A New Malware Attack Pattern Generalization.

Malaysian Technical Universities International Conference on Engineering & Technology (MUiCET 2011)

A NEW MALWARE ATTACK PATTERN
GENERALIZATION
Robiah Y., Siti Rahayu S., Shahrin Sahib, Mohd Zaki M., Faizal M. A., Marliza R.
Faculty of Information and Communication Technology
Univeristi Teknikal Malaysia Melaka,
Durian Tunggal, Melaka,
Malaysia

Malaysian Technical Universities International Conference on Engineering & Technology (MUiCET 2011)
Abstract— The significant threats of malware are still
continuing due to their rapid distribution nature on the
internet. The malware attack pattern from nine different attack
scenarios have been extracted from various logs at different
OSI layers such as victim logs, attacker logs and IDS alert log.
These malware attack pattern are further analyzed to form the
general malware attack pattern which describes the process of
malware infection. This paper proposes a general attack
pattern for malware in three different perspectives which is
attacker, victim and victim/attacker or multi-step attack using

only traditional worm variant. Hence, the general malware
attack pattern can be extended into research areas in alert
correlation and computer forensic investigation.
Index Terms — malware attack pattern, log, malware attack

I. INTRODUCTION
It is essential to identify the dynamic propagation of the
current malware infection so as to protect us against the
attack of the future malware. Their fast spreading character
in exploiting the vulnerability of the operating system has
threatened the services offered on the internet. Thus, there is
a need to find a solution to detect and predict the propagation
of the malware.
This paper propose the general malware attack pattern for
detecting and predicting the malware by examining the
various OSI layer’s log from the malware source and the
other machine that are infected with it and investigate the
evidence leave by the attacker which is considered as the
attack pattern. For the purpose of this paper, the researchers
have select nine scenarios: scenario A to scenario I; and used

Blaster, Sasser and Lovesan.T variants during the
experiment. This attack pattern is based on the fingerprint of
these three variants’ attack on victim’s logs, attacker’s logs
and Intrusion Detection System (IDS) alert’s log.
II. RELATED WORK
A. What is Malware?
Malware is a program that has malicious intention as
mentioned by [1]. Nevertheless [2] has defined it as a
generic term that encompasses viruses, Trojans, spywares
and other intrusive codes. The malware implies malice of
forethought by malware inventor and its intention is to
destroy a system. Moreover, malware even if it has
destructive consequences, is not a defect in a legitimate
software program.
According to [3], generally malware is consists of three
types of malware of the same level as depicted in Fig. 1
which are virus, worm and Trojan horse.

T
r

o
j
a
n

M
W
a
o
l
r
m w
a
r
e

V
i
r
u

s

Fig. 1. General Malware Taxonomy by Karresand

For the purpose of this paper, the researchers have scope
the malware to traditional worms. This is due to the fact that
these types of worm are still persistent in internet as claimed
by [4] and [5]; and hence they are selected for further
research. According to [6], worm taxonomy can be further
categorized into four types of worms which are traditional
worm, e-mail worms, windows file sharing worm and hybrid
worm. The most well-known traditional worms such as
Blaster, Sasser, Code Red and Slammer, are the main threats
to the security of the internet. Thus, the researchers have
selected Blaster, Sasser and Lovesan.T variants for the
experiment.
The Blaster worm launch on August, 11 th 2003 infected at
least 100,000 Microsoft Windows systems and cost millions
in damage. In spite of cleanup efforts, an anti-worm, and a
removal tool from Microsoft, the worm persists [6].

Meanwhile, Sasser was first noticed to spread on April 30th,
2004 and then Lovesan.T is another name for Blaster with
variant T has been found on 21st April 2004 and has similar
scanning characteristics with Sasser but different malware
code. Most of these computer worms affect computers
running vulnerable versions of Windows XP and Windows
2000 and have the potential to generate the multi-step attack
which can increase the recovery cost of the infected system
and would initiate serious cyber crimes.
Blaster worms spreads by exploiting DCOM RPC
vulnerability in Microsoft Windows as described in
Microsoft Security Bulletin MS03-026. The worms scan
port 135 on random subnets in sequential or random order,
and the target are the discovered systems. The exploit code
opens a backdoor on TCP port 4444 and instructing them to
download and execute the file MSBLAST.EXE from a remote
system via Trivial File Transfer Protocol (TFTP) on UDP
port 69 to the %WinDir%\system32 directory of the infected
system and execute it as stated by [7]. The goal of the
Blaster attacker is to make the system unstable by

terminating the RPC services and causes the system to
reboot. Meanwhile, Sasser spreads it code by exploiting a
buffer overflows in the component known as LSASS (Local
Security Authority Subsystem Service) on the affected
operating systems. This malware scans different ranges of IP
addresses and connects to victim’s computers primarily
through TCP port 445 and it may also spread through port
139.
B. What Is Attack Pattern?

