Tag Archives: scams

Scam USPS and E-Z Pass Texts and Websites

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/11/scam-usps-and-e-z-pass-texts-and-websites.html

Google has filed a complaint in court that details the scam:

In a complaint filed Wednesday, the tech giant accused “a cybercriminal group in China” of selling “phishing for dummies” kits. The kits help unsavvy fraudsters easily “execute a large-scale phishing campaign,” tricking hordes of unsuspecting people into “disclosing sensitive information like passwords, credit card numbers, or banking information, often by impersonating well-known brands, government agencies, or even people the victim knows.”

These branded “Lighthouse” kits offer two versions of software, depending on whether bad actors want to launch SMS and e-commerce scams. “Members may subscribe to weekly, monthly, seasonal, annual, or permanent licenses,” Google alleged. Kits include “hundreds of templates for fake websites, domain set-up tools for those fake websites, and other features designed to dupe victims into believing they are entering sensitive information on a legitimate website.”

Google’s filing said the scams often begin with a text claiming that a toll fee is overdue or a small fee must be paid to redeliver a package. Other times they appear as ads—­sometimes even Google ads, until Google detected and suspended accounts—­luring victims by mimicking popular brands. Anyone who clicks will be redirected to a website to input sensitive information; the sites often claim to accept payments from trusted wallets like Google Pay.

Cybercriminals Targeting Payroll Sites

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/11/cybercriminals-targeting-payroll-sites.html

Microsoft is warning of a scam involving online payroll systems. Criminals use social engineering to steal people’s credentials, and then divert direct deposits into accounts that they control. Sometimes they do other things to make it harder for the victim to realize what is happening.

I feel like this kind of thing is happening everywhere, with everything. As we move more of our personal and professional lives online, we enable criminals to subvert the very systems we rely on.

Social Engineering People’s Credit Card Details

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/10/social-engineering-peoples-credit-card-details.html

Good Wall Street Journal article on criminal gangs that scam people out of their credit card information:

Your highway toll payment is now past due, one text warns. You have U.S. Postal Service fees to pay, another threatens. You owe the New York City Department of Finance for unpaid traffic violations.

The texts are ploys to get unsuspecting victims to fork over their credit-card details. The gangs behind the scams take advantage of this information to buy iPhones, gift cards, clothing and cosmetics.

Criminal organizations operating out of China, which investigators blame for the toll and postage messages, have used them to make more than $1 billion over the last three years, according to the Department of Homeland Security.

[…]

Making the fraud possible: an ingenious trick allowing criminals to install stolen card numbers in Google and Apple Wallets in Asia, then share the cards with the people in the U.S. making purchases half a world away.

Cryptocurrency ATMs

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/10/cryptocurrency-atms.html

CNN has a great piece about how cryptocurrency ATMs are used to scam people out of their money. The fees are usurious, and they’re a common place for scammers to send victims to buy cryptocurrency for them. The companies behind the ATMs, at best, do not care about the harm they cause; the profits are just too good.

Use of Generative AI in Scams

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/10/use-of-generative-ai-in-scams.html

New report: “Scam GPT: GenAI and the Automation of Fraud.”

This primer maps what we currently know about generative AI’s role in scams, the communities most at risk, and the broader economic and cultural shifts that are making people more willing to take risks, more vulnerable to deception, and more likely to either perpetuate scams or fall victim to them.

AI-enhanced scams are not merely financial or technological crimes; they also exploit social vulnerabilities ­ whether short-term, like travel, or structural, like precarious employment. This means they require social solutions in addition to technical ones. By examining how scammers are changing and accelerating their methods, we hope to show that defending against them will require a constellation of cultural shifts, corporate interventions, and eff­ective legislation.

Details of a Scam

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/09/details-of-a-scam.html

Longtime Crypto-Gram readers know that I collect personal experiences of people being scammed. Here’s an almost:

Then he added, “Here at Chase, we’ll never ask for your personal information or passwords.” On the contrary, he gave me more information—two “cancellation codes” and a long case number with four letters and 10 digits.

