Next-Generation Vapt

Combining Osint and Ai-ML for Enhanced Vulnerability Assessment and Penetration Testing
Erscheinungsjahr 2026
ISBN: 978-0-443-45584-1
Verlag: Elsevier Science

Buch, Englisch, 250 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 449 g

Next-Generation VAPT: Combining OSINT and AI/ML for Enhanced Vulnerability Assessment and Penetration Testing empowers information security threat intelligence with the fusion of Open-Source Intelligence Tools (OSINT) and Artificial Intelligence and Machine Learning (AI/ML) to identify and detect vulnerabilities more efficiently and effectively. The book highlights the concept of OSINT for gathering actionable threat intelligence and AI/ML for automating threat detection, which ultimately enhances VAPT processes. The authors explain concepts for assessing the security of networks, wireless networks, performing VAPT on mobile devices, and conducting red teaming, which helps end users deal with upcoming threats at an early stage.

It focuses on using machine intelligence for developing and validating exploits and AI-driven exploitation testing, which helps field experts discover and exploit vulnerabilities more quickly and accurately. Readers will find essential ethical and legal considerations in AI/ML and OSINT-based VAPT, ensuring responsible and compliant testing practices, accountability, and transparency. Industry Case Studies with solutions and safeguards are an integral part of the books applied approach.

Autoren/Hrsg.

Iyer, Sailesh

Maleh, Yassine

Kshetri, Naresh

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Kryptographie, Datenverschlüsselung
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie

Inhaltsverzeichnis

1. Introduction to Next-Gen VAPT
2. Fundamentals of OSINT for VAPT
3. AI-ML concepts and methodology for VAPT
4. Integrating OSINT with VAPT: A new paradigm
5. AI-ML powered vulnerability scanning and management
6. Machine learning for predictive vulnerability assessment
7. OSINT based Threat Intelligence for VAPT
8. Advanced penetration testing with AI-ML driven tools
9. AI-ML assisted exploit development and validation
10. OSINT-Based social engineering attacks
11. AI-ML and OSINT based Web Application Scanning and Testing
12. Next generation network scanning with AI-ML and OSINT
13. AI-ML and OSINT based Wireless Network Security Assessment
14. Mobile VAPT using AI-ML and OSINT
15. AI-ML driven Incident Response and Threat Hunting
16. OSINT and AI-ML for red teaming and adversarial testing
17. Ethics and Legal Considerations in AI-ML and OSINT based VAPT
18. Future of VAPT: Emerging Trends and Innovations

Über Autor(innen)

Kshetri, Naresh
Dr Naresh Kshetri: Dr. Naresh Kshetri is currently a full-time Faculty (Cybersecurity) at College of Computing, Rochester Institute of Technology. He was an Assistant Professor (tenure-track) of Cybersecurity / CS at the Emporia State University apart from Research Fellow at Cybersecurity and Research Outreach Center. He was an Assistant Professor of Cybersecurity and Adjunct Instructor of Computer Science at Lindenwood University. Dr. Kshetri completed his PhD (Computer Science with concentration in Cybersecurity) from University of Missouri – St. Louis, graduated with an MS (Cybersecurity) from Webster University, and also earned an MCA (Computer Applications) degree from University of Allahabad. With more than ten years of experience and research interests in Cybersecurity, Blockchain technology, he has published in various journals, conferences, and book chapters. His research is funded by the University of Missouri – St. Louis, the Lindenwood University, and the Emporia State University. Dr. Naresh has taught various Cybersecurity and CS courses at both the undergraduate and graduate levels.

Maleh, Yassine
Prof. Yassine Maleh is a cybersecurity professor and practitioner with industry and academic experience. He is a Ph.D. degree in Computer Sciences. Since 2019, He working as a professor of cybersecurity at Sultan Moulay Slimane University, Morocco. He worked for the National Port agency (ANP) in Morocco as a Senior Security Analyst from 2012 to 2019. He is a senior member of IEEE, a member of the International Association of Engineers and the Machine Intelligence Research Labs. Dr. Maleh has made contributions in information security and privacy, Internet of Things security, and wireless and constrained network security. His research interests include information security and privacy, Internet of Things, networks security, information system and IT governance. He has published over 60 papers (book chapters, international journals, conferences/workshops), 10 edited books, and 3 authored books. He is the editor-in-chief of the International Journal of Smart Security Technologies. He serves as an associate editor for IEEE Access (2019 Impact Factor 4.098), the International Journal of Digital Crime and Forensics, and the International Journal of Information Security and Privacy. He was also a guest editor of a special issue on 'Recent Advances on Cyber Security and Privacy for Cloud-of-Things' of the International Journal of Digital Crime and Forensics, Volume 10, Issue 3, July-September 2019.

Iyer, Sailesh
Dr. Sailesh Iyer has a Ph.D. (Computer Science), pursuing Post Doc from University of Louisiana, Lafayette, USA, and currently serving as a Professor with Rai University, Ahmedabad. He has more than 23 years of experience in academics, industry and corporate training. He has been awarded a Research Excellence Award for 2021 by Rai University and an Honorary Adjunct Research Scientist at Neurolabs International under Dana Brain Health Institute, Iran, from August 2022 to August 2025. He is an editor for book projects with various international publishers. He has been invited as keynote speaker in various international conferences. He has excelled in corporate training, delivered more than 100 expert talks in various AICTE sponsored STTP’s, ATAL FDP’s, reputed universities, government organized workshops, orientations and refresher courses. His research interest areas include computer vision and image processing, cybersecurity, data mining and analytics, artificial intelligence, machine learning, and blockchain.