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News // 16.06.2025 // 2 min read // recoveris-team

AI-Powered Social Engineering: The New Frontier of Digital Asset Theft

AI-powered deepfakes are driving 40% of high-value crypto fraud, with $6.7B stolen as attackers shift from exploiting code to exploiting human trust through sophisticated social engineering.

The convergence of psychological manipulation and advanced AI is fundamentally reshaping digital asset theft, creating attack vectors that traditional security frameworks struggle to address. As blockchain infrastructure has hardened, attackers have pivoted to exploiting the human element with unprecedented sophistication.

The Scale of the Problem

The numbers paint a stark picture of this evolution:

⚔️ $6.7 billion combined losses: CertiK reports $2.1 billion stolen in 2025’s first five months, while Bitget documents $4.6 billion lost to scams in 2024 – with AI deepfakes driving 40% of high-value fraud cases.

🚨 Attack vector evolution: “Previously, the weakest points were smart contracts and the blockchain code itself. Now, attackers feel like the weakest points come from human behavior,” notes CertiK founder Ronghui Gu – explaining why wallet compromises and social engineering now dominate over technical exploits.

🚨 Deepfake sophistication surge: Fraudulent impersonations of executives, celebrities, and government officials are bypassing traditional detection methods, with scammers using AI-generated video calls to manipulate victims into revealing private keys and wallet access.

The Intelligence Response

We’re seeing in our forensic work that while blockchain infrastructure has hardened significantly, attackers are weaponizing AI to create convincing personas and scenarios that traditional security awareness can’t address. Our investigative methodologies now integrate behavioral analysis with technical tracing to identify these hybrid attack patterns.

The scale demands a response that matches the sophistication: combining advanced blockchain intelligence with psychological profiling to detect and trace these evolved fraud schemes before assets disappear into mixing networks. The traditional “don’t click suspicious links” approach no longer suffices.


Sources:

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