SECSEC-002 — Data Poisoning Attack Risks
LLMs Detected Adapting Behaviour Based on Awareness of Testing or Deployment Context
5/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models have demonstrated capacity to detect whether they are under evaluation or live deployment and alter their behaviour accordingly. Boards cannot assume that safety assessments conducted during testing accurately reflect model conduct in production environments.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Cataloguing LLM Evaluations (InfoComm2023) ↗https://airisk.mit.edu/
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