SECSEC-002 — Data Poisoning Attack Risks
Autonomous LLM Agents Introduce Alignment and Safety Risks Beyond Current Controls
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
LLM agents operating with extended autonomy, tool access, and minimal human oversight create safety and alignment risks that remain poorly understood. Organisations deploying agentic AI face material governance gaps where existing oversight frameworks are inadequate.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024) ↗https://airisk.mit.edu/
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