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Recent data highlight the growing scale of fraud harms. The FBI reports that Americans aged 60 and older lost more than $3.4 billion to scams in 2023.2 Industry analyses also indicate that deepfake-enabled fraud attempts increased by roughly 3,000 percent between 2022 and 2023 as generative AI tools became more widely available.3 Globally, the Global Anti-Scam Alliance estimates that scam losses exceeded $1 trillion over a recent 12-month period.4

From: Agentic Commerce: Is This Really the Best We Can Do?.

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Jan 3, 2026, 10:36 AM GMT

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Bitcoin ATM fraud hit $333 million in losses in 2025, the FBI said.
Over 10,000 people have fallen victim to bitcoin ATM scams, with older adults being the most affected.
Bitcoin ATM fraud losses have more than doubled since 2022, according to FTC data.
Bitcoin ATM fraud reached new highs in 2025, with scammers reportedly stealing $333 million from victims, the FBI said.

From: Bitcoin ATM Fraud Rises As FBI Reports $333 Million Stolen in 2025 – Business Insider.

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In December 2024, criminals stole thousands of dollars from Steve Beckett at a Circle K convenience store in Indiana. The robbery happened in broad daylight.

The thieves didn’t use a gun or a knife. There was no getaway car. The instrument of the crime was a machine, much like an ATM, owned by Bitcoin Depot and placed in the convenience store as part of a nationwide agreement with Circle K.

Beckett, 66 at the time, had been paying bills at home when his computer froze and a message directed him to call what turned out to be a phony Microsoft service hotline.

On the phone, a man named “Josh” told Beckett that someone had hacked his computer and used his credit cards and bank accounts to purchase child pornography. Soon, Beckett was speaking to another man, who claimed to work at his bank, and then someone else, who said he represented the Federal Reserve. His life savings were at risk, the men said, and there was only one way to protect them: converting the money into bitcoin.

Over the course of two days, the men cajoled and threatened Beckett, warning him he could go to prison. He had spent years working in management at a casino and selling securities and felt something was wrong, but he was terrified.

“My heart was racing, my blood pressure’s going through the roof,” he said.

Panicked, Beckett withdrew $4,000 from his bank and, at the men’s direction, drove to a Circle K with a Bitcoin Depot ATM. Beckett had never bought bitcoin and knew little about it, but he didn’t ask too many questions. On the phone, one of the men walked him through how to deposit the funds. “I was shaking like a leaf,” he said. The next day, he deposited another $3,000.

The machine, often called a crypto ATM or bitcoin ATM, converted the cash into bitcoin and transferred it to a digital address the men provided. For completing the transaction, Bitcoin Depot received about $2,000 in fees.

From: Retailers keep cashing in on crypto ATMs as scams surge – ICIJ.

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An 80-year-old man in Sunrise was the victim of a fraud that cost him and his family nearly $60,000, according to police.

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After his son reported it to police, the victim told a police officer that he was on his computer when a pop-up window opened and he clicked on it.

“He began receiving messages and phone calls from unknown numbers,” a police officer wrote after meeting with the victim on Oct. 6, according to a police report.

The scammer manipulated the victim into making withdrawals from JPMorgan Chase, driving to a Bitcoin ATM at 10129 West Oakland Park Boulevard, and using it to send $57,420 in Bitcoin to two wallets, according to a police report.

From: Police: Scammer impersonating bank employee uses Bitcoin ATM to steal nearly $60,000 from Sunrise victim.

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In a lawsuit against Bitcoin Depot filed in early 2025, Iowa’s attorney general wrote that an analysis of transactions conducted in the state on the company’s machines between October 2021 and July 2024 suggested that more than half involved scams.

From: Retailers keep cashing in on crypto ATMs as scams surge – ICIJ.

