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Automated Discovery of Deserialization Gadget Chains - Ian Haken
Although vulnerabilities stemming from the deserialization of untrusted data have been understood for many years, unsafe deserialization continues to be a vulnerability class that isn't going away. Attention on Java deserialization vulnerabilities skyrocketed in 2015 when Frohoff and Lawrence published an RCE gadget chain in the Apache Commons library and as recently as last year's Black Hat, Muñoz and Miroshis presented a survey of dangerous JSON deserialization libraries. While much research and automated detection technology has so far focused on the discovery of vulnerable entry points (i.e. code that deserializes untrusted data), finding a "gadget chain" to actually make the vulnerability exploitable has thus far been a largely manual exercise. In this talk, I present a new technique for the automated discovery of deserialization gadget chains in Java, allowing defensive teams to quickly identify the significance of a deserialization vulnerability and allowing penetration testers to quickly develop working exploits. At the conclusion, I will also be releasing a FOSS toolkit which utilizes this methodology and has been used to successfully develop many deserialization exploits in both internal applications and open source projects. About Ian Ian Haken is a senior security software engineer at Netflix where he works on the platform security team to develop tools and services that defend the Netflix platform. Before working at Netflix, he spent two years as security researcher at Coverity where he developed defensive application security tools and helped to develop automated discovery of security vulnerabilities through static software analysis. He received his PhD in mathematics from the University of California, Berkeley in 2014 with a focus in computability theory and algorithmic information theory.

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