this to push a second download while the real infection happens in the background
The file name looks right, but the source feels wrong
Familiar names can be faked easily
Your PC suddenly slows down or overheats
Hidden cryptominers often abuse system resources
You notice new, unrelated software installed
The campaign sometimes used unwanted software installs as a distraction
How To Stay Safe From Malware Hidden in Fake Downloads
This campaign is a reminder that not every convincing file is a safe one. A few habits can reduce your risk significantly.
Safety step
Why it helps
Download software only from official sources
This lowers the chance of accidentally installing a trojanized file
Avoid cheats, cracks, and unofficial mods
These categories are common bait for malware campaigns
Be skeptical of dependency prompts
Unexpected requests to install helper files or missing components can be part of the attack
Keep your security software updated
Current protection can help detect known threats and suspicious behavior
Pay attention to system performance
A suddenly hot, loud, or slow PC may be a sign something is running in the background
Review what you download before opening it
Even a familiar file name does not guarantee a file is legitimate
McAfee helps protect against malware threats like these with multiple layers of security, including malware detection and safer browsing protections designed to help stop risky downloads before they can do damage.
What To Do If You Think You Opened One of These Files
If you think you downloaded and ran a suspicious file like one described in this campaign:
Action
Why it matters
Disconnect from the internet
This can help interrupt communication with attacker-controlled servers
Run a full security scan
A trusted scan can help identify malicious files and behavior
Delete suspicious downloads
Remove the file and avoid reopening it
Check for unfamiliar software or startup items
The infection may have installed additional components
Change important passwords from a clean device
This is especially important if data-stealing malware may have been involved
Monitor accounts for unusual activity
Keep an eye on email, banking, and other sensitive accounts
If your computer continues acting strangely after a scan, it may be worth getting professional help.
What This Means for the Future of Malware
This campaign highlights how cybercrime is evolving.
The core risk is not just fake downloads. It is the fact that attackers are using AI tools to help generate code, create variations, and speed up parts of the malware development process.
That can make campaigns like this easier to scale and harder to ignore.
For everyday users, the takeaway is simple: if a file seems unofficial, rushed, or too good to be true, pause before opening it. A fake download may look like a shortcut, but it can quietly turn your device into a target.
Frequently Asked Questions
FAQs
Q: What is AI-written malware?
A: AI-written malware generally refers to malicious code, or parts of a malware campaign, that appear to have been created with help from AI coding tools or large language models.
Q: Did AI create this entire malware campaign?
A: McAfee Labs did not say that. The research suggests that certain components, especially some scripts, were likely generated with help from large language models.
Q: What was this malware disguised as?
A: The malicious files impersonated game mods, AI tools, drivers, trading utilities, VPNs, emulators, and other software downloads.
Q: What can happen if you open one of these fake files?
A: Depending on the sample, the malware may install coin miners, steal data, establish persistence, or download additional malicious tools.
Q: Can malware really use my computer to mine cryptocurrency?
A: Yes. McAfee observed samples in this campaign that used victims’ CPU and GPU resources to mine cryptocurrency in the background.
Q: What is the safest way to avoid this kind of malware?
A: Download software only from official or trusted sources, avoid unofficial tools and cheats, be cautious of fake dependency prompts, and keep your security protection up to date.
The term ‘Vibe coding,’ first coined back in February of 2025 by OpenAI researchers, has exploded across digital platforms. With hundreds of articles and YouTube Videos discussing the dangers of Vibe coding and warning the internet about the rise of “Vibe Coders”, while others labelled it as the fundamental shift in software development and the future of coding.
Vibe Coding is an approach where the AI does heavy lifting, rather than the user. Instead of manually writing code or implementing algorithms, users describe their intent through text-based prompt, and the LLMs respond with fully functional code and explanation. Unsurprisingly, the internet is now flooded with guides on the best LLMs and prompts to generate “perfect” code.
Given the ease of generating fully functional code, McAfee Labs has also seen a rise in vibe-coded malware. In these campaigns, certain components of the kill chain contain AI-generated code, significantly reducing the effort and knowledge required to execute new malware campaigns. This shift not only makes malware campaigns more scalable but also lowers the barrier to entry for new malware authors.
