SECSEC-001 — Model Security Vulnerabilities
Model Extraction Attack Exposes Proprietary AI Architecture and Parameters
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Adversaries systematically query deployed AI systems to reconstruct proprietary model architecture, parameters, and hyperparameters without authorisation. Organisations face loss of competitive advantage, potential regulatory scrutiny over data governance, and liability where extracted models encode sensitive training data.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data (Marchal2024) ↗https://airisk.mit.edu/
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