Over the past few decades, it’s become easier and easier to create fake receipts. Decades ago, it required special paper and printers—I remember a company in the UK advertising its services to people trying to cover up their affairs. Then, receipts became computerized, and faking them required some artistic skills to make the page look realistic.
Several receipts shown to the FT by expense management platforms demonstrated the realistic nature of the images, which included wrinkles in paper, detailed itemization that matched real-life menus, and signatures.
[…]
The rise in these more realistic copies has led companies to turn to AI to help detect fake receipts, as most are too convincing to be found by human reviewers.
The software works by scanning receipts to check the metadata of the image to discover whether an AI platform created it. However, this can be easily removed by users taking a photo or a screenshot of the picture.
To combat this, it also considers other contextual information by examining details such as repetition in server names and times and broader information about the employee’s trip.
Good Wall Street Journalarticle 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.
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.”
Reporting on the rise of fake students enrolling in community college courses:
The bots’ goal is to bilk state and federal financial aid money by enrolling in classes, and remaining enrolled in them, long enough for aid disbursements to go out. They often accomplish this by submitting AI-generated work. And because community colleges accept all applicants, they’ve been almost exclusively impacted by the fraud.
The article talks about the rise of this type of fraud, the difficulty of detecting it, and how it upends quite a bit of the class structure and learning community.
Card draining is when criminals remove gift cards from a store display, open them in a separate location, and either record the card numbers and PINs or replace them with a new barcode. The crooks then repair the packaging, return to a store and place the cards back on a rack. When a customer unwittingly selects and loads money onto a tampered card, the criminal is able to access the card online and steal the balance.
[…]
In card draining, the runners assist with removing, tampering and restocking of gift cards, according to court documents and investigators.
A single runner driving from store to store can swipe or return thousands of tampered cards to racks in a short time. “What they do is they just fly into the city and they get a rental car and they just hit every big-box location that they can find along a corridor off an interstate,” said Parks.
The Wall Street Journal is reporting that the CEO of a still unnamed company has been indicted for creating a fake auditing company to falsify security certifications in order to win government business.
After retiring in 2014 from an uncharacteristically long tenure running the NSA (and US CyberCommand), Keith Alexander founded a cybersecurity company called IronNet. At the time, he claimed that it was based on IP he developed on his own time while still in the military. That always troubled me. Whatever ideas he had, they were developed on public time using public resources: he shouldn’t have been able to leave military service with them in his back pocket.
In any case, it was never clear what those ideas were. IronNet never seemed to have any special technology going for it. Near as I could tell, its success was entirely based on Alexander’s name.
Turns out there was nothing there. After some crazy VC investments and an IPO with a $3 billion “unicorn” valuation, the company has shut its doors. It went bankrupt a year ago—ceasing operations and firing everybody—and reemerged as a private company. It now seems to be gone for good, not having found anyone willing to buy it.
Last September the never-profitable company announced it was shutting down and firing its employees after running out of money, providing yet another example of a tech firm that faltered after failing to deliver on overhyped promises.
The firm’s crash has left behind a trail of bitter investors and former employees who remain angry at the company and believe it misled them about its financial health.
IronNet’s rise and fall also raises questions about the judgment of its well-credentialed leaders, a who’s who of the national security establishment. National security experts, former employees and analysts told The Associated Press that the firm collapsed, in part, because it engaged in questionable business practices, produced subpar products and services, and entered into associations that could have left the firm vulnerable to meddling by the Kremlin.
“I’m honestly ashamed that I was ever an executive at that company,” said Mark Berly, a former IronNet vice president. He said the company’s top leaders cultivated a culture of deceit “just like Theranos,” the once highly touted blood-testing firm that became a symbol of corporate fraud.
There has been one lawsuit. Presumably there will be more. I’m sure Alexander got plenty rich off his NSA career.
It’s possible to cancel other people’s voter registrations:
On Friday, four days after Georgia Democrats began warning that bad actors could abuse the state’s new online portal for canceling voter registrations, the Secretary of State’s Office acknowledged to ProPublica that it had identified multiple such attempts…
…the portal suffered at least two security glitches that briefly exposed voters’ dates of birth, the last four digits of their Social Security numbers and their full driver’s license numbers—the exact information needed to cancel others’ voter registrations.
