<doc>
<cover>
<heading>Whitepaper:
The Inception Framework:
Cloud-hosted APT</heading>


By Snorre Fagerland and Waylon Grange
Blue Coat Systems, Inc
</cover>



<footer>1</footer>

<section>
<heading>Executive summary</heading>

Blue Coat researchers have uncovered a previously-undocumented, highly
automated, and extremely sophisticated framework for performing targeted
attacks. The framework is notable for a number of reasons, including (but not
limited to) its use of a cloud-based infrastructure for command-and-control and its
use of the WebDAV protocol to send instructions and receive exfiltrated
information from compromised systems.

Initial malware components were embedded in Rich Text Format (RTF) files.
Exploitation of vulnerabilities in this file format is leveraged to gain remote access
to victim’s computers.

The framework, thus far, has been using the services of a cloud service provider
based in Sweden, CloudMe.com, for its main command-and-control
infrastructure. Malware payloads designed for a wide array of potential devices,
including home routers and mobile devices running iOS, BlackBerryOS or
Android, were also recovered during the course of our research.

The framework is designed in such a way that all post-infection communication
(i.e. target surveying, configuration updates, malware updates, and data
exfiltration) can be performed via the cloud service. The malware components of
this framework follow a plugin model, where new malware rely on other,
previously delivered malware components to interact with the framework.

Initial attacks were largely focused on Russia and a few other Eastern European
countries. However, we have later seen that attackers are interested in targets all
over the globe.

The framework is itself target-agnostic, and seems highly automated.

The operational security exhibited by the attackers is very good - among the best
we have seen. Most interaction between attackers and their infrastructure is
performed via a convoluted network of router proxies and rented hosts.

Although the attackers have left a few clues, we have been unable to provide
attribution with any degree of accuracy.
</section>



<footer>2</footer>

<section>
<heading>Introduction</heading>

The use of software vulnerabilities in order to execute malicious software on
unsuspecting users’ computers is an important parameter to monitor. This
method of attack is not only known to have a considerable success rate, it is also
often deployed by resourceful attackers and, as such, marks a threat worth
paying attention to.

The use of exploits in document formats like PDF, DOC and RTF is in some
ways especially noteworthy. Documents are commonly exchanged via mail,
which make them perfect for email-borne targeted attacks; what is otherwise
known as spear phishing.

In March, 2014, Microsoft published information about a new vulnerability in Rich
Text Format (RTF). This vulnerability, named CVE-2014-1761 (Microsoft Word
RTF Object Confusion), had already been used effectively by attackers at the
time of the announcement. Two previous vulnerabilities in the RTF file format,
known as CVE-2010-3333 and CVE-2012-0158, had become, by that time,
mainstays of targeted attacks, so we tracked how attackers implemented this
new exploit with keen interest.

By late August, we identified a malware espionage operation that used both the
CVE-2014-1761 and CVE-2012-0158 vulnerabilities to trigger execution of the
malicious payload, and which leveraged a single cloud service as the backbone
of its entire visible infrastructure.

When we examined the suspicious documents, it was discovered that they were
somewhat anomalous compared to the run-of-the-mill material. They turned out
to belong to a highly advanced and professional targeted attack framework,
which utilized a complex series of techniques to survey potential targets.

Due to the many levels of obfuscation and indirection, we named this the
Inception framework; but there ends all similarity with the movie by the same
name. Leonardo DiCaprio is not associated with this investigation.
</section>



<footer>3</footer>

<cover>
<heading>PART I:

CloudMe</heading>
</cover>



<footer>4</footer>

<section>
<heading>Use of trojanized documents</heading>

We initially knew little about who the actual targets were; apart from one. In that
particular case we had the actual phishing email, so we knew the apparent
recipient – the CEO of a large Russian bank. The email was apparently sent from
“Mrs. World”; note the Mrs., and not Miss - World.


<figure></figure>

<caption>The weaponized Microsoft Word document attached to the email message
(“photo.doc”) contained two separate exploits: one targeting the vulnerability
detailed in CVE-2012-0158 (MSCOMCTL ActiveX Buffer Overflow); the other
targeting the aforementioned CVE-2014-1761.</caption>




<footer>5</footer>


<figure></figure>

<caption>Above: “Mrs. World”. Text and picture apparently taken from the news site mk.ru</caption>


We soon discovered that our malware repository contained several other, similar
documents, but these had come from other sources which did not include the
email message, or any identifiable information about the targets. However, the
text of the documents covered a variety of topics mostly revolving around
Russian issues relating to a variety of business sectors. The following pages
highlight a representative selection of these documents.




<footer>6</footer>


<figure></figure>

<caption>An article cribbed verbatim from the
Novye Izvestiya news Web site
about the Russian financial situation
in light of the Ukrainian crisis.</caption>

<figure></figure>


<caption>An application form to participate in
a seminar supposedly organized by
Russia’s Federal Service for
Defense Contracts (“Федеральная
служба по оборонному заказу”)
scheduled for Sept 24/25 2014.</caption>

<figure></figure>


<caption>An article, in English, about the
Ukraine situation taken from the
Financial Times (UK) newspaper.</caption>

<figure></figure>


<caption>An “advertisement” from a supplier
of diesel engines and related
mechanical services. The letter lists
the Russian navy and the Border
Guard department of the FSB
among their customers.</caption>



<footer>7</footer>


<figure></figure>

<caption>“Organigrama Gobierno Rusia.doc”
– a summary profile of several high-
level Russian government officials –
originally submitted to VirusTotal
from an IP address in Spain.</caption>

<figure></figure>


<caption>An advertisement of a used car for
sale that purportedly originated from
an employee at the German
Embassy in Moscow.</caption>

<figure></figure>


<caption>Invitation to Russian Art Week</caption>

</section>


<footer>8</footer>

<section>
<header>Document metadata</header>


All documents that we have found so far have been rather standard Word
documents, of the old 97-2003 compatible format based on OLE2.

Such documents can, and typically do, contain quite a bit of metadata: The name
of the document creator; the user who edited it most recently; the name of the
company whose copy of Word was used to create the document, et al. Users can
optionally configure Word to remove this metadata when a document is saved,
and that’s exactly what the creator of these documents did, stripping out this
potential source of attribution data.

However, Word documents in this format contain additional information, if you
know where to look.

All Word documents of this format contain what’s known as a File Information
Block (FIB). The FIB contains information about the file’s internal structure, and
also – to some extent – data on the program used to create the file. In the case
of the samples we analyzed, all of the documents were saved using the same
build of Microsoft Word from Office14 (better known as Office 2010).

In addition, documents can contain slack space in which old data remains. For
example, the decoy that came with the attack named “Organigrama Gobierno
Rusia.doc” contains Visual Basic leftovers indicating that it originally was created
on a computer that was configured to be used by a native Spanish speaker,
apparently by an advisor at the Spanish Embassy in Moscow. This document
was presumably obtained by the attackers and repurposed for the attack.


<figure></figure>
</section>
<footer>9</footer>

<section>
<heading>Targeted verticals</heading>


Despite the limited information at our disposal about the targets of these attacks,
their content reveals some context about who the possible targets may have
been.

First of all, we have the decoy documents which indicate an interest in:
<list>
   -   Embassies
   -   Politics
   -   Finance
   -   Military
   -   Engineering
</list>
We also have a set of phishing mails, which were targeted at:
<list>
   -   The finance sector in Russia
   -   The oil and energy industry in Romania, Venezuela, and Mozambique
   -   Embassies and diplomats from various countries
</list>

</section>

<footer>10</footer>

<section>
<heading>Shellcode</heading>


The shellcode used is a pretty standard variant previously used by a number of
campaigns typically operating out of China, but with some minor changes. The
malicious content is stored inside the document in encoded form, and the
shellcode decodes and writes this to disk.

