• Title/Summary/Keyword: Java Script Injection

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Detecting Security Vulnerabilities in TypeScript Code with Static Taint Analysis (정적 오염 분석을 활용한 타입스크립트 코드의 보안 취약점 탐지)

  • Moon, Taegeun;Kim, Hyoungshick
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.31 no.2
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    • pp.263-277
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    • 2021
  • Taint analysis techniques are popularly used to detect web vulnerabilities originating from unverified user input data, such as Cross-Site Scripting (XSS) and SQL Injection, in web applications written in JavaScript. To detect such vulnerabilities, it would be necessary to trace variables affected by user-submitted inputs. However, because of the dynamic nature of JavaScript, it has been a challenging issue to identify those variables without running the web application code. Therefore, most existing taint analysis tools have been developed based on dynamic taint analysis, which requires the overhead of running the target application. In this paper, we propose a novel static taint analysis technique using symbol information obtained from the TypeScript (a superset of JavaScript) compiler to accurately track data flow and detect security vulnerabilities in TypeScript code. Our proposed technique allows developers to annotate variables that can contain unverified user input data, and uses the annotation information to trace variables and data affected by user input data. Since our proposed technique can seamlessly be incorporated into the TypeScript compiler, developers can find vulnerabilities during the development process, unlike existing analysis tools performed as a separate tool. To show the feasibility of the proposed method, we implemented a prototype and evaluated its performance with 8 web applications with known security vulnerabilities. We found that our prototype implementation could detect all known security vulnerabilities correctly.

Supplementary Event-Listener Injection Attack in Smart Phones

  • Hidhaya, S. Fouzul;Geetha, Angelina;Kumar, B. Nandha;Sravanth, Loganathan Venkat;Habeeb, A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.10
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    • pp.4191-4203
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    • 2015
  • WebView is a vital component in smartphone platforms like Android, Windows and iOS that enables smartphone applications (apps) to embed a simple yet powerful web browser inside them. WebView not only provides the same functionalities as web browser, it, more importantly, enables a rich interaction between apps and webpages loaded inside the WebView. However, the design and the features of WebView lays path to tamper the sandbox protection mechanism implemented by browsers. As a consequence, malicious attacks can be launched either against the apps or by the apps through the exploitation of WebView APIs. This paper presents a critical attack called Supplementary Event-Listener Injection (SEI) attack which adds auxiliary event listeners, for executing malicious activities, on the HTML elements in the webpage loaded by the WebView via JavaScript Injection. This paper also proposes an automated static analysis system for analyzing WebView embedded apps to classify the kind of vulnerability possessed by them and a solution for the mitigation of the attack.

Vulnerability Analysis using the Web Vulnerability Scanner (Web Vulnerability Scanner를 이용한 취약성 분석)

  • Jang, Hee-Seon
    • Convergence Security Journal
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    • v.12 no.4
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    • pp.71-76
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    • 2012
  • As the use of Mashups, web3.0, JavaScript and AJAX(Asynchronous JavaScript XML) widely increases, the new security threats for web vulnerability also increases when the web application services are provided. In order to previously diagnose the vulnerability and prepare the threats, in this paper, the classification of security threats and requirements are presented, and the web vulnerability is analyzed for the domestic web sites using WVS(Web Vulnerability Scanner) automatic evaluation tool. From the results of vulnerability such as XSS(Cross Site Scripting) and SQL Injection, the total alerts are distributed from 0 to 31,177, mean of 411, and standard deviation of 2,563. The results also show that the web sites of 22.5% for total web sites has web vulnerability, and the previous defenses for the security threats are required.