[ Technical Teardown: Malware Targetting Singapore Banks ]

[ Background ]
Originally i wanted to let one of the local student to write about it but he was busy with school, internship and solving challenges.
It’s also been a very long time since we written any “Technical Teardown” on malware/exploits here.

I got hold of this particular malware sample just days after these 2 reports.

The Association of Banks in Singapore (ABS) released an advisory to alert consumers on malware targeting mobile banking customers in Singapore.
We hope this technical teardown might be interesting to some of you.

[ Sample used in the analysis ]
MD5: 76745CE873B151CFD7260E182CBFD404
SHA1: 0F7C012466157891C1D12ADDDD4DFA0B8291DD75
Malware Sample: 76745ce873b151cfd7260e182cbfd404
Password is “infected29A”

Since it’s an Android malware, let’s check the permissions of this malware and further dissect it. Now, use apktool and run the following command:

Now let’s take a look at the AndroidManifest.xml file, you should see the following and the permissions requested by the APK file.

As we can see from the AndroidManifest.xml, it ask for quite a lot of permissions and it’s probably obfuscated.

Looking at the strings.xml and styles.xml, we can see that customised themes had been created for various banking applications.
This malware targets a number of banks by trying to mimic the authentic one and phishes for important banking information from the infected user as shown below.
Figure 1 – Customised Themes

[ Junk Codes as Anti-Analysis? ]
It took me 20-30mins to realise that this author uses lots of junk code. Possibly with the purpose of deterring people like me from reversing the malware.
Import metadata such as strings and function names are also obfuscated as shown in the image below.

Figure 2 – Junk Code with no useful functionality

Since the malware sample is heavily obfuscated, some of the things that i usually look out for is commands like Base64.decode or loadDataWithBaseURL or sendTextMessage

[ Revealing of Hidden Configuration Strings ]
So i did a quick grep and found out that it did use “Base64.decode” as shown below.
Figure 3 – Base64 encoded string

The following is the base64 string which i extracted from the malware.

After doing a base64 decoding on it, i got back the following strings.

As we can see, the decoded strings contained IP addresses and other interesting strings. We also can safely assume that the malware author uses “@” as a delimiter.
For better illustration, i replaced all the “@” with newline.

[ Assessment of Malware ]
We can see that the IP addresses are the C&C servers communicating on port 34580.

Within the malware sample, we also found out that it is targeting victims with the following bank accounts.

Dexia Kommunalkredit Bank
Bank Austria
Erste Bank und Sparkassen (Thanks to Alex Inführ for pointing my mistake.)
RGB (Raiffeisen Banking Group)
George (https://mygeorge.at/)
DK (Deutsche Kreditbank AG)
Bawag (BAWAG P.S.K)


St George
National Australia Bank

New Zealand

Bank of New Zealand
ANZ Bank New Zealand



Hong Kong

Bank Of China
Hang Seng Bank

I’ll update this post later on how we can reverse such malware much more easily.
In the meantime, i do hope you enjoy reading it.

Happy Reversing,
Jacob Soo