Iranian Hackers Breached Kash Patel’s Email—but Not the FBI’s
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.

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:
Either way, the goal is the same: get you to act fast before you have time to question it.

The red flags in this message
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.
First, don’t panic. Then:
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.
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:
That’s more than enough for scammers to build highly believable follow-ups.
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.
McAfee+ Advanced gives you multiple layers working together so you’re not left figuring it out in the moment:
Plus our instant QR code scam checks will flag suspicious QR codes before you scan them.
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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.
The post Got a “Court Notice” Text? Ignore It. Plus, the Crunchyroll Breach: This Week in Scams appeared first on McAfee Blog.
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 Morag wrote. “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).
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.
We’ll walk through what happened, what to watch for, and how McAfee’s tools can help you stay safe.
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:
| 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 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:
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.
Not all scams start with a message. Some start with a search.
McAfee Labs uncovered a large-scale malware campaign hiding inside hundreds of fake downloads, including game mods, AI tools, drivers, and trading utilities.
In January alone, researchers identified:
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:
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:
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:
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.
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:
Stay skeptical, verify before you click, and we’ll see you next week with more.
The post This Week in Scams: Why That “Booking Confirmation” Message Might Be Fake appeared first on McAfee Blog.
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 Synthient publicly 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.
In January 2026, researchers observed 443 malicious ZIP files impersonating software people might actively search for online. Across those files, McAfee identified 48 malicious WinUpdateHelper.dll variants used to infect devices. The campaign was spread through a mix of file-hosting and content delivery services, including Discord, SourceForge, FOSSHub, and mydofiles[.]com.
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.
Want the full research? Dive in here.
We break down the top takeaways below.
| Finding | What it means |
| 443 malicious ZIP files | 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 |
In this case, “AI-written malware” does not mean an 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.

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 |
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.
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.
In many cases, the malware was used to turn victims’ computers into quiet crypto-mining machines.
McAfee observed mining activity involving several cryptocurrencies, including:
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 |
| Background malware activity | unknown processes, suspicious downloads, unexpected behavior |
| Potential data theft | 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.
This campaign was observed most heavily in:
That does not mean users elsewhere were unaffected. These were simply the countries where researchers saw the highest prevalence.

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 |
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.
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.
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.
| 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. |
Want to learn more? Dive into the full research here.
The post New Research: Hackers Are Using AI-Written Code to Spread Malware appeared first on McAfee Blog.