Information System Security: Analysis of APT Threats and Impacts

This report delves into the critical domain of information system security, with a specific focus on Advanced Persistent Threats (APTs). It investigates the impact of APTs on various sectors, including telecommunications, finance, manufacturing, and aerospace. The report analyzes several APT attacks, including APT39, APT38, APT37, and APT34, detailing their methods, targets, and consequences. It examines the malware used, such as SEAWEED, CACHEMONEY, POWBAT, and BONDUPDATER, and the social engineering techniques employed by attackers. Furthermore, it highlights the vulnerabilities exploited and the disruptions caused by these threats, providing insights into the evolving landscape of cyber security and the importance of robust defense mechanisms. The report references several research papers to support its analysis, offering a comprehensive understanding of APTs and their implications.

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Considering the current industrial growth it has been noticed that in the IT enabled
organization there is a huge impact of external threats into the business services of the
organization. Followed by this aspect it has been noticed from the investigation that along
with the other cyber security threats there is a significant risk present on the possibilities of
Advance Persistent Threats (APT) which holds the tendency to steel the users data with the
purpose to destroy or interrupt the services of the targeted organization. Followed by this
aspect a detail investigation has been conducted in the field of cyber systems in order to
determine the threats of APT as well as the impact and the mechanism of those threats (Li et
al., 2016). Considering the above mentioned aspects a list of instances that has happened in
current years are listed below:
APT39:
In the recent years 2018 it has been noticed that one of the most harmful APT attack
titled as the APT39 holds a significant impact of the telecommunication sectors of the Iran.
Followed by this aspect it has been also noticed that along with targeting the
telecommunication sector it has also targeted the travel sectors and the IT firms of Iran.
Followed by this identification it has been also noticed that the nominated APT attack APT39
has intended to analyse, monitor as well as to track the user data of the nominated industries
with the purpose to gather the entire data. This identified attack has been primarily based on
the malware of SEAWEED and the CACHEMONEY which has performed in the nominated
industries infrastructure and injected POWBAT infection. Followed by this operation this has
spread the malicious element through mail attachment (Abomhara 2015).
APT38:
Along with the above mentioned APT threats it has been also noticed that in the year
2018 a suspicious activity has been accounted which has primarily targeted the financial

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institute of North Korea. Followed by this investigation it has been also noticed that in this
year the nominated APT group has significantly targeted a cyber-heist for the financial
industries of North Korea. Followed by which it has been also noticed that due to application
of the nominated threats the cyber criminals has steel millions of dollar from the banks across
the world. Considering this aspect it has been also noticed that behind this attack there is a
significant influence of tunneler’s, data miners as well as several other malware families’
which has successfully stolen the industrial data as well as the money from the banks.
Followed by this aspect it has been also noticed that APT38 group has been utilized among
11 countries among which 16 popular banks has been victimized. While investigating the
implementation process of this APT group it has been noticed that this is considered as one of
the most effective attacks whose planning period is considered as one of the longest period of
time (Johnson 2019).
APT37:
Along with the above threats in the year 2018 another APT attack has been accounted
which has significantly impacted the services of the manufacturing, automotive as well as the
aerospace company with the purpose to steel the organizational data. Followed by this aspect
after a detail investigation it has been noticed that this APT attacker has significantly stolen
the organizational data as well as several important government data. Following this
discussion it has been noticed that behind the application of APT37 there is a huge
significance of disruptive malware present which has spread a harmful intrusion into the
targeted industries. After analysing the above aspect a detail investigation has been conducted
on the vendors of this attack in which it has been noticed that by applying the social
engineering techniques it has primarily targeted the web sources and the cyber operation due
to which a significant disruption has been identified which has significantly affected the
services of the manufacturing, automotive as well as the aerospace industries. Followed by

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this aspect it has been also noticed that APT37 holds the ability to inject the vulnerabilities
among the every activities present in the organizational operations (Chen et al., 2018).
APT34:
Followed by the above mentioned APT threats it has been also noticed that in recent
year a significant APT attack has been identified which holds a harmful impact on the
telecommunication, electronic as well as the financial industries of Iran. Considering this
aspect it has been noticed that behind this attack there is a huge application of POWBAT,
BONDUPDATER and POWRUNER is present which has significantly impacted nominated
industries by stealing its important information (Husari 2019).

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Reference:
Abomhara, M. (2015). Cyber security and the internet of things: vulnerabilities, threats,
intruders and attacks. Journal of Cyber Security and Mobility, 4(1), 65-88.
Chen, C. M., Lai, G. H., & Wen, D. W. M. (2018, December). Evolution of Advanced
Persistent Threat (APT) Attacks and Actors. In International Computer
Symposium (pp. 76-81). Springer, Singapore.
Husari, G. (2019). Data-Driven Analytics for Extracting and Inferring Threat Actions and
Attack Patterns from the Unstructured Text of Cyber Threat Intelligence (Doctoral
dissertation, The University of North Carolina at Charlotte).
Johnson, A. (2019). Utilizing Role Based Modeling Language to Determine a System’s
Safety From an Advanced Persistent Threat.
Li, M., Huang, W., Wang, Y., Fan, W., & Li, J. (2016, June). The study of APT attack stage
model. In 2016 IEEE/ACIS 15th International Conference on Computer and
Information Science (ICIS) (pp. 1-5). IEEE.