Researching Employment Scams
Researchers built a fake company to study fake employee scams.
Researchers built a fake company to study fake employee scams.
To subscribe to my monthly email newsletter, you have to enter your information on the webpage, and then reply to an automatically generated email. This is, of course, to prevent people from subscribing addresses other than their own.
Starting last weekend, I have been receiving a lot of individual responses to those emails. Always one line:
Thank you for the positive impact your emails have had on my life.
Your emails are a game-changer.
Your emails are a constant reminder of why I subscribed.
Your emails rock.
Thank you for the time and effort you put into creating these informative emails.
Thank you for the passion and enthusiasm you infuse into your email content.
Your emails consistently exceed my expectations. Thank you for the exceptional value!
I responded to the first few, because sometimes I do get these nice emails from readers and I hadn’t yet realized it was all fake. But so many, and all at once—this is obviously AI. And obviously a scam, except I can’t figure out what the scam is.
The addresses are things like:
jnnvcddghjgfdryhj67@gmail.com
nbhgdfhjedty896565@gmail.com
jesikawells6873@gmail.com
niffelatopserean92@gmail.com
reinareyes983@gmail.com
htfhtfhhjkgth@gmail.com
All Gmail. None of the addresses has actually subscribed to Crypto-Gram. They could; whoever is sending the emails could easily have confirmed the subscription.
My first thought was pig butchering—wanting me to respond and turn this into a conversation—but no one has responded to any of my responses. Anyone have any idea?
OpenAI disrupted a social engineering group from Cambodia that used ChatGPT. Its scope is impressive:
The network simultaneously conducted multiple types of scams, often blending elements from different schemes. For instance, operators used dating personas to build trust before introducing fraudulent investment opportunities involving cryptocurrencies and spot gold trading. Other users engaged in lengthy romantic conversations with targets using fictitious identities, posed as representatives of online gambling platforms offering fake bonuses and winnings, or impersonated law enforcement agencies to tell targets they needed to pay fines for committing serious criminal offenses.
Although the narratives varied, users across the network consistently displayed the same underlying pattern of deceptive behavior. For example, they created and operated fake dating profiles, fictitious investment experts, and fraudulent law enforcement personas. They also generated images of forged documents, including passports, legal notices, stock-purchase confirmations, and gambling platform interfaces.

What Happened
HMRC Issues Warning to TikTok Users
Lloyds Bank found Two Thirds of Fraud Cases Started on Meta
UK Finance Recorded £221.5m Lost to Investment Scams
Fraudsters arrested in Nigeria following NCA intelligence sharing
Analyst Comment
H1 2026 reinforces the transition from email-centric fraud campaigns to social-media-powered fraud operations, with platforms increasingly serving as the primary source of victims for organised cybercriminal groups. Fraudsters are also adapting scams to the culture and user behaviour of individual platforms, such as generate short promotional videos on TikTok or listing fake items for sale on Facebook Marketplace. Rather than deploying identical scams everywhere, criminals tailor campaigns to the platform's intended purpose. Recommendation algorithms and advertising ecosystems provide fraudsters with scalable victim acquisition channels that were previously unavailable through traditional phishing campaigns.
Advances in artificial intelligence (AI) and large language models (LLMs) has also meant it is much easier for cybercriminals to carry out scams on a much larger scale than they were previously able to. Autonomous systems can enable them to send out messages at scale and contact users by telephone at scale. Plus the scam attempts are also more convincing as they can mimic voices and appearance of celebrities or even a target’s friends and family.
The scale of fraudulent activities across social media is so large, it requires vast resources and expertise to monitor, detect, and prevent. At the same time, the response from HMRC, banks, social media companies, the NCA, and international law enforcement suggests increasing recognition that combating social media fraud requires coordinated action.
The volume of fake accounts on social media used for scams does also validate the calls for increased verification and security checks on such platforms. The UK Government's proposal to introduce a national digital ID system, however, was met with fierce opposition. Up to 2.9 million people signed a UK parliament petition to show their disagreement with such a system.
