Biblio

Web technologies are typically built with time constraints and security vulnerabilities. Automatic software vulnerability scanners are common tools for detecting such vulnerabilities among software developers. It helps to illustrate the program for the attacker by creating a great deal of engagement within the program. SQL Injection and Cross-Site Scripting (XSS) are two of the most commonly spread and dangerous vulnerabilities in web apps that cause to the user. It is very important to trust the findings of the site vulnerability scanning software. Without a clear idea of the accuracy and the coverage of the open-source tools, it is difficult to analyze the result from the automatic vulnerability scanner that provides. The important to do a comparison on the key figure on the automated vulnerability scanners because there are many kinds of a scanner on the market and this comparison can be useful to decide which scanner has better performance in term of SQL Injection and Cross-Site Scripting (XSS) vulnerabilities. In this paper, a method by Jose Fonseca et al, is used to compare open-source automated vulnerability scanners based on detection coverage and a method by Yuki Makino and Vitaly Klyuev for precision rate. The criteria vulnerabilities will be injected into the web applications which then be scanned by the scanners. The results then are compared by analyzing the precision rate and detection coverage of vulnerability detection. Two leading open source automated vulnerability scanners will be evaluated. In this paper, the scanner that being utilizes is OW ASP ZAP and Skipfish for comparison. The results show that from precision rate and detection rate scope, OW ASP ZAP has better performance than Skipfish by two times for precision rate and have almost the same result for detection coverage where OW ASP ZAP has a higher number in high vulnerabilities.

Nowadays, Cross Site Scripting (XSS) is one of the major threats to Web applications. Since it's known to the public, XSS vulnerability has been in the TOP 10 Web application vulnerabilities based on surveys published by the Open Web Applications Security Project (OWASP). How to effectively detect and defend XSS attacks are still one of the most important security issues. In this paper, we present a novel approach to detect XSS attacks based on deep learning (called DeepXSS). First of all, we used word2vec to extract the feature of XSS payloads which captures word order information and map each payload to a feature vector. And then, we trained and tested the detection model using Long Short Term Memory (LSTM) recurrent neural networks. Experimental results show that the proposed XSS detection model based on deep learning achieves a precision rate of 99.5% and a recall rate of 97.9% in real dataset, which means that the novel approach can effectively identify XSS attacks.

Figuring innovations and development of web diminishes the exertion required for different procedures. Among them the most profited businesses are electronic frameworks, managing an account, showcasing, web based business and so on. This framework mostly includes the data trades ceaselessly starting with one host then onto the next. Amid this move there are such a variety of spots where the secrecy of the information and client gets loosed. Ordinarily the zone where there is greater likelihood of assault event is known as defenceless zones. Electronic framework association is one of such place where numerous clients performs there undertaking as indicated by the benefits allotted to them by the director. Here the aggressor makes the utilization of open ranges, for example, login or some different spots from where the noxious script is embedded into the framework. This scripts points towards trading off the security imperatives intended for the framework. Few of them identified with clients embedded scripts towards web communications are SQL infusion and cross webpage scripting (XSS). Such assaults must be distinguished and evacuated before they have an effect on the security and classification of the information. Amid the most recent couple of years different arrangements have been incorporated to the framework for making such security issues settled on time. Input approvals is one of the notable fields however experiences the issue of execution drops and constrained coordinating. Some other component, for example, disinfection and polluting will create high false report demonstrating the misclassified designs. At the center, both include string assessment and change investigation towards un-trusted hotspots for totally deciphering the effect and profundity of the assault. This work proposes an enhanced lead based assault discovery with specifically message fields for viably identifying the malevolent scripts. The work obstructs the ordinary access for malignant so- rce utilizing and hearty manage coordinating through unified vault which routinely gets refreshed. At the underlying level of assessment, the work appears to give a solid base to further research.

The Web today is a growing universe of pages and applications teeming with interactive content. The security of such applications is of the utmost importance, as exploits can have a devastating impact on personal and economic levels. The number one programming language in Web applications is PHP, powering more than 80% of the top ten million websites. Yet it was not designed with security in mind and, today, bears a patchwork of fixes and inconsistently designed functions with often unexpected and hardly predictable behavior that typically yield a large attack surface. Consequently, it is prone to different types of vulnerabilities, such as SQL Injection or Cross-Site Scripting. In this paper, we present an interprocedural analysis technique for PHP applications based on code property graphs that scales well to large amounts of code and is highly adaptable in its nature. We implement our prototype using the latest features of PHP 7, leverage an efficient graph database to store code property graphs for PHP, and subsequently identify different types of Web application vulnerabilities by means of programmable graph traversals. We show the efficacy and the scalability of our approach by reporting on an analysis of 1,854 popular open-source projects, comprising almost 80 million lines of code.