<figure></figure>


<caption>Above: The decoding loop</caption>


Upon successful execution this code drops a Word document and a Visual Basic
script. The Word document is displayed to the user to avoid arousing any
suspicion while the script is executed in the background.

Unusual for many exploit campaigns, the names of the dropped files vary; for
example HyHa9AJ.vbs, ew_Rg.vbs, 0_QHdN.vbs, etc. – clearly randomized in
order to avoid detection by name.


</section>

<footer>11</footer>

<section>
<heading>Visual Basic Script dropper</heading>


The VBScript dropper code is also a little unusual. It declares a Windows
Management Instrumentation (WMI) object in order to reach components like the
registry and file system. This seems adapted from Microsoft example code, like
the one found at http://msdn.microsoft.com/en-us/library/aa387236(v=vs.85).aspx

<figure></figure>


When the VBSript is run it drops two files to disk. One is a polymorphed dll file
and the other a binary data file with no obvious internal structure. This data file
turns out to be encrypted using AES-256.




<footer>12</footer>

The files will be installed in several locations:
<list>
%WinDir%,            ex. “C:\Windows”.
%APPDATA%,           ex. “C:\Users\USERNAME\AppData\Roaming”
%ALLUSERSPROFILE%, ex. “C:\ProgramData”
%CommonProgramFiles%, ex. “C:\Program Files\Common Files”
%USERPROFILE%,       ex. “C:\Users\USERNAME”
</list>
These locations will vary some between operating system versions.

The VBScript then sets a startup key in the
“HKCU\Software\Microsoft\Windows\CurrentVersion\Run” registry path to
execute the DLLs at boot time.

Regardless of whether the registry launches the DLL or when another malware
executable starts the DLL directly, the DLL is launched using regsrv32.exe with
the /s (silent) option.

The names of these dropped files change from attack to attack. The one above
drops ctfmonrc.dll. Other names observed were:
<list>
ctfmonm.dll
ctfmonrn.dll
wmiprvse.dll
alg.dll
dwm.dll
</list>
The encrypted data files are named using random words apparently taken from a
dictionary – “acholias”, “arzner”, “bicorporate”, “crockrell”, “damnatorily” etc.

</section>


<footer>13</footer>

<section>
<heading>DLL payload</heading>

Looking at one of the dropped dlls we can see the authors originally called it
95Num3P3gm.dll.polymorphed.dll. When executed it will rebuild the original dll
(95Num3p3gm.dll, presumably), load it from memory and pass over execution.

<figure></figure>


<caption>In the early stages of our research, most other payloads followed the same
naming convention, eg., fvK3J15B5d.DLL.polymorphed.DLL;
LvwU9gnFO.DLL.polymorphed.DLL; NR5vaFTe9R.DLL.polymorphed.DLL;
hs78lg7x5F.DLL.polymorphed.DLL, etc. More recently collected samples no
longer contain the “polymorphed” string.</caption>

It is hard to describe the polymorphed dlls with any real depth, as there is little
consistency between them. When two nearly identical dlls are encoded using the
polymorphic scheme there is very little code in common. The call graphs are
different and key functions have varying number of arguments. The polymorphing
mechanism also generates, and inserts, unique functions all of which make calls
to different floating-point operations – all done just to obfuscate the actual
decoding process. The sizes of buffers allocated are also randomized to mask
their intent.




<footer>14</footer>


<figure></figure>

<caption>A portion of one of the dynamically generated functions.</caption>

What is common is that somewhere along the execution cycle is one extremely
large function (over 200 kb in length) where early in a large allocation is made
where the un-obfuscated binary will be placed. The binary is then built from de-
obfuscating segments of it that have been dispersed through the ‘.rdata’ section.
The order, size, and locations of these segments vary from build to build but
somewhere near the end of the large function there will be a call to a subfunction
that loads the PE image into memory, followed by a call to free the PE image
allocation from memory. Simply halting execution before this function call permits
a researcher to extract the reconstructed DLL from memory.


<footer>15</footer>


<figure></figure>

Here, pausing execution before the call to ‘load_pe_from_memory’ reveals the
extracted PE at the memory address pointed to by edx.

This reconstructed DLL, once loaded, will decode a configuration structure from
its ‘.data’ section which contains three important details: the name of the
encrypted data file dropped by the VBScript; the AES key used to decrypt the file;
and the name of a unique global mutex to hold while running to prevent multiple
instances.

This configuration information is used to load the encrypted file into memory and
decrypt it. This turns out to be yet another dll. The first ordinal exported by this dll
is located and then called, passing in the configuration and the name of the
encrypted file on disk as parameters.




<footer>16</footer>


<figure></figure>

This last dll is the heart of the threat (originally called q5Byo.dll in this instance.
This file contains the true intent of this campaign. It is designed as a survey tool.
The PE file gathers system information including OS version, computer name,
user name, user group membership, the process it is running in, locale ID’s, as
well as system drive and volume information. All of this is encrypted and then
sent to cloud storage via WebDAV.




<footer>17</footer>


<figure></figure>

<caption>The malware installation chain</caption>


</section>

<footer>18</footer>

<section>
<heading>WebDAV cloud usage</heading>

WebDAV is a communication standard that allows file management over HTTP
or HTTPS. Windows allows WebDAV sessions to be mapped as network
resources.

The use of WebDAV as the communication channel is atypical for most malware
samples we see. By using a network resource, the actual web traffic originates
from the system itself, and not from the process in which the malware resides.
Additionally, once the resource is established, the malware can transfer files to
and from the command and control servers using standard file IO commands.

All the authentication information for the WebDAV session including the URL,
folders, path, user name, and password is stored within this last DLL in another
AES-encrypted configuration structure in the binary.

A unique path, username, and password were used for each malware instance
we’ve seen in the wild. This allows the attackers to uniquely identify every
targeted attack and track how successful each phishing campaign is.

Also contained within the configuration structure is information on how to name
the survey data on the remote file server. The binary reads from its configuration
a string on how to generate the remote filename, and a list of extensions to use.
An example would be “_1-7d_0-8s”, [“TIF”, “TAR”, “SIT”] which instructs the
binary to generate a filename with 1 to 7 numeric digit characters followed by 0 to
8 ASCII letters with one of the three listed extensions such as “664gher.TAR”.
The survey is then uploaded to the server in a specified folder with the generated
name.

Files are compressed using a modified LZMA-compression and encrypted using
AES cipher-block-chaining (CBC) before being uploaded to the cloud server.

The binary also checks a separate folder on the cloud service designated to
contain new configuration information. If such a file is present on the server, the
malware downloads the new configuration file then deletes it from the server.




<footer>19</footer>

The cloud storage provider in every case we have seen was the Swedish
company CloudMe.com, which offers free and paid WebDAV cloud storage.

<figure></figure>


The URI model used by the malware is
http://webdav.cloudme.com/%username%/CloudDrive/ which is a direct
reference to file storage.

It must be noted that the CloudMe service is not actively spreading the malicious
content; the attackers are only using it for storing their files.

We notified CloudMe.com about the abuse of their services. Their CEO, Mr.
Daniel Arthursson, was none too happy about this, and was very helpful in our
further research. CloudMe has shared a great deal of log information related to
this attack. These indicate that there are many other accounts (over 100) likely
related to this attack system. We have no way of verifying this with absolute
certainty, but this is what we regard as a high confidence assumption.




