A newly proposed framework argues that AI penetration testing must move beyond conventional infrastructure compromise and assess whether an adversary can make an AI-enabled system act against its intended operational purpose. Traditional penetration testing typically measures compromise through outcomes such as unauthorized access, privilege escalation, data theft, service disruption, or persistence. Those outcomes remain critical […]

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Mayura Kathir

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