Litcius/Paper detail

Evaluation of Black-Box Web Application Security Scanners in Detecting Injection Vulnerabilities

Muzun Althunayyan, Neetesh Saxena, Shancang Li, Prosanta Gope

2022Electronics23 citationsDOIOpen Access PDF

Abstract

With the Internet’s meteoric rise in popularity and usage over the years, there has been a significant increase in the number of web applications. Nearly all organisations use them for various purposes, such as e-commerce, e-banking, e-learning, and social networking. More importantly, web applications have become increasingly vulnerable to malicious attack. To find web vulnerabilities before an attacker, security experts use black-box web application vulnerability scanners to check for security vulnerabilities in web applications. Most studies have evaluated these black-box scanners against various vulnerable web applications. However, most tested applications are traditional (non-dynamic) and do not reflect current web. This study evaluates the detection accuracy of five black-box web application vulnerability scanners against one of the most modern and sophisticated insecure web applications, representing a real-life e-commerce. The tested vulnerabilities are injection vulnerabilities, in particular, structured query language (SQLi) injection, not only SQL (NoSQL), and server-side template injection (SSTI). We also tested the black-box scanners in four modes to identify their limitations. The findings show that the black-box scanners overlook most vulnerabilities in almost all modes and some scanners missed all the vulnerabilities.

Topics & Concepts

Computer scienceBlack boxWeb applicationWeb application securityVulnerability (computing)World Wide WebSQL injectionPopularityCross-site scriptingComputer securityThe InternetSecure codingWeb developmentInformation securitySoftware security assuranceArtificial intelligenceWeb search queryPsychologySearch engineQuery by ExampleSocial psychologySecurity serviceWeb Application Security VulnerabilitiesSecurity and Verification in ComputingSpam and Phishing Detection