ICSREF: A Framework for Automated Reverse Engineering of Industrial Control Systems Binaries
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Dec 2018.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 2; 2026: 1.
5 papers.
- 2022Pop Quiz! Can a Large Language Model Help With Reverse Engineering?cited by 13
- 2025AGNOMIN -- Architecture Agnostic Multi-Label Function Name Predictioncited by 1
- 2022ICSML: Industrial Control Systems ML Framework for native inference using IEC 61131-3 codecited by 0
- 2025Bridging the PLC Binary Analysis Gap: A Cross-Compiler Dataset and Neural Framework for Industrial Control Systemscited by 0
- 2026PLCBench: Can Autonomous LLM Agents Turn PLC Access into Sustained Physical Impact?cited by 0
- 2026PLCBench: Can Autonomous LLM Agents Turn PLC Access into Sustained Physical Impact?27 Aug 2026
- 2025AGNOMIN -- Architecture Agnostic Multi-Label Function Name Prediction29 Sep 2025
- 2025Bridging the PLC Binary Analysis Gap: A Cross-Compiler Dataset and Neural Framework for Industrial Control Systems27 Feb 2025
- 2022ICSML: Industrial Control Systems ML Framework for native inference using IEC 61131-3 code21 Feb 2022
- 2022Pop Quiz! Can a Large Language Model Help With Reverse Engineering?2 Feb 2022