AVISE provides a new framework and automated SET that identifies jailbreak vulnerabilities in language models with 92% accuracy, finding all nine tested models vulnerable to an augmented Red Queen attack.
Exploring Research and Tools in AI Security: A Systematic Mapping Study
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Empirical evaluation shows that code generated by all seven tested LLMs contains vulnerabilities, the majority of critical or high severity.
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AVISE: Framework for Evaluating the Security of AI Systems
AVISE provides a new framework and automated SET that identifies jailbreak vulnerabilities in language models with 92% accuracy, finding all nine tested models vulnerable to an augmented Red Queen attack.
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Security of LLM-generated Code: A Comparative Analysis
Empirical evaluation shows that code generated by all seven tested LLMs contains vulnerabilities, the majority of critical or high severity.