SHOGUN: An Integrated Dashboard for Vulnerability Analysis via Internet-Wide Search Engines
Resumo
The increasing exposure of digital assets on the Internet demands efficient solutions for identifying and continuously monitoring vulnerabilities. While search engines like Shodan provide a targeted retrieval of exposure data, longitudinal risk assessment requires extensive data preparation. To bridge this gap, we present SHOGUN, an interactive dashboard engineered for the multidimensional analysis of internet-wide vulnerability data. Built upon a decoupled architecture, our tool abstracts raw search engine dumps into structured analytical datasets. The tool features a reactive web interface that combines geospatial and statistical visualizations with a cross-view drill-down navigation model, allowing security analysts to transition from macro-level network overviews to granular, asset-level forensic investigations.Referências
Abuserrieh, L. and Alalfi, M. H. (2024). A Survey on Verification of Security and Safety in IoT Systems. IEEE Access, 12:138627–138645.
Huang, S.-C., Griffioen, H., van der Horst, M., Smaragdakis, G., van Eeten, M., and Zhauniarovich, Y. (2025). Trust but verify: an assessment of vulnerability tagging services. In Proceedings of the 34th USENIX Conference on Security Symposium, SEC ’25, pages 823–842, Berkeley, CA, United States. USENIX Association.
Li, R., Shen, M., Yu, H., Li, C., Duan, P., and Zhu, L. (2020). A Survey on Cyberspace Search Engines. In Lu, W., Wen, Q., Zhang, Y., Lang, B., Wen, W., Yan, H., Li, C., Ding, L., Li, R., and Zhou, Y., editors, Cyber Security, pages 206–214, Singapore. Springer Singapore.
Mousavi, S., Khansari, M., and Rahmani, R. (2020). A fully scalable big data framework for Botnet detection based on network traffic analysis. Information Sciences, 512:629–640.
Ponce, L., Cunha, I., Matos, I., Ítalo Cunha, Fazzion, E., Hoepers, C., Steding-Jessen, K., Chaves, M., Guedes, D., and Jr., W. M. (2024). Arcabouço Multi-motor para Detecção de Vulnerabilidades na Internet Brasileira. In Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 197–210, Porto Alegre, RS, Brazil. SBC.
Telesíntese (2026). Ransomware cresce 42% globalmente e amplia pressão sobre redes. URL: [link] (visited on 2026-06-22).
Huang, S.-C., Griffioen, H., van der Horst, M., Smaragdakis, G., van Eeten, M., and Zhauniarovich, Y. (2025). Trust but verify: an assessment of vulnerability tagging services. In Proceedings of the 34th USENIX Conference on Security Symposium, SEC ’25, pages 823–842, Berkeley, CA, United States. USENIX Association.
Li, R., Shen, M., Yu, H., Li, C., Duan, P., and Zhu, L. (2020). A Survey on Cyberspace Search Engines. In Lu, W., Wen, Q., Zhang, Y., Lang, B., Wen, W., Yan, H., Li, C., Ding, L., Li, R., and Zhou, Y., editors, Cyber Security, pages 206–214, Singapore. Springer Singapore.
Mousavi, S., Khansari, M., and Rahmani, R. (2020). A fully scalable big data framework for Botnet detection based on network traffic analysis. Information Sciences, 512:629–640.
Ponce, L., Cunha, I., Matos, I., Ítalo Cunha, Fazzion, E., Hoepers, C., Steding-Jessen, K., Chaves, M., Guedes, D., and Jr., W. M. (2024). Arcabouço Multi-motor para Detecção de Vulnerabilidades na Internet Brasileira. In Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 197–210, Porto Alegre, RS, Brazil. SBC.
Telesíntese (2026). Ransomware cresce 42% globalmente e amplia pressão sobre redes. URL: [link] (visited on 2026-06-22).
Publicado
01/09/2026
Como Citar
MATOS, Isabelle et al.
SHOGUN: An Integrated Dashboard for Vulnerability Analysis via Internet-Wide Search Engines. In: SALÃO DE FERRAMENTAS - SIMPÓSIO BRASILEIRO DE CIBERSEGURANÇA (SBSEG), 26. , 2026, Armação dos Búzios/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 215-223.
DOI: https://doi.org/10.5753/sbseg_estendido.2026.33700.
