Analysis · curated 25 Sep 2026
What Is LLM Poisoning? Definition & Examples
First reported nhimg.org
Coverage timeline
Single-source analysis — first reported, latest, and curated coincide.
Why it matters
LLM poisoning attacks the model lifecycle before inference, requiring defenders to treat dataset provenance as a security control distinct from prompt-injection defenses.
A glossary entry from NHI Mgmt Group defines LLM poisoning as the deliberate corruption of a model's training, fine-tuning, retrieval, or evaluation data to insert backdoors, degrade safety, or bias output. The piece describes examples such as seeded malicious code repositories, altered instruction-tuning corpora with hidden triggers, and polluted retrieval datasets, and references NIST AI 600-1 and MITRE ATLAS.