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.

View More Papers

When Cryptography Needs a Hand: Practical Post-Quantum Authentication for...

Geoff Twardokus (Rochester Institute of Technology), Nina Bindel (SandboxAQ), Hanif Rahbari (Rochester Institute of Technology), Sarah McCarthy (University of Waterloo)

Read More

DRAINCLoG: Detecting Rogue Accounts with Illegally-obtained NFTs using Classifiers...

Hanna Kim (KAIST), Jian Cui (Indiana University Bloomington), Eugene Jang (S2W Inc.), Chanhee Lee (S2W Inc.), Yongjae Lee (S2W Inc.), Jin-Woo Chung (S2W Inc.), Seungwon Shin (KAIST)

Read More

Secure Control of Connected and Automated Vehicles Using Trust-Aware...

H M Sabbir Ahmad, Ehsan Sabouni, Akua Dickson (Boston University), Wei Xiao (Massachusetts Institute of Technology), Christos Cassandras, Wenchao Li (Boston University)

Read More

Scrappy: SeCure Rate Assuring Protocol with PrivacY

Kosei Akama (Keio University), Yoshimichi Nakatsuka (ETH Zurich), Masaaki Sato (Tokai University), Keisuke Uehara (Keio University)

Read More