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Sofacy Groupβs Parallel Attacks .
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data/reports_final/0001.txt
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Sofacy Groupβs Parallel Attacks .
The Sofacy group remains a persistent global threat .
Unit 42 and others have shown in the first half of 2018 how this threat actor group continues to target multiple organizations throughout the world with a strong emphasis on government , diplomatic and other strategic organizations primarily in North America and Europe .
Following up our most recent Sofacy research in February and March of 2018 , we have found a new campaign that uses a lesser known tool widely attributed to the Sofacy group called Zebrocy .
Zebrocy is delivered primarily via phishing attacks that contain malicious Microsoft Office documents with macros as well as simple executable file attachments .
This third campaign is consistent with two previously reported attack campaigns in terms of targeting : the targets were government organizations dealing with foreign affairs .
In this case however the targets were in different geopolitical regions .
An interesting difference we found in this newest campaign was that the attacks using Zebrocy cast a far wider net within the target organization : the attackers sent phishing emails to a an exponentially larger number of individuals .
The targeted individuals did not follow any significant pattern , and the email addresses were found easily using web search engines .
This is a stark contrast with other attacks commonly associated with the Sofacy group where generally no more than a handful of victims are targeted within a single organization in a focus-fire style of attack .
In addition to the large number of Zebrocy attacks we discovered , we also observed instances of the Sofacy group leveraging the Dynamic Data Exchange ( DDE ) exploit technique previously documented by McAfee .
The instances we observed , however , used the DDE exploit to deliver different payloads than what was observed previously .
In one instance the DDE attack was used to deliver and install Zebrocy .
In another instance , the DDE attack was used to deliver an open-source penetration testing toolkit called Koadic .
The Sofacy group has leveraged open source or freely available tools and exploits in the past but this is the first time that Unit 42 has observed them leveraging the Koadic toolkit .
In our February report , we discovered the Sofacy group using Microsoft Office documents with malicious macros to deliver the SofacyCarberp payload to multiple government entities .
In that report , we documented our observation that the Sofacy group appeared to use conventional obfuscation techniques to mask their infrastructure attribution by using random registrant and service provider information for each of their attacks .
In particular , we noted that the Sofacy group deployed a webpage on each of the domains .
This is odd because attackers almost never set up an actual webpage on adversary C2 infrastructure .
Even stranger , each webpage contained the same content within the body .
Since that report , we continued our research into this oddity .
Using this artifact , we were able to pivot and discover another attack campaign using the DealersChoice exploit kit with similar victimology to what we saw in February .
Continuing to use this artifact , we discovered another domain with the same content body , supservermgr.com .
This domain was registered on December 20 , 2017 and within a few days was resolving to 92.222.136.105 , which belonged to a well-known VPS provider often used by the Sofacy group .
Unfortunately , at the time of collection , the C2 domain had been sinkholed by a third party .
Based on dynamic and static analysis of the malware sample associated with the supservermgr.com domain however , we were able to determine several unique artifacts which allowed us to expand our dataset and discover additional findings .
First , we determined the sample we collected , d697160aecf152a81a89a6b5a7d9e1b8b5e121724038c676157ac72f20364edc was attempting to communicate to its C2 at http://supservermgr.com/sys/upd/pageupd.php to retrieve a Zebrocy AutoIT downloader .
Because the domain had been sinkholed , this activity could not be completed .
Using AutoFocus , we pivoted from the user agent string to expand our data set to three additional Zebrocy samples using the exact same user agent .
This led us to additional infrastructure for Zebrocy at 185.25.51.198 and 185.25.50.93 .
At this point we had collected nearly thirty samples of Zebrocy in relation to the original sample and its associated C2 domain .
Additional pivoting based on artifacts unique to this malware family expanded our dataset to hundreds of samples used over the last several years .
Most of the additional samples were the Delphi and AutoIT variants as reported by ESET .
However , several of the collected samples were a C++ variant of the Zebrocy downloader tool .
In addition , we discovered evidence of a completely different payload in Koadic being delivered as well .
Also , we found the IP address 185.25.50.93 hosting C2 services for a Delphi backdoor that ESET βs report states is the final stage payload for these attacks .
Please note this is not a comprehensive chart of all Zebrocy and Koadic samples we were able to collect .
Only samples mentioned or relevant to the relational analysis have been included .
From the 185.25.50.93 C2 IP , we discovered another hard-coded user agent being used by Zebrocy :Mozilla ( Windows NT 6.1 ; WOW64 ) WinHttp/1.6.3.8 ( WinHTTP/5.1 ) like Gecko .
We observed several samples of Zebrocy using this user agent targeting the foreign affairs ministry of a large Central Asian nation .
Pivoting off of this artifact provided us additional Zebrocy samples .
One sample in particular , cba5ab65a24be52214736bc1a5bc984953a9c15d0a3826d5b15e94036e5497df used yet another unique user agent string in combination with the previous user agent for its C2 : Mozilla v5.1 ( Windows NT 6.1 ; rv : 6.0.1 ) Gecko Firefox .
A malware sample using two separate unique user agent strings is uncommon .
A closer examination of the tool revealed the second user agent string was from a secondary payload that was retrieved by the cba5ab65a24be52214736bc1a5bc984953a9c15d0a3826d5b15e94036e5497df sample .
Pivoting from the Mozilla v5.1 user agent revealed over forty additional Zebrocy samples , with several again targeting the same Central Asian nation .
Two samples specifically , 25f0d1cbcc53d8cfd6d848e12895ce376fbbfaf279be591774b28f70852a4fd8 and 115fd8c619fa173622c7a1e84efdf6fed08a25d3ca3095404dcbd5ac3deb1f03 provided additional artifacts we were able to pivot from to discover weaponized documents to deliver Zebrocy as well as a Koadic .
Examining the use of the unique user agents β strings over time shows that while previously only the Mozilla user agent was in use , since mid 2017 all three user agent strings have been used by the Zebrocy tool for its C2 communications .
The two weaponized documents we discovered leveraging DDE were of particular interest due to victimology and a change in tactics .
While examining 25f0d1cbcc53d8cfd6d848e12895ce376fbbfaf279be591774b28f70852a4fd8 , we were able to pivot from its C2220.158.216.127 to gather additional Zebrocy samples as well as a weaponized document .
This document 85da72c7dbf5da543e10f3f806afd4ebf133f27b6af7859aded2c3a6eced2fd5 appears to have been targeting a North American government organization dealing with foreign affairs .
It leveraged DDE to retrieve and install a payload onto the victim host .
A decoy document is deployed in this attack , with the contents purporting be a publicly available document from the United Nations regarding the Republic of Uzbekistan .
The creator of the weaponized document appended their DDE instructions to the end of the document after all of the decoy contents .
When the document is opened in Word , the instructions are not immediately visible , as Word does not display these fields contents by default .
As you can see in the following screenshot , simply attempting to highlight the lines in which the DDE instructions reside does not display them .
Enabling the β Toggle Field Codes β feature reveals the DDE instructions to us and shows that the author had set instructions to size 1 font and with a white coloring .
The use of a white font coloring to hide contents within a weaponized document is a technique we had previously reported being used by the Sofacy group in a malicious macro attack .
The DDE instructions attempt to run the following the following command on the victim host , which attempts to download and execute a payload from a remote server .
During our analysis , we observed this DDE downloading and executing a Zebrocy AutoIt downloader f27836430742c9e014e1b080d89c47e43db299c2e00d0c0801a2830b41b57bc1 , configured to attempt to download an additional payload from 220.158.216.127 .
The DDE instructions also included another command that it did not run , which suggests it is an artifact of a prior version of this delivery document .
The following shows this unused command , which exposed an additional server within Sofacy βs infrastructure would download and execute an encoded PowerShell script from 92.114.92.102 .
The unused command above appears to be related to previous attacks , specifically attacks that occurred in November 2017 as discussed by McAfee and ESET .
The payload delivered in these November 2017 attacks using DDE enabled documents was SofacyCarberp , which differs from the Zebrocy downloader delivered in the February 2018 attacks .
115fd8c619fa173622c7a1e84efdf6fed08a25d3ca3095404dcbd5ac3deb1f03 was another Zebrocy sample we were able to pivot from by gathering additional samples connecting to its C2 86.106.131.177 .
The additional samples targeted the same large Central Asian nation state as previously mentioned but more interestingly , one of the samples was a weaponized document also leveraging DDE and containing a non-Zebrocy payload .
The payload turned out to be an open source penetration test toolkit called Koadic .
It is a toolkit similar to Metasploit or PowerShell Empire and is freely available to anyone on Github .
The RTF document 8cf3bc2bf36342e844e9c8108393562538a9af2a1011c80bb46416c0572c86ff was very small in size at 264 bytes .
The contents above use the DDE functionality in Microsoft Word to run a PowerShell script to download the Koadic payload from a remote server , save it as an executable file on the system and then execute the payload .
The Sofacy group continues their targeted attack campaigns in 2018 .
As mentioned in this blog , Sofacy is carrying out parallel campaigns to attack similar targets around the world but with different toolsets .
The Zebrocy tool associated with this current strain of attacks is constructed in several different forms based on the programming language the developer chose to create the tool .
We have observed Delphi , AutoIt , and C++ variants of Zebrocy , all of which are related not only in their functionality , but also at times by chaining the variants together in a single attack .