I get that this is a hard problem to solve. We want the portal to be easy for people to use—even non-tech-savvy people—and hard for fraudsters to abuse, and it turns out to be impossible to do both without an overarching digital identity infrastructure. But Georgia is making it easy to abuse.
EDITED TO ADD (8/14): There was another issue with the portal, making it easy to request cancellation of any Georgian’s registration. The elections director said that cancellations submitted this way wouldn’t have been processed because they didn’t have all the necessary information, which I guess is probably true, but it shows just how sloppy the coding is.
Citations of scientific work abide by a standardized referencing system: Each reference explicitly mentions at least the title, authors’ names, publication year, journal or conference name, and page numbers of the cited publication. These details are stored as metadata, not visible in the article’s text directly, but assigned to a digital object identifier, or DOI—a unique identifier for each scientific publication.
References in a scientific publication allow authors to justify methodological choices or present the results of past studies, highlighting the iterative and collaborative nature of science.
However, we found through a chance encounter that some unscrupulous actors have added extra references, invisible in the text but present in the articles’ metadata, when they submitted the articles to scientific databases. The result? Citation counts for certain researchers or journals have skyrocketed, even though these references were not cited by the authors in their articles.
[…]
In the journals published by Technoscience Academy, at least 9% of recorded references were “sneaked references.” These additional references were only in the metadata, distorting citation counts and giving certain authors an unfair advantage. Some legitimate references were also lost, meaning they were not present in the metadata.
In addition, when analyzing the sneaked references, we found that they highly benefited some researchers. For example, a single researcher who was associated with Technoscience Academy benefited from more than 3,000 additional illegitimate citations. Some journals from the same publisher benefited from a couple hundred additional sneaked citations.
Be careful what you’re measuring, because that’s what you’ll get. Make sure it’s what you actually want.
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.
In an era dominated by digital landscapes, protecting your brand’s identity has become more challenging than ever. Malicious actors regularly build lookalike websites, complete with official logos and spoofed domains, to try to dupe customers and employees. These kinds of phishing attacks can damage your reputation, erode customer trust, or even result in data breaches.
In March 2023 we introduced Cloudflare’s Brand and Phishing Protection suite, beginning with Brand Domain Name Alerts. This tool recognizes so-called “confusable” domains (which can be nearly indistinguishable from their authentic counterparts) by sifting through the trillions of DNS requests passing through Cloudflare’s DNS resolver, 1.1.1.1. This helps brands and organizations stay ahead of malicious actors by spotting suspicious domains as soon as they appear in the wild.
Today we are excited to expand our Brand Protection toolkit with the addition of Logo Matching. Logo Matching is a powerful tool that allows brands to detect unauthorized logo usage: if Cloudflare detects your logo on an unauthorized site, you receive an immediate notification.
The new Logo Matching feature is a direct result of a frequent request from our users. Phishing websites often use official brand logos as part of their facade. In fact, the appearance of unauthorized logos is a strong signal that a hitherto dormant suspicious domain is being weaponized. Being able to identify these sites before they are widely distributed is a powerful tool in defending against phishing attacks. Organizations can use Cloudflare Gateway to block employees from connecting to sites with a suspicious domain and unauthorized logo use.
Imagine having the power to fortify your brand’s presence and reputation. By detecting instances where your logo is being exploited, you gain the upper hand in protecting your brand from potential fraud and phishing attacks.
Getting started with Logo Matching
For most brands, the first step to leveraging Logo Matching will be to configure Domain Name Alerts. For example, we might decide to set up an alert for example.com, which will use fuzzy matching to detect lookalike, high-risk domain names. All sites that trigger an alert are automatically analyzed by Cloudflare’s phishing scanner, which gathers technical information about each site, including SSL certificate data, HTTP request and response data, page performance data, DNS records, and more — all of which inform a machine-learning based phishing risk analysis.
Logo Matching further extends this scan by looking for matching images. The system leverages image recognition algorithms to crawl through scanned domains, identifying matches even when images have undergone slight modifications or alterations.
