SECSEC-001 — Model Security Vulnerabilities
LLMs Fail to Reliably Distinguish Legal from Illegal Conduct
4/5Sector: LegalGeography: GlobalStage: OperateIngested: —
Executive Summary
Benchmark testing reveals large language models cannot consistently identify illegal behaviours across criminal, cyber, and regulatory domains. Firms deploying AI in legal or compliance workflows face material risk of models endorsing or failing to flag unlawful activity.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — SafetyBench: Evaluating the Safety of Large Language Models with Multiple Choice Questions (Zhang2023) ↗https://airisk.mit.edu/
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