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It emerged that, in this case, Lloyds had done a really good job of not only spotting the potential fraud but alerting James to it.
The bank blocked a number of transactions, it spoke to James on the phone to warn him and even called him into a branch to speak to him face-to-face.
However, the scammer’s hold over James was so strong after being indoctrinated to this supposed plight, he insisted the payments went through.
After our investigation began, though, Lloyds carried out a thorough review of James’ case.
In a statement it said it had a great deal of sympathy for James and his family.
“Sadly in this case, our customer did not take appropriate steps to verify that the person he met online was genuine. We blocked a number of the transfers and provided warnings about the risk of this being a scam, however he chose to proceed with the transactions.
“Given the complexity of this case and his personal circumstances at that time, we have now provided a full refund of the money he lost to the fraudsters.”

From: Fraud victim gets surprise £153,000 refund despite rules – BBC News.

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Integrating separate hardware components and implementing a higher level of segregation for critical use cases, including key management, provides greater protection than mobile devices’ general-purpose hardware and operating systems, or general-purpose cloud infrastructures.[32] This is why DIWs should be deployed in devices that contain dedicated secure elements (SEs), which provide a physically separate secure environment, and/or platform-specific trusted execution environments (TEEs) for isolating cryptographic operations and sensitive data storage.

An SE contains a microprocessor chip engineered in a way that can store sensitive data and perform critical operations while offering lower exposure to threats. It acts as a vault, protecting the applications and data from typical malware attacks on the host operating system. Examples of secure elements for mobile devices include external hardware devices specifically designed for cryptographic operations, such as security tokens or smart ID cards. Secure elements such as SIMs, embedded SIMs (eSIMs) and embedded secure elements (eSEs) can also be integrated within the mobile device’s architecture. Current versions of mobile operating systems offer APIs to support operations with SEs, including embedded ones.

A TEE is an isolated environment within a device’s main processor[33] designed to protect sensitive operations and data from the rest of the device processing components, including the operating system and other applications. Often TEEs are used in combination with SEs, and some authors use the term TEE as already encompassing the integrated solution.

In cloud infrastructures, the solution may be provided by an isolated environment supported by dedicated hardened servers.[34] Hardware Secure Modules (HSMs) and other secure elements can also be deployed within a cloud infrastructure and connected to servers. A cloud-based architecture can relieve the mobile device of the burden of security management, enabling features such as credential recovery in the event of a lost device. However, it can present challenges in terms of availability and use in an offline context, where the device is not connected to the internet and proximity-based protocols are used instead.

From: TechDispatch #3/2025 – Digital Identity Wallets | European Data Protection Supervisor.

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Less than a day after staking over $30,000 on Venezuela President Maduro’s exit on a new Polymarket account, a trader reportedly earned $400,000 as US authorities moved against the South American leader.

His winnings have already drawn the attention of the online community and even Congress. Some lawmakers have shared their frustrations about insider trading.

From: Betting on Venezuela President Maduro’s exit, a trader earned over $400,000.

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Third, smart contracts, such as the one-to-one exchange facilities backing Dai, can create interlinkages between DeFi participants. Such facilities can be created at the discretion of any individual participant and operate autonomously. Without appropriate consideration of the risks posed to the wider ecosystem, these interlinkages can channel and amplify contagion.

This paper provides a detailed account of how SVB’s failure affected USDC and other stablecoins during March 2023. Our account is backed by granular data on both the primary and secondary market activities of the affected stablecoins.

From: The Fed – In the Shadow of Bank Runs: Lessons from the Silicon Valley Bank Failure and Its Impact on Stablecoins.

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The Federal Trade Commission reported a staggering $12.5 billion in consumer fraud losses in 2024 — a 25% increase over the previous year… While younger populations fall victim more frequently, the financial severity of the loss is significantly higher for seniors.

From: The Credit Card AI Crime Wave, and How to Fight Back in 2026 – The Financial Brand.

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It’s not very easy for me to criticise the digital ID policy – because there isn’t one yet.

From: Identity politics: What do we know so far about government’s digital ID plans? – PublicTechnology.

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The legislation means acting as a director without being verified has become a criminal offence.

The rules, also being phased in for existing owners and directors over the next year, are intended to ensure that “people setting up, running and controlling companies are who they say they are”. It follows longstanding concerns that the register is being abused to facilitate financial crime and money laundering.

From: Anti-fraud law sparks ‘dramatic fall’ in new company registrations.