Once configured, Domain Name Alerts and the scans they trigger will continue on an ongoing basis. In addition, Logo Matching monitors for images across all domains scanned by Cloudflare’s phishing scanner, including those scanned by other Brand Protection users, as well as scans initiated via the Cloudflare Radar URL scanner, and the Investigate Portal within Cloudflare’s Security Center dashboard.
How we built Logo Matching for Brand Protection
Under the hood of our API Insights
Now, let’s dive deeper into the engine powering this feature – our Brand Protection API. This API serves as the backbone of the entire process. Not only does it enable users to submit logos and brand images for scanning, but it also orchestrates the complex matching process.
When a logo is submitted through the API, the Logo Matching feature not only identifies potential matches but also allows customers to save a query, providing an easy way to refer back to their queries and see the most recent results. If a customer chooses to save a query, the logo is swiftly added to our data storage in R2, Cloudflare’s zero egress fee object storage. This foundational feature enables us to continuously provide updated results without the customer having to create a new query for the same logo.
The API ensures real-time responses for logo submissions, simultaneously kick-starting our internal scanning pipelines. An image look-back ID is generated to facilitate seamless tracking and processing of logo submissions. This identifier allows us to keep a record of the submitted images, ensuring that we can efficiently manage and process them through our system.
Scan result retrieval
As images undergo scanning, the API remains the conduit for result retrieval. Its role here is to constantly monitor and provide the results in real time. During scanning, the API ensures users receive timely updates. If scanning is still in progress, a “still scanning” status is communicated. Upon completion, the API is designed to relay crucial information — details on matches if found, or a simple “no matches” declaration.
Storing and maintaining logo data
In the background, we maintain a vectorized version of all user-uploaded logos when the user query is saved. This system, acting as a logo matching subscriber, is entrusted with the responsibility of ensuring accurate and up-to-date logo matching.
To accomplish this, two strategies come into play. Firstly, the subscriber stays attuned to revisions in the logo set. It saves vectorized logo sets with every revision and regular checks are conducted by the subscriber to ensure alignment between the vectorized logos and those saved in the database.
While monitoring the query, the subscriber employs a diff-based strategy. This recalibrates the vectorized logo set against the current logos stored in the database, ensuring a seamless transition into processing.
Shaping the future of brand protection: our roadmap ahead
With the introduction of the Logo Matching feature, Cloudflare’s Brand Protection suite advances to the next level of brand integrity management. By enabling you to detect and analyze, and act on unauthorized logo usage, we’re helping businesses to take better care of their brand identity.
At Cloudflare, we’re committed to shaping a comprehensive brand protection solution that anticipates and mitigates risks proactively. In the future, we plan to add enhancements to our brand protection solution with features like automated cease and desist letters for swift legal action against unauthorized logo use, proactive domain monitoring upon onboarding, simplified reporting of brand impersonations and more.
Getting started
If you’re an Enterprise customer, sign up for Beta Access for Brand protection now to gain access to private scanning for your domains, logo matching, save queries and set up alerts on matched domains. Learn more about Brand Protection here.
Online marketplaces sell tiny pink cowboy hats. They also sell miniature pencil sharpeners, palm-size kitchen utensils, scaled-down books and camping chairs so small they evoke the Stonehenge scene in “This Is Spinal Tap.” Many of the minuscule objects aren’t clearly advertised.
[…]
But there is no doubt some online sellers deliberately trick customers into buying smaller and often cheaper-to-produce items, Witcher said. Common tactics include displaying products against a white background rather than in room sets or on models, or photographing items with a perspective that makes them appear bigger than they really are. Dimensions can be hidden deep in the product description, or not included at all.
In those instances, the duped consumer “may say, well, it’s only $1, $2, maybe $3—what’s the harm?” Witcher said. When the item arrives the shopper may be confused, amused or frustrated, but unlikely to complain or demand a refund.
“When you aggregate that to these companies who are selling hundreds of thousands, maybe millions of these items over time, that adds up to a nice chunk of change,” Witcher said. “It’s finding a loophole in how society works and making money off of it.”
Defrauding a lot of people out of a small amount each can be a very successful way of making money.
