SECSEC-001 — Model Security Vulnerabilities
LLM Model Attacks: Exploitation of Vulnerabilities for Data Theft and Manipulation
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models are actively targeted by adversarial attacks designed to extract sensitive data or induce harmful outputs. Boards face material liability exposure where deployed LLMs lack formal adversarial testing and documented mitigation controls.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024) ↗https://airisk.mit.edu/
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