DATDAT-002 — Data Privacy and Protection Failures
Prompt Leaking Exposes System Instructions in Large Language Models
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Adversarial inputs can extract confidential system prompts from large language models, revealing proprietary configuration and operational details. Organisations deploying AI systems face material risk of intellectual property loss and security compromise through this attack vector.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Safety Assessment of Chinese Large Language Models (Sun2023) ↗https://airisk.mit.edu/
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