Social media plays an integral part in individual's everyday lives as well as for companies. Social media brings numerous benefits in people's lives such as to keep in touch with close ones and specially with relatives who are overseas, to make new friends, buy products, share information and much more. Unfortunately, several threats also accompany the countless advantages of social media. The rapid growth of the online social networking sites provides more scope for criminals and cyber-criminals to carry out their illegal activities. Hackers have found different ways of exploiting these platform for their malicious gains. This research englobes some of the common threats on social media such as spam, malware, Trojan horse, cross-site scripting, industry espionage, cyber-bullying, cyber-stalking, social engineering attacks. The main purpose of the study to elaborates on phishing, malware and click-jacking attacks. The main purpose of the research, there is no particular research available on the forensic investigation for Facebook. There is no particular forensic investigation methodology and forensic tools available which can follow on the Facebook. There are several tools available to extract digital data but it's not properly tested for Facebook. Forensics investigation tool is used to extract evidence to determine what, when, where, who is responsible. This information is required to ensure that the sufficient evidence to take legal action against criminals.

Software systems nowadays communicate via a number of complex languages. This is often the cause of security vulnerabilities like arbitrary code execution, or injections. Whereby injections such as cross-site scripting are widely known from textual languages such as HTML and JSON that constantly gain more popularity. These systems use parsers to read input and unparsers write output, where these security vulnerabilities arise. Therefore correct parsing and unparsing of messages is of the utmost importance when developing secure and reliable systems. Part of the challenge developers face is to correctly encode data during unparsing and decode it during parsing. This paper presents McHammerCoder, an (un)parser and encoding generator supporting textual and binary languages. Those (un)parsers automatically apply the generated encoding, that is derived from the language's grammar. Therefore manually defining and applying encoding is not required to effectively prevent injections when using McHammerCoder. By specifying the communication language within a grammar, McHammerCoder provides developers with correct input and output handling code for their custom language.

Web Application becomes the leading solution for the utilization of systems that need access globally, distributed, cost-effective, as well as the diversity of the content that can run on this technology. At the same time web application security have always been a major issue that must be considered due to the fact that 60% of Internet attacks targeting web application platform. One of the biggest impacts on this technology is Cross Site Scripting (XSS) attack, the most frequently occurred and are always in the TOP 10 list of Open Web Application Security Project (OWASP). Vulnerabilities in this attack occur in the absence of checking, testing, and the attention about secure coding practices. There are several alternatives to prevent the attacks that associated with this threat. Network Intrusion Detection System can be used as one solution to prevent the influence of XSS Attack. This paper investigates the XSS attack recognition and detection using regular expression pattern matching and a preprocessing method. Experiments are conducted on a testbed with the aim to reveal the behaviour of the attack.

In recent years, with the advances in JavaScript engines and the adoption of HTML5 APIs, web applications begin to show a tendency to shift their functionality from the server side towards the client side, resulting in dense and complex interactions with HTML documents using the Document Object Model (DOM). As a consequence, client-side vulnerabilities become more and more prevalent. In this paper, we focus on DOM-sourced Cross-site Scripting (XSS), which is a kind of severe but not well-studied vulnerability appearing in browser extensions. Comparing with conventional DOM-based XSS, a new attack surface is introduced by DOM-sourced XSS where the DOM could become a vulnerable source as well besides common sources such as URLs and form inputs. To discover such vulnerability, we propose a detecting framework employing hybrid analysis with two phases. The first phase is the lightweight static analysis consisting of a text filter and an abstract syntax tree parser, which produces potential vulnerable candidates. The second phase is the dynamic symbolic execution with an additional component named shadow DOM, generating a document as a proof-of-concept exploit. In our large-scale real-world experiment, 58 previously unknown DOM-sourced XSS vulnerabilities were discovered in user scripts of the popular browser extension Greasemonkey.

