Fangzhou Dong (Arizona State University), Arvind S Raj (Arizona State University), Efrén López-Morales (New Mexico State University), Siyu Liu (Arizona State University), Yan Shoshitaishvili (Arizona State University), Tiffany Bao (Arizona State University), Adam Doupé (Arizona State University), Muslum Ozgur Ozmen (Arizona State University), Ruoyu Wang (Arizona State University)

Programmable Logic Controllers (PLCs) are industrial computers that control devices with real-world physical effects, and safety vulnerabilities in these systems can lead to catastrophic consequences. While prior research has proposed techniques to detect safety issues in PLC state machines, most approaches require access to design specifications or source code—resources often unavailable to analysts or end users.

This paper targets a prevalent class of vulnerabilities, which we name Blind-Trust Vulnerabilities, caused by missing or incomplete safety checks on peripheral inputs. We introduce Ta’veren, a novel static analysis-based framework that identifies such vulnerabilities directly from PLC binaries without relying on firmware rehosting, which remains an open research problem in firmware analysis. Ta’veren recovers the finite state machines of the PLC binaries, enabling repeated safety analyses under various policy specifications. To abstract the state from program states to logic-related states, we leverage our insight that PLCs consistently use specific variables to represent internal states, thus allowing for aggressive state deduplication. This insight enables us to effectively deduplicate states without compromising soundness. We develop a prototype of Ta’veren and evaluate it on real-world PLC binaries. Our experiments show that Ta’veren efficiently recovers meaningful FSMs and uncovers critical safety violations with high effectiveness.

View More Papers

SoK: Take a Deep Step into Linux Kernel Hardening...

Yinhao Hu (Huazhong University of Science and Technology & Zhongguancun Laboratory), Pengyu Ding (Huazhong University of Science and Technology & Zhongguancun Laboratory), Zhenpeng Lin (Independent Researcher), Dongliang Mu (Huazhong University of Science and Technology), Yuan Li (Zhongguancun Laboratory)

Read More

ReFuzz: Reusing Tests for Processor Fuzzing with Contextual Bandits

Chen Chen (Texas A&M University, USA), Zaiyan Xu (Texas A&M University, USA), Mohamadreza Rostami (Technische Universitat Darmstadt, Germany), David Liu (Texas A&M University, USA), Dileep Kalathil (Texas A&M University, USA), Ahmad-Reza Sadeghi (Technische Universitat Darmstadt, Germany), Jeyavijayan (JV) Rajendran (Texas A&M University, USA)

Read More

BINALIGNER: Aligning Binary Code for Cross-Compilation Environment Diffing

Yiran Zhu (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Tong Tang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Jie Wan (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Ziqi Yang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University; Hangzhou High-Tech Zone…

Read More