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An Approach to Generate Attack Graphs with a Case Study on Siemens PCS7 Blueprint for Water Treatment Plants

arXiv Security Archived Mar 27, 2026 ✓ Full text saved

arXiv:2603.24888v1 Announce Type: new Abstract: Assessing the security posture of Industrial Control Systems (ICS) is critical for protecting essential infrastructure. However, the complexity and scale of these environments make it challenging to identify and prioritize potential attack paths. This paper introduces a semi-automated approach for generating attack graphs in ICS environments to visualize and analyze multi-step attack scenarios. Our methodology integrates network topology informatio

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    Computer Science > Cryptography and Security [Submitted on 26 Mar 2026] An Approach to Generate Attack Graphs with a Case Study on Siemens PCS7 Blueprint for Water Treatment Plants Lucas Miranda, Carlos Banjar, Daniel Menasche, Anton Kocheturov, Gaurav Srivastava, Tobias Limmer Assessing the security posture of Industrial Control Systems (ICS) is critical for protecting essential infrastructure. However, the complexity and scale of these environments make it challenging to identify and prioritize potential attack paths. This paper introduces a semi-automated approach for generating attack graphs in ICS environments to visualize and analyze multi-step attack scenarios. Our methodology integrates network topology information with vulnerability data to construct a model of the system. This model is then processed by a stateful traversal algorithm to identify potential exploit chains based on preconditions and consequences. We present a case study applying the proposed framework to the Siemens PCS7 Cybersecurity Blueprint for Water Treatment Plants. The results demonstrate the framework's ability to simulate different attack scenarios, including those originating from known CVEs and potential device misconfigurations. We show how a single point of failure can compromise network segmentation and how patching a critical vulnerability can protect an entire security zone, providing actionable insights for risk mitigation. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2603.24888 [cs.CR]   (or arXiv:2603.24888v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2603.24888 Focus to learn more Submission history From: Carlos Eduardo Banjar [view email] [v1] Thu, 26 Mar 2026 00:06:20 UTC (81 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Mar 27, 2026
    Archived
    Mar 27, 2026
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