Preparing AI augmented security products for EU Cyber Resilience rules
Preparing an AI-Augmented SIEM for the EU Cyber Resilience Act: A Practitioner Case Study
Cryptography and SecurityComputers and Society
Summary
New EU rules require digital products to handle cybersecurity through their entire life, including reporting problems before they go to market. This paper shows how one security product with AI was prepared to meet these rules. The authors provide a clear, step-by-step plan and examples to help similar companies get ready for the EU law. This approach links legal requirements directly to practical security actions and documentation.
What this means in practice
- •For security product developers: Use the six-step method to align AI-powered security tools with EU cybersecurity regulations before market release.
- •For compliance teams at smes: Implement traceability processes that connect product risks and controls to legal cyber resilience requirements effectively.
Authors
Georgios Koutidis, Nikolaos Kekatos, Marina Korgiala-Karyda, Alexios Lekidis, Tom Nianios
Abstract
The EU Cyber Resilience Act (CRA), Regulation (EU) 2024/2847, makes product cybersecurity a lifecycle obligation for products with digital elements on the EU market: risk assessment, vulnerability handling, conformity documentation, and Article 14 incident- and vulnerability-reporting readiness must be operational before market placement. Small and medium-sized enterprises that build security products are doubly exposed, since their products are in scope while their customers expect them to be exemplary. This case study documents a CRA preparedness pilot for one such product, SEUXDR, an AI-augmented security monitoring product with a large-language-model active-response component, on the open-source CYBERFORT platform. We contribute a reproducible six-step recipe (Scope and Classify, Asset Registration, Produce Evidence, Map to CRA, Gap and Actions, Audit Pack), two end-to-end traceability threads, and a pilot snapshot tracing product risks through baseline and AI-specific controls and policies to CRA objectives. It offers practitioners a replicable starting point for translating CRA legal text into operational preparedness for incident response, vulnerability reporting, and conformity assessment.