SECSEC-001 — Model Security Vulnerabilities
Prompt Injection Hijacks LLM Task Goals
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Attackers redirect large language models from their intended function by injecting override instructions into user inputs. Firms deploying LLM-based workflows face material risk of unauthorised task execution and loss of operational control.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024) ↗https://airisk.mit.edu/
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