How Defenders Can Make Social Engineering Less Profitable

Summary

The article argues that defenders can disrupt AI-scaled social-engineering campaigns by poisoning attacker reconnaissance data, using conversational honeypots to consume attackers’ compute, and feeding false telemetry to hinder campaign optimization.

Key points

• The article frames AI- and automation-enabled social engineering as a profit-driven operation that can scale campaigns across multiple channels.
• It cites published estimates that the cost of producing a convincing lure has fallen by 95 percent.
• It recommends seeding public information sources with defensive disinformation to undermine attacker reconnaissance and targeting.
• It proposes conversational honeypots or tarpits to occupy attackers’ automated agents and increase their compute costs.
• It advises feeding false success signals to attacker infrastructure from safely isolated environments, disrupting campaign optimization.
• It recommends measuring attacker time wasted, infrastructure rotation, and changes in campaign frequency or effectiveness.

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