Policy-based confinement, employed in SELinux and specification-based intrusion detection systems, is a popular approach for defending against exploitation of vulnerabilities in benign software. Conventional access control policies employed in these approaches are effective in detecting privilege escalation attacks. However, they are unable to detect attacks that “hijack ” legitimate access privileges granted to a program, e.g., an attack that subverts an FTP server to download the password file. (Note that an FTP server would normally need to access the password file for performing user authentication.) Some of the common attack types reported today, such as SQL injection and cross-site scripting, involve such subversion of legitimate access privileges. In this paper, we present a new approach to strengthen policy enforcement by augmenting security policies with information about the trustworthiness of data used in securitysensitive operations. We evaluated this technique using 9 available exploits involving several popular software packages containing the above types of vulnerabilities. Our technique sucessfully defeated these exploits. 1

Web applications typically interact with a back-end database to retrieve persistent data and then present the data to the user as dynamically generated output, such as HTML web pages. However, this interaction is commonly done through a low-level API by dynamically constructing query strings within a general-purpose programming language, such as Java. This low-level interaction is ad hoc because it does not take into account the structure of the output language. Accordingly, user inputs are treated as isolated lexical entities which, if not properly sanitized, can cause the web application to generate unintended output. This is called a command injection attack, which poses a serious threat to web application security. This paper presents the first formal definition of command injection attacks in the context of web applications, and gives a sound and complete algorithm for preventing them based on context-free grammars and compiler parsing techniques. Our key observation is that, for an attack to succeed, the input that gets propagated into the database query or the output document must change the intended syntactic structure of the query or document. Our definition and algorithm are general and apply to many forms of command injection attacks. We validate our approach with SQLCHECK, an implementation for the setting of SQL command injection attacks. We evaluated SQLCHECK on real-world web applications with systematically compiled real-world attack data as input. SQLCHECK produced no false positives or false negatives, incurred low runtime overhead, and applied straightforwardly to web applications written in different languages.

Web applications are popular targets of security attacks. One common type of such attacks is SQL injection, where an attacker exploits faulty application code to execute maliciously crafted database queries. Both static and dynamic approaches have been proposed to detect or prevent SQL injections; while dynamic approaches provide protection for deployed software, static approaches can detect potential vulnerabilities before software deployment. Previous static approaches are mostly based on tainted information flow tracking and have at least some of the following limitations: (1) they do not model the precise semantics of input sanitization routines; (2) they require manually written specifications, either for each query or for bug patterns; or (3) they are not fully automated and may require user intervention at various points in the analysis. In this paper, we address these limitations by proposing a precise, sound, and fully automated analysis technique for SQL injection. Our technique avoids the need for specifications by considering as attacks those queries for which user input changes the intended syntactic structure of the generated query. It checks conformance to this policy by conservatively characterizing the values a string variable may assume with a context free grammar, tracking the nonterminals that represent user-modifiable data, and modeling string operations precisely as language transducers. We have implemented the proposed technique for PHP, the most widely-used web scripting language. Our tool successfully discovered previously unknown and sometimes subtle vulnerabilities in real-world programs, has a low false positive rate, and scales to large programs (with approx. 100K loc).

Swift is a new, principled approach to building web applications that are secure by construction. In modern web applications, some application functionality is usually implemented as client-side code written in JavaScript. Moving code and data to the client can create security vulnerabilities, but currently there are no good methods for deciding when it is secure to do so. Swift automatically partitions application code while providing assurance that the resulting placement is secure and efficient. Application code is written as Java-like code annotated with information flow policies that specify the confidentiality and integrity of web application information. The compiler uses these policies to automatically partition the program into JavaScript code running in the browser, and Java code running on the server. To improve interactive performance, code and data are placed on the client side. However, security-critical code and data are always placed on the server. Code and data can also be replicated across the client and server, to obtain both security and performance. A max-flow algorithm is used to place code and data in a way that minimizes client–server communication.

Web applications are ubiquitous, perform missioncritical tasks, and handle sensitive user data. Unfortunately, web applications are often implemented by developers with limited security skills, and, as a result, they contain vulnerabilities. Most of these vulnerabilities stem from the lack of input validation. That is, web applications use malicious input as part of a sensitive operation, without having properly checked or sanitized the input values prior to their use. Past research on vulnerability analysis has mostly focused on identifying cases in which a web application directly uses external input in critical operations. However, little research has been performed to analyze the correctness of the sanitization process. Thus, whenever a web application applies some sanitization routine to potentially malicious input, the vulnerability analysis assumes that the result is innocuous. Unfortunately, this might not be the case, as the sanitization process itself could be incorrect or incomplete. In this paper, we present a novel approach to the analysis of the sanitization process. More precisely, we combine static and dynamic analysis techniques to identify faulty sanitization procedures that can be bypassed by an attacker. We implemented our approach in a tool, called Saner, and we applied it to a number of real-world applications. Our results demonstrate that we were able to identify several novel vulnerabilities that stem from erroneous sanitization procedures. 1

