Caracterização Escalável de Vulnerabilidades de Segurança: um Estudo de Caso na Internet Brasileira

  • Lucas M. Ponce UFMG
  • Matheus Gimpel UFMG
  • Elverton Fazzion UFSJ / UFMG
  • Ítalo Cunha UFMG
  • Cristine Hoepers NIC.br
  • Klaus Steding-Jessen NIC.br
  • Marcelo H. P. C. Chaves NIC.br
  • Dorgival Guedes UFMG
  • Wagner Meira Jr. UFMG

Abstract


Monitoring services such as Shodan are increasingly popular for tracking applications and vulnerabilities on the Internet. In this paper we analyze monitoring data from Shodan to characterize vulnerabilities found in Brazilian networks. In addition, we discuss Data Science methods to scale and improve the depth of the analyses, and combine external network and vulnerability metadata to support richer results and conclusions. Our characterization exposes several vulnerabilities of high severity, and some of them remain widespread despite being five years old. We hope that the analyses presented in this paper will encourage organizations to deploy updates and protection mechanisms to mitigate these threats.

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Published
2022-05-23
PONCE, Lucas M. et al. Caracterização Escalável de Vulnerabilidades de Segurança: um Estudo de Caso na Internet Brasileira. In: BRAZILIAN SYMPOSIUM ON COMPUTER NETWORKS AND DISTRIBUTED SYSTEMS (SBRC), 40. , 2022, Fortaleza. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 433-446. ISSN 2177-9384. DOI: https://doi.org/10.5753/sbrc.2022.222341.

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