Malaysian Technical Universities International Conference on Engineering & Technology (MUiCET 2011)

An attack pattern is a method to cause an exploit against
software used by attackers as stated by [8]. It is a systematic
explanation of the attack goals and attack strategies for
defending against attack. Moreover [9] has described that an
attack pattern as the steps in a generic attack, while [10] has
clarify the term attack pattern as the attack steps, attack goal,
pre-conditions and post-conditions of an attack. Thus, an
attack pattern is recognized as one of the important element

to protect from any potential attack. Subsequently, [11] and
[12] have discussed on issues related to how the attack is
performed, the attack goals, how to defences against the
attack and how to trace once it has occurred. Nevertheless,
based on the research, the victim’s perspective is not
considered as the focus is on the attacker’s perspective only.
Thus, in this research, the researchers has proposed the attack
patterns that focus on the attacker’s, victim’s and
attacker/victim’s (multi-step) perspectives to present a
logical perception on how the attack is accomplished and the
effect caused by the attack.
III. ATTACK SCENARIO
In this experiment, nine attack scenarios: scenario A to
scenario I are designed using the framework which consists
of four phases: Network Environment Setup, Attack
Activation, Log Collection and Log Analysis as described in
[13]. The attack scenario A, B, C for Blaster attack can be
referred to [14] and scenario D, E, F for Sasser attack can be
referred to [15]. Each attack scenario is attained through
thorough log analysis.


In this attack scenario, the hosts that are marked with
135, 4444, 69 and 3xxx shows that it has been successfully
exploited by the attacker and this host has been infected. In
this case, port 3xxx is port 3033 and it is the communication
port use between Selamat and Mohd. Port 3xxx is generated
randomly by this variant as it can be any number from 3000
to 3999. Hence, similar to Sasser.B’s attack, the researcher
has decided to call this port as 3xxx. Meanwhile, those
marks with port 135 shows the attacker is trying to
communicate with the victims by scanning the victim’s IP
address.
IV. ANALYSIS AND FINDINGS
The nine attack scenarios are further analysed and the
example of the detail analysis can be referred to [13] and
[14] and the findings from this analysis are used as the
primary guideline in developing the general malware attack
pattern. These attack patterns are constructed in three
different perspectives: attacker, victim and victim/attacker or
multi-step attack. The details of these perspectives are

elaborated in the following sub-sections.
A. Analysis of General Malware Attack Pattern in Attacker
Perspective
In the attacker perspective, there is significant attack
pattern found in the analysis of this general malware’s
attacker pattern and its summary is shown in TABLE I.
TABLE I
Summary on general malware’s attacker pattern
(attributes found=√, attributes not found=nil)

Fig. 2

Lovesan.T attack in scenario G which consists of first
step and multi-step of attack
The diverse logs involve in this analysis are divided into
two categories which are host logs and network logs. The
host logs categories: personal firewall log, security log,
system log, application log and network logs categories: alert
log by IDS. The sample of scenario G for Lovesan.T attack
is as shown in Fig. 2 where the analysis of scenario G shows

that the Lovesan.T attack is activated in Selamat and this
host has successfully exploited hosts Mohd, but partially has
exploited Ramly. Subsequently, hosts Mohd which has been
previously exploited by Selamat has organized an attack on
host Abdollah and this attack is called multi-step attack.
Later on, Abdollah attacks Sahib and then Sahib attacks
Tarmizi.

General General

With reference to TABLE I, the data detected in attacker’s
personal firewall log for all malware’s scenario have similar
log attributes which are action, protocol and destination port.
Therefore, the generalized log attributes for scan and exploits
attack steps are action, protocol and destination port.
Meanwhile, in the attacker’s security log the log attributes
selected are event id and image filename. For system log, the
data can only be detected in Sasser.B’s and Lovesan.T’s
scenario; and, application log can only be found in
Sasser.B’s scenario.

However, the researcher has decided to consider the
availability of the data detected in the general malware
attacker pattern due to the fact that both logs are not

Malaysian Technical Universities International Conference on Engineering & Technology (MUiCET 2011)

necessarily generated once it is being infected by the
malware, unless the device is restarted.
Hence, the
generalized log attributes for both logs are event id and event
message. In the IDS alert log, the data detected in all
malware’s scenario are similar, thus the generalized log
attributes are error message and source IP address.

