Innovative Ways A.I. Accelerates Crypto Fraud

When A.I. and Crypto Fraud meet.

Artificial Intelligence (A.I.) and cryptocurrency are two groundbreaking technologies that have captured the world’s attention. While both offer incredible potential for innovation, their intersection has given rise to a new breed of digital threats. As cryptocurrencies like Bitcoin and Ethereum gain popularity, so do the sophisticated methods criminals use to exploit them. At the forefront of this criminal evolution is A.I., providing new tools and techniques for perpetrating crypto fraud.

A.I. and crypto fraud: An unholy union

In this post I explore the innovative (and alarming) ways in which A.I. is currently or will likely be used to perpetuate crypto fraud, shedding light on the evolving landscape of digital financial crime. I am looking at what is happening now, as well as some trends we expect will accelerate with the help of A.I. models.

We must come at this problem from a pragmatic perspective: What has been invented cannot be uninvented, and I predict that the unholy union between the inventions of A.I. and cryptocurrency is going to drive crypto fraud to new levels we’ve never seen before. Collectively, we are going to need to find innovative ways to fight back.

Innovative Uses of A.I. in Crypto Fraud

There’s no doubt A.I. is a powerful and time-saving tool, and it’s incredible how fast it is developing and how easy it is to develop and train your own A.I. models. This also makes A.I. super scary, because it lowers the barriers to entry for ill-intentioned actors to undertake scams and frauds at scale. A.I. can be used to identify targets, build and exploit scams at scale in rapid time, and so enabling bad actors to ‘hit and run’ a scam before law enforcement has time or capacity to shut it down.

But just what makes A.I. so powerful in the hands of crypto fraud scammers?

Here are some of the superpowers A.I. brings to the crypto fraud fraternity:

A. Identification of Fraudulent Patterns

A.I. is good at identifying patterns because it can analyze vast amounts of data quickly. When this is applied to crypto data, A.I. algorithms have and will become adept at exploiting vulnerabilities in cryptocurrency networks through advanced transaction data analysis. These systems can identify patterns that human fraudsters might miss, allowing for more targeted and effective crypto fraud attempts. More fraud, faster and easier.

One such method involves using machine learning algorithms to analyze trading patterns. There’s nothing new about predictive models, or bots that implement certain trading strategies based on meta data, but where this may become crypto fraud is when the A.I. model identifies potential targets for exploitation either of them or the market. For example, the A.I. may identify vulnerable traders. Nothing illegal about that, but if the A.I. can target traders with specific vulnerabilities, then the fraudster behind it could bribe, extort, coerce illegal behaviour or crypto laundering.

Pump-and-Dump Schemes are a second example: A.I. can conceivably execute sophisticated “pump-and-dump” strategies, identifying when to manipulate trading volumes and prices to deceive other traders into buying before the orchestrators dump large amounts of cryptocurrency for profit.

B. Automated Phishing Attacks

“Phishing” is a term you may of heard of, but hopefully never been the target of. However, its likely at some point, you will be. Phishing is the attempt to steal sensitive information, typically usernames, passwords, credit card numbers, bank account information or other important data to utilize or sell. The phishing scammer will masquerade as a reputable source, an attempt to lure you to trick you into biting their scam (yes, just how a fisherman uses a lure to catch fish).

Phishing, a long-standing tactic in the fraudster’s playbook, has received a significant boost from A.I. In the realm of crypto fraud, A.I.-powered tools are amplifying the impact and reach of phishing scams targeting cryptocurrency investors.

A.I.-driven phishing attacks can generate highly personalized and convincing emails or messages. These systems analyze vast amounts of data from social media and other online sources to craft messages that are tailored to each potential victim. For instance, an A.I. might create a phishing email that references recent cryptocurrency purchases or discussions the target has had online, making the scam far more believable.

Furthermore, A.I. can automate the process of sending out these phishing attempts, allowing fraudsters to target a much larger number of potential victims than would be impossible manually. This increased scale significantly boosts the chances of successful crypto fraud.

C. Deepfake Technology

Deepfake technology, which uses A.I. to create highly realistic but fabricated video and audio content, has emerged as a powerful tool in the crypto fraud arsenal. Fraudsters are using deepfakes to impersonate trusted figures in the cryptocurrency world, creating convincing but false endorsements or announcements.

For example, a deepfake video might show a well-known cryptocurrency expert endorsing a new, fraudulent coin. In August 2024, the NYT had a report on this deepfake involving Elon Musk. The realistic nature of these deepfakes can fool even savvy investors, leading them to make decisions based on false information. This technology is particularly dangerous in the fast-moving world of cryptocurrency, where quick decisions based on breaking news can have significant financial implications.

A.I.’s ability to process and generate human-like text has revolutionized social engineering tactics in crypto fraud. A.I.-powered chatbots and language models can craft highly convincing narratives and engage in real-time conversations, manipulating victims more effectively than ever before.

These A.I. systems can be trained on vast datasets of human conversations, allowing them to mimic natural language patterns and adapt their communication style to each individual target. For instance, an A.I. engine might engage a potential victim in a seemingly innocuous conversation about cryptocurrency investing, gradually building trust before introducing a fraudulent investment opportunity.

