When ChatGPT Meets Vulnerability Management: The Good, the Bad, and the Ugly

McClanahan, Kylie; Elder, Sky; Uwibambe, Marie Louise; Liu, Yaling; Heng, Rithyka; Li, Qinghua

doi:10.1109/icnc59896.2024.10555953

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2024

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Cited by 3 publications

References 19 publications

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Development Generative AI for Cybersecurity: Evaluating Script Generation and Attack Classification in Penetration Testing

Elashmawi,

Osman,

Osama

et al. 2024

Lecture Notes in Networks and Systems

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Development Generative AI for Cybersecurity: Evaluating Script Generation and Attack Classification in Penetration Testing

Elashmawi,

Osman,

Osama

et al. 2024

Lecture Notes in Networks and Systems

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Towards Automatically Matching Security Advisories to CPEs: String Similarity-based Vendor Matching

McClanahan,

2024

2024 International Conference on Computing, Networking and Communications (ICNC)

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A Comprehensive Review and Assessment of Cybersecurity Vulnerability Detection Methodologies

Bennouk,

Ait Aali,

El Bouzekri El Idrissi

et al. 2024

JCP

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The number of new vulnerabilities continues to rise significantly each year. Simultaneously, vulnerability databases have challenges in promptly sharing new security events with enough information to improve protections against emerging cyberattack vectors and possible exploits. In this context, several organizations adopt strategies to protect their data, technologies, and infrastructures from cyberattacks by implementing anticipatory and proactive approaches to their system security activities. To this end, vulnerability management systems play a crucial role in mitigating the impact of cyberattacks by identifying potential vulnerabilities within an organization and alerting cyber teams. However, the effectiveness of these systems, which employ multiple methods and techniques to identify weaknesses, relies heavily on the accuracy of published security events. For this reason, we introduce a discussion concerning existing vulnerability detection methods through an in-depth literature study of several research papers. Based on the results, this paper points out some issues related to vulnerability databases handling that impact the effectiveness of certain vulnerability identification methods. Furthermore, after summarizing the existing methodologies, this study classifies them into four approaches and discusses the challenges, findings, and potential research directions.

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When ChatGPT Meets Vulnerability Management: The Good, the Bad, and the Ugly

Cited by 3 publications

References 19 publications

Development Generative AI for Cybersecurity: Evaluating Script Generation and Attack Classification in Penetration Testing

Development Generative AI for Cybersecurity: Evaluating Script Generation and Attack Classification in Penetration Testing

Towards Automatically Matching Security Advisories to CPEs: String Similarity-based Vendor Matching

A Comprehensive Review and Assessment of Cybersecurity Vulnerability Detection Methodologies

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