Executive summary
In January 2026, McAfee Labs observed 443 malicious zip files impersonating a wide range of software, including AI image generators and voice-changing tools, stock-market trading utilities, game mods and modding tools, game hacks, graphics card and USB drivers, ransomware decryptors, VPNs, emulators, and even infostealer, cookie-stealer, and backdoor malware, to infect users.
Across the 440+ zip files, we observed 48 unique malicious WinUpdateHelper.dll variants, responsible for the infections. McAfee has been detecting variants of this threat since December 2024, although the vibe coding observed in certain components appears to be a recent addition. These files are distributed through various legitimate content delivery network (CDN) services and file-hosting websites, such as Discord, SourceForge, FOSSHub, and MediaFire, to name a few. Another website that was actively delivering this malware was mydofiles[.]com.
Here, the attackers implement volume-driven malware distribution techniques to infect as many users as possible.
Figure 1: Attack Vector
This attack begins when users surf the internet looking for tools and software that promise to simplify their tasks. Instead, they encounter trojanized zip files.
We discovered over 100 URLs actively spreading this malware, of which approximately 61 were hosted on Discord, 17 on SourceForge, and 15 on mydofiles[.]com.
On running the executable, it loads a malicious WinUpdateHelper.dll file, which redirects the user to file-hosting websites, under the disguise that they are missing crucial dependencies and tricks them into installing unrelated software, which is a distraction. Meanwhile, the DLL has already requested and executed a malicious PowerShell script from a command-and-control (C2) server.
This script infects the user’s system and downloads additional mining software, and abuses the system’s resources, or it downloads additional payloads such as SalatStealer or Mesh Agent, depending on the WinUpdateHelper.dll sample which infected the user.
In this PowerShell script, the presence of explanatory comments and structured sections strongly indicates the use of LLM models to generate this code.
Read more about this in the Using AI to generate malware? section below.
So far, we’ve observed the mining of Ravencoin, Zephyr, Monero, Bitcoin Gold, Ergo, andClorecryptocurrencies.
Due to the presence of hardcoded Bitcoin wallet credentials within these malware samples, we were able to trace on-chain transactions and identify wallets containing over $4,500 USD that are part of this campaign.
Since most of the mining activity targets privacy-focused cryptocurrencies such as Zephyr, Ravencoin and Monero, the real financial impact is likely to be nearly double the amount identified through Bitcoin tracing alone.
Geographical Prevalence
Figure 2: Geographical Prevalence
This malware campaign has specifically targeted users in the following counties, ranked by prevalence: The United States of America, followed by United Kingdom, India, Brazil, France, Canada, Australia.
Bottom Line
The availability of LLMs capable of generating code instantly, combined with the widespread accessibility of technical knowledge, has created a low-effort, high-reward environment, making malware deployment increasingly accessible.
At McAfee Labs, we have been doing hard work so that you don’t need to worry. But it always helps to be informed and educated on the latest threat that steps into the threat landscape. We will continue monitoring these campaigns to ensure our customers remain informed and protected across platforms.
Technical Analysis
Impersonated Applications
Here we see malware distribution at a large scale and by analyzing the filenames of these ZIP archives, we can infer to the users that are being targeted. These are some of the names we’ve witnessed in the wild.
Figure 3: Malware Impersonating gaming software
The attackers are actively impersonating video game cheats and game mods for popular titles, and well-known script executors for Roblox, such as Delta Executor and Solara as seen above.
Figure 4: Malware Impersonating tools, malware and drivers
Names such as Panther-Stealer and Zerotrace-Stealer indicate that even users looking for malware on the internet are not safe either, reinforcing the notion that there is truly no honor among thieves.
The campaign also leverages drivers and AI-themed tools as part of its lure portfolio among other tools. Interestingly, we see the name ‘DeepSeek.zip’, where attackers are exploiting a prominent LLM model, DeepSeek. McAfee had encountered these types of attacks in early 2025 and covered them extensively.
Once the user downloads the ZIP archive from Discord or any other website. They get the following set of files.
Figure 5: Files within the zip archive.
