Hybrid Security AssessmentMethodology forWeb Applications

Abstract

This study presents a methodology to evaluate and prevent security vulnerabilities issues for web applications. The analysis process is based on the use of techniques and tools that allow to perform security assessments of white box and black box, to carry out the security validation of a web application in an agile and precise way. The objective of the methodology is to take advantage of the synergies of semi-automatic static and dynamic security analysis tools and manual checks. Each one of the phases contemplated in the methodology is supported by security analysis tools of different degrees of coverage, so that the results generated in one phase are used as feed for the following phases in order to get an optimized global security analysis result. The methodology can be used as part of other more general methodologies that do not cover how to use static and dynamic analysis tools in the implementation and testing phases of a Secure Software Development Life Cycle (SSDLC). A practical application of the methodology to analyze the security of a real web application demonstrates its effectiveness by obtaining a better optimized vulnerability detection result against the true and false positive metrics. Dynamic analysis with manual checking is used to audit the results, 24.6 per cent of security vulnerabilities reported by the static analysis has been checked and it allows to study which vulnerabilities can be directly exploited externally. This phase is very important because it permits that each reported vulnerability can be checked by a dynamic second tool to confirm whether a vulnerability is true or false positive and it allows to study which vulnerabilities can be directly exploited externally. Dynamic analysis finds six (6) additional critical vulnerabilities. Access control analysis finds other five (5) important vulnerabilities such as Insufficient Protected Passwords or Weak Password Policy and Excessive Authentication Attacks, two vulnerabilities that permit brute force attacks.

Benchmarking Android malware analysis tools

“…The current advancement in programming improvement, the sundried methods for concealing noxious code (malware jumbling) by developers, adding hyper-availability in present society, makes malware investigation, analysis, identification, and classification develop into a real and increasingly complex problem to deal with nowadays. Android is an open-source operating system with over 1 billion users, covering many devices (smartphones, tablets, IoT, gadgets, and so on).The amount of confidential data presented across these devices (servers, smartphones, tablets, IoT, gadgets, and so on) boosts the complexity of attacks [1], which is a problem of concern to society. It becomes a priority to develop a method to analyze, detect, and classify malware on devices using the Android operating system.…”

“…The amount of confidential data presented across these devices (servers, smartphones, tablets, IoT, gadgets, and so on) boosts the complexity of attacks [1], which is a problem of concern to society. It becomes a priority to develop a method to analyze, detect, and classify malware on devices using the Android operating system.…”