<footer>20</footer>


<figure></figure>

<caption>Distribution of logged victim connections towards CloudMe.</caption>


The cloud accounts are not used for one-way communication only. The malware
also checks configured subfolders for updates; and if these are found they will be
downloaded, decrypted and used as appropriate.

One such case is the franko7046 account, used against the previously
mentioned bank CEO. In this account there was hidden another encrypted
configuration file which the malware downloaded and decrypted.

<figure></figure>


<caption>Above: The configuration file of the depp3353 account. Password is redacted.</caption>



<footer>21</footer>

This is how we found the depp3353 account. In this new account there was
another surprise waiting for us – a download folder with two new encrypted files,
921.bin and 922.bin. Once decrypted, these turned out to be PE executables.
</section>

<section>
<heading>Downloaded plugins: Cloud persistence</heading>

The two new executables are plugins - quite similar to each other and obviously
compiled on the same setup. They are lightweight and intended to pull specific
survey information from their target. Of interest, both of the DLLs originally had
the same internal name (78wO13YrJ0cB.dll). Presumably the same PE
sanitization script and parameters were used on both.

None of these plugins contain any means of CnC communication. Instead, when
they are executed they are passed a pointer to a function to use for sending data
back home. Neither are they ever written to disk. They are executed in memory
only, and once they have completed the memory is freed. This makes these
modules extremely stealthy, flexible and compatible with multiple toolsets
independent of what CnC method is being used.

921.bin retrieves several datapoints about the infected machine: Domain info; a
list of running processes with all loaded modules in each; the list of installed
software; and a complete hardware profile of the target machine. 922.bin
compiles a dirwalk – a complete listing of every file path – of each fixed drive. All
of this information is exfiltrated back via the same WebDAV connection.

This model makes it possible to do the intrusion in steps, with verification stages
in between; and the files will not be easily found on affected computers.

Based on the information gathered from these modules, the attackers appear to
move to the next stage of their attack by placing more new components on the
WebDAV shares. Information about these uploads is limited by the fact that we
do not have the AES keys to decrypt much of the uploaded data, but we have
been able to see some upload patterns.

What we assume to be third-stage plugins appear on the shares as *.bin files of
roughly 72kb. As with other plugins, these are downloaded and deleted from the
share in one go. However, the next day, another *.bin file of the same size will be
uploaded to the share. This is a pattern that repeats itself over all live accounts. It
seems that because the plugins exist in memory only, they are injected daily to
ensure persistence on victim computers. Our theory is that this malware is a
more typical datastealer, and we have observed that after this type of file is
planted on the account, encrypted data uploads from compromised users
increase.

</section>


<footer>22</footer>

<section>
<heading>The Sheep and the Wolves</heading>

Victims of this attack will connect using the Windows WebDAV redirector, and
the HTTP request user-agent string will reflect this. For Windows XP this will
typically be “Microsoft-WebDAV-MiniRedir/5.1.2600”, and for Windows 7 a
common user-agent is “Microsoft-WebDAV-MiniRedir/6.1.7601”.

Security researchers – and there are a few of them - connect in a variety of ways;
first of all, we see a number of connections that are indistinguishable from the
way victims connect. This happens when researchers use lab machines with live
internet access to run the malware. The only way we can tell these are
researchers is because they connect from IP address ranges that are unlikely to
be victims; and they also tend to consist of short-lived sessions.

Some researchers set up scheduled tasks to scan the shares for new updates
and malware. We see a few variations of these – one typical configuration is
where the requests contain a Python-related user-agent string.

Attackers, on the other hand, don’t appear to use Windows.
Common across multiple accounts, multiple IP’s, and over time, is that the
probable attackers have used a HTTP user-agent of “davfs2/1.4.6 neon/0.29.6”.

We know these are not researchers, because we can see malware files being
uploaded by them:

<figure>
[17/Sep/2014:09:42:38 +0200] "PUT
/white3946/CloudDrive/QxM9C/st/V1oINDJtnqy/1768.bin
HTTP/1.0" 201 0 "-" "davfs2/1.4.6 neon/0.29.6"
</figure>
<caption>
Above: Log entry for the account white3946. We have been unable to locate the
malware that uses this account.
</caption>

We have a log fragment in which the attackers uploaded a sequential series of
updates (from 1746.bin to 1774.bin) within 1.5 hours on Sept 17th, spread over
27 different accounts and using 27 different IP addresses in the process.

The user-agent string shows that attackers likely have used a client based on the
open source davfs2 file system for Linux to mount the WebDAV shares.




<footer>23</footer>

This client is used when uploading new malware, but also when the attackers
scan their shares for new victim updates, in which case the shares are
enumerated by requests in a scheduled manner.

<figure></figure>


<caption>An attacker scans the tem5842 account for updates.</caption>

<figure></figure>


<caption>At intervals, scans hop to new IP addresses.</caption>

The attackers have used a large number of IP addresses to access the shares.
As mentioned above, there is a rotation scheme in place in which a new IP
address will be used after a few minutes of access against CloudMe accounts.

These IP’s are distributed widely over geographical locations and service
providers, with a heavy bias towards South Korean ranges.




<footer>24</footer>


<table>
S. Korea                                85   Australia                                 1
China                                    7   Austria                                   1
United States                            7   Bulgaria                                  1
Brazil                                   5   Canada                                    1
Sweden                                   3   Denmark                                   1
Czech Republic                           2   France                                    1
Norway                                   2   Germany                                   1
Romania                                  2   Kuwait                                    1
Russia                                   2   Latvia                                    1
Spain                                    2   Ukraine                                   1
</table>
<caption>Distribution of attacker IP addresses</caption>


At first we thought these IP’s belonged to some commercial proxy service,
particularly since several such proxy services also offer IP rotation. However, this
turned out to be a wrong assumption.
</section>



<footer>25</footer>

<cover>
<heading>
PART II:

Support infrastructure
</heading>

</cover>


<footer>26</footer>

<section>
<heading>An embedded device proxy network</heading>

A superficial examination of the proxy IP addresses that connected to CloudMe
showed them to be internet-connected devices of various kinds. Many were
Korean Tera-EP home routers; but there were several other products
represented.

<figure></figure>


It is believed that the attackers were able to compromise these devices based on
poor configurations or default credentials.

We were able to do some forensic work on a compromised Tera-EP TE-800
device and discovered another dimension of the attacker’s infrastructure.
</section>



<footer>27</footer>

<section>
<heading>Router malware</heading>

Under the ramfs mounted partition we found a stripped and statically linked
MIPS-el binary named tail-. Instances of this were also found under the running
process list.

tail- serves as a SOCKS proxy for the attackers. Each sample of the binary we
were able to acquire was configured with a unique 32byte blowfish key and a
small, encrypted section appended to the end of the binary.

Upon execution the binary uses its hardcoded key to decrypt the configuration
section and retrieve the listening port to use for incoming connections. This acts
as a management interface. From here the attackers can request a specific port
to be opened as one of the following types: SOCKET, SOCKSS, SOCKAT,
SOCKS5, or STATUSPORT.

To prevent anyone else from accessing this service all communication on the
management interface is encrypted using the same blowfish key. This means
that the attackers must maintain a list of where each of these implants are
installed, as well as what port and key each is configured to use.

This setup makes it difficult to identify embedded devices compromised with this
malware by scanning open ports.

In the wild we witnessed the attackers connect to the management port and
request SOCKSS connections. This would open the specified port and wait for
configuration data, which consists of a domain name (webdav.cloudme.com), the
destination port, and a variable length RC4 key, all of which encrypted using the
blowfish key. Once received the malware would attempt to connect to the
domain name on the specified port and would start tunneling all traffic received
from the SOCKSS port to the destination and vise-versa. The communication
between the attacker and the SOCKSS is encoded using the RC4 key. The
graphic below illustrates a typical session.


