Case Studies On Ai-Assisted Cybercrime Involving Cryptocurrency And Blockchain
1. BitConnect Ponzi Scheme (United States, 2022)
Facts:
BitConnect promised investors huge returns using a “proprietary trading bot” that supposedly traded cryptocurrencies automatically. Investors were encouraged to lend their bitcoins to the platform in exchange for daily returns. In reality, the returns were paid from new investors’ funds rather than any real trading activity.
Legal Issues:
Wire fraud and securities fraud.
Misrepresentation of automated trading software (bot) as a legitimate profit-generating mechanism.
Outcome:
The founders and promoters were indicted for multi-billion-dollar fraud. Courts emphasized that the claimed trading bot was part of the fraudulent scheme.
Forensic Insight:
Blockchain transaction analysis was used to trace funds from new investors to pay earlier investors.
Investigators analyzed marketing materials and software claims to demonstrate that the “bot” did not exist.
2. EmpiresX Cryptocurrency Ponzi (United States, 2022)
Facts:
Operators promoted EmpiresX as a high-yield crypto investment platform using a proprietary trading bot. Investors were guaranteed profits, but funds were laundered through multiple crypto exchanges instead of being used for trading.
Legal Issues:
Conspiracy to commit wire fraud and money laundering.
Use of automation claims (trading bot) to lure investors.
Outcome:
Defendants faced indictments for raising over $100 million. Potential sentences included decades of imprisonment.
Forensic Insight:
Blockchain analytics traced fund flows through multiple wallets and foreign exchanges.
Forensic investigators evaluated the claimed trading bot to show it was non-functional.
3. Wash Trading Using Bots (United States, 2024)
Facts:
A group of crypto market makers used automated trading bots to inflate trading volumes for over 60 different cryptocurrency tokens. The bots performed repeated self-trades to mislead investors into believing there was high market activity.
Legal Issues:
Conspiracy to commit market manipulation and wire fraud.
Selling bot services to clients to artificially boost token metrics.
Outcome:
Over $25 million in cryptocurrency was seized. Some individuals pleaded guilty; market-maker firms faced fines and operational bans.
Forensic Insight:
Analysis of bot trading patterns (self-trades, repeated volume spikes) helped establish fraudulent activity.
Investigators correlated promotional materials and Telegram communications with on-chain bot activity.
4. Flash Loan / Smart Contract Exploit (United States, 2023)
Facts:
A security engineer exploited a decentralized exchange’s smart contract using a “flash loan” attack to manipulate contract fees and siphon approximately $9 million in cryptocurrency. Automated scripts executed the attack.
Legal Issues:
Wire fraud and unauthorized access to computer systems.
Use of automated scripts to exploit blockchain systems.
Outcome:
The individual was charged in federal court.
Forensic Insight:
Blockchain forensics traced the sequence of flash loan transactions and smart contract calls.
Investigators linked the attacker to the exploit by analyzing scripts and transaction metadata.
5. MEV (Maximum Extractable Value) Bot Fraud (United States, 2024)
Facts:
An individual marketed a MEV trading bot to investors, promising high returns from arbitrage opportunities on blockchain transactions. The bot was fraudulent, and investors lost significant funds.
Legal Issues:
Wire fraud through misrepresentation of an automated trading system.
Misleading investors about the bot’s existence and functionality.
Outcome:
The perpetrator pled guilty to wire fraud.
Forensic Insight:
Investigators reviewed investor communications and promotional materials.
Blockchain analysis traced investor deposits and withdrawals.
6. Arbitrage Bot Scam on Decentralized Exchanges (Global, Academic Documentation)
Facts:
Scammers promoted arbitrage bots on social media and YouTube, promising automated profit from crypto trades. Victims invested funds into smart contracts controlled by scammers. Estimated losses exceeded $15 million globally.
Legal Issues:
Fraud and theft of cryptocurrency via automated smart contracts.
Misrepresentation of AI or bot capabilities to investors.
Forensic Insight:
Forensic review of smart contract code revealed malicious fund-routing.
Wallet clustering and transaction tracing helped identify patterns of victim exploitation.
Social media promotion provided evidence linking perpetrators to victims.
Summary of Patterns Across Cases
Automation/Bots as Key Lures: Many schemes used “trading bots” or “arbitrage bots” as central to the scam.
Human Liability: Courts hold human actors responsible even if automation performs transactions or attacks.
Forensic Challenges: Blockchain pseudonymity requires careful tracing of wallet activity, smart contract analysis, and correlation with promotional evidence.
Legal Tools Used: Wire fraud, market manipulation, money laundering, and securities fraud statutes are commonly applied.
Emerging AI Implications: As AI-driven trading and automated strategies become more sophisticated, investigators must adapt to identify algorithmic intent and detect fraudulent bot behaviour.
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