An Efficient and Effective Agentic Group Shilling Attack on Recommender Systems

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arXiv:2609.09551v1 Announce Type: new Abstract: Recommender systems have become core infrastructure for modern online platforms, personalizing content at scale and strongly influencing what users see, click on, and purchase. However, this dependence on user interaction also exposes them to shilling attacks, where malicious actors can inject fake profiles to distort item rankings and control visibility. Existing attacks often rely on target-specific fine-tuning or fixed profile templates, making