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You’re scrolling through Facebook or TikTok and see it. 

A flash sale from a brand you recognize. A limited-time investment opportunity. A job posting that promises quick money. 

The ad has comments. The account looks polished. Maybe someone you follow even liked it. 

So you click. 

From there, things move fast. You’re pushed to act quickly, enter your information, or send payment before the “deal” disappears. And just like that, the money is gone or your account is compromised. 

This isn’t an edge case anymore. According to new FTC data, nearly 30% of people who reported losing money to a scam in 2025 said it started on social media, with total losses hitting $2.1 billion. 

That’s why McAfee+ Advanced includes comprehensive protection designed to help you spot and stop scams at every step, including McAfee’s Scam Detector, which flags suspicious links and messages and explains why they may be risky, along with identity and privacy tools that help protect your information if a scam slips through. 

How Social Media Ad Scams Work 

A social media ad scam is when scammers use paid ads, fake profiles, or hijacked accounts on platforms like Facebook, Instagram, or TikTok to promote fake products, services, or investment opportunities in order to steal money or personal information. 

Red Flags To Watch For 

• Deals that feel unusually cheap or urgent  
• Ads linking to unfamiliar or slightly misspelled websites  
• Requests to move conversations off-platform quickly  
• Payment requests via apps, crypto, or wire transfer  
• Accounts with limited history or inconsistent engagement  

And that is the first part of This Week in Scams! This Friday we’re taking a different format to talk about this new FTC data and all that it reveals.  

Let’s keep digging in: 

FTC Report: Social Media Scams Are Now The Most Costly Fraud Channel 

New data from the FTC shows just how dominant social media has become in the scam landscape. 

• Social media scams drove $2.1 billion in reported losses in 2025  
• Losses have increased eightfold since 2020  
• Investment scams alone accounted for $1.1 billion of those losses 

Where Scams Are Happening And What’s Changing 

How Scams Play Out Across Platforms 

 How McAfee Protects You from Scams and Cyber Threats 

McAfee+ Advanced gives you multiple layers working together so you are not left figuring it out after the damage is done:   

• Identity Monitoring alerts you if your personal info shows up where it should not, so you can act fast  
• Personal Data Cleanup helps remove your information from data broker sites, making you harder to target in the first place  
• Scam Detector flags suspicious texts, emails, links, and even deepfake videos before you engage  
• Safe Browsing helps block risky sites if you do click  
• Device Security helps detect malicious apps or downloads  
• Secure VPN keeps your data private, especially on public Wi-Fi    

McAfee Safety Tips This Week 

Our advice based on this week’s scams and schemes: 

• Treat social media ads like any other unknown source, not a trusted recommendation  
• Pause before clicking, especially when urgency is involved  
• Verify brands by going directly to their official website  
• Avoid sending money or personal information through social media  
• Use tools like Scam Detector to check suspicious links before engaging  

And we’ll be back next week with more scams making headlines.

The post Ad Impersonation Scams and Record-Breaking Social Media Fraud Losses: This Week in Scams appeared first on McAfee Blog.

Someone pleaded guilty to secretly working for a ransomware gang as he negotiated ransomware payments for clients.

A Brazilian tech firm that specializes in protecting networks from distributed denial-of-service (DDoS) attacks has been enabling a botnet responsible for an extended campaign of massive DDoS attacks against other network operators in Brazil, KrebsOnSecurity has learned. The firm’s chief executive says the malicious activity resulted from a security breach and was likely the work of a competitor trying to tarnish his company’s public image.

An Archer AX21 router from TP-Link. Image: tp-link.com.

For the past several years, security experts have tracked a series of massive DDoS attacks originating from Brazil and solely targeting Brazilian ISPs. Until recently, it was less than clear who or what was behind these digital sieges. That changed earlier this month when a trusted source who asked to remain anonymous shared a curious file archive that was exposed in an open directory online.

The exposed archive contained several Portuguese-language malicious programs written in Python. It also included the private SSH authentication keys belonging to the CEO of Huge Networks, a Brazilian ISP that primarily offers DDoS protection to other Brazilian network operators.

Founded in Miami, Fla. in 2014, Huge Networks’s operations are centered in Brazil. The company originated from protecting game servers against DDoS attacks and evolved into an ISP-focused DDoS mitigation provider. It does not appear in any public abuse complaints and is not associated with any known DDoS-for-hire services.