These attacks are still largely perpetrated via spear phishing campaigns , whether via simple executable attachments in hopes that a victim will launch the file to using a previously observed DDE exploitation technique .
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Sofacy Uses DealersChoice to Target European Government Agency .
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Sofacy Uses DealersChoice to Target European Government Agency .
Back in October 2016 , Unit 42 published an initial analysis on a Flash exploitation framework used by the Sofacy threat group called DealersChoice .
The attack consisted of Microsoft Word delivery documents that contained Adobe Flash objects capable of loading additional malicious Flash objects embedded in the file or directly provided by a command and control server .
Sofacy continued to use DealersChoice throughout the fall of 2016 , which we also documented in our December 2016 publication discussing Sofacy βs larger campaign .
On March 12 and March 14 , we observed the Sofacy group carrying out an attack on a European government agency involving an updated variant of DealersChoice .
The updated DealersChoice documents used a similar process to obtain a malicious Flash object from a C2 server , but the inner mechanics of the Flash object contained significant differences in comparison to the original samples we analyzed .
One of the differences was a particularly clever evasion technique : to our knowledge this has never been observed in use .
With the previous iterations of DealersChoice samples , the Flash object would immediately load and begin malicious tasks .
In the March attacks , the Flash object is only loaded if the user scrolls through the entire content of the delivery document and views the specific page the Flash object is embedded on .
Also , DealersChoice requires multiple interactions with an active C2 server to successfully exploit an end system .
The overall process to result in a successful exploitation is :User must open the Microsoft Word email attachment ;User must scroll to page three of the document , which will run the DealersChoice Flash object ;The Flash object must contact an active C2 server to download an additional Flash object containing exploit code ;The initial Flash object must contact the same C2 server to download a secondary payload ;Victim host must have a vulnerable version of Flash installed .
The attack involving this updated variant of DealersChoice was targeting a European government organization .
The attack relied on a spear-phishing email with a subject of β Defence & Security 2018 Conference Agenda β that had an attachment with a filename of β Defence&Security_2018_Conference_Agenda.docx β .
The attached document contains a conference agenda that the Sofacy group appears to have copied directly from the website for the β Underwater Defence & Security 2018 Conference β here .
Opening the attached β Defence & Security 2018 Conference Agenda.docx β file does not immediately run malicious code to exploit the system .
Instead , the user must scroll to the third page of the document , which will load a Flash object that contains ActionScript that will attempt to exploit the user βs system to install a malicious payload .
The Flash object embedded within this delivery document is a variant of an exploit tool that we call DealersChoice .
This suggests that the Sofacy group is confident that the targeted individuals would be interested enough in the content to peruse through it .
We analyzed the document to determine the reason that the malicious Flash object only ran when the user scrolled to the third page .
According to the document.xml file , the DealersChoice loader SWF exists after the β covert-shores-small.png β image file within the delivery document .
This image file exists on the third page of the document , so the user would have to scroll down in the document to this third page to get the SWF file to run .
The user may not notice the Flash object on the page , as Word displays it as a tiny black box in the document , as seen in Figure 1 .
This is an interesting anti-sandbox technique , as it requires human interaction prior to the document exhibiting any malicious activity .
This DealersChoice Flash object shares a similar process to previous variants ; however , it appears that the Sofacy actors have made slight changes to its internal code .
Also , it appears that the actors used ActionScript from an open source video player called β f4player β , which is freely available on GitHub .
The Sofacy developer modified the f4player βs ActionScript to include additional code to load an embedded Flash object .
The additions include code to decrypt an embedded Flash object and an event handler that calls a newly added function ( β skinEvent2 β ) that plays the decrypted object .
The above code allows DealersChoice to load a second SWF object , specifically loading it with an argument that includes a C2 URL of β http://ndpmedia24.com/0pq6m4f.m3u8 β .
The embedded SWF extracts the domain from the C2 URL passed to it and uses it to craft a URL to get the server βs β crossdomain.xml β file in order to obtain permissions to load additional Flash objects from the C2 domain .
The ActionScript relies on event listeners to call specific functions when the event β Event.COMPLETE β is triggered after successful HTTP requests are issued to the C2 server .
The event handlers call functions with the following names , which includes an incrementing number that represents the order in which the functions are called : onload1 , onload2 , onload3 , onload5 .
With these event handlers created , the ActionScript starts by gathering system data from the flash.system.Capabilities.serverString property ( just like in the original DealersChoice.B samples ) and issues an HTTP GET with the system data as a parameter to the C2 URL that was passed as an argument to the embedded SWF when it was initially loaded .
When this HTTP request completes , the event listener will call the β onload1 β function .
The β onload1 β function parses the response data from the request to the C2 URL using regular expressions .
The regular expressions suggest that the C2 server responds with content that is meant to resemble HTTP Live Steaming ( HLS ) traffic , which is a protocol that uses HTTP to deliver audio and video files for streaming .
The use of HLS coincides with the use of ActionScript code from the f4player to make the traffic seem legitimate .
The variables storing the results of the regular expression matches are used within the ActionScript for further interaction with the C2 server .
The β onload1 β function then sends an HTTP GET request to the C2 domain using the value stored in the β r3 β variable as a URL .
When this HTTP request completes , the event listener will call the β onload2 β function .
The β onload2 β function decrypts the response received from the HTTP request issued in β onload1 β function .
It does so by calling a sub-function to decrypt the content , using the value stored in the β r1 β variable as a key .
The sub-function to decrypt the content skips the first 4 bytes , suggesting that the first four bytes of the downloaded content is in cleartext ( most likely the β FWS β or β CWS β header to look legitimate ) .
After decrypting the content , the β onload2 β function will issue another HTTP GET request with the system data as a parameter , but this time to the C2 using a URL from the β r4 β variable .
When this request completes , the event listener will call the β onload3 β function .
The β onload3 β function will take the response to the HTTP request in β onload2 β and treat it as the payload .
The ActionScript will read each byte of the C2 response and get the hexadecimal value .
This hexadecimal string will most likely be a string of shellcode that will contain and decrypt the ultimate portable executable ( PE ) payload .
The string of comma separated hexadecimal values is passed as a parameter when loading the SWF file downloaded in β onload2 β .
This function creates an event listener for when the SWF file is successfully loaded , which will call the β onload5 β function .
The β onload5 β function is responsible for adding the newly loaded SWF object as a child object .
This loads the SWF file , effectively running the malicious code on the system .
During our analysis , we were unable to coerce the C2 into providing a malicious SWF or payload .
As mentioned in our previous blogs on DealersChoice , the payload of choice for previous variants was SofacyCarberp ( Seduploader ) , but we have no evidence to suggest this tool was used in this attack .
We are actively researching and will update this blog in the event we discover the malicious Flash object and payload delivered in this attack .
The delivery document used in this attack was last modified by a user named β Nick Daemoji β , which provides a linkage to previous Sofacy related delivery documents .
The previous documents that used this user name were macro-laden delivery documents that installedpayloads , as discussed in Talos β blog .
This overlap also points to a similar social engineering theme between these two campaigns , as both used content from upcoming military and defense conferences as a lure .
The Sofacy threat group continues to use their DealersChoice framework to exploit Flash vulnerabilities in their attack campaigns .
In the most recent variant , Sofacy modified the internals of the malicious scripts , but continues to follow the same process used by previous variants by obtaining a malicious Flash object and payload directly from the C2 server .
Unlike previous samples , this DealersChoice used a DOCX delivery document that required the user to scroll through the document to trigger the malicious Flash object .
0cd9ac328d858d8d83c9eb73bfdc59a958873b3d71b24c888d7408d9512a41d7 ( Defence&Security_2018_Conference_Agenda.docx ) ndpmedia24.com .
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Corporate IoT β a path to intrusion .
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Corporate IoT β a path to intrusion .
Several sources estimate that by the year 2020 some 50 billion IoT devices will be deployed worldwide .
IoT devices are purposefully designed to connect to a network and many are simply connected to the internet with little management or oversight .
Such devices still must be identifiable , maintained , and monitored by security teams , especially in large complex enterprises .
Some IoT devices may even communicate basic telemetry back to the device manufacturer or have means to receive software updates .
In most cases however , the customers β IT operation center donβt know they exist on the network .
In 2016 , the Mirai botnet was discovered by the malware research group MalwareMustDie .
The botnet initially consisted of IP cameras and basic home routers , two types of IoT devices commonly found in the household .
As more variants of Mirai emerged , so did the list IoT devices it was targeting .
The source code for the malware powering this botnet was eventually leaked online .
In 2018 , hundreds of thousands of home and small business networking and storage devices were compromised and loaded with the so-called β VPN Filter β malware .
The FBI has publicly attributed this activity to a nation-state actor and took subsequent actions to disrupt this botnet , although the devices would remain vulnerable to re-infection unless proper firmware or security controls were put in place by the user .
There were also multiple press reports of cyber-attacks on several devices during the opening ceremonies for the 2018 Olympic Games in PyeongChang .
Officials did confirm a few days later that they were a victim of malicious cyber-attacks that prevented attendees from printing their tickets to the Games and televisions and internet access in the main press center simply stopped working .
In April , security researchers in the Microsoft Threat Intelligence Center discovered infrastructure of a known adversary communicating to several external devices .
Further research uncovered attempts by the actor to compromise popular IoT devices ( a VOIP phone , an office printer , and a video decoder ) across multiple customer locations .