<figure></figure>
</section>
<footer>28</footer>

<section>
<heading>Additional servers</heading>

The router proxy network provides another layer of indirection masking the
attackers’ infrastructure. However, because we captured traffic through one of
these embedded devices we could identify other parts of their operation.

We identified four IP addresses that connected to the proxy malware:
<list>
Cloud enumerator:
Apparently a rented server at AS34224 NETERRA-AS, Bulgaria
</list>
This host belongs to a Bulgarian VPS service and would use the router proxy to
connect to webdav.cloudme.com. This host does all scanning of webdav shares
for stolen user data, and also uploads new malware components.
<list>
Health checker:
Apparently a rented server at AS5577 ROOT root SA, Luxembourg.
</list>
This IP would make connections hourly and poll the status of the router proxy
malware. This machine is most likely used to track which compromised routers
are currently available for use.
<list>
Unlocker:
Apparently a rented server at AS52048 DATACLUB DataClub S.A. Latvia.
</list>
Traffic from this IP had a very specific purpose: It unlocked routers for proxying in
connection with the sending of phishing emails.

In the wild we observed this IP connect to our router on the malware
management port and specify a SOCKSS proxy port to be opened. Immediately
after, the newly opened port would be connected to by another IP and used to
send phishing emails with malicious attachments.

However, later we observed that the Email sender IP at VOLIA vanished and the
Unlocker server taking over its role as well.
<list>
Email sender:
An IP at AS25229 VOLIA-AS, Ukraine. Possibly a compromised host.
</list>
After a router SOCKSS port was opened by Unlocker, this IP would connect to
the opened port and tunnel its email traffic through the router.

Each of these connections used the correct encryption key, so we know that
these accesses came from the attackers and not some opportunistic third party.



<footer>29</footer>

Mail proxies:

Through our router monitoring we identified two mail proxies used by the
attackers. We were later notified by Symantec (thanks, guys!) about a third.
These servers were hosted on domains that were registered by the attackers,
using domain names clearly meant to look legitimate. This is the only time we
have seen attackers register domains in this investigation.

The mail proxies were:
<list>
haarmannsi.cz       : Spoof of the legitimate domain haarmannsi.com
sanygroup.co.uk     : Spoof of the legitimate domain sanygroup.com
ecolines.es         : Spoof of the legitimate domain ecolines.net
</list>
Registrant WHOIS information seems forged:
<list>
haarmannsi.cz
name:      Sanyi TERRAS
address: R. FREI CANECA 1120
           SAO PAULO
           01307-003
           BR
e-mail:    sanyi_terras@outlook.com
created: 12.06.2014
NS:        ns*.frankdomains.com

sanygroup.co.uk:
name:      Alan
address: Uddmansgatan 13
           Pitea
           Norrbottenalän
           94471
           SE
created: 06.05.2014
NS:        ns*.domains4bitcoins.com

ecolines.es:
name:        Lyisa Almeida
address: N/A
created: 04.06.2014
NS:          ns*.frankdomains.com

.
</list>
</section>



<footer>30</footer>

<section>
<heading>Observed phishing emails</heading>

The connections made from the Ukrainian host to the router were interesting.
After being proxied though the router, each of these would authenticate with one
of the dedicated mail proxies and send out phishing attacks.

From captured traffic it appears that the mail proxies have SOCKSv5 services
running on obscure high ports. We have documented that the attackers log in to
these using apparently randomly generated usernames and passwords, a unique
pair for each server. The mail proxy would then relay the spearphishing mail as
seen below.


<figure></figure>

<caption>Above: Captured SMTP session, sending the malicious attachment MQ1474.doc</caption>

This way the attack can be mistaken to come from legitimate businesses and
trusted organizations. In some cases the organization from which the phishing
email originates would appear to be a known associate to the target.




<footer>31</footer>

The email shown above was one of a number of messages sent to targets in the
oil industry. Investigating the target email addresses, we saw several of these
were found in this public document from the World Petroleum Council, including
some addresses that are, at the present time, no longer valid.

And then, the ground shifted again.
</section>



<footer>32</footer>

<cover>
<heading>
PART III:

Attacks on mobile devices
</heading>
</cover>



<footer>33</footer>

<section>
One of the spearphishing mails we observed coming through the router network
was this one, sent to an address under the gov.py (Government of Paraguay)
domain.


<figure></figure>

<caption>Get WhatsApp now for your iPhone, Android, BlackBerry or Windows Phone</caption>

There was no executable attachment in this mail, but instead a link shortened by
the URL shortener service bit.ly, with the underlying link pointing to an IP address
on a Dutch hosting service. Clicking that link from a Windows PC only yielded a
redirection to the BBC homepages, and using other devices did not give more
data.

The bit.ly service does however provide information on the user creating the
shortened link, and other links associated with this account. In this case, the user
was named nicolatesla53.




<footer>34</footer>


<figure></figure>

<caption>The nicolatesla53 bit.ly profile page</caption>

The nicolatesla53 account was created in July 2014. From Oct 24th to Nov 21st
this user created nearly 10000 shortened links – we harvested 9990 unique
ones. Three IP addresses were used for these links:
<list>
82.221.100.55
82.221.100.60
94.102.50.60
</list>
The links themselves were on this format:
<list>
http://server_ip/page/index?id=target_identifier&type2=action_code
</list>
As far as we were able to tell, there were three main types of action_code:
<list>
743 : Serve malware disguised as WhatsApp updates
1024 : Serve malware disguised as Viber updates
other : Serve MMS phishing content. The code identifies mobile operator and
determines which logo will be displayed when the user follows the link.
</list>

</section>

<footer>35</footer>

<section>
<heading>MMS Phishing</heading>

We have no sample of the actual MMS phishing messages apparently being
sent, but we can see the page served when a user clicks a spammed link. This is
just a dialogue box asking for the password presumably included in the initial
message, and the next stage likely involves download of malicious content.

<figure></figure>


<caption>The password screen for action code 16611 (TELE2)</caption>

We were in the middle of harvesting the servers for data on the various action
codes when they all were abruptly taken offline; so our data on which mobile
operators are targeted is not complete. We managed to get 66 of a total of 190.
The ones we know of are shown below. A full breakdown of mobile operators
and related links is included in the appendix.


<figure></figure>

<footer>36</footer>

The composition of links created for the various mobile operators is quite
interesting, as one can speculate that they represent amount of actual or planned
attacks in different countries. With the top three operators being Vodafone, T-
Mobile and Proximus (Belgacom) it seems these apparent phishing attacks are
less focused on the Russian sphere than the previously discussed malware.

This map is not complete, though. It represents only about 35% (66/190) of all
mobile operators targeted and 66% (3152/4781) of all phishing links we managed
to harvest. In addition, some operators like Vodafone are global actors, so the
map might show an unfair intensity in their HQ locations.

<figure></figure>


<caption>MMS phishing heat map</caption>


The rest of the bit.ly links used the action codes 743 or 1024. And now things
really get interesting. By using mobile device HTTP User-Agents we were able to
trigger downloads of malware components from some of these links.
</section>



<footer>37</footer>

<section>
<heading>Mobile malware: Android</heading>


Accessing the link from an Android User-Agent initiated a download of an
Android installer package named WhatsAppUpdate.apk. The package we
analyzed was 1.2MB in size.

The apparent main purpose of this malware is to record phone call audio.
Recordings are stored as *.mp4 files, and uploaded to the attackers periodically.

