Hidden Ads: Behavior Triggered Semantic Backdoors for Advertisement Injection in Vision Language Models
Vision-Language Models (VLMs) are increasingly deployed in consumer applications where users seek recommendations about products, dining, and services. We introduce Hidden Ads, a new class of backdoor attacks that exploit this recommendation-seeking behavior to inject unauthorized advertisements. Unlike traditional pattern-triggered backdoors that rely on artificial triggers such as pixel patches or special tokens, Hidden Ads activates on natural user behaviors: when users upload images containing semantic content of interest (e.g., food, cars, animals) and ask recommendation-seeking questions, the backdoored model provides correct, helpful answers while seamlessly appending attacker-spec...
| Authors | Duanyi Yao, Changyue Li, Zhicong Huang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 29 March 2026 |
| Last updated at source | 29 March 2026 |
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