The investigation uncovered that an actor had used these devices to gain initial access to corporate networks .
In two of the cases , the passwords for the devices were deployed without changing the default manufacturer βs passwords and in the third instance the latest security update had not been applied to the device .
These devices became points of ingress from which the actor established a presence on the network and continued looking for further access .
Once the actor had successfully established access to the network , a simple network scan to look for other insecure devices allowed them to discover and move across the network in search of higher-privileged accounts that would grant access to higher-value data .
After gaining access to each of the IoT devices , the actor ran tcpdump to sniff network traffic on local subnets .
They were also seen enumerating administrative groups to attempt further exploitation .
As the actor moved from one device to another , they would drop a simple shell script to establish persistence on the network which allowed extended access to continue hunting .
Analysis of network traffic showed the devices were also communicating with an external command and control ( C2 ) server .
The following IP addresses are believed to have been used by the actor for command and control ( C2 ) during these intrusions :167.114.153.55 94.237.37.28 82.118.242.171 31.220.61.251 128.199.199.187 .
We attribute the attacks on these customers using three popular IoT devices to an activity group that Microsoft refers to as STRONTIUM .
Since we identified these attacks in the early stages , we have not been able to conclusively determine what STRONTIUM βs ultimate objectives were in these intrusions .
Over the last twelve months , Microsoft has delivered nearly 1400 nation-state notifications to those who have been targeted or compromised by STRONTIUM .
One in five notifications of STRONTIUM activity were tied to attacks against non-governmental organizations , think tanks , or politically affiliated organizations around the world .
The remaining 80% of STRONTIUM attacks have largely targeted organizations in the following sectors : government , IT , military , defense , medicine , education , and engineering .
We have also observed and notified STRONTIUM attacks against Olympic organizing committees , anti-doping agencies , and the hospitality industry .
The β VPN Filter β malware has also been attributed to STRONTIUM by the FBI .
Today we are sharing this information to raise awareness of these risks across the industry and calling for better enterprise integration of IoT devices , particularly the ability to monitor IoT device telemetry within enterprise networks .
Today , the number of deployed IoT devices outnumber the population of personal computers and mobile phones , combined .
With each networked IoT device having its own separate network stack , it βs quite easy to see the need for better enterprise management , especially in today βs β bring your own device β world .
While much of the industry focuses on the threats of hardware implants , we can see in this example that adversaries are happy to exploit simpler configuration and security issues to achieve their objectives .
These simple attacks taking advantage of weak device management are likely to expand as more IoT devices are deployed in corporate environments .
Upon conclusion of our investigation , we shared this information with the manufacturers of the specific devices involved and they have used this event to explore new protections in their products .
However , there is a need for broader focus across IoT in general , both from security teams at organizations that need to be more aware of these types of threats , as well as from IoT device makers who need to provide better enterprise support and monitoring capabilities to make it easier for security teams to defend their networks .
Below are a series of indicators Microsoft has observed as active during the STRONTIUM activity discussed in this article .
Command-and-Control ( C2 ) IP addresses :167.114.153.55 94.237.37.28 82.118.242.171 31.220.61.251 128.199.199.187 .
Operation RussianDoll : Adobe & Windows Zero-Day Exploits Likely Leveraged by Russia βs APT28 in Highly-Targeted Attack .
FireEye Labs recently detected a limited APT campaign exploiting zero-day vulnerabilities in Adobe Flash and a brand-new one in Microsoft Windows .
Using the Dynamic Threat Intelligence Cloud ( DTI ) , FireEye researchers detected a pattern of attacks beginning on April 13th , 2015 .
Adobe independently patched the vulnerability ( CVE-2015-3043 ) in APSB15-06 .
Through correlation of technical indicators and command and control infrastructure , FireEye assess that APT28 is probably responsible for this activity .
Microsoft is aware of the outstanding local privilege escalation vulnerability in Windows ( CVE-2015-1701 ) .
While there is not yet a patch available for the Windows vulnerability , updating Adobe Flash to the latest version will render this in-the-wild exploit innocuous .
We have only seen CVE-2015-1701 in use in conjunction with the Adobe Flash exploit for CVE-2015-3043 .
The Microsoft Security Team is working on a fix for CVE-2015-1701 .
The high level flow of the exploit is as follows :User clicks link to attacker controlled website .
HTML/JS launcher page serves Flash exploit .
Flash exploit triggers CVE-2015-3043 , executes shellcode .
Shellcode downloads and runs executable payload .
Executable payload exploits local privilege escalation ( CVE-2015-1701 ) to steal System token .
The Flash exploit is served from unobfuscated HTML/JS .
The launcher page picks one of two Flash files to deliver depending upon the target βs platform ( Windows 32 versus 64bits ) .
The Flash exploit is mostly unobfuscated with only some light variable name mangling .
The attackers relied heavily on the CVE-2014-0515 Metasploit module , which is well documented .
It is ROPless , and instead constructs a fake vtable for a FileReference object that is modified for each call to a Windows API .
The payload exploits a local privilege escalation vulnerability in the Windows kernel if it detects that it is running with limited privileges .
It uses the vulnerability to run code from userspace in the context of the kernel , which modifies the attacker βs process token to have the same privileges as that of the System process .
The primary difference between the CVE-2014-0515 metasploit module and this exploit is , obviously , the vulnerability .
CVE-2014-0515 exploits a vulnerability in Flash βs Shader processing , whereas CVE-2015-3043 exploits a vulnerability in Flash βs FLV processing .
The culprit FLV file is embedded within AS3 in two chunks , and is reassembled at runtime .
A buffer overflow vulnerability exists in Adobe Flash Player ( <=17.0.0.134 ) when parsing malformed FLV objects .
Attackers exploiting the vulnerability can corrupt memory and gain remote code execution .
In the exploit , the attacker embeds the FLV object directly in the ActionScript code , and plays the video using NetStream class .
Files of the FLV file format contain a sequence of Tag structures .
Beginning within the data field , all contents of the FLV stream become 0xEE .
Consequently , the data and lastsize fields are mangled .
Since the size is controlled by the attacker , it βs possible to overflow the fixed size buffer with certain data .
As the previous picture demonstrated , the followed Vector object βs length field being overflowed as 0x80007fff , which enables the attacker to read/write arbitrary data within user space .
Shellcode is passed to the exploit from HTML in flashvars .
The shellcode downloads the next stage payload , which is an executable passed in plaintext , to the temp directory with UrlDownloadToFileA , which it then runs with WinExec .
This exploit delivers a malware variant that shares characteristics with the APT28 backdoors CHOPSTICK and CORESHELL malware families , both described in our APT28 whitepaper .
The malware uses an RC4 encryption key that was previously used by the CHOPSTICK backdoor .
And the C2 messages include a checksum algorithm that resembles those used in CHOPSTICK backdoor communications .
In addition , the network beacon traffic for the new malware resembles those used by the CORESHELL backdoor .
Like CORESHELL , one of the beacons includes a process listing from the victim host .
And like CORESHELL , the new malware attempts to download a second-stage executable .
One of the C2 locations for the new payload , 87.236.215.246 , also hosts a suspected APT28 domain ssl-icloud.com .
The same subnet ( 87.236.215.0 / 24 ) also hosts several known or suspected APT28 domains .
The payload contains an exploit for the unpatched local privilege escalation vulnerability CVE-2015-1701 in Microsoft Windows .
The exploit uses CVE-2015-1701 to execute a callback in userspace .
The callback gets the EPROCESS structures of the current process and the System process , and copies data from the System token into the token of the current process .
Upon completion , the payload continues execution in usermode with the privileges of the System process .
Because CVE-2015-3043 is already patched , this remote exploit will not succeed on a fully patched system .
If an attacker wanted to exploit CVE-2015-1701 , they would first have to be executing code on the victim βs machine .
Barring authorized access to the victim βs machine , the attacker would have to find some other means , such as crafting a new Flash exploit , to deliver a CVE-2015-1701 payload .
Microsoft is aware of CVE-2015-1701 and is working on a fix .
CVE-2015-1701 does not affect Windows 8 and later .
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Sofacy Attacks Multiple Government Entities .
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Sofacy Attacks Multiple Government Entities .
Release_Time : 2018-02-28Report_URL : https://unit42.paloaltonetworks.com/unit42-sofacy-attacks-multiple-government-entities/The Sofacy group ( AKA APT28 , Fancy Bear , STRONTIUM , Sednit , Tsar Team , Pawn Storm ) is a well-known adversary that remains highly active in the new calendar year of 2018 .
Unit 42 actively monitors this group due to their persistent nature globally across all industry verticals .
Recently , we discovered a campaign launched at various Ministries of Foreign Affairs around the world .
Interestingly , there appear to be two parallel efforts within the campaign , with each effort using a completely different toolset for the attacks .
In this blog , we will discuss one of the efforts which leveraged tools that have been known to be associated with the Sofacy group .
At the beginning of February 2018 , we discovered an attack targeting two government institutions related to foreign affairs .
These entities are not regionally congruent , and the only shared victimology involves their organizational functions .
Specifically , one organization is geographically located in Europe and the other in North America .
The initial attack vector leveraged a phishing email , using the subject line of Upcoming Defense events February 2018 and a sender address claiming to be from Jane βs 360 defense events [email protected] .