Here, the executable named ‘gta-5-online-mod-menu.exe’ (Highlighted in Blue) is a legitimate and clean file. Whereas the file named ‘WinUpdateHelper.dll’ (Highlighted in Red) is malicious.
Figure 6: Command Prompt misinforming the user
On executing ‘gta-5-online-mod-menu.exe’, the malicious DLL is loaded. The user is informed that they are missing dependencies, and they’re redirected to the following URL via default browser.
Here, within the URL, a tracker variable is used to identify which malware has infected the user. In this instance, it was ‘gta-5-online-mod-menu’.
Figure 7: Website prompting users to download dependencycore.zip
Dependecycore.zip is a setup file. On execution, it installs unrelated 3rd party software on the victim’s system.
Figure 8: Files dropped by Dependecycore.zip in temp folder
In this instance, iTop Easy Desktop was installed.
This unwanted installation is meant to subvert users’ attention. As, the WinUpdateHelper.dll has already connected to the C2 server and infected the system.
Stage 1 Payload – Malicious Functionality
Once the redirection code is executed, the malware executes the malicious code.
Figure 9: Malicious code within WinUpdateHelper.dll
In the above code snippet, which is present in the WinUpdateHelper.dll, we can see that a new service has been created under the name “Microsoft Console Host” to make it appear to be benign (Highlighted in Red). The parameters passed to this service ensure that it executes at system boot. This is done to maintain persistence in the system.
The service executes a PowerShell command that dynamically generates the C2 domain using the UNIX time stamp.
Using the following code, $([Math]::Floor([DateTimeOffset]::UtcNow.ToUnixTimeSeconds() / 5000000) * 5000000).xyz
It generates a domain name that changes once every 5,000,000 seconds or 58 days.
The latest C2 domain we’ve discovered that is up and running is 1770000000[.]xyz/script?id=fA9zQk2L0M&tag=WinUpdateHelper
During our analysis we observed the following domain 1765000000[.]xyz/script?id=fA9zQk2L0M&tag=WinUpdateHelper, which is present in the following images.
Here the id=fA9zQk2L0M is randomly generated, to uniquely identify the user and tag=WinUpdateHelper is used to identify the malware campaign.
The malware connects to the above-mentioned C2 server to download a PowerShell script and execute it in memory. This fileless execution ensures improved evasion against signature-based detections.
Stage 2 Payload – PowerShell Script
Figure 10: PowerShell downloaded from the C2 server
It is funny to note here, that the first comment of this script says “# I am forever sorry” which indicates that the attacks do carry some guilt regarding their actions, but not enough to stop the campaign. We found similar comments, such as “# sorry lol”, across multiple PowerShell scripts we discovered.
The first set of commands (Highlighted in Green) are used to delete windows services and scheduled tasks. This is done to remove older or conflicting persistence mechanisms and to avoid duplicate miners from running on the same system.
The second set of commands (Highlighted in Red) are registry modifications, that adds “C:\ProgramData” to Windows Defender exclusion paths. That is, ProgramData Folder won’t be scanned by Windows Defender anymore. This exclusion allows malware to drop additional payloads to disk, without the risk of them being detected and removed.
The third set of commands (Highlighted in Blue) does exactly that. It downloads the next level payload from the URL “hxxps://1765000000[.]xyz/download/xbhgjahddaa” and stored it at this path “C:\ProgramData\fontdrvhost.exe”.
Again the name ‘fontdrvhost.exe’ imitates a legitimate Windows binary, to masquerade its true intent. After the download, the file is decoded using a simple arithmetic decryption routine. This provides protection against static signature detection and network detection.
The payload is an XMRIG miner sample. In the next command, the miner is initialized and executed. Here, we see the miner connecting to “solo-zeph.2miners.com:4444” and start CPU based Zephyr coin mining using the following wallet address: ‘ZEPHsCY4zbcHGgz2U8PvkEjkWjopuPurPNv8nnSFnM5MN8hBas8kBN4hoNKmc7uMRfUQh4Fc9AHyGxL6NFARnc217m2vYgbKxf’.
