SECSEC-001 — Model Security Vulnerabilities
Language Models Weaponised for Identity Theft and Targeted Financial Fraud
5/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models can be fine-tuned on personal speech data to impersonate individuals, materially lowering the cost and scale of identity theft and fraud. Boards face heightened liability exposure as AI-enabled deception outpaces existing customer verification and anti-fraud controls.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Taxonomy of Risks posed by Language Models (Weidinger2022) ↗https://airisk.mit.edu/
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