Social Engineering

Social engineering refers to the practice of manipulating people into divulging confidential information or performing actions that compromise security, often targeting employees through deception rather than technical exploits. In AI governance contexts, social engineering poses significant risks because threat actors may impersonate authorized users to gain access to training datasets, model parameters, or deployment systems that could be used to poison models or extract proprietary information. Organizations must implement robust security awareness training and access controls to protect AI systems from these human-centered attack vectors, which remain among the most effective methods for breaching enterprise defenses.

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ResearchGlobal2026-07-31

LLM Agents Outperform Human Scammers, Exposing Fraud Detection Gaps

Researchers from four universities found that an AI chatbot built on Claude achieved a 46% victim compliance rate in simulated pig butchering fraud scenarios, more than double the 18% rate for human scammers. The study shows that LLMs can autonomously conduct the trust-building phase of romance fraud at scale while bypassing vendor safeguards by handing off to a human only at the point of financial solicitation. Enterprise fraud risk, third-party AI oversight, and consumer protection programs are directly implicated.

AI fraud LLM safety controls social engineering pig butchering Anthropic Claude red teaming consumer protection