Jane βs by IHSMarkit is a well-known supplier of information and analysis often times associated with the defense and government sector .
Analysis of the email header data showed that the sender address was spoofed and did not originate from IHSMarkit at all .
The lure text in the phishing email claims the attachment is a calendar of events relevant to the targeted organizations and contained specific instructions regarding the actions the victim would have to take if they had β trouble viewing the document β .
The attachment itself is an Microsoft Excel XLS document that contains malicious macro script .
The document presents itself as a standard macro document but has all of its text hidden until the victim enables macros .
Notably , all of the content text is accessible to the victim even before macros are enabled .
However , a white font color is applied to the text to make it appear that the victim must enable macros to access the content .
The code above changes the font color to black within the specified cell range and presents the content to the user .
On initial inspection , the content appears to be the expected legitimate content , however , closer examination of the document shows several abnormal artifacts that would not exist in a legitimate document .
Figure 2 below shows how the delivery document initially looks and the transformation the content undergoes as the macro runs .
As mentioned in a recent ISC diary entry , the macro gets the contents of cells in column 170 in rows 2227 to 2248 to obtain the base64 encoded payload .
The macro prepends the string ββBEGIN CERTIFICATEββ to the beginning of the base64 encoded payload and appends ββEND CERTIFICATEββ to the end of the data .
The macro then writes this data to a text file in the C:\Programdata folder using a random filename with the .txt extension .
The macro then uses the command certutil -decode to decode the contents of this text file and outputs the decoded content to a randomly named file with a .exe extension in the C:\Programdata folder .
The macro sleeps for two seconds and then executes the newly dropped executable .
The newly dropped executable is a loader Trojan responsible for installing and running the payload of this attack .
We performed a more detailed analysis on this loader Trojan , which readers can view in this report βs appendix .
Upon execution , the loader will decrypt the embedded payload ( DLL ) using a custom algorithm , decompress it and save it to the following file : %LOCALAPPDATA%\cdnver.dll .
The loader will then create the batch file %LOCALAPPDATA%\cdnver.bat , which it will write the following :start rundll32.exe β C:\Users\user\AppData\Local\cdnver.dll β .
The loader Trojan uses this batch file to run the embedded DLL payload .
For persistence , the loader will write the path to this batch file to the following registry key .
The cdnver.dll payload installed by the loader executable is a variant of the SofacyCarberp payload , which is used extensively by the Sofacy threat group .
Overall , SofacyCarberp does initial reconnaissance by gathering system information and sending it to the C2 server prior to downloading additional tools to the system .
This variant of SofacyCarberp was configured to use the following domain as its C2 server : cdnverify.net .
The loader and the SofacyCarberp sample delivered in this attack is similar to samples we have analyzed in the past but contains marked differences .
These differences include a new hashing algorithm to resolve API functions and to find running browser processes for injection , as well as changes to the C2 communication mechanisms .
It appears that Sofacy may have used an open-source tool called Luckystrike to generate the delivery document and/or the macro used in this attack .
Luckystrike , which was presented at DerbyCon 6 in September 2016 , is a Microsoft PowerShell based tool that generates malicious delivery documents by allowing a user to add a macro to an Excel or Word document to execute an embedded payload .
We believe Sofacy used this tool , as the macro within their delivery document closely resembles the macros found within Luckystrike .
To confirm our suspicions , we generated a malicious Excel file with Luckystrike and compared its macro to the macro found within Sofacy βs delivery document .
We found that there was only one difference between the macros besides the random function name and random cell values that the Luckystrike tool generates for each created payload .
The one non-random string difference was the path to the β .txt β and β .exe β files within the command β certutil -decode β , as the Sofacy document used β C:\Programdata\ β for the path whereas the Luckystrike document used the path stored in the Application.UserLibraryPath environment variable .
Figure 3 below shows a diff with the LuckyStrike macro on the left and Sofacy macro on the right , where everything except the file path and randomly generated values in the macro are exactly the same , including the obfuscation attempts that use concatenation to build strings .
With much of our research , our initial direction and discovery of emerging threats is generally some combination of previously observed behavioral rulesets or relationships .
In this case , we had observed a strange pattern emerging from the Sofacy group over the past year within their command and control infrastructure .
Patterning such as reuse of WHOIS artifacts , IP reuse , or even domain name themes are common and regularly used to group attacks to specific campaigns .
In this case , we had observed the Sofacy group registering new domains , then placing a default landing page which they then used repeatedly over the course of the year .
No other parts of the C2 infrastructure amongst these domains contained any overlapping artifacts .
Instead , the actual content within the body of the websites was an exact match in each instance .
Specifically , the strings 866-593-54352 ( notice it is one digit too long ) , 403-965-2341 , or the address 522 Clematis .
Suite 3000 was repeatedly found in each instance .
ThreatConnect had made the same observation regarding this patterning in September 2017 .
Hotfixmsupload.com is particularly interesting as it has been identified as a Sofacy C2 domain repeatedly , and was also brought forth by Microsoft in a legal complaint against STRONTIUM ( Sofacy ) as documented here .
Leveraging this intelligence allowed us to begin predicting potential C2 domains that would eventually be used by the Sofacy group .
In this scenario , the domain cdnverify.net was registered on January 30 , 2018 and just two days later , an attack was launched using this domain as a C2 .
The Sofacy group should no longer be an unfamiliar threat at this stage .
They have been well documented and well researched with much of their attack methodologies exposed .
They continue to be persistent in their attack campaigns and continue to use similar tooling as in the past .
This leads us to believe that their attack attempts are likely still succeeding , even with the wealth of threat intelligence available in the public domain .
Application of the data remains challenging , and so to continue our initiative of establishing playbooks for adversary groups , we have added this attack campaign as the next playbook in our dataset .
Palo Alto Networks customers are protected from this threat by :WildFire detects all SofacyCarberp payloads with malicious verdicts .
AutoFocus customers can track these tools with the Sofacy , SofacyMacro and SofacyCarberp .
Traps blocks the Sofacy delivery documents and the SofacyCarberp payload .
SHA256 : ff808d0a12676bfac88fd26f955154f8884f2bb7c534b9936510fd6296c543e8 SHA256 : 12e6642cf6413bdf5388bee663080fa299591b2ba023d069286f3be9647547c8 SHA256 : cb85072e6ca66a29cb0b73659a0fe5ba2456d9ba0b52e3a4c89e86549bc6e2c7 SHA256 : 23411bb30042c9357ac4928dc6fca6955390361e660fec7ac238bbdcc8b83701 Sofacy : Cdnverify.net Sofacy Filename : Upcoming_Events_February_2018.xls .
APT28 Targets Hospitality Sector , Presents Threat to Travelers .
Release_Time : 2017-08-11 Report_URL : https://www.fireeye.com/blog/threat-research/2017/08/apt28-targets-hospitality-sector.htmlFireEye has moderate confidence that a campaign targeting the hospitality sector is attributed to Russian actor APT28 .
We believe this activity , which dates back to at least July 2017 , was intended to target travelers to hotels throughout Europe and the Middle East .
The actor has used several notable techniques in these incidents such as sniffing passwords from Wi-Fi traffic , poisoning the NetBIOS Name Service , and spreading laterally via the EternalBlue exploit .
FireEye has uncovered a malicious document sent in spear phishing emails to multiple companies in the hospitality industry , including hotels in at least seven European countries and one Middle Eastern country in early July .
Successful execution of the macro within the malicious document results in the installation of APT28 βs signature GAMEFISH malware .
The malicious document β Hotel_Reservation_Form.doc ( MD5 : 9b10685b774a783eabfecdb6119a8aa3 ) , contains a macro that base64 decodes a dropper that then deploys APT28 βs signature GAMEFISH malware ( MD5 : 1421419d1be31f1f9ea60e8ed87277db ) , which uses mvband.net and mvtband.net as command and control ( C2 ) domains .
APT28 is using novel techniques involving the EternalBlue exploit and the open source tool Responder to spread laterally through networks and likely target travelers .
Once inside the network of a hospitality company , APT28 sought out machines that controlled both guest and internal Wi-Fi networks .
No guest credentials were observed being stolen at the compromised hotels ; however , in a separate incident that occurred in Fall 2016 , APT28 gained initial access to a victim βs network via credentials likely stolen from a hotel Wi-Fi network .
Upon gaining access to the machines connected to corporate and guest Wi-Fi networks , APT28 deployed Responder .
Responder facilitates NetBIOS Name Service ( NBT-NS ) poisoning .
This technique listens for NBT-NS ( UDP ) broadcasts from victim computers attempting to connect to network resources .
Once received , Responder masquerades as the sought-out resource and causes the victim computer to send the username and hashed password to the attacker-controlled machine .
APT28 used this technique to steal usernames and hashed passwords that allowed escalation of privileges in the victim network .
To spread through the hospitality company βs network , APT28 used a version of the EternalBlue SMB exploit .
This was combined with the heavy use of py2exe to compile Python scripts .
This is the first time we have seen APT28 incorporate this exploit into their intrusions .
In the 2016 incident , the victim was compromised after connecting to a hotel Wi-Fi network .
Twelve hours after the victim initially connected to the publicly available Wi-Fi network , APT28 logged into the machine with stolen credentials .
These 12 hours could have been used to crack a hashed password offline .
After successfully accessing the machine , the attacker deployed tools on the machine , spread laterally through the victim's network , and accessed the victim's OWA account .
