AI Security
Training Data Poisoning
Injecting malicious data into a model's training set to corrupt its behavior.
Training data poisoning occurs when attackers manipulate training data to introduce backdoors or bias the model. A poisoned model may behave normally on benign inputs but trigger malicious behavior on specific inputs. Critical for fine-tuning and RAG pipelines.