Taint analysis has been used in numerous scripting languages such as Perl and Ruby to defend against various form of code injection attacks, such as cross-site scripting (XSS) and SQL-injection. However, most taint analysis systems simply fail when tainted information is used in a possibly unsafe manner. In this paper, we explore how precise taint tracking can be used in order to secure web content. Rather than simply crashing, we propose that a library-writer defined sanitization function can instead be used on the tainted portions of a string. With this approach, library writers or framework developers can design their tools to be resilient, even if inexperienced developers misuse these libraries in unsafe ways. In other words, developer mistakes do not have to result in system crashes to guarantee security. We implement both coarse-grained and precise taint tracking in JavaScript, and show how our precise taint tracking API can be used to defend against SQL injection and XSS attacks. We further evaluate the performance of this approach, showing that precise taint tracking involves an overhead of approximately 22%.

JavaScript is the source of many security problems, including cross-site scripting attacks and malicious advertising code. Central to these problems is the fact that code from untrusted sources runs with full privileges. Information flow controls help prevent violations of data confidentiality and integrity. This article explores faceted values, a mechanism for providing information flow security in a dynamic manner that avoids the stuck executions of some prior approaches, such as the no-sensitive-upgrade technique. Faceted values simultaneously simulate multiple executions for different security levels to guarantee termination-insensitive noninterference. We also explore the interaction of faceted values with exceptions, declassification, and clearance.

This paper presents principles of Defensive Programming and examines the growing concern that these principles are not effectively incorporated into Computer Science and related computing degree programs' curricula. To support this concern, Defensive Programming principles are applied to a case study - Cross-site Scripting cybersecurity attacks. This paper concludes that Defensive Programming plays an important role in preventing these attacks and should thus be more aggressively integrated into CS courses such as Programming, Algorithms, Databases, Computer Architecture and Organization, and Computer Networks.

Cross-Site Scripting (XSS) is an unremitting problem for the Web. Since its initial public documentation in 2000 until now, XSS has been continuously on top of the vulnerability statistics. Even though there has been a considerable amount of research and developer education to address XSS on the source code level, the overall number of discovered XSS problems remains high. Because of this, various approaches to mitigate XSS have been proposed as a second line of defense, with HTML sanitizers, Web Application Firewalls, browser-based XSS filters, and the Content Security Policy being some prominent examples. Most of these mechanisms focus on script tags and event handlers, either by removing them from user-provided content or by preventing their script code from executing. In this paper, we demonstrate that this approach is no longer sufficient for modern applications: We describe a novel Web attack that can circumvent all of theses currently existing XSS mitigation techniques. In this attack, the attacker abuses so called script gadgets (legitimate JavaScript fragments within an application's legitimate code base) to execute JavaScript. In most cases, these gadgets utilize DOM selectors to interact with elements in the Web document. Through an initial injection point, the attacker can inject benign-looking HTML elements which are ignored by these mitigation techniques but match the selector of the gadget. This way, the attacker can hijack the input of a gadget and cause processing of his input, which in turn leads to code execution of attacker-controlled values. We demonstrate that these gadgets are omnipresent in almost all modern JavaScript frameworks and present an empirical study showing the prevalence of script gadgets in productive code. As a result, we assume most mitigation techniques in web applications written today can be bypassed.

Hybrid mobile applications are coded in both standard web languages and native language. The including of web technologies results in that Hybrid applications introduce more security risks than the traditional web applications, which have more possible channels to inject malicious codes to gain much more powerful privileges. In this paper, Cross-site Scripting attacks specific to Android Hybrid apps developed with PhoneGap framework are investigated. We find out that the XSS vulnerability on Hybrid apps makes it possible for attackers to bypass the access control policies of WebView and WebKit to run malicious codes into victim's WebView. With the PhoneGap plugins, the malicious codes can steal user's private information and destroy user's file system, which are more damaging than cookie stealing.

Web applications are used on a large scale worldwide, which handles sensitive personal data of users. With web application that maintains data ranging from as simple as telephone number to as important as bank account information, security is a prime point of concern. With hackers aimed to breakthrough this security using various attacks, we are focusing on SQL injection attacks and XSS attacks. SQL injection attack is very common attack that manipulates the data passing through web application to the database servers through web servers in such a way that it alters or reveals database contents. While Cross Site Scripting (XSS) attacks focuses more on view of the web application and tries to trick users that leads to security breach. We are considering three tier web applications with static and dynamic behavior, for security. Static and dynamic mapping model is created to detect anomalies in the class of SQL Injection and XSS attacks.