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.
Whether you’re a hardcore basketball fan or the office colleague who gets roped into filling out a bracket every year, March Madness is the season for brackets, office pools, and last-minute picks.
More than half of Americans (57%) plan to watch the NCAA basketball tournament, and 55% say they participate in some kind of betting or bracket activity during March Madness, from office pools to licensed sportsbook wagers.
But where there’s excitement and money, scammers aren’t far behind.
New research from McAfee finds that 1 in 3 Americans (32%) say they’ve experienced a betting or gambling scam, and 24% say they’ve lost money to one, with victims losing an average of $547.
Big events like March Madness create the perfect storm: massive attention, constant betting promotions, and fans searching online for predictions, tips, and an edge.
Scammers know it, and they’re exploiting the moment.
This example shows an incredibly realistic, but fake, FanDuel site created by scammers to impersonate the real thing.
Why March Madness is Prime Time for Betting Scams
Sports betting promotions are everywhere during major events like March Madness.
According to McAfee research, 82% of Americans say they’ve seen sports betting promotions or offers in the past year, often on social media, streaming broadcasts, and sports websites.
That flood of promotions makes it easier for scams to blend in with legitimate content.
Many scams start the same way legitimate offers do, through messages, ads, or links promising bonuses or tips. But once someone clicks or responds, the situation can escalate quickly.
For example:
42% of Americans say they’ve been asked to click a link sent via email tied to a betting offer
Others report links sent through social media messages or text messages directing them to betting sites, apps, or private betting groups
In many cases, victims are then asked to send money to unlock winnings, activate accounts, or access premium betting picks.
The payout rarely exists.
The Most Common Betting Scams Fans Encounter
Betting scams come in several forms, but many follow familiar patterns.
Here are some of the most common tactics reported in McAfee’s research:
Scam Type
Definition
How It Works
Red Flags
Guaranteed Win Scam
A betting scam where someone promises a “guaranteed win,” “sure bet,” or “can’t lose” outcome in exchange for money, clicks, or sign-ups. According to McAfee Findings, about 1 in 6 Americans say they’ve received these kinds of messages, which are designed to lure fans looking for an edge.
Scammers send private messages, emails, or social posts claiming they have insider knowledge or a lock on a game. The goal is usually to get the victim to pay for picks, join a private group, or click a malicious link.
Claims that a bet is guaranteed, pressure to act fast, requests for payment to access picks, and promises that sound risk-free.
Fake Free Bet Promotion Scam
A scam that pretends to offer bonus bets, deposit matches, or free credits through a fake sportsbook promotion.
The victim sees what looks like a real sportsbook offer, often through social media, email, or text. Clicking may lead to a fake site that steals login details, payment information, or deposits.
Unfamiliar brand names, unofficial links, urgent sign-up language, and promotions that seem unusually generous.
Winnings Release Fee Scam
A scam where a victim is told they have winnings waiting, but must first pay a fee, deposit, or processing charge to collect them.
The scammer claims the user has won money, then invents a reason payment is required before the funds can be released. Once the fee is sent, the payout never arrives.
Requests to pay before receiving winnings, vague “processing” or “verification” fees, and pressure to send money immediately.
Fake Betting App or Website Scam
A scam involving a fraudulent app or website designed to look like a real sportsbook or betting platform.
Victims are directed to a fake platform where they may create an account, enter personal information, or deposit money. The site may appear legitimate, but withdrawals are blocked or impossible.
Slightly misspelled URLs, strange app download paths, poor website quality, and platforms that make deposits easy but withdrawals difficult.
Sportsbook Impersonation Scam
A scam in which someone pretends to represent a legitimate betting platform or sportsbook support team.
The scammer contacts the victim claiming there is an issue with an account, a bonus, or winnings. They then ask for login credentials, payment details, or personal information.
Requests for passwords, bank details, or identity information; unexpected outreach; and messages pushing you to resolve an “account issue” through a link.
