About: SQL injection is a(n) research topic. Over the lifetime, 2174 publication(s) have been published within this topic receiving 33241 citation(s). The topic is also known as: SQLI.
27 Oct 2003-
TL;DR: A new, general approach for safeguarding systems against any type of code-injection attack, by creating process-specific randomized instruction sets of the system executing potentially vulnerable software that can serve as a low-overhead protection mechanism, and can easily complement other mechanisms.
Abstract: We describe a new, general approach for safeguarding systems against any type of code-injection attack. We apply Kerckhoff's principle, by creating process-specific randomized instruction sets (e.g., machine instructions) of the system executing potentially vulnerable software. An attacker who does not know the key to the randomization algorithm will inject code that is invalid for that randomized processor, causing a runtime exception. To determine the difficulty of integrating support for the proposed mechanism in the operating system, we modified the Linux kernel, the GNU binutils tools, and the bochs-x86 emulator. Although the performance penalty is significant, our prototype demonstrates the feasibility of the approach, and should be directly usable on a suitable-modified processor (e.g., the Transmeta Crusoe).Our approach is equally applicable against code-injecting attacks in scripting and interpreted languages, e.g., web-based SQL injection. We demonstrate this by modifying the Perl interpreter to permit randomized script execution. The performance penalty in this case is minimal. Where our proposed approach is feasible (i.e., in an emulated environment, in the presence of programmable or specialized hardware, or in interpreted languages), it can serve as a low-overhead protection mechanism, and can easily complement other mechanisms.
21 May 2006-
TL;DR: This paper uses flow-sensitive, interprocedural and context-sensitive dataflow analysis to discover vulnerable points in a program and applies it to the detection of vulnerability types such as SQL injection, cross-site scripting, or command injection.
Abstract: The number and the importance of Web applications have increased rapidly over the last years. At the same time, the quantity and impact of security vulnerabilities in such applications have grown as well. Since manual code reviews are time-consuming, error-prone and costly, the need for automated solutions has become evident. In this paper, we address the problem of vulnerable Web applications by means of static source code analysis. More precisely, we use flow-sensitive, interprocedural and context-sensitive dataflow analysis to discover vulnerable points in a program. In addition, alias and literal analysis are employed to improve the correctness and precision of the results. The presented concepts are targeted at the general class of taint-style vulnerabilities and can be applied to the detection of vulnerability types such as SQL injection, cross-site scripting, or command injection. Pixy, the open source prototype implementation of our concepts, is targeted at detecting cross-site scripting vulnerabilities in PHP scripts. Using our tool, we discovered and reported 15 previously unknown vulnerabilities in three Web applications, and reconstructed 36 known vulnerabilities in three other Web applications. The observed false positive rate is at around 50% (i.e., one false positive for each vulnerability) and therefore, low enough to permit effective security audits.
31 Jul 2005-
TL;DR: This paper proposes a static analysis technique for detecting many recently discovered application vulnerabilities such as SQL injections, cross-site scripting, and HTTP splitting attacks based on a scalable and precise points-to analysis.
Abstract: This paper proposes a static analysis technique for detecting many recently discovered application vulnerabilities such as SQL injections, cross-site scripting, and HTTP splitting attacks. These vulnerabilities stem from unchecked input, which is widely recognized as the most common source of security vulnerabilities in Web applications. We propose a static analysis approach based on a scalable and precise points-to analysis. In our system, user-provided specifications of vulnerabilities are automatically translated into static analyzers. Our approach finds all vulnerabilities matching a specification in the statically analyzed code. Results of our static analysis are presented to the user for assessment in an auditing interface integrated within Eclipse, a popular Java development environment. Our static analysis found 29 security vulnerabilities in nine large, popular open-source applications, with two of the vulnerabilities residing in widely-used Java libraries. In fact, all but one application in our benchmark suite had at least one vulnerability. Context sensitivity, combined with improved object naming, proved instrumental in keeping the number of false positives low. Our approach yielded very few false positives in our experiments: in fact, only one of our benchmarks suffered from false alarms.
01 Jan 2006-
TL;DR: An extensive review of the different types of SQL injection attacks known to date is presented, including descriptions and examples of how attacks of that type could be performed and existing detection and prevention techniques against SQL injections.
Abstract: SQL injection attacks pose a serious security threat to Web applications: they allow attackers to obtain unrestricted access to the databases underlying the applications and to the potentially sensitive information these databases contain. Although researchers and practitioners have proposed various methods to address the SQL injection problem, current approaches either fail to address the full scope of the problem or have limitations that prevent their use and adoption. Many researchers and practitioners are familiar with only a subset of the wide range of techniques available to attackers who are trying to take advantage of SQL injection vulnerabilities. As a consequence, many solutions proposed in the literature address only some of the issues related to SQL injection. To address this problem, we present an extensive review of the different types of SQL injection attacks known to date. For each type of attack, we provide descriptions and examples of how attacks of that type could be performed. We also present and analyze existing detection and prevention techniques against SQL injection attacks. For each technique, we discuss its strengths and weaknesses in addressing the entire range of SQL injection attacks.
07 Nov 2005-
TL;DR: A new technique using a model-based approach to detect illegal queries before they are executed on the database and was able to stop all of the attempted attacks without generating any false positives.
Abstract: The use of web applications has become increasingly popular in our routine activities, such as reading the news, paying bills, and shopping on-line. As the availability of these services grows, we are witnessing an increase in the number and sophistication of attacks that target them. In particular, SQL injection, a class of code-injection attacks in which specially crafted input strings result in illegal queries to a database, has become one of the most serious threats to web applications. In this paper we present and evaluate a new technique for detecting and preventing SQL injection attacks. Our technique uses a model-based approach to detect illegal queries before they are executed on the database. In its static part, the technique uses program analysis to automatically build a model of the legitimate queries that could be generated by the application. In its dynamic part, the technique uses runtime monitoring to inspect the dynamically-generated queries and check them against the statically-built model. We developed a tool, AMNESIA, that implements our technique and used the tool to evaluate the technique on seven web applications. In the evaluation we targeted the subject applications with a large number of both legitimate and malicious inputs and measured how many attacks our technique detected and prevented. The results of the study show that our technique was able to stop all of the attempted attacks without generating any false positives.