Nevertheless, the exposed archive shows that a Brazil-based threat actor maintained root access to Huge Networks infrastructure and built a powerful DDoS botnet by routinely mass-scanning the Internet for insecure Internet routers and unmanaged domain name system (DNS) servers on the Web that could be enlisted in attacks.

DNS is what allows Internet users to reach websites by typing familiar domain names instead of the associated IP addresses. Ideally, DNS servers only provide answers to machines within a trusted domain. But so-called “DNS reflection” attacks rely on DNS servers that are (mis)configured to accept queries from anywhere on the Web. Attackers can send spoofed DNS queries to these servers so that the request appears to come from the target’s network. That way, when the DNS servers respond, they reply to the spoofed (targeted) address.

By taking advantage of an extension to the DNS protocol that enables large DNS messages, botmasters can dramatically boost the size and impact of a reflection attack — crafting DNS queries so that the responses are much bigger than the requests. For example, an attacker could compose a DNS request of less than 100 bytes, prompting a response that is 60-70 times as large. This amplification effect is especially pronounced when the perpetrators can query many DNS servers with these spoofed requests from tens of thousands of compromised devices simultaneously.

A DNS amplification and reflection attack, illustrated. Image: veracara.digicert.com.

The exposed file archive includes a command-line history showing exactly how this attacker built and maintained a powerful botnet by scouring the Internet for TP-Link Archer AX21 routers. Specifically, the botnet seeks out TP-Link devices that remain vulnerable to CVE-2023-1389, an unauthenticated command injection vulnerability that was patched back in April 2023.

Malicious domains in the exposed Python attack scripts included DNS lookups for hikylover[.]st, and c.loyaltyservices[.]lol, both domains that have been flagged in the past year as control servers for an Internet of Things (IoT) botnet powered by a Mirai malware variant.

The leaked archive shows the botmaster coordinated their scanning from a Digital Ocean server that has been flagged for abusive activity hundreds of times in the past year. The Python scripts invoke multiple Internet addresses assigned to Huge Networks that were used to identify targets and execute DDoS campaigns. The attacks were strictly limited to Brazilian IP address ranges, and the scripts show that each selected IP address prefix was attacked for 10-60 seconds with four parallel processes per host before the botnet moved on to the next target.

The archive also shows these malicious Python scripts relied on private SSH keys belonging to Huge Networks’s CEO, Erick Nascimento. Reached for comment about the files, Mr. Nascimento said he did not write the attack programs and that he didn’t realize the extent of the DDoS campaigns until contacted by KrebsOnSecurity.

“We received and notified many Tier 1 upstreams regarding very very large DDoS attacks against small ISPs,” Nascimento said. “We didn’t dig deep enough at the time, and what you sent makes that clear.”

Nascimento said the unauthorized activity is likely related to a digital intrusion first detected in January 2026 that compromised two of the company’s development servers, as well as his personal SSH keys. But he said there’s no evidence those keys were used after January.

“We notified the team in writing the same day, wiped the boxes, and rotated keys,” Nascimento said, sharing a screenshot of a January 11 notification from Digital Ocean. “All documented internally.”

Mr. Nascimento said Huge Networks has since engaged a third-party network forensics firm to investigate further.

“Our working assessment so far is that this all started with a single internal compromise — one pivot point that gave the attacker downstream access to some resources, including a legacy personal droplet of mine,” he wrote.

“The compromise happened through a bastion/jump server that several people had access to,” Nascimento continued. “Digital Ocean flagged the droplet on January 11 — compromised due to a leaked SSH key, in their wording — I was traveling at the time and addressed it on return. That droplet was deprecated and destroyed, and it was never part of Huge Networks infrastructure.”

The malicious software that powers the botnet of TP-Link devices used in the DDoS attacks on Brazilian ISPs is based on Mirai, a malware strain that made its public debut in September 2016 by launching a then record-smashing DDoS attack that kept this website offline for four days. In January 2017, KrebsOnSecurity identified the Mirai authors as the co-owners of a DDoS mitigation firm that was using the botnet to attack gaming servers and scare up new clients.

In May 2025, KrebsOnSecurity was hit by another Mirai-based DDoS that Google called the largest attack it had ever mitigated. That report implicated a 20-something Brazilian man who was running a DDoS mitigation company as well as several DDoS-for-hire services that have since been seized by the FBI.

Nascimento flatly denied being involved in DDoS attacks against Brazilian operators to generate business for his company’s services.