The malware is able to collect a lot of other information, not all of which is
actually used:
<list>
   •   Account data
   •   Location
   •   Contacts
   •   External and Internal Storage (files written)
   •   Audio (microphone)
   •   Outgoing calls
   •   Incoming calls
   •   Call log
   •   Calendar
   •   Browser bookmarks
   •   Incoming SMS
</list>
Through the encrypted C&C protocol, the attackers can issue commands and
binary updates to the malware.

It uses a custom DAO/Database scheme which uses accounts belonging to the
virtual community Live Journal (livejournal.com) as data stores. Three such
accounts were found hardcoded in the package:

<figure></figure>


The accounts all state that they belong to Iranian users. This is very likely false.




<footer>38</footer>


<figure></figure>

The text in these posts starts first out in cleartext, but quickly turns into
unreadable gibberish. The HTML source code reveals that the encoded portion is
encapsulated in blog-index tags:

<figure></figure>


The three accounts contain different configuration blocks pointing to C&C servers
apparently located in Poland, Germany and Russia, respectively. Based on
registration data and folder configuration we believe these are legitimate but
compromised Joomla servers.

And then an unexpected oddity shows up in the Java source:

<figure></figure>


<caption>The sign in front of SizeRandomStr is “Truti” - a Hindi word meaning “Error”.</caption>




<footer>39</footer>

We were also able to download a similar malware sample (BrowserUpdate.apk)
from one of the C&C servers. This sample used different online accounts for its
DAO/database functionality, but is otherwise quite similar to the first.
</section>



<footer>40</footer>

<section>
<heading>Mobile malware: Apple IOS</heading>


Using an IOS User-Agent triggered the download of a Debian installer package,
WhatsAppUpdate.deb, also 1.2Mb in size.

This application impersonates a Cydia installer, and can only be installed on a
jailbroken phone.


Once installed, it may collect
<list>
   •   Device platform, name, model, system name, system version
   •   ICCID
   •   User’s address book
   •   Roaming status
   •   Phone number
   •   Carrierbundlename
   •   Iso country name
   •   Carrier name
   •   Wifi status
   •   MAC address
   •   Device battery level
   •   Free and total space
   •   Cpu frequency and count
   •   Total and user memory
   •   Maxsocketbuffersize
   •   Language local identifier and language display name
   •   Default and local time zone
   •   Account data: AccountAvailableServiceTypes, AccountKind,
       AccountSocialEnabled, etc
   •   AppleID
   •   CreditDisplayString
   •   DSPersonID
   •   IOS specific data; ex LastBackupComputerName,
       LastBackupComputerType, iTunes.store-UserName, iTunes.store-
       downloaded-apps etc.
</list>



<footer>41</footer>

These data are encrypted and uploaded to an FTP account which is taken from
an encrypted configuration file named /usr/bin/cores.

In this particular case, the FTP account is located on a legitimate (if struggling)
hosting service in the UK.

In this case, there’s another clue:

<figure></figure>


<caption>The project path in the package contains the name JohnClerk.</caption>

The WhatsAppUpdate project seems derived from an earlier template named
SkypeUpdate.
</section>



<footer>42</footer>

<section>
<heading>Mobile malware: Blackberry</heading>


By now, it came as no surprise when we triggered a download with a BlackBerry
User-Agent. The initial download was a Java Applications Descriptor, a text file
designed for Over-The-Air installation of Java-based applications. This JAD file
contained the locations of the two Blackberry *.COD binaries which we then
could download directly.

The application impersonates a settings utility. This collects:
<list>
   •   deviceName, manufacturerName
   •   platformVersion, softwareVersion
   •   brandVendorId, brandVersion
   •   total and free flash size of the device
   •   amount of memory/storage already allocated
   •   ownerName, ownerInformation
   •   Phone mumber
   •   PIN
   •   IMSI
   •   IMEI
   •   mcc and mnc (Mobile Carrier ID)
   •   cellID
   •   Location area code
   •   isPasswordEnabled
   •   Battery data (level, temperature, voltage, etc)
   •   Installed applications
   •   Address book
   •   APChannel
   •   Connected Network Type
   •   BSSID
   •   DataRate
   •   Profile Name
   •   RadioBand
   •   SecurityCategory
   •   SignalLevel
   •   SSID
</list>
Collected data will be uploaded to a DynDNS domain currently hosted on a US
webhosting service.




<footer>43</footer>


<figure></figure>
<caption>“God_Save_The_Queen” is used as a reference in one of the Blackberry
binaries.</caption>

Since these COD files are also compiled Java code, they are possible to
decompile to original source code. In a similar fashion to the Android version, we
find interesting strings there. This time they are in Arabic:

<figure></figure>


<caption>“Reading files” in Arabic</caption>
</section>



<footer>44</footer>

<cover>
<heading>
PART IV:

Attribution
</heading>
</cover>



<footer>45</footer>

<section>
<heading>Timelines and activity patterns</heading>

The earliest sample of Inception-related malware we have been able to obtain,
was submitted to us in June 2014. However, decoy document metadata shows
that it was created late May. The related cloud account was created just before
that. An examination of the other documents associated with the attacks show
that they have been created at a steady pace all through summer and autumn
2014 and attacks are still ongoing.

Of interest is also the attackers’ activity patterns over the 24h cycle. The main
upload of new components to shares seems to be divided over two high–activity
periods: 6:00 -10:00 UTC and 17:00 - 21:00 UTC. No uploads were seen
between 23:00 and 05:00 UTC.

It is however doubtful how indicative these timeframes are. To illustrate, we
looked into another and more obscure timing factor: The timing of the AES
InitVector random seeds. A random seed is the initial value passed into a
pseudo-randomizer function. The malware uses the random output to create
what is known as an InitVector - a starting point for the AES
encryption/decryption function.

The code used in some of the DLLs indicate that the attackers tend to use the C
time() function to generate random seeds. This function returns values of
granularity down to seconds. Thus random seeds, and ultimately the InitVectors,
are functions of these quite coarse units of time.

The encrypted files uploaded to the WebDAV shares come with their InitVectors
stored at the end of the file. Since we know the time window to be within a few
days of the upload time we were able to brute force the time values that would
generate the corresponding InitVectors. Thus, we were able to say to the second
when the file was created – and most times were identified to be in the range
1500 - 2200 GMT.

Unfortunately, we had to reject these data. The file creation times turned out to
be hours after the files themselves were uploaded to the WebDAV share. Either
the attackers’ system clock is wrong or a fixed offset is added to the random
seed. Either way, the data can’t be trusted; and shows that nothing can be taken
at face value.
</section>



<footer>46</footer>

<section>
<heading>The Chinese connection</heading>

On at least two occasions during our surveillance of the Inception framework, the
malware downloaded something unexpected and wholly different from what we
have discussed until now.

These files were downloaded as encrypted *.bin files from the accounts
carter0648 and frogs6352. When decrypted, these turned out to be dropper
packages containing one dropper executable clearly created for the Inception
framework, and one other, very different executable.

This executable, (sccm.exe, md5 dd8790455109497d49c2fa2442cf16f7) is a
classical Chinese APT implant. It is a downloader and remote shell program,
designed to connect to a C&C server to interact with the attacker and/or
download more malware.

The C&C server in this case is ict32.msname.org.

When connecting to this server, sccm.exe issues the following request:

<figure>
POST /check.jsp HTTP/1.1
Accept: */*..Accept-Language:en-us
Content-Type: application/octet-stream
Accept-Encoding: gzip, deflate
User-Agent: Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)
Host: www.antivir.com
Content-Length: 8
Connection: Keep-Alive
Cache-Control: no-cache
</figure>

This C&C domain is used by many other malwares related to sccm.exe; some of
which share obvious connections to the Quarian malware family, a known APT
intrusion tool.