The login originated from a computer on the same subnet , indicating that the attacker machine was physically close to the victim and on the same Wi-Fi network .
We cannot confirm how the initial credentials were stolen in the 2016 incident ; however , later in the intrusion , Responder was deployed .
Since this tool allows an attacker to sniff passwords from network traffic , it could have been used on the hotel Wi-Fi network to obtain a user βs credentials .
Cyber espionage activity against the hospitality industry is typically focused on collecting information on or from hotel guests of interest rather than on the hotel industry itself , though actors may also collect information on the hotel as a means of facilitating operations .
Business and government personnel who are traveling , especially in a foreign country , often rely on systems to conduct business other than those at their home office , and may be unfamiliar with threats posed while abroad .
APT28 isnβt the only group targeting travelers .
South Korea nexus Fallout Team ( aka Darkhotel ) has used spoofed software updates on infected Wi-Fi networks in Asian hotels , and Duqu 2.0 malware has been found on the networks of European hotels used by participants in the Iranian nuclear negotiations .
Additionally , open sources have reported for several years that in Russia and China , high-profile hotel guests may expect their hotel rooms to be accessed and their laptops and other electronic devices accessed .
These incidents show a novel infection vector being used by APT28 .
The group is leveraging less secure hotel Wi-Fi networks to steal credentials and a NetBIOS Name Service poisoning utility to escalate privileges .
APT28 βs already wide-ranging capabilities and tactics are continuing to grow and refine as the group expands its infection vectors .
Travelers must be aware of the threats posed when traveling β especially to foreign countries β and take extra precautions to secure their systems and data .
Publicly accessible Wi-Fi networks present a significant threat and should be avoided whenever possible .
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Sofacy Continues Global Attacks and Wheels Out New Cannon Trojan .
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Sofacy Continues Global Attacks and Wheels Out New Cannon Trojan .
Release_Time : 2018-11-20Report_URL : https://unit42.paloaltonetworks.com/unit42-sofacy-continues-global-attacks-wheels-new-cannon-trojan/In late October and early November 2018 , Unit 42 intercepted a series of weaponized documents that use a technique to load remote templates containing a malicious macro .
These types of weaponized documents are not uncommon but are more difficult to identify as malicious by automated analysis systems due to their modular nature .
Specific to this technique , if the C2 server is not available at the time of execution , the malicious code cannot be retrieved , rendering the delivery document largely benign .
The weaponized documents targeted several government entities around the globe , including North America , Europe , and a former USSR state .
Fortunately for us , the C2 servers for several of these documents were still operational allowing for retrieval of the malicious macro and the subsequent payloads .
Analysis revealed a consistent first-stage payload of the well-documented Zebrocy Trojan .
Additional collection of related documents revealed a second first-stage payload that we have named β Cannon β .
Cannon has not been previously observed in use by the Sofacy group and contains a novel email-based C2 communication channel .
email as a C2 channel is not a new tactic , but it is generally not observed in the wild as often as HTTP or HTTPS .
Using email as a C2 channel may also decrease the chance of detection , as sending email via non-sanctioned email providers may not necessarily construe suspicious or even malicious activity in many enterprises .
The activity discussed in this blog revolves around two of the multitude of weaponized documents that we collected .
These two documents shared multiple data artifacts , such as a shared C2 IP , shared author name , and shared tactics .
Details of the extended attack campaign associated with the Cannon Trojan will be discussed in a later blog .
A particularly interesting aspect of one of the two documents we analyzed was the filename used , crash list ( Lion Air Boeing 737 ).docx .
This is not the first instance of an adversary group using recent current events as a lure , but it is interesting to see this group attempt to capitalize on the attention of a catastrophic event to execute their attack .
The initial sample we intercepted was a Microsoft Word document ( SHA256 : 2cfc4b3686511f959f14889d26d3d9a0d06e27ee2bb54c9afb1ada6b8205c55f ) with the filename crash list ( Lion Air Boeing 737 ).docx using the author name Joohn .
This document appeared to be targeting a government organization dealing with foreign affairs in Europe via spear-phishing .
Once the user attempts to open the document , Microsoft Word immediately attempts to load the remote template containing a malicious macro and payload from the location specified within the settings.xml.rels file of the DOCX document .
If the C2 has already been taken offline the document will still open , but Word will be unable to retrieve the remote template and thus Word will not load a macro .
In this situation , Word will present the same lure document to the victim as seen in Figure 2 , but without the ability to enable macros via an Enable Content button .
Assuming the C2 is still operational however , Word loads the remote template ( SHA256 : f1e2bceae81ccd54777f7862c616f22b581b47e0dda5cb02d0a722168ef194a5 ) and the user is presented with the screen .
Once the victim presses the Enable content button , the embedded macro is executed .
The macros used for these delivery documents use a less common method of using the AutoClose function .
This is a form of anti-analysis as Word will not fully execute the malicious code until the user closes the document .
If an automated sandbox exits its analysis session without specifically closing out the document , the sandbox may miss the malicious activity entirely .
Once successfully executed , the macro will install a payload and save a document to the system .
Typically , we expect to see a decoy document saved to the system and later displayed to make the victim less suspicious of malicious activity ; however , in this case the document saved to the system was never displayed and does not contain any pertinent content to the Lion Air tragedy theme seen in the filename .
The macro obtains the document saved to the system from within the document stored as UserForm1.Label1.Caption and will write it to : %TEMP%\~temp.docm .
The macro obtains the payload saved to the system from within the document stored as UserForm1.Label2.Caption and will write it to : %APPDATA%\MSDN\~msdn.exe .
The macro executes this payload in a rather interesting way by loading the dropped ~temp.docm document and calling a function within its embedded macro to run the payload .
We believe the creator of this delivery document chose to run the payload from the dropped file as an evasion technique .
Also , the fact the initial macro uses this dropped document for the execution of the payload may also explain why the document did not contain any decoy contents .
To carry out this functionality , after writing the~temp.docm and ~msdn.exe files to the system , the initial macro will load the ~temp.docm file as a Word Document object and attempts to run the function Proc1 in the Module1 macro within the ~temp.docm file .
The Proc1 function within the Module1 does nothing more than build the %APPDATA%\MSDN\~msdn.exe path to the dropped payload and executes it using the built-in Shell function .
The payload dropped to the system ( SHA256 : 6ad3eb8b5622145a70bec67b3d14868a1c13864864afd651fe70689c95b1399a ) is a UPX packed Zebrocy variant written in the Delphi language .
This variant of Zebrocy is functionally very similar to the Delphi based payloads discussed in our previous publication on Sofacy attacks using Zebrocy earlier this year .
The developer of this particular payload configured it to use the following URL to communicate with as its C2 :The Zebrocy Trojan gathers system specific information that it will send to the C2 server via an HTTP POST request to the above URL .
Like other Zebrocy samples , this Trojan collects system specific information it will send to the C2 server by running the command SYSTEMINFO & TASKLIST on the command line and by enumerating information about connected storage devices .
This specific variant of Zebrocy will also send a screenshot of the victim host as a JPEG image to the C2 server .
The C2 server will then provide a secondary payload to the beacon in ASCII hexadecimal representation , which the Trojan will decode and write to the following location : %APPDATA%\Roaming\Audio\soundfix.exe .
During our analysis , the C2 server provided a secondary payload that functionally appeared similar to the initial Zebrocy sample .
The secondary payload was also written in Delphi and its developer configured it to communicate with its C2 server using HTTPS via the following URL : https://200.122.181.25/catalog/products/books.php .
We were able to collect a second delivery document that shared the Joohn author from the crash list ( Lion Air Boeing 737 ).docx document , as well as the 188.241.58.170 C2 IP to host its remote template .
Structurally this sample was very similar to the initially analyzed document , but the payload turned out to be a completely new tool which we have named Cannon .
The tool is written in C# whose malicious code exists in a namespace called cannon , which is the basis of the Trojan βs name .
The Trojan functions primarily as a downloader that relies on emails to communicate between the Trojan and the C2 server .
To communicate with the C2 server , the Trojan will send emails to specific email addresses via SMTPS over TCP port 587 .
This tool also has a heavy reliance on EventHandlers with timers to run its methods in a specific order and potentially increase its evasion capability .
The overall purpose of Cannon is to use several email accounts to send system data ( system information and screenshot ) to the threat actors and to ultimately obtain a payload from an email from the actors .
In addition to the following step-by-step process illustrates how Cannon communicates with the actor-controlled C2 email address to obtain a secondary payload .
Cannon gathers system information and saves it to a file named ini .
The Trojan sends an email to [email protected] with i.ini as the attachment , S_inf within the body and a subject with a unique system identifier via SMTPS from one of the following accounts : Bishtr.cam47 , Lobrek.chizh , Cervot.woprov .
Cannon takes a screenshot and saves it to a file named ops .
The Trojan sends an email to [email protected] with sysscr.ops as the attachment , the string SCreen within the body and a subject with the unique system identifier via SMTPS from one of three previously used accounts .
The actors likely log into [email protected] and process the system information and screenshot sent by the Trojan to determine if the compromised host is of interest .
If the actor wishes to download an additional payload to the compromised host , they will respond by sending emails in the following steps .
The actor sends an email to [email protected] with the unique system identifier as a subject with a secondary email account and credentials in ASCII hexadecimal format within the message body .