Defensive Takeaways
Relevant Sources
Not sure this will have any effect, but I support the effort:
According to Google’s legal filing, Outsider Enterprise operates through Telegram. The group offers phishing-as-a-service to individuals who may not be technically savvy enough to set up fraudulent websites and text campaigns on their own. In its Telegram channels, Outsider Enterprise reportedly provided instructions on how to use Google’s Gemini AI to create websites that imitate those of Google, YouTube, and government agencies such as New York’s E-ZPass. The group offered nearly 300 scam templates.
[…]
Google worked with AT&T, Verizon, and T-Mobile to block many of these malicious text messages, and Google notes that its on-device scam detection in Google Messages probably helped reduce the number of successful phishing attempts, too. This AI-powered feature apparently stops 10 billion scam texts every month, so it’s fair to expect it caught at least some Outsider Enterprise activity.
Another article.
Analyst Comment
For both everyday UK consumers and UK retail risk teams, these alerts provide several layered insights. Retailers have spent years optimising Click & Collect to be as frictionless as possible to compete with online shopping giants like Amazon. However, this alert shows how Click & Collect can be a security liability. As Argos allows quick collections, criminals can buy an item online and pick it up at a local store before the real account owner notices an order confirmation email.
The police alerts also note that the items may even be paid for using payment details not connected to the victim. Criminals are mixing stolen accounts with stolen credit cards. This is likely due to an established Argos account with a multi-year history buying expensive items would look pretty normal to a fraud detection engines.
The combination of an Account Takeover (ATO) and Buy Now Pay Later (BNPL) fraud creates a difficult scenario for retailers, credit providers, and consumers. The regulatory and reputational fallout for a retailer under the rules of the UK Financial Conduct Authority (FCA) could be severe. If a retailer's poor account security allows fraudsters to easily spin up a finance plan in a victim's name, the FCA will view this as a systemic failure to protect consumers, resulting in massive fines.
These attacks are possible due to the practice of Argos users who are reusing the same previously leaked password across multiple accounts, plus users not having multi-factor authentication (MFA) turned on in their account settings.
Campaigns like this can trigger a reputational hit to retailers as victims often do not suffer silently. They take to social media to share stories and the public narrative can shift to being about a retailer who is complicit in disrupting innocent people's financial lives.
Defensive Takeaways
Relevant Sources
Social Media Intelligence (SOCMINT)
Relevant CTI Resources

What Happened
Analyst Comment
When analysing fraud statistics, it is important to remember that underreporting is very common, with many victims staying silent out of shame. Therefore, this is likely only a fraction of the real figures and the problem is likely much worse than we know. The data we do have, however, still reveals there is essentially an army of digital scammers routinely bleeding UK citizens dry, using not much more than a Midjourney AI subscription, a ChatGPT script, face-swapping services, and an entirely fictitious character with an emotional backstory.
Losing £102 million in a single year to fake internet characters is a truly wild national milestone. The fact that reports surged by nearly a third (29%) proves that in our society, emotional vulnerability is being monetised at industrial scale. We aren’t just looking at a clumsy email from a Nigerian prince anymore. This is industrial-grade social engineering. Scammers are playing the long game, spending months "love-bombing" victims before dropping the inevitable bombshell that they need a quick bank transfer to cover a “medical emergency” or an unmissable cryptocurrency investment opportunity.
In March 2026, the UK Government took some action against this threat and sanctioned Xinbi, a Chinese-language cryptocurrency marketplace accused of enabling large-scale online fraud and human exploitation. Xinbi reportedly processed more than $19.9 billion in transactions between 2021 and 2025, highlighting how much money the scam industry is generating globally.
Until we treat the underground scam economy with the same significance we treat ransomware or nation state attacks, the UK will continue to be one of the world's most lucrative money spinners for heartless cybercriminals.
Defensive Takeaways
Relevant Sources
Relevant CTI Resources