SECSEC-001 — Model Security Vulnerabilities
LLMs Enabling Personalised Social-Engineering and Impersonation Attacks
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models can generate convincing, targeted impersonation content to manipulate specific individuals for financial or security-compromising ends. Boards must treat LLM-assisted social engineering as a material fraud and cyber risk requiring updated controls and staff awareness programmes.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024) ↗https://airisk.mit.edu/
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