AI Insights Blog

How a Handful of Lines Can Hijack Any LLM — The Poisoning Threat You’re Ignoring

Imagine shipping a new assistant to your customers that performs perfectly on every validation test — until, one day, a user types a seemingly meaningless phrase and the assistant issues dangerous, incorrect, or malicious instructions. You search the logs; nothing obvious.

How a Small Number of Samples Can Poison LLMs of Any Size

In recent years, the tremendous growth of large language models (LLMs) has transformed artificial intelligence — from generative chatbots to code assistants and domain-specific agents. With model sizes soaring into billions of parameters and training datasets spanning billions of tokens.