International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 05 | May 2025
p-ISSN: 2395-0072
www.irjet.net
AUTOMATED PENETRATION TESTING TOOL Adarsh CS 1, Aslam T A,2 Fathima Firoz3, Sharafudeen K A 4 1 2 3 Student , Ilahia College Of Engineering and Technology, Muvattupuzha, Kerala, India 4 Assistant professor, Ilahia College Of Engineering and Technology, Muvattupuzha, Kerala, India
---------------------------------------------------------------------------***--------------------------------------------------------------------------Abstract—To tackle the increasing complexity of cyber threats, this study introduces an Automated Penetration Testing Tool aimed at making security evaluations easier through automation and AI analysis. Although traditional penetration testing methods are effective, they can be slow, require expert knowledge, and consume many resources, making them hard for organizations with limited security manpower to access. The proposed tool automates vulnerability scanning, integrates exploitation frameworks, and provides real-time security insights, enabling both cybersecurity professionals and beginners to conduct thorough assessments. Key Words: Automated Penetration Testing, Cybersecurity, AI-driven Security, Vulnerability Assessment, API Security, Container Security.
1. INTRODUCTION As virtual infrastructures become more complex and interdependent, cybersecurity has emerged as a top priority for organizations looking to safeguard their data and infrastructure. Penetration Testing (PT) is one of the essential proactive security activities that can be used to identify and remediate vulnerabilities. Traditional PT approaches tend to demand high technical expertise, time, and resources, making them unaffordable for smaller organizations or individuals with limited technical personnel. This is a major impediment to guaranteeing strong cybersecurity for all business sizes. Additionally, as cyber attacks become increasingly sophisticated, depending on periodic manual testing could expose organizations to risk between testing intervals. Automated penetration testing tools have surfaced as a possible alternative, providing ongoing security analysis with minimal human interaction. Yet, current automated tools can be inflexible and unadaptable compared to human testers, creating vulnerability detection and remediation gaps. To fill this gap, there is increasing demand for intelligent, user-friendly penetration testing tools that find a balance between automation and sophisticated threat analysis. These tools should offer full-spectrum vulnerability scanning, real-time risk assessment, and thorough remediation instructions without being too complicated for users with different levels of cybersecurity knowledge. By combining artificial
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intelligence, machine learning, and automation, these emerging generation penetration testing tools can enable organizations of various sizes to tighten their security position without needing excessive technical resources. In addition, with the emergence of cloud-native environments, containerized apps, and API-based architectures, contemporary organizations need security tools that go beyond legacy web application testing. The suggested Automated Penetration Testing Tool embeds cutting-edge features like container security scanning, API testing, and real-time anomaly detection to provide coverage of emerging attack surfaces. In contrast to traditional tools, this tool is developed with customizability, modular test frameworks, and AI-driven report generation, enabling security assessments to be more accessible and efficient. Moreover, the incorporation of Large Language Models (LLMs) improves the tool's usability through the creation of human-readable vulnerability reports with remediation plans, lessening the dependence on cybersecurity professionals. This paper seeks to introduce a scalable, smart penetration testing framework that not only identifies vulnerabilities effectively but also offers actionable recommendations for enhancing security postures in various digital infrastructures. The focus of this business sets the boundaries and objectives of the automated penetration testing tool. It is designed to serve the needs of small to medium-sized enterprises, freelance security professionals, and security enthusiasts. These groups typically don't have the resources or skills to carry out complete security scans, so an automated and easy- to-use tool is extremely valuable. The main features of the tool are automating the vulnerability detection with Python and employing YAML templates. Through server response analysis, the tool is able to detect security vulnerabilities like SQL injection and cross- site scripting (XSS). It also incorporates AI-powered reporting, which provides technical results in understandable human-friendly reports. This makes it easy for users at any level of expertise to easily comprehend vulnerabilities and perform remediation.
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