That’s when he offered to transfer me to his supervisor. That simple phrase, familiar from countless customer-service calls, draped a cloak of corporate competence over this unfolding drama. His supervisor. I mean, would a scammer have a supervisor?

The line went mute for a few seconds, and a second man greeted me with a voice of authority. “My name is Mike Wallace,” he said, and asked for my case number from the first guy. I dutifully read it back to him.

“Yes, yes, I see,” the man said, as if looking at a screen. He explained the situation—new account, Zelle transfers, Texas—and suggested we reverse the attempted withdrawal.

I’m not proud to report that by now, he had my full attention, and I was ready to proceed with whatever plan he had in mind.

It happens to smart people who know better. It could happen to you.

Baggage Tag Scam

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/08/baggage-tag-scam.html

I just heard about this:

There’s a travel scam warning going around the internet right now: You should keep your baggage tags on your bags until you get home, then shred them, because scammers are using luggage tags to file fraudulent claims for missing baggage with the airline.

First, the scam is possible. I had a bag destroyed by baggage handlers on a recent flight, and all the information I needed to file a claim was on my luggage tag. I have no idea if I will successfully get any money from the airline, or what form it will be in, or how it will be tied to my name, but at least the first step is possible.

But…is it actually happening? No one knows. It feels like a kind of dumb way to make not a lot of money. The origin of this rumor seems to be single Reddit post.

And why should I care about this scam? No one is scamming me; it’s the airline being scammed. I suppose the airline might ding me for reporting a damage bag, but it seems like a very minor risk.

The “Incriminating Video” Scam

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/08/the-incriminating-video-scam.html

A few years ago, scammers invented a new phishing email. They would claim to have hacked your computer, turned your webcam on, and videoed you watching porn or having sex. BuzzFeed has an article talking about a “shockingly realistic” variant, which includes photos of you and your house—more specific information.

The article contains “steps you can take to figure out if it’s a scam,” but omits the first and most fundamental piece of advice: If the hacker had incriminating video about you, they would show you a clip. Just a taste, not the worst bits so you had to worry about how bad it could be, but something. If the hacker doesn’t show you any video, they don’t have any video. Everything else is window dressing.

I remember when this scam was first invented. I calmed several people who were legitimately worried with that one fact.

Ghostwriting Scam

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/06/ghostwriting-scam.html

The variations seem to be endless. Here’s a fake ghostwriting scam that seems to be making boatloads of money.

This is a big story about scams being run from Texas and Pakistan estimated to run into tens if not hundreds of millions of dollars, viciously defrauding Americans with false hopes of publishing bestseller books (a scam you’d not think many people would fall for but is surprisingly huge). In January, three people were charged with defrauding elderly authors across the United States of almost $44 million ­by “convincing the victims that publishers and filmmakers wanted to turn their books into blockbusters.”

DoorDash Hack

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2025/05/doordash-hack.html

A DoorDash driver stole over $2.5 million over several months:

The driver, Sayee Chaitainya Reddy Devagiri, placed expensive orders from a fraudulent customer account in the DoorDash app. Then, using DoorDash employee credentials, he manually assigned the orders to driver accounts he and the others involved had created. Devagiri would then mark the undelivered orders as complete and prompt DoorDash’s system to pay the driver accounts. Then he’d switch those same orders back to “in process” and do it all over again. Doing this “took less than five minutes, and was repeated hundreds of times for many of the orders,” writes the US Attorney’s Office.

Interesting flaw in the software design. He probably would have gotten away with it if he’d kept the numbers small. It’s only when the amount missing is too big to ignore that the investigations start.

Hacking the “Bike Angels” System for Moving Bikeshares

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/hacking-the-bike-angels-system-for-moving-bikeshares.html

I always like a good hack. And this story delivers. Basically, the New York City bikeshare program has a system to reward people who move bicycles from full stations to empty ones. By deliberately moving bikes to create artificial problems, and exploiting exactly how the system calculates rewards, some people are making a lot of money.

