Andrew Aleksandrov

A Hyperliquid whale lost $20M+ after a private-key compromise. Using AMLBot’s Tracer, we mapped the visible on-chain flow: ~$17M moved from the trader’s wallet to Arbitrum, was bridged (incl. via deBridge) and converted to DAI. Another ~$3.1M in MSYRUPUSDP was taken from the Plasma Syrup

The hacker got hacked. But was it real? Dive into our on-chain breakdown of the UXLINK exploit and its tangled money trail.

The cryptocurrency adoption has brought opportunities alongside risks. As digital asset markets mature, criminals have developed complex attack vectors to steal funds from unsuspecting victims. In this environment, crypto recovery service providers like AMLBot have emerged as critical allies for victims seeking to recover their stolen assets through professional blockchain

Traditional AML tools struggle to keep pace with the scale and speed of illicit activity in crypto. In this exploratory study, the AMLBot Team investigates whether behavior-based machine learning can spot suspicious entities before they appear on blacklists and how explainability tools like SHAP make this process transparent. We

Download the Full Report Tether’s USDT stablecoin is usually perceived as a compliance-friendly instrument in the crypto industry, with the company using its ability to freeze suspicious wallets as per law enforcement requests.  However, AMLBot’s Forensics Team finds a critical vulnerability: a significant lag between the initiation

What Happened?  Earlier this year, a Czech company fell victim to an address poisoning scam scheme, resulting in the loss of $50,000+ in USDT. The scam exploited the company's operational routine, targeting its treasury wallet and leveraging address similarities to divert funds to a malicious actor'