This development was unexpected for several reasons. First of all, it apparently
breaks the strict, obfuscatory operational security built into the Inception
framework. Inception has the capacity to perform all steps needed for scouting
out and exfiltrating data without resorting to traditional hosted command &
control. By using a well-understood APT tool and a known malicious C&C
domain name, the attackers permit much clearer attribution.




<footer>47</footer>

Another factor which is out of character is the coding style. All Inception-related
malware is written using Visual Studio 2010. The downloaded sccm.exe is written
using Visual C++ 6; and has a PE header compile date of October 2010.
This date can be forged, and indeed, all Inception-related malware has some
level of forgery in the compile dates. However, the sccm.exe compile date
matches the Quarian developer toolset and coding style to a better degree than
the other files distributed through Inception.

Then there is the C&C domain used. According to DomainTools.com the
msname.org domain registration timed out September 27th 2014. It was left
inactive and was not renewed until Nov 12th. This means that the attackers
distributed malware that would be out of action for a long time (last distribution of
sccm.exe was September 26th).

Because of all this we consider sccm.exe as an unreliable indicator. It is likely to
be a red herring purposefully placed on shares where the attackers have seen
signs of access by security researchers.
</section>

<section>
<heading>An odd indicator</heading>

At one instance the attackers seem to have slipped up. Instead of using their
scheduled task, they apparently did something manually on a WebDAV share.
This is visible because the request came from an apparent attacker IP, but used
yet another User-Agent: “gvfs/1.12.3”.

Gvfs is the virtual filesystem for Gnome desktop. The action on the account was
abnormal as well; an apparent file upload:

<figure>
83.53.147.144 - - [02/Sep/2014:09:53:56 +0200] "PUT
/tem5842/Documento%20sin%20t%C3%ADtulo HTTP/1.1" 408 0 "-"
"gvfs/1.12.3"
</figure>

<caption>“Documento sin título” means “Untitled document” in Spanish.</caption>

When WebDAV shares are mapped up as drives by the operating system, any
action taken by the attacker follows the same pattern as on the attacker’s local
drive. In the case above, it seems the attacker attempted to edit a new
document, which by default is given the name “Untitled document” in Gnome.

This might indicate that the attacker’s operating system language is Spanish.
Of course, Spanish is one of the world’s most widespread languages, so one
cannot infer much from this. There is even a small possibility that the
phenomenon is a pure artifact; for example that a Spanish-speaking researcher
connected to the same account using the same Linux-based setup as the
attackers.
</section>

<footer>48</footer>

<section>
<heading>Similarities with Red October</heading>


This attack system shares a number of properties that are somewhat similar with
the Red October campaigns detailed by Kaspersky Labs in 2013.
For more information about this see:

The "Red October" Campaign - An Advanced Cyber Espionage Network
Targeting Diplomatic and Government Agencies
<list>
       -   Target countries and verticals overlap to some extent
       -   The topics of some decoy documents are the same (eg. “Diplomatic
           Car for sale”)
       -   Similar overall loading architecture, with dropping of encrypted binaries
           that are later decrypted and loaded
       -   Exploited documents contain certain similarities (i.e. the magic string
           “PT@T” used as a marker to locate the shellcode)
</list>

However, there are also clear differences. The code is fully rewritten; there
appears to be little code overlap, at least in the initial stage malware. The coding
style is different, with different solutions to programmatic problems, different use
of exception handling, and different use of C++ classes. It’s hard to believe that
the same programmers are responsible for the two code bases.

The Red October malware contained linguistic markers that pointed towards
Russian speaking attackers. No such clues have been found in the Inception-
related malware; there is a marked difference in the attention to detail and
information leakage.

It is certainly possible that the same people have organized both Inception and
Red October, but there are no clear indications to this effect.
</section>



<footer>49</footer>

<section>
<heading>Strings in malware</heading>


The Windows-based malware in this paper generally contains very few
noticeable strings apart from what is commonly found in software, and clearly
randomized strings. What exists – like the word “polymorphed” in the early DLL
versions - is standard English with few discerning features.

This changes a bit when we look at the mobile malware. In the Android malware
we find Hindi comments in the Java source code. In the Iphone malware we find
project paths referencing one “JohnClerk”, and a few typos like “conutry”. In one
of the Blackberry binaries we find the string “God_Save_The_Queen”, a rather
blunt hint towards Britain, as well as Arabic log strings.

These and other indicators have led us to conclude that the Inception attackers
are setting a new standard for deliberate disinformation and red herrings in a
malware espionage operation. Some clues might have been added by accident,
but none of these indicators can be trusted in any way. Thus we are not going to
assume anything about who might be behind these attacks.
</section>



<footer>50</footer>
              
<section>
<heading>Conclusion</heading>


              The whole Inception setup shows signs of automation and seasoned
              programming. The amount of layers used in this scheme to protect the payload
              of their attack seems excessively paranoid. Not only is the initial DLL apparently
              polymorphed using some backend tool – the compile time stamps in the PE
              header are clearly forged, resources are removed so as not to give away any
              location information, and import tables are shuffled around, rendering import
              hashes (aka imphashes) useless.

              The names of the files both when dropped and their original names along with
              the callback directories, paths and mutexes used all seem to be dynamically
              generated.

              The attackers utilize compromised embedded devices – typically routers- on the
              Internet as well as multiple dedicated hosting providers and VPN services to
              mask their identity from the cloud storage provider and others. The same router
              botnet is used as a spreading and management platform for attacks on mobile
              devices as well.

              This suggests that this a large campaign and we’ve only seeing the beginning of
              it. Initially many of the targets were located in Russia or related to Russian
              interests, but as the campaign has evolved we have verified targets in countries
              all over the world.

              It is clear that this infrastructure model does not need to be applied solely against
              a few targets, or even need to be hosted at CloudMe. The framework is generic,
              and will work as an attack platform for a multitude of purposes with very little
              modification.

              The attribution indicators point in different directions and can’t be given much
              weight. These attacks can in theory be the creation of nation states or
              resourceful private entities - we consider it very unlikely that they are performed
              by one or just a few individuals.
</section>


<footer>
© 2014 Blue Coat Systems, Inc. All rights reserved. Blue Coat, the Blue Coat logos, ProxySG, PacketShaper, CacheFlow, IntelligenceCenter, CacheEOS, CachePulse, Crossbeam,
K9, the K9 logo, DRTR, Mach5, Packetwise, Policycenter, ProxyAV, ProxyClient, SGOs, WebPulse, Solera Networks, the Solera Networks logos, DeepSee, “See Everything. Know
Everything.”, “Security Empowers Business”, and BlueTouch are registered trademarks or trademarks of Blue Coat Systems, Inc. or its affiliates in the U.S. and certain other
countries. This list may not be complete, and the absence of a trademark from this list does not mean it is not a trademark of Blue Coat or that Blue Coat has stopped using the
trademark. All other trademarks mentioned in this document owned by third parties are the property of their respective owners. This document is for informational purposes
only. Blue Coat makes no warranties, express, implied, or statutory, as to the information in this document.
</footer>



