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Footprinting and Scanning the Organization: Assessment Methodology


Maintaining digital security has become increasingly more complex over the past few years due to the rise in the accessibility of tools for security breach and the development of malicious software. Therefore, creating the strategies for improving the security of a company’s information has become a crucial step in maintaining the safety of a company. Footprinting and scanning are presently deemed the foundational strategies for preventing security breach in a company (Ammar, Russello, & Crispo, 2018). To evaluate the efficacy of the footprinting and scanning processes within a firm, one may need the strategy such as ethical hacking. Specifically, the adoption of the DNS footprinting may be required as the method of gathering information about the key hosts located within the selected network (Yan & Yan, 2018). The proposed strategy is expected to shed light on the vulnerabilities within the present security system.

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In the course of the assessment and the scanning for the existing vulnerabilities, one will have to perform several key steps. Namely, it will be necessary to map a network within which the process will be planted. The specified stage involves using the tools such as Nslookup and typing in the name of the target machine. Afterward, the process can be completed by considering the zone transfer lookup as the means of extracting critical data. After a series of manipulations performed with the help of the Nslookup tool and the eventual command that involves typing in the name of the target domain, two outcomes are possible. In the first instance, the process will return zero outcomes, which will imply that the data is fully protected. In a less fortunate outcome, the specified step will return a plethora of information stored at the specified computer.


The main reason to use the suggested framework of DNS footprinting is the opportunity to collect information about the servers of the company, as well as their locations. The specified approach will ostensibly allow hacking the company’s data unless a proper security system is introduced. In addition, the DNS attack is characterized by a significantly milder nature, which makes it much more elusive for traditional security systems. Thus, spotting a DNS attack on time becomes a rather problematic task, which is why using it as a tool for testing the security system should be seen as ideal (Yan & Yan, 2018). If the devised security framework withstands DNS footprinting, it can be considered entirely protected from any malicious software.

Moreover, the use of DNS footprinting will help to identify the vulnerabilities that may be overlooked when considering only the https-related concerns in the current security framework. With a detailed analysis of the effects that a DNS attack will have on a computer, one will be able to avoid the scenarios that will lead to the disclosure of crucial personal data, as well as the information related to third parties. In addition, DNS footprinting is typically seen as one of the easiest ways of hacking computers, which is why it is likely to be the first choice of criminals attempting at extracting information from an organization (Coppolino, D’Antonio, Mazzeo, & Romano, 2017). Therefore, the application of the specified strategy will allow reinforcing the security within an organization. After performing the specified type of assessment, one may consider applying more elaborate tools for assessing the quality of the chosen security system. However, as the first-choice framework, the DNS footprinting technique is likely to lead to rather impressive results.


Ammar, M., Russello, G., & Crispo, B. (2018). Internet of Things: A survey on the security of IoT frameworks. Journal of Information Security and Applications, 38, pp. 8-27.

Coppolino, L., D’Antonio, S., Mazzeo, G., & Romano, L. (2017). Cloud security: Emerging threats and current solutions. Computers & Electrical Engineering, 59, pp. 126-140.

Yan, P., & Yan, Z. (2018). A survey on dynamic mobile malware detection. Software Quality Journal, 26(3), pp. 891-919.

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