QUANTITATIVE SECURITY EVALUATION OF WEB APPS USING STATIC ANALYSIS TOOLS

this paper presents a study on Static Application Security Testing (SAST) with a focus on the Snyk Code tool. SAST enables early detection and remediation of security vulnerabilities during software development, improving overall system security. The research introduces the General Application Vulnerability Rate (GAVR) model, which quantifies vulnerability risks based on the CVSS 3.1 framework. A case study using Snyk Code demonstrates the identification and assessment of security flaws, such as XSS and certificate validation issues. The study highlights the need for an integrated approach to security testing, emphasizing automation and structured vulnerability assessment to enhance software security. The GAVR model enhances traditional security evaluations by incorporating exploitability probabilities, offering a more dynamic risk assessment. The findings suggest that integrating SAST within the software development lifecycle significantly reduces security risks and improves remediation efficiency. By leveraging automation and systematic vulnerability quantification, this study underscores the importance of proactive security strategies to safeguard web applications against evolving threats.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-16
DOI
https://doi.org/10.5281/zenodo.18711853
Primary Topic
Web Application Security Vulnerabilities
Type
article
Field-Weighted Citation Impact
0.00
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article

QUANTITATIVE SECURITY EVALUATION OF WEB APPS USING STATIC ANALYSIS TOOLS

Andrii Oleksandrovych
Zenodo (CERN European Organization for Nuclear Research)
Web Application Security Vulnerabilities
article

QUANTITATIVE SECURITY EVALUATION OF WEB APPS USING STATIC ANALYSIS TOOLS

Andrii Oleksandrovych
article en

Abstract

this paper presents a study on Static Application Security Testing (SAST) with a focus on the Snyk Code tool. SAST enables early detection and remediation of security vulnerabilities during software development, improving overall system security. The research introduces the General Application Vulnerability Rate (GAVR) model, which quantifies vulnerability risks based on the CVSS 3.1 framework. A case study using Snyk Code demonstrates the identification and assessment of security flaws, such as XSS and certificate validation issues. The study highlights the need for an integrated approach to security testing, emphasizing automation and structured vulnerability assessment to enhance software security. The GAVR model enhances traditional security evaluations by incorporating exploitability probabilities, offering a more dynamic risk assessment. The findings suggest that integrating SAST within the software development lifecycle significantly reduces security risks and improves remediation efficiency. By leveraging automation and systematic vulnerability quantification, this study underscores the importance of proactive security strategies to safeguard web applications against evolving threats.

Zenodo (CERN European Organization for Nuclear Research)
State University of Information and Communication Technologies (UA)
Openalex Percentile: Top 14%
Web Application Security Vulnerabilities
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QUANTITATIVE SECURITY EVALUATION OF WEB APPS USING STATIC ANALYSIS TOOLS — Andrii Oleksandrovych · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS