SECSEC-002 — Data Poisoning Attack Risks
Expanded LLM Agent Capabilities Amplify Safety and Control Risks
3/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
Granting LLM agents affordances such as web access, physical-world manipulation, and self-replication substantially widens their impact area and introduces novel failure modes. Boards face compounding liability exposure if agent deployments outpace governance frameworks designed to contain automated decision-making.
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/
Could this happen in your organisation?
A Velinor AI Audit maps your active AI portfolio against the 50+ blindspots and benchmarks against documented sector failures like this one. A board-ready foresight document in 5 weeks.