Anastasis Keliris (NYU), Michail Maniatakos (NYU Abu Dhabi)

The security of Industrial Control Systems (ICS) has been attracting increased attention over the past years, following the discovery of real threats targeting industrial environments. Despite this attention, automation of the reverse engineering process of ICS binaries for programmable logic controllers remains an open problem, mainly due to the use of proprietary compilers by ICS vendors. Such automation could be a double-edged sword; on the one hand it could accelerate digital forensic investigations and incident response actions, while on the other hand it could enable dynamic generation of malicious ICS payloads. In this work, we propose a structured methodology that automates the reverse engineering process for ICS binaries taking into account their unique domain-specific characteristics. We apply this methodology to develop the modular Industrial Control Systems Reverse Engineering Framework (ICSREF), and instantiate ICSREF modules for reversing binaries compiled with CODESYS, a widely used software stack and compiler for PLCs. To evaluate our framework we create a database of samples by collecting real PLC binaries from public code repositories, as well as developing binaries in-house. Our results demonstrate that ICSREF can successfully handle diverse PLC binaries from varied industry sectors, irrespective of the programming language used. Furthermore, we deploy ICSREF on a commercial smartphone which orchestrates and launches a completely automated process-aware attack against a chemical process testbed. This example of dynamic payload generation showcases how ICSREF can enable sophisticated attacks without any prior knowledge.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 34 ) ) ) [post__not_in] => Array ( [0] => 4539 ) )

PeriScope: An Effective Probing and Fuzzing Framework for the...

Dokyung Song (University of California, Irvine), Felicitas Hetzelt (Technical University of Berlin), Dipanjan Das (University of California, Santa Barbara), Chad Spensky (University of California, Santa Barbara), Yeoul Na (University of California, Irvine), Stijn Volckaert (University of California, Irvine and KU Leuven), Giovanni Vigna (University of California, Santa Barbara), Christopher Kruegel (University of California, Santa Barbara),…

Read More

One Engine To Serve 'em All: Inferring Taint Rules...

Zheng Leong Chua (National University of Singapore), Yanhao Wang (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences), Teodora Baluta (National University of Singapore), Prateek Saxena (National University of Singapore), Zhenkai Liang (National University of Singapore), Purui Su (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences)

Read More

Countering Malicious Processes with Process-DNS Association

Suphannee Sivakorn (Columbia University), Kangkook Jee (NEC Labs America), Yixin Sun (Princeton University), Lauri Korts-Pärn (Cyber Defense Institute), Zhichun Li (NEC Labs America), Cristian Lumezanu (NEC Labs America), Zhenyu Wu (NEC Labs America), Lu-An Tang (NEC Labs America), Ding Li (NEC Labs America)

Read More

CodeAlchemist: Semantics-Aware Code Generation to Find Vulnerabilities in JavaScript...

HyungSeok Han (KAIST), DongHyeon Oh (KAIST), Sang Kil Cha (KAIST)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)