“We don’t run DDoS attacks against Brazilian operators to sell protection,” Nascimento wrote in response to questions. “Our sales model is mostly inbound and through channel integrator, distributors, partners — not active prospecting based on market incidents. The targets in the scripts you received are small regional providers, the vast majority of which are neither in our customer base nor in our commercial pipeline — a fact verifiable through public sources like QRator.”

Nascimento maintains he has “strong evidence stored on the blockchain” that this was all done by a competitor. As for who that competitor might be, the CEO wouldn’t say.

“I would love to share this with you, but it could not be published as it would lose the surprise factor against my dishonest competitor,” he explained. “Coincidentally or not, your contact happened a week before an important event – ​​one that this competitor has NEVER participated in (and it’s a traditional event in the sector). And this year, they will be participating. Strange, isn’t it?”

Strange indeed.

Researchers have reverse-engineered a piece of malware named Fast16. It’s almost certainly state-sponsored, probably US in origin, and was deployed against Iran years before Stuxnet:

“…the Fast16 malware was designed to carry out the most subtle form of sabotage ever seen in an in-the-wild malware tool: By automatically spreading across networks and then silently manipulating computation processes in certain software applications that perform high-precision mathematical calculations and simulate physical phenomena, Fast16 can alter the results of those programs to cause failures that range from faulty research results to catastrophic damage to real-world equipment.”

Another news article.

Lots of interesting details at the links.

That’s a lot. No, it’s an extraordinary number:

Since February, the Firefox team has been working around the clock using frontier AI models to find and fix latent security vulnerabilities in the browser. We wrote previously about our collaboration with Anthropic to scan Firefox with Opus 4.6, which led to fixes for 22 security-sensitive bugs in Firefox 148.

As part of our continued collaboration with Anthropic, we had the opportunity to apply an early version of Claude Mythos Preview to Firefox. This week’s release of Firefox 150 includes fixes for 271 vulnerabilities identified during this initial evaluation.

As these capabilities reach the hands of more defenders, many other teams are now experiencing the same vertigo we did when the findings first came into focus. For a hardened target, just one such bug would have been red-alert in 2025, and so many at once makes you stop to wonder whether it’s even possible to keep up.

Our experience is a hopeful one for teams who shake off the vertigo and get to work. You may need to reprioritize everything else to bring relentless and single-minded focus to the task, but there is light at the end of the tunnel. We are extremely proud of how our team rose to meet this challenge, and others will too. Our work isn’t finished, but we’ve turned the corner and can glimpse a future much better than just keeping up. Defenders finally have a chance to win, decisively.

They’re right. Assuming the defenders can patch, and push those patches out to users quickly, this technology favors the defenders.

News article.

Two weeks ago, Anthropic announced that its new model, Claude Mythos Preview, can autonomously find and weaponize software vulnerabilities, turning them into working exploits without expert guidance. These were vulnerabilities in key software like operating systems and internet infrastructure that thousands of software developers working on those systems failed to find. This capability will have major security implications, compromising the devices and services we use every day. As a result, Anthropic is not releasing the model to the general public, but instead to a limited number of companies.

The news rocked the internet security community. There were few details in Anthropic’s announcement, angering many observers. Some speculate that Anthropic doesn’t have the GPUs to run the thing, and that cybersecurity was the excuse to limit its release. Others argue Anthropic is holding to its AI safety mission. There’s hype and counterhype, reality and marketing. It’s a lot to sort out, even if you’re an expert.

We see Mythos as a real but incremental step, one in a long line of incremental steps. But even incremental steps can be important when we look at the big picture.

How AI Is Changing Cybersecurity

We’ve written about shifting baseline syndrome, a phenomenon that leads people—the public and experts alike—to discount massive long-term changes that are hidden in incremental steps. It has happened with online privacy, and it’s happening with AI. Even if the vulnerabilities found by Mythos could have been found using AI models from last month or last year, they couldn’t have been found by AI models from five years ago.

The Mythos announcement reminds us that AI has come a long way in just a few years: The baseline really has shifted. Finding vulnerabilities in source code is the type of task that today’s large language models excel at. Regardless of whether it happened last year or will happen next year, it’s been clear for a while this kind of capability was coming soon. The question is how we adapt to it.

