SECSEC-001 — Model Security Vulnerabilities
LLM Training Data Exposed via Inference Attacks
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Adversaries can exploit inference attacks against large language models to reconstruct or deduce sensitive training data, including membership and property information. Organisations deploying LLMs on proprietary datasets face material data protection liability and regulatory exposure.
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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