

Interesting bit from the court docs of how they traced it to him:
Based on cryptocurrency tracing analysis performed by FBI personnel, I have learned the following, among other things: on or about November 12, 2025, and November 13, 2025, in a total of approximately three transactions, Wallet-0xAf6 sent a total of approximately $149,980 of cryptocurrency to particular cryptocurrency swapping service (“Swapping Service- 1”).2,3 Based on documents from Swapping Service-1, I have learned that shortly after those three transactions, Swapping Service-1 sent approximately $149,980 of cryptocurrency to a particular cryptocurrency payment processor (“Payment Processor-1”). Based on documents from Payment Processor-1, I have learned that the November 12 and 13, 2025 transactions were received by account in the name of “Michele Spagnuolo,” and that an Italian Government identification card was used to open the account at Payment Processor-1. A copy of that identification card, which I have reviewed, appears to be a government identification card for MICHELE SPAGNUOLO, a/k/a “AlphaRaccoon,” the defendant.
Seems like whatever swapping service he used is what got him as he probably assumed that they wouldn’t comply with law enforcement or have detailed records.





LLMs are just a tool, just like airplanes or hammers. An airplane is very expensive, but better at going really far distances than humans can on foot. A hammer is cheaper than a human, but by itself is useless unless operated properly. Despite the tone of the outputs, LLMs should not be authoritative and human judgement shouldn’t be replaced with them.
Just on the security side of coding, highly skilled security engineers at Mozilla were able to use Claude Mythos to identify and address many issues to make Firefox more secure. Some if these issues were introduced over 10 years ago, and a human could have identified and fixed them but human speed of reading and finding will always be a bottleneck. Having highly skilled humans offload the slow task to go through the codebase and raise issues, allowed them to find and understand the nuanced problem, and work on a fix. The key here is giving the people with the skills the ability be enhanced with LLMs, not replace them with one.