Unveiling Security Vulnerabilities in Generative AI

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Author(s): Geeta Sharma (Lovely Professional University, India), Pooja Chopra (Lovely Professional University, India)and Souravdeep Singh (Lovely Professional University, India)
Copyright: 2025
Pages: 20
Source title: Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices
Source Author(s)/Editor(s): Loveleen Gaur (University of South Pacific, Fiji & Taylor's University, Malaysia)
DOI: 10.4018/979-8-3693-3691-5.ch012

Keywords: Artificial Intelligence / Business & Management / Cyber Ethics / Engineering Science Reference

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Abstract

Generative Artificial Intelligence (GenAI) has sparked significant transformations across various sectors, including machine learning, healthcare, business, and entertainment, due to its remarkable capability to generate realistic data. Popular GenAI tools like DALL-E, RunwayML, DeepArt, and GANPaint have become increasingly prevalent in everyday use. However, these advancements also present new avenues for exploitation by malicious entities. This comprehensive survey meticulously examines the privacy and security challenges inherent in GenAI. It provides a thorough overview of the security vulnerabilities associated with GenAI and discusses potential malicious applications in cybercrimes, such as automated hacking, phishing attacks, social engineering tactics, cryptographic manipulation, creation of attack payloads, and malware development.

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