2026
Multi-Faceted Attack: Exposing Cross-Model Vulnerabilities in Defense-Equipped Vision-Language Models
AAAI 2026technical
The growing misuse of Vision-Language Models (VLMs) has led providers to deploy multiple safeguards—alignment tuning, system prompt, and content moderation. Yet the real-world robustness of these defenses against adversarial attack remains underexplored. We introduce Multi-Faceted Attack (MFA), a fr