SECSEC-001 — Model Security Vulnerabilities
Adversarial Attacks and Jailbreaking Vulnerabilities in Transport AI Systems
4/5Sector: TransportGeography: GlobalStage: OperateIngested: —
Executive Summary
Generative AI systems in transport are exposed to prompt injection, model poisoning, and backdoor attacks that bypass safety guardrails. Boards face liability and operational risk if adversarial exploits compromise autonomous or safety-critical transport functions.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024) ↗https://airisk.mit.edu/
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