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Data Poisoning and Backdoors: Corrupting the Model Before It Ships

You do not need to touch the deployed model if you can touch what it learned from. Poisoning is a supply-chain attack on the training distribution, and small poison fractions have outsized, targeted effects. This threat lab covers the poisoning threat model, backdoor-trigger construction and the stealth/attack-success trade-off, the practical economics of poisoning web-scale corpora, dose-response of RAG and fine-tune poisoning, and detection with dataset provenance — each paired with a hardening. Grounded in the primary backdoor and web-scale-poisoning literature.