We don’t believe that an AI that can hack autonomously will create permanent asymmetry between offense and defense; it’s likely to be more nuanced than that. Some vulnerabilities can be found, verified, and patched automatically. Some vulnerabilities will be hard to find but easy to verify and patch—consider generic cloud-hosted web applications built on standard software stacks, where updates can be deployed quickly. Still others will be easy to find (even without powerful AI) and relatively easy to verify, but harder or impossible to patch, such as IoT appliances and industrial equipment that are rarely updated or can’t be easily modified.

Then there are systems whose vulnerabilities will be easy to find in code but difficult to verify in practice. For example, complex distributed systems and cloud platforms can be composed of thousands of interacting services running in parallel, making it difficult to distinguish real vulnerabilities from false positives and to reliably reproduce them.

So we must separate the patchable from the unpatchable, and the easy to verify from the hard to verify. This taxonomy also provides us guidance for how to protect such systems in an era of powerful AI vulnerability-finding tools.

Unpatchable or hard to verify systems should be protected by wrapping them in more restrictive, tightly controlled layers. You want your fridge or thermostat or industrial control system behind a restrictive and constantly updated firewall, not freely talking to the internet.

Distributed systems that are fundamentally interconnected should be traceable and should follow the principle of least privilege, where each component has only the access it needs. These are bog-standard security ideas that we might have been tempted to throw out in the era of AI, but they’re still as relevant as ever.

Rethinking Software Security Practices

This also raises the salience of best practices in software engineering. Automated, thorough, and continuous testing was always important. Now we can take this practice a step further and use defensive AI agents to test exploits against a real stack, over and over, until the false positives have been weeded out and the real vulnerabilities and fixes are confirmed. This kind of VulnOps is likely to become a standard part of the development process.

Documentation becomes more valuable, as it can guide an AI agent on a bug-finding mission just as it does developers. And following standard practices and using standard tools and libraries allows AI and engineers alike to recognize patterns more effectively, even in a world of individual and ephemeral instant software—code that can be generated and deployed on demand.

Will this favor offense or defense? The defense eventually, probably, especially in systems that are easy to patch and verify. Fortunately, that includes our phones, web browsers, and major internet services. But today’s cars, electrical transformers, fridges, and lampposts are connected to the internet. Legacy banking and airline systems are networked.

Not all of those are going to get patched as fast as needed, and we may see a few years of constant hacks until we arrive at a new normal: where verification is paramount and software is patched continuously.

This essay was written with Barath Raghavan, and originally appeared in IEEE Spectrum.

Sent by a Spanish diplomat. Apparently people have been working on it since it was rediscovered in 1860.

Science news:

Scientists have finally cracked a long-standing mystery about squid and cuttlefish evolution by analyzing newly sequenced genomes alongside global datasets. The research reveals that these bizarre, intelligent creatures likely originated deep in the ocean over 100 million years ago, surviving mass extinction events by retreating into oxygen-rich deep-sea refuges. For millions of years, their evolution barely changed—until a dramatic post-extinction boom sparked rapid diversification as they moved into new shallow-water habitats.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Blog moderation policy.

It was used to track a Dutch naval ship:

Dutch journalist Just Vervaart, working for regional media network Omroep Gelderland, followed the directions posted on the Dutch government website and mailed a postcard with a hidden tracker inside. Because of this, they were able to track the ship for about a day, watching it sail from Heraklion, Crete, before it turned towards Cyprus. While it only showed the location of that one vessel, knowing that it was part of a carrier strike group sailing in the Mediterranean could potentially put the entire fleet at risk.

[…]

Navy officials reported that the tracker was discovered within 24 hours of the ship’s arrival, during mail sorting, and was eventually disabled. Because of this incident, the Dutch authorities now ban electronic greeting cards, which, unlike packages, weren’t x-rayed before being brought on the ship.

404 Media reports (alternate site):

The FBI was able to forensically extract copies of incoming Signal messages from a defendant’s iPhone, even after the app was deleted, because copies of the content were saved in the device’s push notification database….

The news shows how forensic extraction—­when someone has physical access to a device and is able to run specialized software on it—­can yield sensitive data derived from secure messaging apps in unexpected places. Signal already has a setting that blocks message content from displaying in push notifications; the case highlights why such a feature might be important for some users to turn on.

“We learned that specifically on iPhones, if one’s settings in the Signal app allow for message notifications and previews to show up on the lock screen, [then] the iPhone will internally store those notifications/message previews in the internal memory of the device,” a supporter of the defendants who was taking notes during the trial told 404 Media.

EDITED TO ADD (4/24): Apple has patched this vulnerability.