• 융합보안논문지
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• 제13권6호
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• pp.83-89
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• 2013

웹 해킹 대책을 적용할 경우 어느 한가지 기술이나 방법보다 통합된 대책을 구성하고 정보보안을 단계적으로 실행하는 방법이 필요하다. 웹 해킹 대응을 어느 한가지 방법에만 의존 시 많은 보안 공백을 발생 시킬 수 있다. 본 연구에서는 Cross-site scripting 공격 프로세스를 진단하여 웹 해킹 대응절차를 설계한다. 대응체계는 프레임워크를 구성하고 정보보안을 단계적으로 실행하는 방법이다. 단계적 대응모델은 대책의 구조를 시스템 설계단계, 운용단계, 사용단계로 구성하는 방법이다. 시스템 설계단계는 방법은 개발 라이프 사이클에 기초하여 시큐어코딩 설계로 보안 효율성을 높인다. 사용단계에서는 사용자의 보안 이행사항을 체계화한다. 본 방법론을 실무현장에 적용할 경우 현장에서 필요한 종합적인 접근방법론 모델로 활용할 수 있다.

• 한국소프트웨어감정평가학회 논문지
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• 제17권2호
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• pp.125-142
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• 2021

Reports of rampant cross-site scripting (XSS) vulnerabilities raise growing concerns on the effectiveness of current Static Analysis Security Testing (SAST) tools as an internet security device. Attentive to these concerns, this study aims to examine seven open-source SAST tools in order to account for their capabilities in detecting XSS vulnerabilities in PHP applications and to determine their performance in terms of effectiveness and analysis runtime. The representative tools - categorized as either text-based or graph-based analysis tools - were all test-run using real-world PHP applications with known XSS vulnerabilities. The collected vulnerability detection reports of each tool were analyzed with the aid of PhpStorm's data flow analyzer. It is observed that the detection rates of the tools calculated from the total vulnerabilities in the applications can be as high as 0.968 and as low as 0.006. Furthermore, the tools took an average of less than a minute to complete an analysis. Notably, their runtime is independent of their analysis type.

• International journal of advanced smart convergence
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• 제10권4호
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• pp.22-29
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• 2021

For web application vulnerability diagnosis, from the development stage to the operation stage, it is possible to stably operate the web only when there is a policy that is commonly applied to each task through diagnosis of vulnerabilities, removal of vulnerabilities, and rapid recovery from web page damage. KISA presents 28 evaluation items for technical vulnerability analysis of major information and communication infrastructure. In this paper, we diagnose the vulnerabilities in the automobile goods shopping mall website and suggest security measures according to the vulnerabilities. As a result of diagnosing 28 items, major vulnerabilities were found in three items: cross-site scripting, cross-site request tampering, and insufficient session expiration. Cookie values were exposed on the bulletin board, and personal information was exposed in the parameter values related to passwords when personal information was edited. Also, since the session end time is not set, it was confirmed that session reuse is always possible. By suggesting security measures according to these vulnerabilities, the discovered security threats were eliminated, and it was possible to prevent breaches in web applications and secure the stability of web services.

• 디지털융복합연구
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• 제13권2호
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• pp.177-183
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• 2015

크로스사이트 스크립팅은 웹 애플리케이션의 취약점으로 사용자의 정보(쿠키, 세션 등)를 탈취하거나, 비정상적인 기능을 자동으로 수행하게 하거나 할 수 있다. 크로스사이트 스크립팅(XSS) 공격유형은 한 번의 HTTP 요청과 응답에서 행해지는 XSS인 반사 XSS(reflect XSS)와 페이로드를 전송한 뒤 다수의 피해자가 해당 페이지에 접속하면 XSS 공격에 노출되는 저장 XSS(Stored XSS)로 나눌 수 있다. 그리고 크로스사이트 스크립팅 공격에 대한 방어로 사용자 입력하는 데이터에 대한 입력 값 검증, HTML 인코딩 과정에서의 출력 값에 대한 검증, 사용자가 악의적 코드를 웹 어플리케이션에 삽입하기 위한 시도를 막기 위해 위험 가능성 삽입지점 제거를 제시하였다. 본 논문에서는 이 두 가지 방법에 대한 공격방법과 절차를 제시하고 모의해킹을 수행하였다. 이를 통해 크로스사이트 스크립팅 공격에 대한 이해가 가능하고 대응책을 통해 공격에 대비할 수 있도록 하였다.