B. Analysis of Malware Attack Pattern in Victim
Perspective
In victim perspective, there is significant attack pattern
found in the analysis of this general malware’s victim pattern
and the summary of the victim pattern is shown in TABLE II
and the details are discussed.
TABLE II
Summary on general malware’s victim pattern
(attributes found=√, attributes not found=nil)

General General

All of the logs involved: personal firewall log, security log,
system log, application log and IDS alert log in TABLE III
have the similar log attributes detected as in the general
malware’s victim pattern except for attributes found in the
IDS alert log. In the IDS alert log, the attributes for the
victim attack pattern are destination IP address and
destination port whereas the attribute for multi-step attacker
pattern is source IP address only. Therefore, log attributes
selected for this general multi-step attacker pattern are
action, protocol, destination port, event id, image filename,
event message, error message, source IP address, and
destination IP address.

General General

With reference to TABLE II, all of the logs involved:
personal firewall log, security log, system log, application
log and IDS alert log have the similar log attributes detected
as in the general malware’s attacker pattern. Therefore, the
log attributes selected for this general victim pattern are
action, protocol, destination port, event id, image filename,
event message, error message, source IP address, and
destination IP address.
C. Analysis Of Malware Attack Pattern in Multi-Step
(Victim/Attacker) Perspective

The multi-step attacker’s data have been detected in all
malware’s scenario. The summary of the general multi-step
attacker pattern is represented in TABLE III and the details
of the multi-step attacker’s logs are discussed.
TABLE III
Summary on general malware’s multi-step attacker
(victim/attacker) pattern
(attributes found=√, attributes not found=nil)

In this analysis, the researcher has identified the attributes
involved in the victim, attacker and multi-step attacker
pattern. These findings are further used to construct the
proposed general malware’s attacker pattern.

V.

PROPOSED GENERAL MALWARE
ATTACK PATTERN

The general attack pattern for malware is designed based
on the finding from the attack pattern analysis done on
Blaster.A, Sasser.B and Lovesan.T. In constructing the
general malware’s attack pattern, the researcher has decided
to segregate the logs into two categories which are called
primary log and secondary log. In primary log, all of the
information gathered from this log is pre-requisite. From
this log, the researcher can determine the perspective of the
attacker without gathering the information from the
secondary log. In this case, personal firewall log is placed
in the primary log.

Malaysian Technical Universities International Conference on Engineering & Technology (MUiCET 2011)

For the secondary log, most of the log gathered from
security log, system log, application log and IDS alert log
are not necessarily the main factor to determine the
perspective of the attacker. This secondary log is considered
as supportive information to the researcher [16] and not
necessarily true in case of alert gathered from IDS alert log.
Sometime the alert from IDS can turn into false positive or
false negative alarm. In case of security log, system log and
application log; all of these logs are not necessarily
generated once it is being infected by malware; unless the
device is restarted, then only the log is generated. Hence,
this secondary log is more or less unreliable in certain
situation, but act as supportive information in determining
the attacker’s perspective. The following section describes
the details on the primary and secondary log involved in
the attacker, victim and multi-step attacker pattern.

In general malware’s pattern for victim as depicted in Fig. 4;
the finding is based on the discussion in analysis of general
malware’s victim perspective.

This research proposed the general malware attack pattern
based on victim, attacker and multi-step point of view. The
following section describes the details.
A. General Attacker Pattern
Based on the finding from general Blaster.A, Sasser.B
and Lovesan.T malware’s attacker analysis, the overall
malware’s attacker pattern is generalized in Fig. 3.
Fig. 4 General Malware’s Victim Pattern
With reference to Fig. 4, the log files and attributes for the
scan, exploit and impact/effect attack steps are similarly
found in general malware’s pattern for the attacker in Fig. 3.
The only main difference is on the network level where the
alarm’s general attribute found in IDS alert log are source IP
address, destination IP address and destination port.
Moreover, this alarm is found during exploiting and
impact/effect activities compared to scanning and exploiting
activities found in general malware’s attack pattern.
C. General Multi-step (Victim/Attacker/) Pattern

Fi
g. 3 General Malware’s Attacker Pattern
In primary log, the scanning and exploiting activity can
only be found in personal firewall log. These logs have the
general attributes of action, protocol and destination port.
Meanwhile, in secondary log, on host level, the impact can
be found in security log, system log and application log.
These logs have the general attributes of event id, image
filename and event message. Consequently, on network
level, both scanning activity and its impact/effect can be
found in IDS alert log and the general attributes are error
message and source IP address correspondingly.
B. General Victim Pattern

According to the finding for multi-step attacker pattern as
discussed in the analysis of general malware’s multi-step
perspective; the general pattern for malware’s multi-step
attacker (victim/attacker) pattern gathered in Fig. 5 is similar
to the general malware’s victim pattern except for
impact/effect in network log.

