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Australasian Conference on Information Security and Privacy

ACISP 2019: Information Security and Privacy pp 494–513Cite as

Practical Dynamic Taint Tracking for Exploiting Input Sanitization Error in Java Applications

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11547))

Abstract

Errors in the sanitization of user inputs lead to serious security vulnerabilities. Many applications contain such errors, making them vulnerable to input sanitization exploits. Therefore, internet worms via exploiting vulnerabilities in applications infect hundreds of thousands of users in a matter of short time, causing hundreds of millions of dollars in damages. To successfully counter internet worm attacks, we need automatic detection and defense mechanisms. First, we need automatic detection mechanisms that can detect runtime attacks for vulnerabilities. A disclosure mechanism should be simple to deploy, resulting in few false positives and few false negatives.

In this paper we present Tainer, an automatic dynamic taint analysis framework to detect and generate exploits for sanitization based vulnerabilities for Java web applications. Particularly, our method is based on tracking the flow of taint information from untrusted input the application sensitive methods (such as console, file, network, database or another program). Our proposed framework is portable, quick, accurate, and does not need the source code of applications. We demonstrate the usefulness of the framework by detecting several zero-day actual vulnerabilities in popular Java applications.

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Notes

  1. 1.

    https://asm.ow2.io/.

  2. 2.

    http://serp.sourceforge.net/.

  3. 3.

    https://cve.mitre.org.

  4. 4.

    https://www.exploit-db.com.

  5. 5.

    https://curl.haxx.se.

  6. 6.

    https://github.com/xmendez/wfuzz.

  7. 7.

    https://github.com/rapid7/metasploit-framework.

  8. 8.

    https://nvd.nist.gov.

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Author information

Authors and Affiliations

  1. University of Potsdam, August-Bebel-Strasse 89, 14482, Potsdam, Germany

    Mohammadreza Ashouri

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  1. Mohammadreza Ashouri
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Correspondence to Mohammadreza Ashouri .

Editor information

Editors and Affiliations

  1. Massey University, Palmerston North, New Zealand

    Julian Jang-Jaccard

  2. University of Wollongong, Wollongong, NSW, Australia

    Fuchun Guo

Appendix A

Appendix A

Table 3. Some of the specified source and sink methods in Tainer
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Table 4. Some of the regular expressions used in the framework
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Ashouri, M. (2019). Practical Dynamic Taint Tracking for Exploiting Input Sanitization Error in Java Applications. In: Jang-Jaccard, J., Guo, F. (eds) Information Security and Privacy. ACISP 2019. Lecture Notes in Computer Science(), vol 11547. Springer, Cham. https://doi.org/10.1007/978-3-030-21548-4_27

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  • DOI: https://doi.org/10.1007/978-3-030-21548-4_27

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