This secondary email account is unknown at this time , so we will refer to it as β secondary email account β in future steps .
The actor sends an email to the secondary email account with the unique system identifier as a subject with a secondary payload attached with a filename of txt .
Cannon logs into the [email protected] account via POP3S looking for emails with a subject that matches the unique system identifier .
Cannon opens the email with the correct subject and decodes the hexadecimal data in the body of the message to obtain the secondary email account .
Cannon acknowledges the receipt of the secondary email address by sending an email to [email protected] with s.txt ( contains {SysPar = 65} string ) as the attachment , ok within the body and a subject with the unique system identifier via SMTPS from one of the three accounts from Step 1 .
The actor sends an email to [email protected] with the unique system identifier as a subject with a file path that the Cannon Trojan will use to save the secondary payload .
Cannon logs into the secondary email account via POP3S looking for emails with a subject that matches the unique system identifier .
Cannon opens the email with the correct subject and saves the attachment named auddevc.txt .
Cannon acknowledges the receipt of file download by sending an email to [email protected] with l.txt ( contains 090 string ) as the attachment , ok2 within the body and a subject with the unique system identifier via SMTPS from one of the three accounts from Step 1 .
Cannon logs into the [email protected] account via POP3S looking for emails with a subject that matches the unique system identifier .
Cannon opens the email with the correct subject and decodes the hexadecimal data in the body of the message to obtain the file path that it will use to move the downloaded auddevc.txt file .
Cannon acknowledges the receipt of file path by sending an email to [email protected] with s.txt ( contains {SysPar = 65} string ) as the attachment , ok3 within the body and a subject with the unique system identifier via SMTPS from one of the three accounts from Step 1 .
Cannon moves the downloaded file to the specified path .
Cannon acknowledges the successful move by sending an email to [email protected] with l.txt ( contains 090 string ) as the attachment , ok4 within the body and a subject with the unique system identifier via SMTPS from one of the three accounts from Step 1 .
Cannon runs the downloaded file from the specified path .
Cannon acknowledges the successful execution by sending an email to [email protected] with s.txt ( contains {SysPar = 65} string ) as the attachment , ok5 within the body and a subject with the unique system identifier via SMTPS from one of the three accounts from Step 1 .
The Sofacy threat group continues to target government organizations in the EU , US , and former Soviet states to deliver the Zebrocy tool as a payload .
In these attacks , the delivery documents used to install Zebrocy used remote templates , which increases the difficulty to analyze the attack as an active C2 server is needed to obtain the macro-enabled document .
The Sofacy group also leveraged the recent Lion Air disaster as a lure in one of these attacks , which continues to show a willingness to use current events in their social engineering themes .
Of note , we also discovered the Sofacy group using a very similar delivery document to deliver a new Trojan called Cannon .
Cannon uses SMTPS and POP3S as its C2 channel compared to Zebrocy that uses a more commonly observed HTTP or HTTPS based C2 .
This is not a new tactic but may be more effective at evading detection as the external hosts involved are a legitimate email service provider .
Add the layer of encryption that the SMTPS and POP3S protocols provide to the legitimate web-based service and you have a very difficult C2 channel to block While Sofacy βs campaign delivering Zebrocy and Cannon remains active , Palo Alto Networks customers are protected from this threat in the following ways :AutoFocus customers can track these samples with the Zebrocy and Cannon WildFire detects the delivery documents , Zebrocy and Cannon payloads discussed in this blog with malicious verdicts .
Traps blocks the macro-ladened remote templates as Suspicious macro detected , as well as Zebrocy and Cannon payloads as Suspicious executable detected .
The IP addresses hosting remote templates and C2 services in these attacks are classified as Command and Control .
Delivery Hashes :2cfc4b3686511f959f14889d26d3d9a0d06e27ee2bb54c9afb1ada6b8205c55f af77e845f1b0a3ae32cb5cfa53ff22cc9dae883f05200e18ad8e10d7a8106392 .
Remote Template Hashes :f1e2bceae81ccd54777f7862c616f22b581b47e0dda5cb02d0a722168ef194a5 fc69fb278e12fc7f9c49a020eff9f84c58b71e680a9e18f78d4e6540693f557d .
Remote Templates :Zebrocy Hashes :Zebrocy C2 URLs :http://188.241.58.170/local/s3/filters.php https://200.122.181.25/catalog/products/books.php .
Cannon Hashes :Cannon email Accounts :[email protected] [email protected] [email protected] [email protected] [email protected] .
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THE DUKES 7 YEARS OF RUSSIAN CYBERESPIONAGE .
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THE DUKES 7 YEARS OF RUSSIAN CYBERESPIONAGE .
The Dukes are a well-resourced , highly dedicated and organized cyberespionage group that we believe has been working for the Russian Federation since at least 2008 to collect intelligence in support of foreign and security policy decision-making .
The Dukes primarily target Western governments and related organizations , such as government ministries and agencies , political think tanks , and governmental subcontractors .
Their targets have also included the governments of members of the Commonwealth of Independent States ; Asian , African , and Middle Eastern governments ; organizations associated with Chechen extremism ; and Russian speakers engaged in the illicit trade of controlled substances and drugs .
The Dukes are known to employ a vast arsenal of malware toolsets , which we identify as MiniDuke , CosmicDuke , OnionDuke , CozyDuke , CloudDuke , SeaDuke , HammerDuke , PinchDuke , and GeminiDuke .
In recent years , the Dukes have engaged in apparently biannual large-scale spear-phishing campaigns against hundreds or even thousands of recipients associated with governmental institutions and affiliated organizations .
The earliest activity we have been able to definitively attribute to the Dukes are two PinchDuke campaigns from November 2008 .
These campaigns use PinchDuke samples that were , according to their compilation timestamps , created on the 5th and 12th of November 2008 .
The campaign identifiers found in these two samples are respectively , β alkavkaz.com20081105 β and β cihaderi.net20081112 β .
The first campaign identifier , found in the sample compiled on the 5th , references alkavkaz.com , a domain associated with a Turkish website proclaiming to be the β Chechan [sic] Informational Center β .
The second campaign identifier , from the sample compiled on the 12th , references cihaderi.net , another Turkish website that claims to provide β news from the jihad world β and which dedicates a section of its site to Chechnya .
Due to a lack of other PinchDuke samples from 2008 or earlier , we are unable to estimate when the Duke operation originally began .
Based on our technical analysis of the known PinchDuke samples from 2008 however , we believe PinchDuke to have been under development by the summer of 2008 .
In fact , we believe that by the autumn of 2008 , the Dukes were already developing not one but at least two distinct malware toolsets .
This assertion is based on the oldest currently known sample of another Duke related toolset , GeminiDuke , which was compiled on the 26th of January 2009 .
This sample , like the early PinchDuke samples , appears to already be a β fully-grown β sample , which is why we believe GeminiDuke was under development by the autumn of 2008 .
That the Dukes were already developing and operating at least two distinct malware toolsets by the second half of 2008 suggests to us that either the size of their cyberespionage operation was already large enough to warrant such an arsenal of tools , or that they expected their operation to grow significantly enough in the foreseeable future to warrant the development of such an arsenal .
The origins of the Duke toolset names can be traced back to when researchers at Kaspersky Labs coined the term β MiniDuke β to identify the first Duke related malware they found .
As explained in their whitepaper , the researchers observed the surprisingly small MiniDuke backdoor being spread via the same exploit that was being used by a malware that they had already named ItaDuke ; the β Duke β part of this malware βs name had in turn come about because it reminded the researchers of the notable Duqu threat .
Despite the shared history of the name itself however , it is important to note that there is no reason to believe that the Duke toolsets themselves are in any way related to the ItaDuke malware , or to Duqu for that matter .
As researchers continued discovering new toolsets that were created and used by the same group that had been operating MiniDuke , the new toolsets were also given β Duke β -derived names , and thus the threat actor operating the toolsets started to be commonly referred to as β the Dukes β .
The only other publicly used name for the threat actor that we are aware of is β APT29 β .
Based on the campaign identifiers found in PinchDuke samples discovered from 2009 , the targets of the Dukes group during that year included organizations such as the Ministry of Defense of Georgia and the ministries of foreign affairs of Turkey and Uganda .
Campaign identifiers from 2009 also reveal that by that time , the Dukes were already actively interested in political matters related to the United States ( US ) and the North Atlantic Treaty Organization ( NATO ) , as they ran campaigns targeting ( among other organizations ) a US based foreign policy think tank , another set of campaigns related to a NATO exercise held in Europe , and a third set apparently targeting what was then known as the Georgian β Information Centre on NATO β .
Of these campaigns , two clusters in particular stand out .
The first is a set of campaigns from the 16th and 17th of April , 2009 , that targeted a US based foreign policy think tank , as well as government institutions in Poland and the Czech Republic .
These campaigns utilized specially-crafted malicious Microsoft Word documents and PDF files , which were sent as e-mail attachments to various personnel in an attempt to infiltrate the targeted organizations .
We believe this cluster of campaigns had a joint goal of gathering intelligence on the sentiments of the targeted 5 countries with respect to the plans being discussed at the time for the US to locate their β European Interceptor Site β missile defense base in Poland , with a related radar station that was intended to be located in the Czech Republic .
