Sze Yiu Chau (Purdue University), Moosa Yahyazadeh (The University of Iowa), Omar Chowdhury (The University of Iowa), Aniket Kate (Purdue University), Ninghui Li (Purdue University)

We discuss how symbolic execution can be used to not only find low-level errors but also analyze the semantic correctness of protocol implementations. To avoid manually crafting test cases, we propose a strategy of meta-level search, which leverages constraints stemmed from the input formats to automatically generate concolic test cases. Additionally, to aid root-cause analysis, we develop constraint provenance tracking (CPT), a mechanism that associates atomic sub-formulas of path constraints with their corresponding source level origins. We demonstrate the power of symbolic analysis with a case study on PKCS#1 v1.5 signature verification. Leveraging meta-level search and CPT, we analyzed 15 recent open-source implementations using symbolic execution and found semantic flaws in 6 of them. Further analysis of these flaws showed that 4 implementations are susceptible to new variants of the Bleichenbacher low- exponent RSA signature forgery. One implementation suffers from potential denial of service attacks with purposefully crafted signatures. All our findings have been responsibly shared with the affected vendors. Among the flaws discovered, 6 new CVEs have been assigned to the immediately exploitable ones.

View More Papers

Neural Machine Translation Inspired Binary Code Similarity Comparison beyond...

Fei Zuo (University of South Carolina), Xiaopeng Li (University of South Carolina), Patrick Young (Temple University), Lannan Luo (University of South Carolina), Qiang Zeng (University of South Carolina), Zhexin Zhang (University of South Carolina)

Read More

Profit: Detecting and Quantifying Side Channels in Networked Applications

Nicolás Rosner (University of California, Santa Barbara), Ismet Burak Kadron (University of California, Santa Barbara), Lucas Bang (Harvey Mudd College), Tevfik Bultan (University of California, Santa Barbara)

Read More

DIAT: Data Integrity Attestation for Resilient Collaboration of Autonomous...

Tigist Abera (Technische Universität Darmstadt), Raad Bahmani (Technische Universität Darmstadt), Ferdinand Brasser (Technische Universität Darmstadt), Ahmad Ibrahim (Technische Universität Darmstadt), Ahmad-Reza Sadeghi (Technische Universität Darmstadt), Matthias Schunter (Intel Labs)

Read More

Graph-based Security and Privacy Analytics via Collective Classification with...

Binghui Wang (Iowa State University), Jinyuan Jia (Iowa State University), Neil Zhenqiang Gong (Iowa State University)

Read More