Moreover, A.I. can analyze a target’s responses in real-time, adjusting its approach based on the victim’s reactions. This dynamic interaction makes it incredibly difficult for targets to distinguish between genuine communication and A.I.-driven fraud attempts.

E. Exploiting Crypto Network Vulnerabilities

The insane ability for A.I. to not just make calculations, but reason and learn boggles the mind. In a recent test, A.I. successfully completed an IQ test to reveal an IQ equivalent to 120 points in a human being. It’s not quite as smart as me, but it won’t take long before it makes my brain seem like it belongs to a retarded mole. What worries me is intelligence without morals or character.

IQ of A.I. models is increasing:

Source: https://www.maximumtruth.org/p/massive-breakthrough-in-ai-intelligence

“We must remember that intelligence is not enough. Intelligence plus character-that is the goal of true education. The complete education gives one not only power of concentration, but worthy objectives upon which to concentrate. ” – Martin Luther King Jr.

But what if A.I. is set to concentrate on unworthy objectives? One of the ways it can do that is by the A.I. ‘super brain’ exploiting cryptocurrency networks. There are a multitude of ways this can be done, and the detail of which will need to come in future posts, especially since some of them are not obvious to most of us.

Here is a Brief Synopsis of Ways A.I. Can Exploit Network Vulnerabilities to Commit Crypto Fraud

E1: 51% Attack

If a single entity controls more than 51% of the computing power on a blockchain, then it could potentially alter the blockchain’s transaction history.

A.I models could search for vulnerable networks and exploit them by acquiring enough computational resources to rewrite transaction histories, double-spend coins, or prevent new transactions from being confirmed, disrupting trust in the network and allowing the A.I.’s operators to steal funds unnoticed. Sound impossible? It’s happened before. A.I. will make it easier for this type of crypto fraud perpetrator to find vulnerable networks, and may make some networks that were not vulnerable before A.I., vulnerable in the future.

E2. Sybil Attack

A Sybil attack involves creating multiple fake identities to dominate the network and manipulate consensus mechanisms. It seems reasonable to predict that A.I.-run sybil attacks will become more effective and sophisticated as A.I. develops.

With access to enough resources, A.I. could overwhelm the network with fake nodes, disrupt transactions or gain enough influence to manipulate voting or consensus protocols – giving the A.I. control over the network’s decision-making process.

E3. Smart Contract Vulnerabilities

Smart contracts on blockchains like Ethereum can contain coding errors or design flaws that can be exploited. A.I. can quickly scan the network for smart contracts with exploitable vulnerabilities, such as reentrancy attacks, which would allow A.I. to repeatedly withdraw funds from a contract before it registers that the balance has changed.

E4. Front-Running Attacks

When I worked in hedge funds, we would seek out intelligence to front-run other players, and we would be constantly on guard against anyone catching onto our strategies and front running us.

To “front-run” is to get ahead of another player, anticipating their trades to make a quick buck. In the crypto world, information about pending transactions is often visible in the mempool before they’re confirmed. Malicious actors can place their transactions with higher fees to get priority. A.I. has the potential to detect large trades or arbitrage opportunities and place its own higher-fee transactions before the victim’s, profiting from price shifts or manipulating markets.

E5. Private Key Theft

Cryptographic private keys are essential for accessing and transferring funds from a crypto wallet. Whoever has the private keys, owns the crypto. So if A.I. can get your private keys, your crypto is about to follow. One way A.I. could get your private keys is by using A.I.-driven social engineering techniques or malware. It could trick users into revealing their private keys or seed phrases, granting the A.I. crypto fraudster access to the victim’s wallets and enabling the A.I. to steal their funds.

E6. Phishing & Fake Exchanges

We’ve already talked about phishing, and how it involves tricking users into visiting fake websites or entering sensitive data on fraudulent platforms. A.I. can do this faster, more attractively and on a grander scale than mere mortals. The A.I. engine can create highly convincing A.I.-generated phishing emails and websites that mimic legitimate crypto exchanges or wallets, tricking users into depositing funds or giving up their credentials.

E7. Dusting Attacks

You’ve probably heard of or seen gold dust? Well, a dusting attack sends very small amounts of cryptocurrency (“dust”) to multiple wallets to deanonymize the owners by linking wallets together. By using A.I. to automate dusting across many wallets, the A.I. engine could identify high-value targets and use the data to mount further social engineering attacks or blackmail campaigns.

E8. Oracle Manipulation

Many decentralized finance (DeFi) platforms rely on oracles to feed real-world data (like asset prices) into smart contracts.

Oracle manipulation by AI to commit crypto fraud

If oracles are compromised, the data can be manipulated. Potentially, A.I. could attack vulnerable oracles to feed false data into smart contracts, triggering false liquidations, price manipulations, or fraudulent payouts in decentralized finance protocols. This would cause all sorts of havoc, with teams of people trying to work out what’s happened. But the crypto fraud perpetrators would be long gone watching the news from their beach chairs.

