SECSEC-001 — Model Security Vulnerabilities
Multimodal AI Systems Create Exploitable Security Vulnerabilities Across Input Channels
3/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Multimodal AI models introduce varied attack surfaces across text, image, and audio inputs, with adversaries targeting whichever modality is least robust to mount jailbreaks or data poisoning. Boards deploying such systems face compounded security exposure and must mandate cross-modal robustness testing within AI governance frameworks.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) ↗https://airisk.mit.edu/
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