A recent U.S. federal conviction underscores the ongoing risk of insider threats within advanced AI environments.
The case involved the theft of proprietary AI supercomputing data, undisclosed external affiliations, and prolonged misuse of internal access. Prosecutors framed the activity as trade secret theft and economic espionage, with sentencing still pending.
What detection strategies are most effective when insiders operate over long timeframes?
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