At 10 a.m. on a Tuesday last month, seven Bike Angels descended on the docking station at Broadway and 53rd Street, across from the Ed Sullivan Theater. Each rider used his own special blue key -­- a reward from Citi Bike—­ to unlock a bike. He rode it one block east, to Seventh Avenue. He docked, ran back to Broadway, unlocked another bike and made the trip again.

By 10:14, the crew had created an algorithmically perfect situation: One station 100 percent full, a short block from another station 100 percent empty. The timing was crucial, because every 15 minutes, Lyft’s algorithm resets, assigning new point values to every bike move.

The clock struck 10:15. The algorithm, mistaking this manufactured setup for a true emergency, offered the maximum incentive: $4.80 for every bike returned to the Ed Sullivan Theater. The men switched direction, running east and pedaling west.

Nicely done, people.

Now it’s Lyft’s turn to modify its system to prevent this hack. Thinking aloud, it could try to detect this sort of behavior in the Bike Angels data—and then ban people who are deliberately trying to game the system. The detection doesn’t have to be perfect, just good enough to catch bad actors most of the time. The detection needs to be tuned to minimize false positives, but that feels straightforward.

Details of a Phone Scam

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/02/details-of-a-phone-scam.html

First-person account of someone who fell for a scam, that started as a fake Amazon service rep and ended with a fake CIA agent, and lost $50,000 cash. And this is not a naive or stupid person.

The details are fascinating. And if you think it couldn’t happen to you, think again. Given the right set of circumstances, it can.

It happened to Cory Doctorow.

EDITED TO ADD (2/23): More scams, these involving timeshares.

How .tk Became a TLD for Scammers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2023/11/how-tk-became-a-tld-for-scammers.html

Sad story of Tokelau, and how its top-level domain “became the unwitting host to the dark underworld by providing a never-ending supply of domain names that could be weaponized against internet users. Scammers began using .tk websites to do everything from harvesting passwords and payment information to displaying pop-up ads or delivering malware.”

LLMs and Phishing

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2023/04/llms-and-phishing.html

Here’s an experiment being run by undergraduate computer science students everywhere: Ask ChatGPT to generate phishing emails, and test whether these are better at persuading victims to respond or click on the link than the usual spam. It’s an interesting experiment, and the results are likely to vary wildly based on the details of the experiment.

But while it’s an easy experiment to run, it misses the real risk of large language models (LLMs) writing scam emails. Today’s human-run scams aren’t limited by the number of people who respond to the initial email contact. They’re limited by the labor-intensive process of persuading those people to send the scammer money. LLMs are about to change that. A decade ago, one type of spam email had become a punchline on every late-night show: “I am the son of the late king of Nigeria in need of your assistance….” Nearly everyone had gotten one or a thousand of those emails, to the point that it seemed everyone must have known they were scams.

So why were scammers still sending such obviously dubious emails? In 2012, researcher Cormac Herley offered an answer: It weeded out all but the most gullible. A smart scammer doesn’t want to waste their time with people who reply and then realize it’s a scam when asked to wire money. By using an obvious scam email, the scammer can focus on the most potentially profitable people. It takes time and effort to engage in the back-and-forth communications that nudge marks, step by step, from interlocutor to trusted acquaintance to pauper.

Long-running financial scams are now known as pig butchering, growing the potential mark up until their ultimate and sudden demise. Such scams, which require gaining trust and infiltrating a target’s personal finances, take weeks or even months of personal time and repeated interactions. It’s a high stakes and low probability game that the scammer is playing.

Here is where LLMs will make a difference. Much has been written about the unreliability of OpenAI’s GPT models and those like them: They “hallucinate” frequently, making up things about the world and confidently spouting nonsense. For entertainment, this is fine, but for most practical uses it’s a problem. It is, however, not a bug but a feature when it comes to scams: LLMs’ ability to confidently roll with the punches, no matter what a user throws at them, will prove useful to scammers as they navigate hostile, bemused, and gullible scam targets by the billions. AI chatbot scams can ensnare more people, because the pool of victims who will fall for a more subtle and flexible scammer—one that has been trained on everything ever written online—is much larger than the pool of those who believe the king of Nigeria wants to give them a billion dollars.