Regarding the timing of these campaigns , it is curious to note that they began only 11 days after President Barack Obama gave a speech on the 5th of April declaring his intention to proceed with the deployment of these missile defenses .
The second notable cluster comprises of two campaigns that were possibly aimed at gathering information onThe first of these runs used the campaign identifier β natoinfo_ge β , an apparent reference to the www.natoinfo.ge website belonging to a Georgian political body that has since been renamed β Information Centre on NATO and EU β .
Although the campaign identifier itself doesnβt contain a date , we believe the campaign to have originated around the 7th of June 2009 , which was when the PinchDuke sample in question was compiled .
This belief is based on the observation that in all of the other PinchDuke samples we have analyzed , the date of the campaign identifier has been within a day of the compilation date .
The second campaign identifier , which we suspect may be related , is β mod_ge_2009_07_03 β from a month later and apparently targeting the Ministry of Defense of Georgia .
The spring of 2010 saw continued PinchDuke campaigns against Turkey and Georgia , but also numerous campaigns against other members of the Commonwealth of Independent States such as Kazakhstan , Kyrgyzstan , Azerbaijan and Uzbekistan .
Of these , the campaign with the identifier β kaz_2010_07_30 β , which possibly targeted Kazakhstan , is of note because it is the last PinchDuke campaign we have observed .
We believe that during the first half of 2010 , the Dukes slowly migrated from PinchDuke and started using a new infostealer malware toolset that we call CosmicDuke .
The first known sample of the CosmicDuke toolset was compiled on the 16th of January 2010 .
Back then , CosmicDuke still lacked most of the credential-stealing functionality found in later samples .
We believe that during the spring of 2010 , the credential and file stealing capabilities of PinchDuke were slowly ported to CosmicDuke , effectively making PinchDuke obsolete .
During this period of transition , CosmicDuke would often embed PinchDuke so that , upon execution , CosmicDuke would write to disk and execute PinchDuke .
Both PinchDuke and CosmicDuke would then operate independently on the same compromised host , including performing separate information gathering , data Exfiltration and communication with a command and control ( C&C ) server - although both malware would often use the same C&C server .
We believe the purpose of this parallel use was to β fieldtest β the new CosmicDuke tool , while at the same time ensuring operational success with the tried-and-tested PinchDuke .
During this period of CosmicDuke testing and development , the Duke authors also started experimenting with the use of privilege escalation vulnerabilities .
Specifically , on the 19th of January 2010 security researcher Tavis Ormandy disclosed a local privilege escalation vulnerability ( CVE-2010-0232 ) affecting Microsoft Windows .
As part of the disclosure , Ormandy also included the source code for a proof-of- concept exploit for the vulnerability .
Just 7 days later , on the 26th of January , a component for CosmicDuke was compiled that exploited the vulnerability and allowed the tool to operate with higher privileges .
During 2011 , the Dukes appear to have significantly expanded both their arsenal of malware toolsets and their C&C infrastructure .
While the Dukes employed both hacked websites and purposely rented servers for their C&C infrastructure , the group rarely registered their own domain names , preferring instead to connect to their self- operated servers via IP addresses .
The beginning of 2011 however saw a significant break from that routine , when a large grouping of domain names was registered by the Dukes in two batches ; the first batch was registered on the 29th of January and the second on the 13th of February .
All the domains in both batches were initially registered with the same alias : β John Kasai of Klagenfurt , Austria β .
These domains were used by the Dukes in campaigns involving many of their different malware toolsets all the way until 2014 .
Like the β MiniDuke loader β , these β John Kasai β domains also provide a common thread tying together much of the tools and infrastructure of the Dukes .
By 2011 , the Dukes had already developed at least 3 distinct malware toolsets , including a plethora of supporting components such as loaders and persistence modules .
In fact , as a sign of their arsenal βs breadth , they had already decided to retire one of these malware toolsets as obsolete after developing a replacement for it , seemingly from scratch .
The Dukes continued the expansion of their arsenal in 2011 with the addition of two more toolsets : MiniDuke and CozyDuke .
While all of the earlier toolsets β GeminiDuke , PinchDuke , and CosmicDuke β were designed around a core infostealer component , MiniDuke is centered on a simplistic backdoor component whose purpose is to enable the remote execution of commands on the compromised system .
The first observed samples of the MiniDuke backdoor component are from May 2011 .
This backdoor component however is technically very closely related to GeminiDuke , to the extent that we believe them to share parts of their source code .
The origins of MiniDuke can thus be traced back to the origins of GeminiDuke , of which the earliest observed sample was compiled in January of 2009 .
Unlike the simplistic MiniDuke toolset , CozyDuke is a highly versatile , modular , malware β platform β whose functionality lies not in a single core component but in an array of modules that it may be instructed to download from its C&C server .
These modules are used to selectively provide CozyDuke with just the functionality deemed necessary for the mission at hand .
CozyDuke βs modular platform approach is a clear break from the designs of the previous Duke toolsets .
The stylistic differences between CozyDuke and its older siblings are further exemplified by the way it was coded .
All of the 4 previously mentioned toolsets were written in a minimalistic style commonly seen with malware ; MiniDuke even goes as far as having many components written in Assembly language .
CozyDuke however represents the complete opposite .
Instead of being written in Assembly or C , it was written in C++ , which provides added layers of abstraction for the developer βs perusal , at the cost of added complexity .
Contrary to what might be expected from malware , early CozyDuke versions also lacked any attempt at obfuscating or hiding their true nature .
In fact , they were extremely open and verbose about their functionality - for example , early samples contained a plethora of logging messages in unencrypted form .
In comparison , even the earliest known GeminiDuke samples encrypted any strings that might have given away the malware βs true nature .
Finally , early CozyDuke versions also featured other elements that one would associate more with a traditional software development project than with malware .
For instance , the earliest known CozyDuke version utilized a feature of the Microsoft Visual C++ compiler known as run-time error checking .
This feature added automatic error checking to critical parts of the program βs execution at the cost , from a malware perspective , of providing additional hints that make the malware βs functionality easier for reverse engineers to understand .
Based on these and other similar stylistic differences observed between CozyDuke and its older siblings , we speculate that while the older Duke families appear to be the work of someone with a background in malware writing ( or at the least in hacking ) , CozyDuke βs author or authors more likely came from a software development background .
We still know surprisingly few specifics about the Dukes group βs activities during 2012 .
Based on samples of Duke malware from 2012 , the Dukes do appear to have continued actively using and developing all of their tools .
Of these , CosmicDuke and MiniDuke appear to have been in more active use , while receiving only minor updates .
GeminiDuke and CozyDuke on the other hand appear to have been less used in actual operations , but did undergo much more significant development .
On the 12th of February 2013 , FireEye published a blogpost alerting readers to a combination of new Adobe Reader 0-day vulnerabilities , CVE-2013-0640 and CVE-2013-0641 , that were being actively exploited in the wild .
8 days after FireEye βs initial alert , Kaspersky spotted the same exploit being used to spread an entirely different malware family from the one mentioned in the original report .
On 27th February , Kaspersky and CrySyS Lab published research on this previously unidentified malware family , dubbing it MiniDuke .
As we now know , by February 2013 the Dukes group had been operating MiniDuke and other toolsets for at least 4 and a half years .
Their malware had not stayed undetected for those 4 and a half years .
In fact , in 2009 a PinchDuke sample had been included in the malware set used by the AV-Test security product testing organization to perform anti-virus product comparison reviews .
Until 2013 however , earlier Duke toolsets had not been put in a proper context .
That finally started to change in 2013 .
The MiniDuke samples that were spread using these exploits were compiled on the 20th of February , after the exploit was already publicly known .
One might argue that since this took place after the exploits were publicly mentioned , the Dukes simply copied them .
We however do not believe so .
As mentioned by Kaspersky , even though the exploits used for these MiniDuke campaigns were near-identical to those described by FireEye , there were nevertheless small differences .
Of these , the crucial one is the presence of PDB strings in the MiniDuke exploits .
These strings , which are generated by the compiler when using specific compilation settings , means that the components of the exploits used with MiniDuke had to have been compiled independently from those described by FireEye .
We do not know whether the Dukes compiled the components themselves or whether someone else compiled the components before handing them to the group .
This does however still rule out the possibility that the Dukes simply obtained copies of the exploit binaries described by FireEye and repurposed them .
In our opinion , this insistence on using exploits that are already under heightened scrutiny suggests the existence of at least one of three circumstances .
Firstly , the Dukes may have been confident enough in their own abilities ( and in the slowness of their opponents to react to new threats ) that they did not care if their targets may already be on the lookout for anyone exploiting these vulnerabilities .
Secondly , the value the Dukes intended to gain from these MiniDuke campaigns may have been so great that they deemed it worth the risk of getting noticed .
Or thirdly , the Dukes may have invested so much into these campaigns that by the time FireEye published their alert , the Dukes felt they could not afford to halt the campaigns .
We believe all three circumstances to have coexisted at least to some extent .
As will become evident in this report , this was not a one-off case but a recurring theme with the Dukes , in that they would rather continue with their operations as planned than retreat from operating under the spotlight .
As originally detailed in Kaspersky βs whitepaper , the MiniDuke campaigns from February 2013 employed spear-phishing emails with malicious PDF file attachments .
These PDFs would attempt to silently infect the recipient with MiniDuke , while distracting them by displaying a decoy document .
