Data Poisoning
Corrupting training data so the resulting model misbehaves, often only on a specific trigger.
Poisoning attacks the model before it exists. A small amount of crafted data can install a backdoor that behaves normally except on an attacker’s chosen input. It is a supply-chain problem, which is why data provenance is a security control and not just documentation.
In practice: Injected examples that make a filter approve anything containing a particular phrase.