Napoleon Gonzalez, of Etna, assumed the identity of his brother in 1965, a quarter century after his sibling’s death as an infant, and used the stolen identity to obtain Social Security benefits under both identities, multiple passports and state identification cards, law enforcement officials said.
[…]
A new investigation was launched in 2020 after facial identification software indicated Gonzalez’s face was on two state identification cards.
The facial recognition technology is used by the Maine Bureau of Motor Vehicles to ensure no one obtains multiple credentials or credentials under someone else’s name, said Emily Cook, spokesperson for the secretary of state’s office.
In this blog post, we wanted to highlight some ways that Cloudflare and IBM Cloud work together to help drive product innovation and deliver services that address the needs of our mutual customers. On our blog, we often discuss exciting new product developments and how we are solving real-world problems in our effort to make the internet better and many of our customers and partners play an important role.
IBM Cloud and Cloudflare have been working together since 2018 to integrate Cloudflare application security and performance products natively into IBM Cloud. IBM Cloud Internet Services (CIS) has customers across a wide range of industry verticals and geographic regions but they also have several specialist groups building unique service offerings.
The IBM Cloud team specializes in serving clients in highly regulated industries, aiming to ensure their resiliency, performance, security and compliance needs are met. One group that we’ve been working with recently is IBM Cloud for Financial Services. This group extends the capabilities of IBM Cloud to help serve the complex security and compliance needs of banks, financial institutions and fintech companies.
Bot Management
As malicious bot attacks get more sophisticated and manual mitigations become more onerous, a dynamic and adaptive solution is required for enterprises running Internet facing workloads. With Cloudflare Bot Management on IBM Cloud Internet Services, we aim to help IBM clients protect their Internet properties from targeted application abuse such as account takeover attacks, inventory hoarding, carding abuse and more. Bot Management will be available in the second quarter of 2023.
Threat actors specifically target financial services entities with Account Takeover Attacks, and this is where Cloudflare can help. As much as 71% of login requests we see come from bots (Source: Cloudflare Data) Cloudflare’s Bot Management is powered by a global machine learning model that analyses an average of 45 million HTTP requests a second to track botnets across our network. Cloudflare’s Bot Management solution has the potential to benefit all IBM CIS customers.
Supporting banks, financial institutions, and fintechs
IBM Cloud has been a leader when it comes to providing solutions for the financial services industry and has developed several key management solutions that are designed so clients only need to store their private keys in custom built devices.
The IBM CIS team wants to incorporate the right mix of security and performance, which necessitates the use of cloud-based DDoS, WAF, and Bot Management. Specifically, they wanted to incorporate the powerful security tools that were offered through IBM’s Enterprise-level Cloud Internet Services offerings. When using a cloud solution, it is necessary to proxy traffic which can create a potential challenge when it comes to managing private keys. While Cloudflare adopts strict controls to protect these keys, organizations in highly regulated industries may have security policies and compliance requirements that prevent them from sharing these private keys.
Cloudflare built Keyless SSL to allow customers to have total control over exactly where private keys are stored. With Keyless SSL and IBM’s key storage solutions, we aim to help enterprises benefit from the robust application protections available through Cloudflare’s WAF, including Cloudflare Bot Management, while still retaining control of their private keys.
“We aim to ensure our clients meet their resiliency, performance, security and compliance needs. The introduction of Keyless SSL and Bot Management security capabilities can further our collaborative accomplishments with Cloudflare and help enterprises, including those in regulated industries, to leverage cloud-native security and adaptive threat mitigation tools.” — Zane Adam, Vice President, IBM Cloud.
“Through our collaboration with IBM Cloud Internet Services, we get to draw on the knowledge and experience of IBM teams, such as the IBM Cloud for Financial Services team, and combine it with our incredible ability to innovate, resulting in exciting new product and service offerings.” — David McClure, Global Alliance Manager, Strategic Partnerships
This is a familiar story in the world of bot attacks. Cloudflare Bot Management helps customers identify the automated tools behind online fraud, but it’s important to note that not all fraud is committed by bots. If the target is valuable enough, bad actors will contract out the exploitation of online applications to real people. Security teams need to look at more than just bots to better secure online applications and tackle modern, online fraud.