SIF (Servlet Information Flow) is a novel software framework for building high-assurance web applications, using language-based information-flow control to enforce security. Explicit, end-to-end confidentiality and integrity policies can be given either as compile-time program annotations, or as run-time user requirements. Compile-time and run-time checking efficiently enforce these policies. Information flow analysis is known to be useful against SQL injection and cross-site scripting, but SIF prevents inappropriate use of information more generally: the flow of confidential information to clients is controlled, as is the flow of low-integrity information from clients. Expressive policies allow users and application providers to protect information from one another. SIF moves trust out of the web application, and into the framework and compiler. This provides application deployers with stronger security assurance. Language-based information flow promises cheap, strong information security. But until now, it could not effectively enforce information security in highly dynamic applications. To build SIF, we developed new language features that make it possible to write realistic web applications. Increased assurance is obtained with modest enforcement overhead. 1

SQL injection attacks pose a serious threat to the security of Web applications because they can give attackers unrestricted access to databases that contain sensitive information. In this paper, we propose a new, highly automated approach for protecting existing Web applications against SQL injection. Our approach has both conceptual and practical advantages over most existing techniques. From the conceptual standpoint, the approach is based on the novel idea of positive tainting and the concept of syntax-aware evaluation. From the practical standpoint, our technique is at the same time precise and efficient and has minimal deployment requirements. The paper also describes WASP, a tool that implements our technique, and a set of studies performed to evaluate our approach. In the studies, we used our tool to protect several Web applications and then subjected them to a large and varied set of attacks and legitimate accesses. The evaluation was a complete success: WASP successfully and efficiently stopped all of the attacks without generating any false positives.

RESIN is a new language runtime that helps prevent security vulnerabilities, by allowing programmers to specify application-level data flow assertions. RESIN provides policy objects, which programmers use to specify assertion code and metadata; data tracking, which allows programmers to associate assertions with application data, and to keep track of assertions as the data flow through the application; and filter objects, which programmers use to define data flow boundaries at which assertions are checked. RESIN’s runtime checks data flow assertions by propagating policy objects along with data, as that data moves through the application, and then invoking filter objects when data crosses a data flow boundary, such as when writing data to the network or a file. Using RESIN, Web application programmers can prevent a range of problems, from SQL injection and cross-site scripting, to inadvertent password disclosure and missing access control checks. Adding a RESIN assertion to an application requires few changes to the existing application code, and an assertion can reuse existing code and data structures. For instance, 23 lines of code detect and prevent three previously-unknown missing access control vulnerabilities in phpBB, a popular Web forum application. Other assertions comprising tens of lines of code prevent a range of vulnerabilities in Python and PHP applications. A prototype of RESIN incurs a 33 % CPU overhead running the HotCRP conference management application.

We present a technique for finding security vulnerabilities in Web applications. SQL Injection (SQLI) and crosssite scripting (XSS) attacks are widespread forms of attack in which the attacker crafts the input to the application to access or modify user data and execute malicious code. In the most serious attacks (called second-order, or persistent, XSS), an attacker can corrupt a database so as to cause subsequent users to execute malicious code. This paper presents an automatic technique for creating inputs that expose SQLI and XSS vulnerabilities. The technique generates sample inputs, symbolically tracks taints through execution (including through database accesses), and mutates the inputs to produce concrete exploits. Ours is the first analysis of which we are aware that precisely addresses second-order XSS attacks. Our technique creates real attack vectors, has few false positives, incurs no runtime overhead for the deployed application, works without requiring modification of application code, and handles dynamic programming-language constructs. We implemented the technique for PHP, in a tool Ardilla. We evaluated Ardilla on five PHP applications and found 68 previously unknown vulnerabilities (23 SQLI, 33 first-order XSS, and 12 second-order XSS).

With the growing complexity of web applications, identifying web interfaces that can be used for testing such applications has become increasingly challenging. Many techniques that work effectively when applied to simple web applications are insufficient when used on modern, dynamic web applications, and may ultimately result in inadequate testing of the applications ’ functionality. To address this issue, we present a technique for automatically discovering web application interfaces based on a novel static analysis algorithm. We also report the results of an empirical evaluation in which we compare our technique against a traditional approach. The results of the comparison show that our technique can (1) discover a higher number of interfaces and (2) help generate test inputs that achieve higher coverage.