<footer>51</footer>

<section>
<heading>APPENDIX:</heading>
</section>
<section>
<heading>Exploited RTF sample md5’s:</heading>
<list>
0a0f5a4556c2a536ae7b81c14917ec98
19ad782b0c58037b60351780b0f43e43
20c2a4db77aabec46750878499c15354
23d6fabda409d7fc570c2238c5487a90
3ff9c9e3228b630b8a68a05d6c3e396d
4624da84cae0f8b689169e24be8f7410
4a4874fa5217a8523bf4d1954efb26ef
4dcdc1110d87e91cda19801755d0bcf2
516a514bf744efb5e74839ddaf02a540
5e3ecfd7928822f67fbb3cd9c83be841
685d9341228f18b0fd7373b7088e56a7
822d842704596a2cf918863ea2116633
8488303c2a0065d9ac8b5fecf1cb4fc9
8997d23b3d1bd96b596baee810333897
8cd5974a49a9d6c49294312bf09f64ed
9738faf227bcd12bcab577a0fb58744d
bc196dc8a14484e700169e1a78cf879e
b453ec7fd92bee23846ff36bf903ddc0
2fcbea8a344137421a86b046a6840265
</list>
</section>
<section>
<heading>Dropped first-stage DLL’s</heading>
<list>
0bd0fd3cbbcfddc4048228ce08ca26c2
0bda50e05d575446de55d50c631afb53
0f12614fa7a9bf7bcc951eec7b78658d
2f9ca7680ec0945455988d91d9b325f8
352da994d867eb68a178bb7f2fb672bc
3a4a9d26c9c3c8d0fd697b036216319e
43587e5fcf6770259026ec2ca6f41aa6
4628082e11c75b078ff0465523598040
554d4c4da2e3603282b097b0e68ad11a
670ac2e315088d22b2cb92acffc3e997
71bdd14cbc96badb79dfb0f23c52a9ee
72f020b564bc9771e7efe203881f5ef9
80a7883c33a60b4c0178c9c8fb7d1440
84fa976d9ed693668b3f97d991da0e97
89d851cbd2dc1988bb053235414f8928
a5aeda357ba30d87c1187b644baad8a0
c3f2fb7840228924e5af17787e163e07
d007616dd3b2d52c30c0ebb0937e21b4
d171db37ef28f42740644f4028bcf727
d3886495935438f4a130d217d84ae8cb
ea0d80db2075f789fc88c3fdf6e3d93e

<footer>52</footer>

f2840be535fbaf8b15470d61967d527b
90c93c9b80bbf31dce8434a565a0ec7b
</list>
</section>



<footer>53</footer>

<section>
<heading>Downloaded second-stage plugins:</heading>
<list>
5c3de5b2762f4c5f91affaa6bcadd21b
86b2372297619b1a9d8ad5acdf1a6467
43112e09240caebb3c72855c9f6fc9e5
</list>
</section>

<section>
<heading>Downloaded Chinese malware, sccm.exe:</heading>
<list>
dd8790455109497d49c2fa2442cf16f7
</list>
</section>

<section>
<heading>Router proxy malware:</heading>
<list>
a6b2ce1cc02c902ba6374210faf786a3
83b383884405190683d748f4a95f48d4
62fc46151cfe1e57a8fa00065bde57b0
036fbc5bffd664bc369b467f9874fac4
488e54526aa45a47f7974b4c84c1469a
24a9bbb0d4418d97d9050a3dd085a188
b0c2466feb24519c133ee04748ff293f
62dc87d1d6b99ae2818a34932877c0a4
7c6727b173086df15aa1ca15f1572b3f
80528b1c4485eb1f4a306cff768151c5
e1d51aa28159c25121476ffe5f2fc692
</list>
</section>

<section>
<heading>Android malware:</heading>
<list>
046a3e7c376ba4b6eb21846db9fc02df
b0d1e42d342e56bc0d20627a7ef1f612
</list>
</section>

<section>
<heading>IOS malware (WhatsAppUpdate.deb):</heading>
<list>
4e037e1e945e9ad4772430272512831c
</list>
</section>

<section>
<heading>Blackberry malware:</heading>
<list>
0fb60461d67cd4008e55feceeda0ee71
60dac48e555d139e29edaec41c85e2b4
</list>
</section>



<footer>54</footer>

<section>
<heading>Verified malicious CloudMe accounts (based on malware):</heading>
<list>
garristone                               
franko7046                               
sanmorinostar                            
tem5842                                  
bimm4276                                 
carter0648                               
depp3353                                 
frogs6352  
daw0996    
chak2488   
corn6814   
james9611  
lisa.walker
billder1405
droll5587
samantha2064
chloe7400
browner8674935
parker2339915
young0498814
hurris4124867
</list>
</section>

<section>
<heading>Likely malicious CloudMe accounts (based on access patterns):</heading>
<list>
adams2350                           
adison8845                          
allan1252                           
altbrot                             
amandarizweit                       
anderson9357                        
astanaforse                         
baker6737                           
bear9126                            
bell0314                            
betty.swon                          
brown7169                           
brown7356                           
button8437                          
carter0648                          
carter3361                          
clark6821                           
collins2980                         
cook2677                            
cooper2999                          
cooper7271                          
cox7457                             
cruz3540                            
david.miller                        
depp3353                            
diaz1365                            
din8864                             
evans0198                           
farrel0829                          
ferrary2507                         
ferre7053                           
flores5975                          
fox0485                   
frog0722        
gabriel.gonzalez
garsia7871      
gray7631        
great2697       
green3287       
helen.scott     
helenarix       
hill5289        
jackson4996     
james9521       
john.thompson   
kalo3113        
kas2114         
kenneth.wilson  
king7460        
kol8184         
klauseroi       
ksjdkljeijd     
lariopas        
lopez9524       
lorrens6997     
martinez4502    
miller8350      
minesota1459    
moore6562       
moore7529       
morris9351      
morris9461      
murphy5975      
nedola7067      
nelson0000      
ninazer
norbinov
nul7782
parker0519
poulokoel
pourater
red6039
red6247
reed6865
roges2913
roi5991
ronald.campbell
rosse2681
samantares
scott5008
sebastianturne
swon5826
taylor9297
tem5842
thirt1353
thomas9521
thomson3474
turner3027
vasabilas
visteproi
voldemarton
wer8012
white3946
william.moore
wilson2821
wilson2905
wonder7165
wrong8717
</list>
</section>

<footer>55</footer>

<section>
<heading>Bit.ly-shortened MMS phishing links:</heading>
<table>
Action Code     Operator                HQ location    Links created
95501           Vodafone                UK                         270
81825           T-Mobile                Germany                    213
66968           Proximus                Belgium                    197
67840           China Mobile            China                      173
98491           Zain                    Saudi Arabia               126
58129           Mobilkom (A1 Telekom)   Austria                    124
12081           Orange                  France                     124
24806           Hamrah-e-Avval          Iran                       111
41967           Mobilnil                Egypt                      105
46736           TeliaSonera             Sweden                     100
13911           Mobistar                Belgium                      78
65842           O2                      UK, Germany                  78
70887           Telcomsel               Indonesia                    74
98455           Kcell                   Kazakhstan                   74
94382           Mobilink                Pakistan                     72
12988           Airtel                  India                        65
52378           Vodacom                 South Africa                 63
99578           Maxis                   Malaysia                     59
90298           Swisscom                Switzerland                  59
86791           Wind Mobile             Canada                       56
21522           MTN                     South Africa                 56
26059           MTS                     Russia                       55
67838           Alfa                    Lebanon                      51
96735           Kyivstar                Ukraine                      51
99753           T-Mobile                Germany                      50
24906           Omnitel                 Lithuania                    48
17150           MtcTouch                Lebanon                      43
53272           Ooredoo                 Qatar                        36
77008           BASE                    Belgium                      33
31756           Djezzy                  Algeria                      29
14269           Beeline                 Russia                       29
76587           Omantel                 Oman                         28
44974           Velcom                  Belarus                      27
77849           E-plus                  Germany                      26
76102           Celcom                  Malaysia                     26
31021           Azercell                Azerbaijan                   24
16611           TELE2                   Sweden                       24
18675           Mobifone                Vietnam                      22
65942           T-Mobile                Germany                      20
85993           Sudatel                 Sudan                        20
65090           Diallog                 Belarus                      19
61384           Ufone                   Pakistan                     19
11426           TMCell                  Turkmenistan                 19
58043           Globe                   Philippines                  18
70102           SingTel                 Singapore                    18
90374           Avea                    Turkey                       18
57464           DiGi                    Malaysia                     16
77995           Megacom                 Kyrgyzstan                   15
27964           Warid                   Pakistan                     11