Today, we’re excited to announce Cloudflare Fraud Detection. Fraud Detection will give you precise, easy to use tools that can be deployed in seconds to any website on the Cloudflare network to help detect and categorize fraud. For every type of fraud we detect on your website, you will be able to choose the behavior that makes the most sense to you. While some customers will want to block fraudulent traffic at our edge, other customers may want to pass this information in headers to build integrations with their own app, or use our Cloudflare Workers platform to direct high risk users to load an alternate online experience with fewer capabilities.
The online fraud experience today
When we talk to organizations impacted by sophisticated, online fraud, the first thing we hear from frustrated security teams is that they know what they could do to stop fraud in a vacuum: they’ve proposed requiring email verification on signup, enforcing two-factor authentication for all logins, or blocking online purchases from anonymizing VPNs or countries they repeatedly see a disproportionately high number of charge-backs from. While all of these measures would undoubtedly reduce fraud, they would also make the user experience worse. The fear for every company is that a bad UX will mean slower adoption and less revenue, and that’s too steep a price to pay for most run-of-the-mill online fraud.
For those who’ve chosen to preserve that frictionless user experience and bear the cost of fraud, we see two big impacts: higher infrastructure costs and less efficient employees. Bad actors that abuse account creation endpoints or service availability endpoints often do so with floods of highly distributed HTTP requests, quickly moving through residential proxies to pass under IP based rate limiting rules. Without a way to identify fraudulent traffic with certainty, companies are forced to scale up their infrastructure to be able to serve new peaks in request traffic, even when they know the majority of this traffic is illegitimate. Engineering and Trust and Safety Teams suddenly have a whole new set of responsibilities: regularly banning IP addresses that will probably never be used again, routinely purging fraudulent data from over capacity databases, and even sometimes becoming de-facto fraud investigators. As a result, the organization incurs greater costs without any greater value to their customers.
Reduce modern fraud without hurting UX
Organizations have told us loud and clear that an effective fraud management solution needs to reliably stop bad actors before they can create fraudulent accounts, use stolen credit cards, or steal customer data all the while ensuring a frictionless user experience for real users. We are building novel and highly accurate detections, solving for the four common fraud types we hear the most demand for from businesses around the world:
Fake Account Creation: Bad actors signing up for many different accounts to gain access to promotional rewards, or more resources than a single user should have access to.
Account Takeover: Gaining unauthorized access to legitimate accounts, by means such as using stolen username and password combinations from other websites, guessing weak passwords, or abusing account recovery mechanisms.
Card Testing and Fraudulent Transactions: Testing the validity of stolen credit card details or using those same details to purchase goods or services.
Expediting: Obtaining limited availability goods or services by circumventing the normal user flow to complete orders more quickly than should be possible.
In order to trust your fraud management solution, organizations have to understand the decisions or predictions behind the detection of fraud. This is referred to as explainability. For example, it’s not enough to know a signup attempt was flagged as fraud. You need to know, for example, if a signup is fraudulent, exactly what field supplied by the user led us to think this was an issue, why it was an issue, and if it was part of a larger pattern. We will pass along this level of detail when we detect fraud so you can ensure we are only keeping the bad actors out.
Every business that deals with modern, online fraud has a different idea of what risks are acceptable, and a different preference for dealing with fraud once it’s been identified. To give customers maximum flexibility, we’re building Cloudflare’s fraud detection signals to be used individually, or combined with other Cloudflare security products in whichever way best fits each customer’s risk profile and use case, all while using the familiar Cloudflare Firewall Rules interface. Templated rules and suggestions will be available to provide guidance and help customers become familiar with the new features, but each customer will have the option of fully customizing how they want to protect each internet application. Customers can either block, rate-limit, or challenge requests at the edge, or send those signals upstream in request headers, to trigger custom in-application behavior.
Cloudflare provides application performance and security services to millions of sites, and we see 45 million HTTP requests per second on average. The massive diversity and volume of this traffic puts us in a unique position to analyze and defeat online fraud. Cloudflare Bot Management is already built to run our Machine Learning model that detects automated traffic on every request we see. To better tackle more challenging use cases like online fraud, we made our lightning fast Machine Learning even more performant. The typical Machine Learning model now executes in under 0.2 milliseconds, giving us the architecture we need to run multiple specific Machine Learning models in parallel without slowing down content delivery.
