BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning
Prompt learning is a new machine learning paradigm that has attracted ample attention due to its simplicity and proven efficacy. Despite its growing adoption, the security vulnerabilities associated with this paradigm remain underexplored. In this work, we take the first step to propose BadBone, a stealthy and adaptive backdoor attack against prompt learning using bi-level optimization. Instead of backdooring the prompt learning process, we aim to compromise a backbone model such that only target downstream tasks employing prompt learning inherit the backdoor vulnerability. Extensive experiments on three different models and three datasets from various domains show that our targeted/untar...
| Authors | Ziqing Yang, Rui Wen, Xinlei He et al. |
|---|---|
| Primary category | cs.CR |
| Published | 29 May 2026 |
| Last updated at source | 29 May 2026 |
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