SECSEC-001 — Model Security Vulnerabilities
Adversarial Attacks Expose Structural Weaknesses in Safety-Critical AI Models
3/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Complex AI models, particularly neural networks, are vulnerable to adversarial manipulation that can corrupt outputs or extract sensitive model information. Boards deploying AI in safety-critical contexts face elevated liability where standard software assurance frameworks are insufficient.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Sources of Risk of AI Systems (Steimers2022) ↗https://airisk.mit.edu/
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