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Writing in the Financial Times, John Thornhill made an interesting point about intelligence, in the sense of competition between nations and their national interests, saying that a key reason why the West won the Cold War is that democracies are better at processing information. In short, lackeys tell their autocrat masters what they want to hear, not what they themselves actually know. So how can democracies retain an edge on autocracy? In a previous age we needed spies, but now we need SpyGPT.

Back in 2023, for reasons that are too complicated to go into, but related to one of my academic positions, I was tasked with preparing a briefing note on the impact of recent developments in AI on open-source intelligence (OSINT) for the Defence Data Research Centre (DDRC). The DDRC is a UK research consortium that focuses on improving how defence organisations use data, especially for artificial intelligence (AI) and data science applications. It aims to tackle both the technical and cultural barriers that stop defence data being exploited effectively by being a centre of excellence for defence data research but the output from the centre is intended to benefit not just defence, but also the wider UK economy by improving data‑driven innovation practices that can transfer to other sectors.

OSINT, which is what John Thornhill wrote about, is about the gathering of open data sources to support decision making. While you can look at it as a category in its own right, it is useful to think about it as a component of the intelligence gathered in other areas, as shown in the picture below. This perspective is based on the Rand work on Second Generation OSINT but I amended the Rand model to pull out cyberintelligence as a separate category covering intelligence activities focused on the collection, validation, exploitation and dissemination of information concerning the threat posed by an adversary in the virtual world.

***Picture****

(There’s nothing secret about this, you won’t be shot for copy and pasting it. I spent some of the early years of my career working for the government, armed forces and NATO so I am perfectly well-acquainted with the rules.)

Developing the briefing note was both interesting and challenging. It was interesting because there is a great body of work on AI in intelligence already out there and I had to get familiar with it quickly in order to structure the briefing note and it was very challenging because the rules around the briefing note were very tight. Remember the old adage attributed to Pascal “I’m sorry I wrote you such a long letter, I didn’t have time write you a short one”.

(As it happens, I ended up presenting the briefing in person to the CTO of the CIA! Life really does take some strange turns sometimes.)

 

In cyberwar, as in business in general, the march of AI means that as B

 

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The fundamental problem is that AI must compress reality into model-legible forms. In this setting, adversaries can exploit the compression. They don’t have to attack the territory; they can attack the map.

From: Agentic AI’s OODA Loop Problem – Schneier on Security.

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AI systems themselves are becoming targets.

As organizations embed AI across products, operations, and workflows, their AI systems have emerged as a new class of assets requiring protection. Organizations need to protect the integrity of their AI models; training data, interaction, and prompting interfaces; and agentic tools

From: AI Is Raising the Stakes in Cybersecurity | BCG.

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adversaries will switch from attacking the territory to attacking the map.

 

Broadly speaking, my conclusions at the time were that

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While the Trump family is creating its own prediction market, it also has close ties to the industry’s big players. Donald Trump Jr. is an adviser to both Kalshi and Polymarket. Earlier this year, 1789 Capital, an investment firm backed by the president’s family, put money into Polymarket. The prediction market in October also got an investment worth up to $2 billion from the Intercontinental Exchange, which owns the New York Stock Exchange. The wife of ICE’s chief executive is a member of the Trump administration. 

From: Predicting Prediction Markets Is a Tough Call — The Information.

xxxCoinbase CEO Brian Armstrong effectively manipulated one market during  his company’s earnings call in October. Before the call, bettors were predicting whether Armstrong would say words such as bitcoin, ethereum, blockchain, staking and web3. At the end of the call, Armstrong read out a list of all of the words, creating immediate winners and losers in that market. He said he had been watching the prediction markets during the call. 

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For sellers, the subscription economy has distinct advantages. Monthly and annual fees create recurring revenue streams that reassure shareholders and can be securitised to cover debt. A system of multiple small payments also makes it hard for consumers to figure out exactly how much they are spending and with whom.

But the numbers certainly add up. One recent survey, by the tech site CNET, found that the average US adult spends $1,080 a year on subscriptions, including $205 on unused services. Other estimates run as high as $2,600.

From: Subscription overload is exhausting Americans.

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