Fake Insider Tip Scam
A scam that uses claims of insider information, fixed games, or special access to make a betting offer sound exclusive and trustworthy.
Scammers position themselves as experts, insiders, or connected sources who can help the victim beat the odds. The real goal is usually payment, account access, or enrollment in a scam betting channel.
Claims of fixed outcomes, “insider” knowledge, exclusive access, and offers that rely on secrecy or urgency.
Celebrity or Influencer Endorsement Scam
A betting scam that uses fake or misleading celebrity, athlete, or influencer endorsements to make an offer seem legitimate.
Scammers create ads, videos, or posts that appear to feature a public figure recommending a betting platform, app, or tip service. In some cases, AI-generated content makes these endorsements look more convincing.
Endorsements that seem off-brand, videos or graphics that look unnatural, unfamiliar accounts, and promotions tied to fake urgency or suspicious links.
Private Betting Group Scam
A scam that tries to move betting conversations into private channels like WhatsApp, Telegram, or Signal.
After initial contact on social media or another public platform, the scammer encourages the victim to join a private group for “exclusive picks,” “VIP bets,” or “premium insights.” These groups are often used to pressure victims into sending money or clicking malicious links.
Pressure to move off-platform quickly, promises of VIP access, requests for payment to join, and little proof that the group is legitimate.
Who Is Most Likely to Encounter Betting Scams
McAfee’s research found that Americans under 45 are significantly more likely to encounter betting scams, with 44% saying they’ve experienced one compared with 19% of those over 45.
Men also report higher exposure, with 40% saying they’ve experienced a betting scam, compared with 25% of women.
Men and younger adults are also more likely to participate in brackets, fantasy sports, or sportsbook betting, the same spaces where scams often appear.
Example of a scam March Madness betting opportunity that uses real logos and imagery
AI Is Making Betting Scams Harder to Spot
Artificial intelligence is beginning to change how scams look and sound.
About 1 in 5 Americans say they’ve encountered betting scams that appeared more realistic because of AI, and 27% believe they’ve seen AI-generated betting content such as fake promotions, images, or videos.
Among those who encountered AI-driven scams:
58% reported AI-generated images or graphics in betting ads
57% saw AI-written messages that sounded natural or personalized
45% encountered fake celebrity or influencer endorsements
36% interacted with chatbots posing as betting experts or support agents
As these tools improve, scam messages are becoming smoother, more convincing, and harder to distinguish from legitimate promotions.
Safety Check
What To Do
Be skeptical of “guaranteed wins”
No bet is risk-free. Ignore messages promising sure bets, insider picks, or guaranteed outcomes.
Use only licensed sportsbooks
Stick to official betting apps and well-known sportsbooks. Avoid unfamiliar websites or apps.
Don’t click betting links from unknown messages
If you receive a betting offer via email, text, or social media, go directly to the official site instead of clicking the link.
Never pay fees to unlock winnings
If someone says you must send money to claim winnings or activate a betting account, it’s almost certainly a scam.
Be cautious of private betting groups
Invitations to “VIP betting groups” on apps like Telegram or WhatsApp are often used to promote scam picks or collect payments.
Tools like McAfee’s Scam Detector can flag suspicious links, websites, and messages before you engage.
March Madness is meant to be fun, filling out brackets, debating picks with friends, and cheering for the next big upset. Betting can be part of that excitement, but it’s worth remembering that scammers are watching the tournament too.
A simple rule of thumb can go a long way: if a betting offer promises guaranteed wins, asks for money upfront, or pushes you to act quickly, take a step back and verify it first.
The safest plays are the ones where you slow down, stick to trusted platforms, and keep your personal information protected.
This image shows another scam site built around sports betting. It’s important to remember these sports betting scams extend beyond basketball and the U.S.
If You or Someone You Know Needs Help
Sports betting can be fun, but for some people it can become difficult to manage. If you or someone you know is struggling with gambling, help is available through the National Problem Gambling Helpline (1-800-MY-RESET), operated by the National Council on Problem Gambling.
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