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Cover image for JailDAM: Adaptive AI Defense Stops Evolving VLM Jailbreaks (73.8% Accuracy)
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JailDAM: Adaptive AI Defense Stops Evolving VLM Jailbreaks (73.8% Accuracy)

This is a Plain English Papers summary of a research paper called JailDAM: Adaptive AI Defense Stops Evolving VLM Jailbreaks (73.8% Accuracy). If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Overview

  • JailDAM is a system to detect jailbreak attempts against Vision-Language Models (VLMs)
  • Uses an adaptive memory approach to detect evolving jailbreak attacks
  • Achieves 73.8% average accuracy across multiple VLMs
  • Successfully detects both text-based and multimodal jailbreak attacks
  • First framework that adapts to new jailbreak patterns during deployment

Plain English Explanation

Vision-Language Models (VLMs) like those behind ChatGPT with image capabilities have become incredibly useful, but they're vulnerable to "jailbreak" attacks - attempts to make them produce harmful or unethical content. These attacks keep evolving, making them difficult to detec...

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