arXiv: cs.AI preprintsInternational6 November 2026
ARMs: Adaptive Red-Teaming Agent against Multimodal Models with Plug-and-Play Attacks
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arXiv:2510.02677v2 Announce Type: replace Abstract: As vision-language models (VLMs) gain prominence, their multimodal interfaces also introduce new safety vulnerabilities, making the safety evaluation challenging and critical. Existing red-teaming efforts are either restricted to a narrow set of adversarial patterns or depend heavily on manual engineering, lacking scalable exploration of emerging real-world VLM vulnerabilities. To bridge this gap, we propose ARMs, an adaptive red-teaming agent that systematically conducts comprehensive risk assessments for VLMs. Given a target harmful behavio
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