SECSEC-001 — Model Security Vulnerabilities
LLM Jailbreak Vulnerabilities Enable Malicious Outputs via Prompt Manipulation
4/5Sector: GovernmentGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models can be coerced into producing harmful outputs through prompt injection, role-play exploitation, adversarial prompting, and structural prompt transformation. Regulators and operators face material liability exposure where such vulnerabilities are not identified, documented, and mitigated 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 — A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy (Wang2025) ↗https://airisk.mit.edu/
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