<footer>56</footer>


15029   DSTCom              Brunei             10
70959   Smart               Cambodia           10
83722   Asiacell            Iraq               10
97143   Maroc Telecom       Morocco             9
25786   Magti               Georgia             6
34659   Geocell             Georgia             6
56167   Bakcell             Azerbaijan          5
42397   Dhiraagu            Maldives            5
54375   Telfort             Netherlands         5
43142   Banglalink          Bangladesh          2
90128   EMT                 Estonia             2
24709   MTNL                India               2
92444   Safaricom           Kenya               2
60354   Plus                Poland              2
84899   Sabafon             Yemen               2
14115   Sri Lanka Telecom   Sri Lanka           1
42758   Lycamobile          UK                  1
</table>
</section>


<footer>57</footer>

<section>
<heading>Undetermined MMS phishing action codes (code, number of links):</heading>
<table>
13975   320       54780   12     14659       3       19343   1
51557   119       92529   11     16814       3       20732   1
37020   88        61135   10     20247       3       25938   1
11111   71        89838   10     24037       3       26346   1
61925   64        44638   9      27307       3       26842   1
91130   63        60007   9      31785       3       27758   1
91200   58        67648   9      37629       3       30053   1
79711   47        72371   9      49284       3       36962   1
43312   42        96565   9      54512       3       37477   1
75687   37        99094   9      68798       3       37686   1
81544   37        24483   8      79286       3       38686   1
51949   29        46127   8      85076       3       40606   1
23562   28        55223   8      94046       3       42067   1
96780   25        99061   7      11468       2       50935   1
72026   24        20470   6      20460       2       52833   1
78098   23        22798   6      25559       2       55991   1
96878   20        32331   6      41075       2       59635   1
18986   19        40772   6      45834       2       65025   1
21782   19        52741   6      57403       2       65414   1
57673   18        63095   6      65855       2       66185   1
62088   18        70610   6      71103       2       67120   1
37267   16        92826   6      71633       2       74336   1
40019   16        25387   5      75778       2       74800   1
46681   15        69153   5      77776       2       75906   1
47390   15        72564   5      80209       2       89027   1
22775   14        24122   4      91062       2       89675   1
80998   14        47240   4      91212       2       90962   1
98758   14        76002   4      91869       2       91774   1
36942   13        82852   4      13335       1       94776   1
93620   13        83478   4      15318       1       98886   1
97276   13        97561   4      16155       1
</table>
</section>


<footer>58</footer>

<section>
<heading>Attacker-owned domains:</heading>

haarmannsi.cz
sanygroup.co.uk
ecolines.es
blackberry-support.herokuapp.com (DynDNS)
</section>



<footer>59</footer>

<section>
<heading>YARA detection rules:</heading>
<code>
rule InceptionDLL
{
      meta:
            author = "Blue Coat Systems, Inc"
            info = "Used by unknown APT actors:   Inception"
      strings:
            $a = "dll.polymorphed.dll"
            $b = {83 7d 08 00 0f 84 cf 00 00 00   83   7d   0c   00   0f   84 c5   00
            00 00 83 7d 10 00 0f 84 bb 00 00 00   83   7d   14   08   0f   82 b1   00
            00 00 c7 45 fc 00 00 00 00 8b 45 10   89   45   dc   68   00   00}
            $c = {FF 15 ?? ?? ?? ?? 8B 4D 08 8B   11   C7   42   14   00   00 00   00
            8B 45 08 8B 08 8B 55 14 89 51 18 8B   45   08   8B   08   8B   55 0C   89
            51 1C 8B 45 08 8B 08 8B 55 10 89 51   20   8B   45   08   8B   08}
            $d = {68 10 27 00 00 FF 15 ?? ?? ??   ??   83   7D   CC   0A   0F 8D   47
            01 00 00 83 7D D0 00 0F 85 3D 01 00   00   6A   20   6A   00   8D 4D   D4
            51 E8 ?? ?? ?? ?? 83 C4 0C 8B 55 08   89   55   E8   C7   45   D8}
            $e = {55 8B EC 8B 45 08 8B 88 AC 23   03   00   51   8B   55   0C 52   8B
            45 0C 8B 48 04 FF D1 83 C4 08 8B 55   08   8B   82   14   BB   03 00   50
            8B 4D 0C 51 8B 55 0C 8B 42 04}
      condition:
            any of them
}


rule InceptionRTF {
      meta:
            author = "Blue Coat Systems, Inc"
            info = "Used by unknown APT actors: Inception"
      strings:
            $a = "}}PT@T"
            $b = "XMLVERSION \"3.1.11.5604.5606"
            $c = "objclass Word.Document.12}\\objw9355"
      condition:
            all of them
}


rule InceptionMips {
      meta:
            author = "Blue Coat Systems, Inc"
            info = "Used by unknown APT actors: Inception"
      strings:
            $a = "start_sockat" ascii wide
            $b = "start_sockss" ascii wide
            $c = "13CStatusServer" ascii wide
      condition:
            all of them
}




<footer>60</footer>

rule InceptionVBS {
      meta:
            author = "Blue Coat Systems, Inc"
            info = "Used by unknown APT actors: Inception"
      strings:
            $a = "c = Crypt(c,k)"
            $b = "fso.BuildPath( WshShell.ExpandEnvironmentStrings(a),
            nn)"
      condition:
            all of them
}


rule InceptionBlackberry {
      meta:
            author = "Blue Coat Systems, Inc"
            info = "Used by unknown APT actors: Inception"
      strings:
            $a1 = "POSTALCODE:"
            $a2 = "SecurityCategory:"
            $a3 = "amount of free flash:"
            $a4 = "$Ø71|'1'|:"
            $b1 = "God_Save_The_Queen"
            $b2 = "UrlBlog"

      condition:
            all of ($a*) or all of ($b*)
}


rule InceptionAndroid {
      meta:
            author = "Blue Coat Systems, Inc"
            info = "Used by unknown APT actors: Inception"
      strings:
            $a1 = "BLOGS AVAILABLE="
            $a2 = "blog-index"
            $a3 = "Cant create dex="

      condition:
            all of them
}

rule InceptionIOS {
      meta:
            author = "Blue Coat Systems, Inc"
            info = "Used by unknown APT actors: Inception"
      strings:
            $a1 = "Developer/iOS/JohnClerk/"
            $b1 = "SkypeUpdate"
            $b2 = "/Syscat/"
            $b3 = "WhatsAppUpdate"
      condition:
      $a1 and any of ($b*)
}
</code>
</section>


<footer>61</footer>

<section>
<heading>Acknowledgements</heading>


The following entities have helped in big and small ways. Big thanks to all.
<list>
CIRCL.LU
Crowdstrike
F-Secure Corporation
iSight Partners
Kaspersky Labs
Symantec Corporation
</list>

We also owe a big debt of gratitude to Ryan W. Smith of Blue Coat who helped
us tremendously with the analysis of the mobile malware.
</section>



<footer>62</footer>

</doc>