Personal computers are powerful enough today that they can run compact LLMs. After Facebook’s new model, LLaMA, was leaked online, developers tuned it to run fast and cheaply on powerful laptops. Numerous other open-source LLMs are under development, with a community of thousands of engineers and scientists.

A single scammer, from their laptop anywhere in the world, can now run hundreds or thousands of scams in parallel, night and day, with marks all over the world, in every language under the sun. The AI chatbots will never sleep and will always be adapting along their path to their objectives. And new mechanisms, from ChatGPT plugins to LangChain, will enable composition of AI with thousands of API-based cloud services and open source tools, allowing LLMs to interact with the internet as humans do. The impersonations in such scams are no longer just princes offering their country’s riches. They are forlorn strangers looking for romance, hot new cryptocurrencies that are soon to skyrocket in value, and seemingly-sound new financial websites offering amazing returns on deposits. And people are already falling in love with LLMs.

This is a change in both scope and scale. LLMs will change the scam pipeline, making them more profitable than ever. We don’t know how to live in a world with a billion, or 10 billion, scammers that never sleep.

There will also be a change in the sophistication of these attacks. This is due not only to AI advances, but to the business model of the internet—surveillance capitalism—which produces troves of data about all of us, available for purchase from data brokers. Targeted attacks against individuals, whether for phishing or data collection or scams, were once only within the reach of nation-states. Combine the digital dossiers that data brokers have on all of us with LLMs, and you have a tool tailor-made for personalized scams.

Companies like OpenAI attempt to prevent their models from doing bad things. But with the release of each new LLM, social media sites buzz with new AI jailbreaks that evade the new restrictions put in place by the AI’s designers. ChatGPT, and then Bing Chat, and then GPT-4 were all jailbroken within minutes of their release, and in dozens of different ways. Most protections against bad uses and harmful output are only skin-deep, easily evaded by determined users. Once a jailbreak is discovered, it usually can be generalized, and the community of users pulls the LLM open through the chinks in its armor. And the technology is advancing too fast for anyone to fully understand how they work, even the designers.

This is all an old story, though: It reminds us that many of the bad uses of AI are a reflection of humanity more than they are a reflection of AI technology itself. Scams are nothing new—simply intent and then action of one person tricking another for personal gain. And the use of others as minions to accomplish scams is sadly nothing new or uncommon: For example, organized crime in Asia currently kidnaps or indentures thousands in scam sweatshops. Is it better that organized crime will no longer see the need to exploit and physically abuse people to run their scam operations, or worse that they and many others will be able to scale up scams to an unprecedented level?

Defense can and will catch up, but before it does, our signal-to-noise ratio is going to drop dramatically.

This essay was written with Barath Raghavan, and previously appeared on Wired.com.

Complex Impersonation Story

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/10/complex-impersonation-story.html

This is a story of one piece of what is probably a complex employment scam. Basically, real programmers are having their resumes copied and co-opted by scammers, who apply for jobs (or, I suppose, get recruited from various job sites), then hire other people with Western looks and language skills are to impersonate those first people on Zoom job interviews. Presumably, sometimes the scammers get hired and…I suppose…collect paychecks for a while until they get found out and fired. But that requires a bunch of banking fraud as well, so I don’t know.

EDITED TO ADD (10/11): Brian Krebs writes about fake LinkedIn profiles, which is probably another facet of this fraud system. Someone needs to unravel all of the threads.

Man-in-the-Middle Phishing Attack

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/08/man-in-the-middle-phishing-attack.html

Here’s a phishing campaign that uses a man-in-the-middle attack to defeat multi-factor authentication:

Microsoft observed a campaign that inserted an attacker-controlled proxy site between the account users and the work server they attempted to log into. When the user entered a password into the proxy site, the proxy site sent it to the real server and then relayed the real server’s response back to the user. Once the authentication was completed, the threat actor stole the session cookie the legitimate site sent, so the user doesn’t need to be reauthenticated at every new page visited. The campaign began with a phishing email with an HTML attachment leading to the proxy server.