The purpose of this paper is to evaluate if automated vulnerability scanning accurately identifies vulnerabilities in computer networks and if this accuracy is contingent on the platforms used.
Both qualitative comparisons of functionality and quantitative comparisons of false positives and false negatives are made for seven different scanners. The quantitative assessment includes data from both authenticated and unauthenticated scans. Experiments were conducted on a computer network of 28 hosts with various operating systems, services and vulnerabilities. This network was set up by a team of security researchers and professionals.
The data collected in this study show that authenticated vulnerability scanning is usable. However, automated scanning is not able to accurately identify all vulnerabilities present in computer networks. Also, scans of hosts running Windows are more accurate than scans of hosts running Linux.
This paper focuses on the direct output of automated scans with respect to the vulnerabilities they identify. Areas such as how to interpret the results assessed by each scanner (e.g. regarding remediation guidelines) or aggregating information about individual vulnerabilities into risk measures are out of scope.
This paper describes how well automated vulnerability scanners perform when it comes to identifying security issues in a network. The findings suggest that a vulnerability scanner is a useable tool to have in your security toolbox given that user credentials are available for the hosts in your network. Manual effort is however needed to complement automated scanning in order to get satisfactory accuracy regarding network security problems.
Previous studies have focused on the qualitative aspects on vulnerability assessment. This study presents a quantitative evaluation of seven of the most popular vulnerability scanners available on the market.
Holm, H., Sommestad, T., Almroth, J. and Persson, M. (2011), "A quantitative evaluation of vulnerability scanning", Information Management & Computer Security, Vol. 19 No. 4, pp. 231-247. https://doi.org/10.1108/09685221111173058
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