Automated OSINT Techniques for Digital Asset Discovery and Cyber Risk Assessment
Babenko T. Kolesnikova K. Abramkina O. Vitulyova Y.
October 2025Multidisciplinary Digital Publishing Institute (MDPI)
Computers
2025#14Issue 10
Cyber threats are becoming increasingly sophisticated, especially in distributed infrastructures where systems are deeply interconnected. To address this, we developed a framework that automates how organizations discover their digital assets and assess which ones are the most at risk. The approach integrates diverse public information sources, including WHOIS records, DNS data, and SSL certificates, into a unified analysis pipeline without relying on intrusive probing. For risk scoring we applied Gradient Boosted Decision Trees, which proved more robust with messy real-world data than other models we tested. DBSCAN clustering was used to detect unusual exposure patterns across assets. In validation on organizational data, the framework achieved 93.3% accuracy in detecting known vulnerabilities and an F1-score of 0.92 for asset classification. More importantly, security teams spent about 58% less time on manual triage and false alarm handling. The system also demonstrated reasonable scalability, indicating that automated OSINT analysis can provide a practical and resource-efficient way for organizations to maintain visibility over their attack surface.
cyber reconnaissance , cyber risk assessment , DBSCAN , digital assets , GBDT , machine learning , OSINT
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Department of Cybersecurity, International IT University, Manas Str., 34/1, Almaty, 050000, Kazakhstan
Department of Information Systems, International IT University, Manas Str., 34/1, Almaty, 050000, Kazakhstan
Department of Cybersecurity, Almaty University of Power Engineering and Telecommunications Named After Gumarbek Daukeev, Baitursynuly Str., 126, Almaty, 050013, Kazakhstan
National Scientific Laboratory for the Collective Use of Information and Space Technologies (NSLC IST), 22 Satbayev Street, Almaty, 050013, Kazakhstan
JSC “Institute of Digital Engineering and Technology”, 22/5 Satbayev Street, Almaty, 050013, Kazakhstan
Department Smart Technologies in Engineering, International Engineering Technological University, 89/21 Al-Farabi Avenue, Almaty, 050060, Kazakhstan
Department of Cybersecurity
Department of Information Systems
Department of Cybersecurity
National Scientific Laboratory for the Collective Use of Information and Space Technologies (NSLC IST)
JSC “Institute of Digital Engineering and Technology”
Department Smart Technologies in Engineering
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