• ETRI Journal
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• 제38권2호
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• pp.376-386
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• 2016

Currently, web applications are gaining in prevalence. In a web application, an input may not be appropriately validated, making the web application susceptible to cross-site scripting (XSS), which poses serious security problems for Internet users and websites to whom such trusted web pages belong. A taint inference is a type of information flow analysis technique that is useful in detecting XSS on the client side. However, in existing techniques, two current practical issues have yet to be handled properly. One is URL rewriting, which transforms a standard URL into a clearer and more manageable form. Another is HTML sanitization, which filters an input against blacklists or whitelists of HTML tags or attributes. In this paper, we make an analogy between the taint inference problem and the molecule sequence alignment problem in bioinformatics, and transfer two techniques related to the latter over to the former to solve the aforementioned yet-to-be-handled-properly practical issues. In particular, in our method, URL rewriting is addressed using local sequence alignment and HTML sanitization is modeled by introducing a removal gap penalty. Empirical results demonstrate the effectiveness and efficiency of our method.

• 정보처리학회논문지A
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• 제15A권3호
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• pp.181-188
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• 2008

오늘날 대부분의 웹사이트는 웹 응용 프로그램이 적절한 웹 페이지를 생성하여 전송하는 형태인 동적 웹페이지를 사용하고 있다. 이에 대하여, 취약한 웹 응용 프로그램에 악의적인 문자열을 전달하는 공격의 형태가 증가하고 있다. 본 논문에서는 대표적인 문자열 삽입 공격인 SQL 삽입(SQL Injection) 공격과 크로스 사이트 스크립팅(Cross Site Scripting, XSS) 공격에 대하여 웹 응용 프로그램내의 보안 취약성을 자동으로 찾아 주는 프로그램 정적 분석기를 개발하였다. 요약 해석을 사용한 프로그램 분석을 위하여 가능한 문자열 값을 제외 문자열들과 함께 표현하는 요약 자료 공간과 PHP 언어의 요약된 의미 규칙을 설계하였으며, 이를 기반으로 분석기를 구현하였다. 또한 개발된 분석기가 기존의 연구 결과와 비교하여 경쟁력 있는 분석 속도와 정밀도를 가짐을 실험을 통하여 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

• 융합보안논문지
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• 제12권4호
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• pp.71-76
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• 2012

Mashups, web 3.0, 자바스크립트 및 AJAX 등의 이용이 증가하면서 웹애플리케이션 서비스 제공시 웹취약점들에 대한 새로운 보안 위협이 증대되고 있으며, 이에 대한 사전 진단과 함께 대비가 요구된다. 본 논문에서는 웹취약성에 대한 보안 위협과 요구사항을 제시하고, Web Vulnerability Scanner(WVS) 자동화 도구를 이용하여 국내에서 서비스되고 있는 웹사이트를 대상으로 웹취약성을 분석한다. Cross Site Scripting(XSS)와 SQL Injection 등 대표적인 웹취약성에 대한 분석 결과, 약 22.5%에 해당하는 웹사이트가 보안에 취약한 것으로 나타났으며, 취약성 경고 수는 0부터 31,171 alerts로 분포되고, 평균 411 alerts, 편차는 2,563 alerts로서 보안 관리에 취약한 웹사이트의 경우, 경고 수가 높은 값을 나타내고 있어 세부적인 웹취약성에 대한 사전 대비가 필요함을 알 수 있다.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.1014-1028
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• 2017

Social networking services (SNSs) such as Twitter, MySpace, and Facebook have become progressively significant with its billions of users. Still, alongside this increase is an increase in security threats such as cross-site scripting (XSS) threat. Recently, a few approaches have been proposed to detect an XSS attack on SNSs. Due to the certain recent features of SNSs webpages such as JavaScript and AJAX, however, the existing approaches are not efficient in combating XSS attack on SNSs. In this paper, we propose a machine learning-based approach to detecting XSS attack on SNSs. In our approach, the detection of XSS attack is performed based on three features: URLs, webpage, and SNSs. A dataset is prepared by collecting 1,000 SNSs webpages and extracting the features from these webpages. Ten different machine learning classifiers are used on a prepared dataset to classify webpages into two categories: XSS or non-XSS. To validate the efficiency of the proposed approach, we evaluated and compared it with other existing approaches. The evaluation results show that our approach attains better performance in the SNS environment, recording the highest accuracy of 0.972 and lowest false positive rate of 0.87.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3750-3770
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• 2021

This study investigates open-source dynamic XSS filters used as security devices in web applications to account for the effectiveness of filters in protecting against XSS attacks. The experiment involves twelve representative filters, which are examined individually by placing them into the final output function of a custom-built single-input-form web application. To assess the effectiveness of the filters in their tasks of sanitizing XSS payloads and in preserving benign payloads, a black-box testing method is applied using an automated XSS testing framework. The result in working with malicious and benign payloads shows an important trade-off in the filters' tasks. Because the filters that only check for dangerous or safe elements, they seem to neglect to validate their values. As some safe values are mistreated as dangerous elements, their benign payload function is lost in the way. For the filters to be more effective, it is suggested that they should be able to validate the respective values of malicious and benign payloads; thus, minimizing the trade-off. This particular assessment of XSS filters provides important insight regarding the filters that can be used to mitigate threats, including the possible configurations to improve them in handling both malicious and benign payloads.