Stopping fake account creation and adding to Cloudflare’s defense in depth
The first problem our customers asked us to tackle is detecting fake account creation. Cloudflare is perfectly positioned to solve this because we see more account creation pages than anyone else. Using sampled fake account attack data from our customers, we started looking at signup submission data, and how threat intelligence curated by our Cloudforce One team might be helpful. We found that the data used in our Cloudflare One products was already able to identify 72% of fake accounts based on the signup details supplied by the bad actor, such as the email address or the domain they’re using in the attack. We are continuing to add more sources of threat intelligence data specific to fake accounts to get this number close to 100%. On top of these threat intelligence based rules, we are also training new machine learning models on this data as well, that will spot trends like popular fraud domains based on intelligence from the millions of domains we see across the Cloudflare network.
Making fraud inefficient by expediting detection
The second problem customers asked us to prioritize is expediting. As a reminder, expediting means visiting a succession of web pages faster than would be possible for a normal user, and sometimes skipping ahead in the order of web pages in order to efficiently exploit a resource.
For instance, let’s say that you have an Account Recovery page that is being spammed by a sophisticated group of bad actors, looking for vulnerable users they can steal reset tokens for. In this case, the fraudsters have access to a large number of valid email addresses and they’re testing which of these addresses may be used at your website. To prevent your account recovery process from being abused, we need to ensure that no single person can move through the account recovery process faster, or in a different order than a real person would.
In order to complete a valid password reset action on your site, you may know that a user should have made:
A GET request to render your login page
A POST request to the login page (at least one second after receiving the login page HTML)
A GET request to render the Account Recovery page (at least one second after receiving the POST response)
A POST request to the password reset page (at least one second after receiving the Account Recovery page HTML)
Taken a total time of less than 5 seconds to complete the process
To solve this, we will rely on encrypted data stored by the user in a token to help us determine if the user has visited all the necessary pages needed in a reasonable amount of time to be performing sensitive actions on your site. If your account recovery process is being abused, the encrypted token we supply acts as a VIP pass, allowing only authorized users to successfully complete the password recovery process. Without a pass indicating the user has gone through the normal recovery flow in the correct order and time, they are denied entry to complete a password recovery. By forcing the bad actor to behave the same as a legitimate user, we make their task of checking which of their compromised email addresses might be registered at your site an impossibly slow process, forcing them to move on to other targets.
These are just two of the first techniques we use to identify and block fraud. We are also building Account Takeover and Carding Abuse detections that we will be talking about in the future on this blog. As online fraud continues to evolve, we will continue to build new and unique detections, leveraging Cloudflare’s unique position to help keep the internet safe.
Where do I sign up?
Cloudflare’s mission is to help build a better Internet, and that includes dealing with the evolution of modern online fraud. If you’re spending hours cleaning up after fraud, or are tired of paying to serve web traffic to bad actors, you can join in the Cloudflare Fraud Detection Early Access in the second half of 2023 by submitting your contact information here. Early Access customers can opt in to providing training data sets right away, making our models more effective for their use cases. You’ll also get test access to our newest models, and future fraud protection features as soon as they roll out.
“Pig butchering” is the colorful name given to online cons that trick the victim into giving money to the scammer, thinking it is an investment opportunity. It’s a rapidly growing area of fraud, and getting more sophisticated.
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.
Someone in the UK is stealing smartphones and credit cards from people who have stored them in gym lockers, and is using the two items in combination to commit fraud:
Phones, of course, can be made inaccessible with the use of passwords and face or fingerprint unlocking. And bank cards can be stopped.
But the thief has a method which circumnavigates those basic safety protocols.
Once they have the phone and the card, they register the card on the relevant bank’s app on their own phone or computer. Since it is the first time that card will have been used on the new device, a one-off security passcode is demanded.
That verification passcode is sent by the bank to the stolen phone. The code flashes up on the locked screen of the stolen phone, leaving the thief to tap it into their own device. Once accepted, they have control of the bank account. They can transfer money or buy goods, or change access to the account.
The collective thoughts of the interwebz
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