[PDF][PDF] Finding Security Vulnerabilities in Java Applications with Static Analysis.
VB Livshits, MS Lam - USENIX security symposium, 2005 - usenix.org
USENIX security symposium, 2005•usenix.org
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 …
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 …
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.
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