Malaysian Technical Universities International Conference on Engineering & Technology (MUiCET 2011)
[1]

[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]

[11]
[12]

Fig. 5 General Malware’s Multi-Step Attacker Pattern
The considered attributes are only destination IP address and
destination port for victim; and error message and source IP
address for multi-step attacker (victim/attacker) pattern. The
general malware’s victim and attacker pattern are used for
developing a basic malware’s attack model, while the general
multi-step attacker pattern is used to develop multi-step
malware’s attack model which will be further discussed in
next section.
VI. CONCLUSIONS AND FUTURE WORKS
In this paper, the researchers have analyzed diverse logs in
order to identify the attack pattern from attacker and victim
perspective in nine different attack scenario: scenario A to
scenario I. The output of the analysis are the proposed
general malware attacker attack pattern, general malware
victim attack pattern and general malware multi-step attack
pattern. This general malware attack pattern is then extended
to be further used in designing malware attack model. The
finding is essential for further research in alert correlation
and computer forensic investigation.
ACKNOWLEDGEMENT
We thank to Universiti Teknikal Malaysia Melaka for the
Short Grant funding (PJP/2009/FTMK (8D)S557) for this
research project.

[13]
[14]

[15]

[16]

X

REFERENCES
Mihai Christodorescu , Somesh Jha , Sanjit A. Seshia , Dawn Song ,
Randal E. Bryant, “Semantics-Aware Malware Detection”,
Proceedings of the 2005 IEEE Symposium on Security and Privacy,
p.32-46, May 08-11, 2005
Vasudevan, A., & Yerraballi, R., “SPiKE: Engineering Malware
Analysis Tools using Unobtrusive Binary-Instrumentation”.
Australasian Computer Science Conference (ACSC 2006),2006
Karresand, M., “A proposed taxonomy of software weapons” (No.
FOI-R-0840-SE): FOI-Swedish Defence Research Agency, 2003.
IBM. (2011). IBM X-Force® 2010-Trend and Risk Report. Technical
Report for IBM.
Bailey, M., Cooke, E., Jahanian, F., Watson, D., & Nazario, J. (2005).
The Blaster Worm: Then and Now. IEEE Computer Society.
Lazarevic, A., Kumar, V. & Srivastava, J. (2005). Managing Cyber
Threats. On Massive Computing: Springer US. pp. 19-78.
McAfee. (2003). Virus Profile: W32/Lovsan.worm.a [Electronic
Version].
Retrieved
23
July
2009
from
http://home.mcafee.com/VirusInfo/VirusProfile.aspx?key=100547.
Barnum, S., & Sethi, A. (2006). Introduction to Attack Patterns.
[Electronic Version]. Retrieved 18 April 2010.
Hoglund, G., & McGraw, G. (2004). Exploiting Software: How to
Break Code. Boston, Massachussetts: Addison-Wesley/Pearson.
P. Moore, A., J. Ellison, R., & C. Linger, R. (2001). Attack Modeling
for Information Security and Survivability. (No. CMU/SEI-2001-TN001.): Pittsburgh, Pennsylvania: Software Engineering Institute,
Carnegie Mellon University.
Fernandez, E., Pelaez, J., & Larrondo-Petrie, M. (2007). Attack
Patterns: A New Forensic and Design Tool. Paper presented at the
IFIP International Federation for Information Processing.
Kent, K., Chevalier, S., Grance, T., & Dang., H. (2006). Guide to
Integrating Forensic Techniques into Incident Response: NIST
Special Publication 800-86.
Robiah, Y., Siti Rahayu, S., Shahrin, S., Mohd Faizal, A., Mohd Zaki,
M., & Marliza, R. (2010). New Multi-step Worm Attack Model.
Journal of Computing, 2(1), 1-7.
Robiah, Y., Siti Rahayu, S., Shahrin, S., Mohd Faizal, A., Mohd Zaki,
M., & Marliza, R. (2010). An Improved Traditional Worm Attack
Pattern.
Proceedings of the 4 th International Symposium on
Information Technology 2010 (ITSIM 2010).
Siti Rahayu Selamat, Robiah Yusof, Shahrin Sahib, Mohd Zaki
Masud, Mohd Faizal Abdollah, Zaheera Zainal Abidin. 2010.
Advanced Trace Pattern for Computer Intrusion Discovery. Journal
of Computing. Vol. 2 No. 6, June 2010.
Barse, E. L. & Jonsson, E. (2004). Extracting Attack Manifestations
to Determine Log Data Requirements for Intrusion Detection.
Proceedings of the IEEE 20 th Annual Computer Security Applications
Conference, pp. 158-167.