One Polluted Page Is Enough: Evaluating Web Content Pollution in Generative Recommenders

FORGE benchmark reveals search-augmented LLMs vulnerable to fake product promotion via web content pollution

Researchers introduce FORGE, a benchmark measuring how often search-augmented LLMs recommend fake products when retrieval results are polluted with fabricated reviews or promotional pages. Across 12 commercial and open-weights models, a single polluted page causes fooled rates up to 27%, rising to 73.8% when all top-3 results are replaced. Notably, chain-of-thought reasoning does not mitigate the vulnerability and often generates spurious social proof to justify false recommendations. Three defenses tested—skepticism prompting, model-prior filtering, and cross-document consensus—each carry significant drawbacks.