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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CAGE: Complementing Arm CCA with GPU Extensions

Chenxu Wang (Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology (SUSTech)), Yunjie Deng (Southern University of Science and Technology (SUSTech)), Kevin Leach (Vanderbilt University), Jiannong Cao (The Hong Kong Polytechnic University), Zhenyu Ning (Hunan University), Shoumeng Yan (Ant Group), Zhengyu He (Ant…

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Predictive Context-sensitive Fuzzing

Pietro Borrello (Sapienza University of Rome), Andrea Fioraldi (EURECOM), Daniele Cono D'Elia (Sapienza University of Rome), Davide Balzarotti (Eurecom), Leonardo Querzoni (Sapienza University of Rome), Cristiano Giuffrida (Vrije Universiteit Amsterdam)

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Leaking the Privacy of Groups and More: Understanding Privacy...

Jiangrong Wu (Sun Yat-sen University), Yuhong Nan (Sun Yat-sen University), Luyi Xing (Indiana University Bloomington), Jiatao Cheng (Sun Yat-sen University), Zimin Lin (Alibaba Group), Zibin Zheng (Sun Yat-sen University), Min Yang (Fudan University)

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TinyML meets IoBT against Sensor Hacking

Raushan Kumar Singh (IIT Ropar), Sudeepta Mishra (IIT Ropar)

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