Figure 11: PowerShell downloaded from the C2 server continued
In the second half of the script, we see another miner being set up and executed using the same technique (Highlighted in Red). This time the file is stored as “RuntimeBroker.exe” in the ProgramData folder. The miner is connecting to “solo-rvn.2miners.com:7070” to mine Ravencoin and it is using the system’s GPU instead of the CPU for mining (Highlighted in Blue).
This is the wallet address used for mining in this instance ‘bc1q9a59scnfwkdlm6wlcu5w76zm2uesjrqdy4fr8r’.
Hence, we see a dual coin-mining deployment infrastructure utilizing both CPU and GPU resources to optimize mining efficiency.
Bitcoin? Interesting…
What is interesting here is that attackers have used a bitcoin wallet address for mining Ravencoin, which indicates they are using multi-coin pools for mining. The attackers are using the victims’ machine to mine Ravencoin and automatically convert the mining rewards to Bitcoin before the payout.
This is done for a variety of reasons, such as, bitcoin offers higher liquidity and has broader acceptance, but most importantly, Ravencoin is computationally easier and economically viable to mine on victim’s system. Bitcoin requires specialized ASIC hardware for profitable mining and attempting to mine Bitcoin directly on infected systems would generate negligible returns. We’ve seen the same behaviour in multiple samples.
This is a smoking gun. Unlike Zephyr coin or Monero, Bitcoin’s blockchain is fully traceable. Every Satoshi, the smallest unit of Bitcoin, can be traced across the blockchain from the moment it was mined to its current holder. From there, it becomes easy to determine how much cryptocurrency the threat actor is receiving. More on this later.
Anti-Analysis Techniques
The attackers have meticulously designed the campaign and have implemented various anti-analysis techniques to thwart researchers.
The PowerShell script we’ve seen above is responsible for downloading and initializing the coin miner samples. It is only accessible via PowerShell. If we try to access the server via Curl, we get the following response.
Figure 12: 301 Response from the server
This indicates that the server is actively monitoring the User-Agent of incoming requests and deploys the payload only when the request originates from PowerShell.
Similarly, the URLs embedded within the PowerShell script that download the next payload are unique to each victim and remain active for 60 seconds. After that, they return a 404 Not Found error.
Figure 13: URLs within the PowerShell
These techniques are meant to confuse and disorient researchers, making the analysis difficult.
Using AI to generate malware?
While working on this malware campaign, we came across over 440 unique zip files. These same zip files were distributed with over 1700 different names, targeting various software.
Across these 440 zip files, we noticed 48 unique variants of WinUpdateHelper.dll. These 48 files can be clustered together into 17 distinct kill chains, each featuring their own C2 infrastructure, misleading installation setups, second-stage PowerShell scripts and final payloads, yet the cryptocurrency wallet credentials remain similar.
In the above technical analysis, we’ve only covered 1 kill chain. Yet, across these 17 kill chains, we’ve noticed the flow remain the same.
Figure 14: PowerShell Script with LLM-Generated Comments
Across multiple second stage payloads, we encounter multiple comments such as the following, embedded within the code:
# === Create and execute run.bat in C:\ProgramData ===
:: This batch file:
:: – Creates the hidden folder C:\ProgramData\cvtres if it doesn”t exist (using CMD attrib for hidden + system)
:: – Downloads cvtres.exe from your GitHub URL
:: – Saves it to C:\ProgramData\cvtres\cvtres.exe
:: – Executes it immediately
:: – Runs completely hidden/minimized (no window visible)
The presence of such explanatory-style comments indicates that large language models were likely used during the development of these scripts. Especially, the comment “Downloads cvtres.exe from your GitHub URL”, where ‘Your GitHub URL’ refers to the threat actor’s GitHub repository that is hosting the malware, which indicates potential vibe coding.
Tracking Bitcoin Across the Blockchain
During analysis of this malware campaign, we came across few instances where the final payload was Infostealer malware. In most cases it was coin miner samples. In these cases, we encountered wallet credentials and mining pool URLs for several alternative cryptocurrencies such as Ravencoin, Zephyr, Monero, which aren’t traceable.
Fortunately, we came across 7 bitcoin wallets that are part of this malware campaign and are actively receiving mined cryptocurrency.
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