A Framework for Automated and Visualized Penetration Testing

Authors

Corressponding author's email:

vanntth@hcmute.edu.vn

DOI:

https://doi.org/10.54644/jte.2026.1971

Keywords:

Penetration Testing, Security vulnerability, Automation, YAML workflow, Visualization

Abstract

The fragmentation of command-line tools in penetration testing creates inefficient scenarios, additional manual use, and inconsistent results, all of which can make workflows extremely problematic for complex security testing scenarios. This paper presents EzPentest, a framework designed to automate and visualize penetration testing through a single web interface. EzPentest's novelty is its YAML-based workflows, which support conditional logic, looping, and parallelization to create flexible and repeatable testing processes. Key to the use of EzPentest, is the parser engine which will convert the output of different tools into a standardized JSON output, this transformation standardizes vulnerability analysis and reporting. Along with its parser, EzPentest has a modular approach to allow the community to enhance and share the workflows that will connect various tools to create holistic penetration testing scenarios. In experiments with benchmark applications, as in DVWA and bWAPP, EzPentest achieves the highest detection rate of 89.39%. As demonstrated, EzPentest is more than simply an solution to provide scalable, accessible, and collaborative penetration testing, it is an open community resource that is particularly beneficial in educational institutions as it makes easier to understand an advanced area of software vulnerability assessing and security testing and allows small-to-medium enterprises to undertake initiatives to automate pentesting.

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Author Biographies

Thang Loi Nguyen, Ho Chi Minh City University of Technology and Engineering, Vietnam

Thang Loi Nguyen is currently an undergraduate student majoring in Information Security at the Faculty of Information Technology, Ho Chi Minh City University of Technology and Engineering (HCM-UTE) (formerly Ho Chi Minh City University of Technology and Education), Vietnam. His research interests include cybersecurity and penetration testing.

Email: 22162023@student.hcmute.edu.vn. ORCID:  https://orcid.org/0009-0004-5823-443X

Thanh Van Nguyen, Ho Chi Minh City University of Technology and Engineering, Vietnam

Thanh Van Nguyen graduated from university in Infomatics in 1998 at Hue University’s College of Education, Hue University,  and received a master's degree in  computer  science  in 2005 at Da Nang University. She is currently working at the Faculty of Information Technology, Ho Chi Minh City University of Technology and Engineering (HCM-UTE) (formerly Ho Chi Minh City University of Technology and Education). Her research interests include Information and Network security, machine learning and deep learning technologies.

Email: vanntth@hcmute.edu.vn. ORCID:  https://orcid.org/0009-0003-9686-606X

Luu Gia Bao Nguyen, Ho Chi Minh City University of Technology and Engineering, Vietnam

Luu Gia Bao Nguyen is currently an undergraduate student majoring in Information Security at the Faculty of Information Technology, Ho Chi Minh City University of Technology and Engineering (HCM-UTE) (formerly Ho Chi Minh City University of Technology and Education), Vietnam. His research interests include penetration testing and AI technology.

Email: 22162005@student.hcmute.edu.vn. ORCID:  https://orcid.org/0009-0009-9593-444X

References

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Published

28-02-2026

How to Cite

[1]
Thang Loi Nguyen, Thanh Van Nguyen, and Luu Gia Bao Nguyen, “A Framework for Automated and Visualized Penetration Testing”, JTE, vol. 21, no. 01, pp. 47–57, Feb. 2026.

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Research Article

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