# dataset-poisoning
4 articlestagged with “dataset-poisoning”
Poisoning Fine-Tuning Datasets
Techniques for inserting backdoor triggers into fine-tuning datasets, clean-label poisoning that evades content filters, and scaling attacks across dataset sizes -- how adversarial training data compromises model behavior.
Fine-Tuning Security
Comprehensive overview of how fine-tuning can compromise model safety -- attack taxonomy covering dataset poisoning, safety degradation, backdoor insertion, and reward hacking in the era of widely available fine-tuning APIs.
Dataset Poisoning at Scale
Techniques for poisoning web-scale datasets including Common Crawl and The Pile, data contribution attacks, SEO-style poisoning, calculating required poisoning rates, and real-world incidents.
Lab: Poisoning a Training Dataset
Hands-on lab demonstrating dataset poisoning and fine-tuning to show behavioral change, with step-by-step Python code, backdoor trigger measurement, and troubleshooting guidance.