Automatic Creation of SQL Injection and Cross-Site Scripting Attacks

We present a technique for finding security vulnerabilitiesin Web applications. SQL Injection (SQLI) and cross-sitescripting (XSS) attacks are widespread forms of attackin which the attacker crafts the input to the application toaccess or modify user data and execute malicious code. Inthe most serious attacks (called second-order, or persistent,XSS), an attacker can corrupt a database so as to causesubsequent users to execute malicious code.This paper presents an automatic technique for creatinginputs that expose SQLI and XSS vulnerabilities. The techniquegenerates sample inputs, symbolically tracks taintsthrough execution (including through database accesses),and mutates the inputs to produce concrete exploits. Oursis the first analysis of which we are aware that preciselyaddresses second-order XSS attacks.Our technique creates real attack vectors, has few falsepositives, incurs no runtime overhead for the deployed application,works without requiring modification of applicationcode, and handles dynamic programming-languageconstructs. We implemented the technique for PHP, in a toolArdilla. We evaluated Ardilla on five PHP applicationsand found 68 previously unknown vulnerabilities (23 SQLI,33 first-order XSS, and 12 second-order XSS)

Compliance of Open Source EHR Applications with HIPAA and ONC Security and Privacy Requirements

Electronic Health Records (EHRs) are digital versions of paper-based patient\u27s health information. EHR applications are increasingly being adopted in many countries. They have resulted in improved quality in healthcare, convenient access to histories of patient medication and clinic visits, easier follow up of patient treatment plans, and precise medical decision-making process. EHR applications are guided by measures of the Health Insurance Portability and Accountability Act (HIPAA) to ensure confidentiality, integrity, and availability. However, there have been reported breaches of Protected Health Identifier (PHI) data stored by EHR applications. In many reported breaches, improper use of EHRs has resulted in disclosure of patient’s PHI data. Inefficient application design threatens the integrity of EHRs, which leads to fraud and endangering patient\u27s health. The goal of this paper is to identify HIPAA technical requirements, evaluate an open source EHR application (OpenEMR) for security vulnerabilities using an open-source scanner tool (RIPS), and map identified vulnerabilities to HIPAA technical requirements

Analysis of SQL Injection Detection Techniques

SQL Injection is one of the vulnerabilities in OWASPs Top Ten List for Web Based Application Exploitation.These types of attacks takes place on Dynamic Web applications as they interact with the databases for the various operations.Current Content Management System like Drupal, Joomla or Wordpress have all the information stored in their databases. A single intrusion into these types of websites can lead to overall control of websites by the attacker. Researchers are aware of the basic SQL Injection attacks but there are numerous SQL Injection attacks which are yet to be Prevented and Detected. Over here, we present the extensive review for the Advanced SQL Injection attack such as Fast Flux Sql Injection, Compounded SQL Injection and Deep Blind SQL Injection. We also analyze the detection and prevention using the classical methods as well as modern approaches. We will be discussing the Comparative Evaluation for prevention of SQL Injection

Structural Learning of Attack Vectors for Generating Mutated XSS Attacks

Web applications suffer from cross-site scripting (XSS) attacks that resulting from incomplete or incorrect input sanitization. Learning the structure of attack vectors could enrich the variety of manifestations in generated XSS attacks. In this study, we focus on generating more threatening XSS attacks for the state-of-the-art detection approaches that can find potential XSS vulnerabilities in Web applications, and propose a mechanism for structural learning of attack vectors with the aim of generating mutated XSS attacks in a fully automatic way. Mutated XSS attack generation depends on the analysis of attack vectors and the structural learning mechanism. For the kernel of the learning mechanism, we use a Hidden Markov model (HMM) as the structure of the attack vector model to capture the implicit manner of the attack vector, and this manner is benefited from the syntax meanings that are labeled by the proposed tokenizing mechanism. Bayes theorem is used to determine the number of hidden states in the model for generalizing the structure model. The paper has the contributions as following: (1) automatically learn the structure of attack vectors from practical data analysis to modeling a structure model of attack vectors, (2) mimic the manners and the elements of attack vectors to extend the ability of testing tool for identifying XSS vulnerabilities, (3) be helpful to verify the flaws of blacklist sanitization procedures of Web applications. We evaluated the proposed mechanism by Burp Intruder with a dataset collected from public XSS archives. The results show that mutated XSS attack generation can identify potential vulnerabilities.Comment: In Proceedings TAV-WEB 2010, arXiv:1009.330

