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From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMs
Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-source LLMs are increasingly adopted in high-impact applications such as finance, law, and healthcare, systematically investigating their security risks is becom
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