Yaniv David (Columbia University), Neophytos Christou (Brown University), Andreas D. Kellas (Columbia University), Vasileios P. Kemerlis (Brown University), Junfeng Yang (Columbia University)

Managed languages facilitate convenient ways for serializing objects, allowing applications to persist and transfer them easily, yet this feature opens them up to attacks. By manipulating serialized objects, attackers can trigger a chained execution of existing code segments, using them as gadgets to form an exploit. Protecting deserialization calls against attacks is cumbersome and tedious, leading to many developers avoiding deploying defenses properly. We present QUACK, a framework for automatically protecting applications by fixing calls to deserialization APIs. This “binding” limits the classes allowed for usage in the deserialization process, severely limiting the code available for (ab)use as part of exploits. QUACK computes the set of classes that should be allowed using a novel static duck typing inference technique. In particular, it statically collects all statements in the program code that manipulate objects after they are deserialized, and puts together a filter for the list of classes that should be available at runtime. We have implemented QUACK for PHP and evaluated it on a set of applications with known CVEs, and popular applications crawled from GitHub. QUACK managed to fix the applications in a way that prevented any attempt at automatically generating an exploit against them, by blocking, on average, 97% of the application’s code that could be used as gadgets. We submitted a sample of three fixes generated by QUACK as pull requests, and their developers merged them.

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MOCK: Optimizing Kernel Fuzzing Mutation with Context-aware Dependency

Jiacheng Xu (Zhejiang University), Xuhong Zhang (Zhejiang University), Shouling Ji (Zhejiang University), Yuan Tian (UCLA), Binbin Zhao (Georgia Institute of Technology), Qinying Wang (Zhejiang University), Peng Cheng (Zhejiang University), Jiming Chen (Zhejiang University)

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Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated...

Torsten Krauß (University of Würzburg), Jan König (University of Würzburg), Alexandra Dmitrienko (University of Wuerzburg), Christian Kanzow (University of Würzburg)

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Understanding and Analyzing Appraisal Systems in the Underground Marketplaces

Zhengyi Li (Indiana University Bloomington), Xiaojing Liao (Indiana University Bloomington)

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WIP: An Adaptive High Frequency Removal Attack to Bypass...

Yuki Hayakawa (Keio University), Takami Sato (University of California, Irvine), Ryo Suzuki, Kazuma Ikeda, Ozora Sako, Rokuto Nagata (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

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