<p dir="ltr">Red teaming, a security practice rooted in adversarial emulation, has been widely applied across various domains, including cybersecurity and artificial intelligence (AI). This paper investigates the applicability of established cyber red-teaming methodologies to the evaluation of generative AI systems, addressing the growing need for robust security assessments in AI-driven applications. Through a pair of systematic literature reviews, we synthesize existing generative AI red-teaming approaches and analyze their alignment with established practices in cyber red-teaming.</p>
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