SCAM: Real-World Typographic Robustness Evaluation for Multimodal Models
Date: 2025-04
Affected: CLIP, SigLIP, downstream VLMs
Attack vector: adversarial-input
Category: research
Severity: Medium

Westerhoff et al. release SCAM, the largest dataset of 1,162 real-world typographic attack images across hundreds of object categories, benchmarking CLIP, SigLIP, and downstream VLMs.


Mitigations:

Architectural layers (MAESTRO):