Data poisoning

Data poisoning is an attack in which an adversary inserts manipulated or malicious examples into a model's training or retrieval data to degrade its performance or plant hidden behaviors.

Data poisoning sits in the Evaluation & safety part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.