E9. Flash Loan Exploits

Flash loans are a crazy concept that can be hard to get your head around. A flash loan allows someone to borrow vast amounts of cryptocurrency without collateral, just as long as the loan is repaid in the same transaction. Wild! The borrowing and repayment happen really really close together. In theory, A.I. could manipulate market prices or exploit poorly designed DeFi (Decentralized Finance) protocols by combining flash loans with other exploits (e.g., oracle manipulation or reentrancy), profiting from the loan before the market corrects itself.

E10. Double-Spending on Low-Hash Networks

This crypto fraud is a bit like the coin going into the vending machine with a string tied to it, so it can be pulled out again (not sure if this has ever worked in anything but the movies, but the concept holds true).

So double-spending occurs when the same coin is used in two transactions, made possible by exploiting lower-hash-rate networks. Potentially, A.I. could target smaller cryptocurrencies with lower network security, initiating two conflicting transactions and confirming one while reversing or invalidating the other, effectively allowing the A.I. model to spend the same coins twice.

E11. Routing Attacks

In routing attacks, crypto fraudsters intercept blockchain data as it flows across the network, delaying or altering transaction data. If A.I. could manipulate or delay blockchain transactions through traffic interception, thereby causing transaction disruptions, it may exploit arbitrage opportunities due to time lags between different parts of the network.

E12. Cross-Chain Bridge Exploits

Cross-chain bridges are a common and well-developed area of crypto fraud. Bridges are a cool idea – allowing for cryptocurrency transfers between different blockchains – but they can be a serious weak point if not designed securely. A.I. could be trained to find and exploit bugs in the code of cross-chain bridges. Once found, the A.I.’s controller could manipulate the transfer process, potentially duplicating tokens or siphoning funds during the transfer between chains.

E13. Reentrancy Attacks

Reentrancy attacks occur when a smart contract allows an attacker to repeatedly call a function before the initial function has finished executing, exploiting the contract’s (incomplete) logic. A.I. could find these vulnerabilities, test them and exploit weak code. A.I. would look for DeFi smart contracts that are vulnerable to reentrancy and exploit them to withdraw funds multiple times in a single transaction. Sound far-fetched, well they’re happening. Here’s a list.

E14. Fake Wallets and Malware Distribution

This is a subset of a phishing attack. A fake wallet application (phone app) or malicious extensions can be created to compromise the user’s private keys or transactions. A.I. could lend its secret source to this type of crypto fraud by creating a legitimate-looking wallet app or browser extension, at scale, that records users’ private keys or redirects transactions to its own wallet, stealing their funds undetected. At Rexxfield, we come across this type of scam a lot, more often websites but fake apps happen too. To stay safe, it helps if you never download an app that isn’t through the official app store, but this isn’t foolproof. Better just to NEVER share your private keys or seed phrase.

E15. Governance Exploits in DAOs

Remember when DAO’s were all the craze? Maybe not – but I created a whole bunch thinking these were a cheaper and cooler option to companies. DAO’s, or Decentralized Autonomous Organizations are on-chain entities governed by voting mechanisms. You can use them (for some things) as an entity in place of a trust or company. They have programmed governance rules, so there’s very little admin or bureaucracy. But if a single entity or a colluding group gains most voting power, they can control decisions. A.I. may be able to accumulate voting tokens through manipulation, then propose or vote for fraudulent governance changes that siphon funds or lock up users’ assets.

The A.I. Advantage in Crypto Fraud

Most of these scams are alive and well now, and so not new. So what is it that makes the introduction of A.I. into crypto fraud so scary? It’s the A.I. Advantage: A.I. is uniquely setup to make these type of crypto fraud attacks more likely and more successful due to its inerrant strengths:

Automation and Scale: A.I. can rapidly create and manage thousands of fake identities, overwhelming a network without the manual effort needed in traditional attacks.

Pattern Recognition and Adaptability: A.I. can recognize network defenses and adapt its behavior to avoid detection, making its fake nodes more difficult to spot.

Resource Efficiency: A.I. can optimize how it uses resources, targeting the most vulnerable parts of the network to maximize disruption with minimal effort.

Enhanced Social Engineering: A.I. can generate convincing fake identities and behaviors, mimicking real users to manipulate social or governance aspects of the network.

Anonymity and Identity Management: A.I. can seamlessly manage and synchronize multiple fake identities, making them appear legitimate and diverse to avoid detection.

Network Analysis and Targeting: A.I. can analyze a network’s structure in real-time, identifying weaknesses and strategically launching attacks in the most effective places.

In future posts we’ll dive into these in more detail and provide some examples and case studies.

Have you become a victim of a crypto fraud?

If you have become the victim of one of these or another type of crypto fraud, then you should reach out to us here at Rexxfield. We have more than 16 years of experience. We have teams of fully qualified crypto blockchain tracers, social engineers, OSINT experts, developers and even a white-hat hacker. Time is of the essence so that data does not perish before we can harvest it. Reach out at https://rexxfield.com/contact/