Optimizing Anti-Phishing Solutions Based on User Awareness, Education and the Use of the Latest Web Security Solutions

Phishing has grown significantly in volume over the time, becoming the most usual web threat today. The present economic crisis is an added argument for the great increase in number of attempts to cheat internet users, both businesses and private ones. The present research is aimed at helping the IT environment get a more precise view over the phishing attacks in Romania; in order to achieve this goal we have designed an application able to retrieve and interpret phishing related data from five other trusted web sources and compile them into a meaningful and more targeted report. As a conclusion, besides making available regular reports, we underline the need for a higher degree of awareness related to this issue.Security, Phishing, Ev-SSL, Security Solutions

The approaches to quantify web application security scanners quality: A review

The web application security scanner is a computer program that assessed web application security with penetration testing technique. The benefit of automated web application penetration testing is huge, which web application security scanner not only reduced the time, cost, and resource required for web application penetration testing but also eliminate test engineer reliance on human knowledge. Nevertheless, web application security scanners are possessing weaknesses of low test coverage, and the scanners are generating inaccurate test results. Consequently, experimentations are frequently held to quantitatively quantify web application security scanner's quality to investigate the web application security scanner's strengths and limitations. However, there is a discovery that neither a standard methodology nor criterion is available for quantifying the web application security scanner's quality. Hence, in this paper systematic review is conducted and analysed the methodology and criterion used for quantifying web application security scanners' quality. In this survey, the experiment methodologies and criterions that had been used to quantify web application security scanner's quality is classified and review using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol. The objectives are to provide practitioners with the understanding of methodologies and criterions that available for measuring web application security scanners' test coverage, attack coverage, and vulnerability detection rate, while provides the critical hint for development of the next testing framework, model, methodology, or criterions, to measure web application security scanner quality

SQL Injection analysis, Detection and Prevention

Web sites are dynamic, static, and most of the time a combination of both. Web sites need protection in their database to assure security. An SQL injection attacks interactive web applications that provide database services. These applications take user inputs and use them to create an SQL query at run time. In an SQL injection attack, an attacker might insert a malicious SQL query as input to perform an unauthorized database operation. Using SQL injection attacks, an attacker can retrieve or modify confidential and sensitive information from the database. It may jeopardize the confidentiality and security of Web sites which totally depends on databases. This report presents a “code reengineering” that implicitly protects the applications which are written in PHP from SQL injection attacks. It uses an original approach that combines static as well as dynamic analysis. [2] In this report, I mentioned an automated technique for moving out SQL injection vulnerabilities from Java code by converting plain text inputs received from users into prepared statements. [3

ADAPTIVE MODEL FOR PROTECTION OF ELECTRONIC RESOURCES AGAINST INFORMATION SECURITY THREATS

The rapid development of digitalization and the creation of electronic resources, in areas such as e-commerce, government portals and others leads to the actualization of data protection issues. The protection of electronic resources is becoming more and more relevant every day. This article presents the concept of adaptive protection of electronic resources from information security threats. In the course of this research, an adaptive model of protection of electronic resources from threats to information security based on behavioral analysis was developed

Mining input sanitization patterns for predicting SQL injection and cross site scripting vulnerabilities

Static code attributes such as lines of code and cyclomatic complexity have been shown to be useful indicators of defects in software modules. As web applications adopt input sanitization routines to prevent web security risks, static code attributes that represent the characteristics of these routines may be useful for predicting web application vulnerabilities. In this paper, we classify various input sanitization methods into different types and propose a set of static code attributes that represent these types. Then we use data mining methods to predict SQL injection and cross site scripting vulnerabilities in web applications. Preliminary experiments show that our proposed attributes are important indicators of such vulnerabilities