The headings of these documents included β Ukraine βs NATO Membership Action Plan ( MAP ) Debates β , β The Informal Asia-Europe Meeting ( ASEM ) Seminar on Human Rights β , and β Ukraine βs Search for a Regional Foreign Policy β .
The targets of these campaigns , according to Kaspersky , were located variously in Belgium , Hungary , Luxembourg and Spain .
Kaspersky goes on to state that by obtaining log files from the MiniDuke command and control servers , they were able to identify high-profile victims from Ukraine , Belgium , Portugal , Romania , the Czech Republic , Ireland , the United States and Hungary .
After the February campaigns , MiniDuke activity appeared to quiet down , although it did not fully stop , for the rest of 2013 .
The Dukes group as a whole however showed no sign of slowing down .
In fact , we saw yet another Duke malware toolset , OnionDuke , appear first in 2013 .
Like CozyDuke , OnionDuke appears to have been designed with versatility in mind , and takes a similarly modular platform approach .
The OnionDuke toolset includes various modules for purposes such as password stealing , information gathering , denial of service ( DoS ) attacks , and even posting spam to the Russian social media network , VKontakte .
The OnionDuke toolset also includes a dropper , an information stealer variant and multiple distinct versions of the core component that is responsible for interacting with the various modules .
What makes OnionDuke especially curious is an infection vector it began using during the summer of 2013 .
To spread the toolset , the Dukes used a wrapper to combine OnionDuke with legitimate applications , created torrent files containing these trojanized applications , then uploaded them to websites hosting torrent files .
Victims who used the torrent files to download the applications would end up getting infected with OnionDuke .
For most of the OnionDuke components we observed , the first versions that we are aware of were compiled during the summer of 2013 , suggesting that this was a period of active development around this toolset .
Critically however , the first sample of the OnionDuke dropper , which we have observed being used only with components of this toolset , was compiled on the 17th of February 2013 .
This is significant because it suggests that OnionDuke was under development before any part of the Duke operation became public .
OnionDuke βs development therefore could not have been simply a response to the outing of one of the other Duke malware , but was instead intended for use alongside the other toolsets .
This indication that the Dukes planned to use an arsenal of 5 malware toolsets in parallel suggests that they were operating with both significant resources and capacity .
In 2013 , many of the decoy documents employed by the Dukes in their campaigns were related to Ukraine ; examples include a letter undersigned by the First Deputy Minister for Foreign Affairs of Ukraine , a letter from the embassy of the Netherlands in Ukraine to the Ukrainian Ministry of Foreign affairs and a document titled β Ukraine βs Search for a Regional Foreign Policy β .
These decoy documents however were written before the start of the November 2013 Euromaidan protests in Ukraine and the subsequent upheaval .
It is therefore important to note that , contrary to what might be assumed , we have actually observed a drop instead of an increase in Ukraine related campaigns from the Dukes following the country βs political crisis .
This is in stark contrast to some other suspected Russian threat actors ( such as Operation Pawn Storm ) who appear to have increased their targeting of Ukraine following the crisis .
This supports our analysis that the overarching theme in the Dukes β targeting is the collection of intelligence to support diplomatic efforts .
The Dukes actively targeted Ukraine before the crisis , at a time when Russia was still weighing her options , but once Russia moved from diplomacy to direct action , Ukraine was no longer relevant to the Dukes in the same way .
In a surprising turn of events , in September 2013 a CosmicDuke campaign was observed targeting Russian speakers involved in the trade of illegal and controlled substances .
Kaspersky Labs , who sometimes refer to CosmicDuke as β Bot Gen Studio β , speculated that β one possibility is that β Bot Gen Studio β is a malware platform also available as a so-called β legal spyware β tool β ;therefore , those using CosmicDuke to target drug dealers and those targeting governments are two separate entities .
We however feel it is unlikely that the CosmicDuke operators targeting drug dealers and those targeting governments could be two entirely independent entities .
A shared supplier of malware would explain the overlap in tools , but it would not explain the significant overlap we have also observed in operational techniques related to command and control infrastructure .
Instead , we feel the targeting of drug dealers was a new task for a subset of the Dukes group , possibly due to the drug trade βs relevance to security policy issues .
We also believe the tasking to have been temporary , because we have not observed any further similar targeting from the Dukes after the spring of 2014 .
While MiniDuke activity decreased significantly during the rest of 2013 following the attention it garnered from researchers , the beginning of 2014 saw the toolset back in full force .
All MiniDuke components , from the loader and downloader to the backdoor , had been slightly updated and modified during the downtime .
Interestingly , the nature of these modifications suggests that their primary purpose was to regain the element of stealth and undetectability that had been lost almost a year earlier .
Of these modifications , arguably the most important were the ones done to the loader .
These resulted in a loader version that would later become known as the β Nemesis Gemina loader β due to PDB strings found in many of the samples .
It is however still only an iteration on earlier versions of the MiniDuke loader .
The first observed samples of the Nemesis Gemina loader ( compiled on 14th December 2013 ) were used to load the updated MiniDuke backdoor , but by the spring of 2014 the Nemesis Gemina loader was also observed in use with CosmicDuke .
Following the MiniDuke expose , CosmicDuke in turn got its moment of fame when F-Secure published a whitepaper about it on 2nd July 2014 .
The next day , Kaspersky also published their own research on the malware .
It should be noted that until this point , even though CosmicDuke had been in active use for over 4 years , and had undergone minor modifications and updates during that time , even the most recent CosmicDuke samples would often embed persistence components that date back to 2012 .
These samples would also contain artefacts of functionality from the earliest CosmicDuke samples from 2010 .
It is therefore valuable to observe how the Dukes reacted to CosmicDuke βs outing at the beginning of July .
By the end of that month , CosmicDuke samples we found that had been compiled on the 30th of July had shed unused parts of their code that had essentially just been relics of the past .
Similarly , some of the hardcoded values that had remained unaltered in CosmicDuke samples for many years had been changed .
We believe these edits were an attempt at evading detection by modifying or removing parts of the toolset that the authors believed might be helpful in identifying and detecting it .
Concurrently with the alterations to CosmicDuke , the Dukes were also hard at work modifying their trusted loader .
Much like the CosmicDuke toolset , the loader used by both MiniDuke and CosmicDuke had previously only undergone one major update ( the Nemesis Gemina upgrade ) since the first known samples from 2010 .
Again , much of the modification work focused on removing redundant code in an attempt to appear different from earlier versions of the loader .
Interestingly however , another apparent evasion trick was also attempted - forging of the loaders β compilation timestamps .
The first CosmicDuke sample we observed after the initial research on CosmicDuke was a sample compiled on the 30th of July 2014 .
The loader used by the sample purported to have been compiled on the 25th of March 2010 .
Due to artefacts left in the loader during compilation time however , we know that it used a specific version of the Boost library , 1.54.0 , that was only published on the 1st of July 2013 .
The compilation timestamp therefore had to have been faked .
F-Secure βs whitepaper on CosmicDuke includes a timeline of the loader βs usage , based on compilation timestamps .
Perhaps the Dukes group thought that by faking a timestamp from before the earliest one cited in the whitepaper , they might be able to confuse researchers .
During the rest of 2014 and the spring of 2015 , the Dukes continued making similar evasionfocused modifications to CosmicDuke , as well as experimenting with ways to obfuscate the loader .
In the latter case however , the group appear to have also simultaneously developed an entirely new loader , which we first observed being used in conjunction with CosmicDuke during the spring of 2015 .
While it is not surprising that the Dukes reacted to multiple companies publishing extensive reports on one of their key toolsets , it is valuable to note the manner in which they responded .
Much like the MiniDuke expose in February 2013 , the Dukes again appeared to prioritize continuing operations over staying hidden .
They could have ceased all use of CosmicDuke ( at least until they had developed a new loader ) or retired it entirely , since they still had other toolsets available .
Instead , they opted for minimal downtime and attempted to continue operations , with only minor modifications to the toolset .
While we now know that CozyDuke had been under development since at least the end of 2011 , it was not until the early days of July 2014 that the first large-scale CozyDuke campaign that we are aware of took place .
This campaign , like later CozyDuke campaigns , began with spear-phishing emails that tried to impersonate commonly seen spam emails .
These spear-phishing emails would contain links that eventually lead the victim to becoming infected with CozyDuke .
Some of the CozyDuke spear-phishing emails from early July posed as e-fax arrival notifications , a popular theme for spam emails , and used the same β US letter fax test page β decoy document that was used a year later by CloudDuke .
In at least one case however , the email instead contained a link to a zip archive file named β Office Monkeys LOL Video.zip β , which was hosted on the DropBox cloud storage service .
What made this particular case interesting was that instead of the usual dull PDF file , the decoy was a Flash video file , more specifically a Super Bowl advertisement from 2007 purporting to show monkeys at an office .
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2015 : The Dukes up the ante .
The end of January 2015 saw the start of the most high- volume Duke campaign seen thus far , with thousands of recipients being sent spear-phishing emails that contained links to compromised websites hosting CozyDuke .
Curiously , the spear-phishing emails were strikingly similar to the e-fax themed spam usually seen spreading ransomware and other common crimeware .
Due to the sheer number of recipients , it may not have been possible to customize the emails in the same way as was possible with lower-volume campaigns .
The similarity to common spam may however also serve a more devious purpose .
It is easy to imagine a security analyst , burdened by the amount of attacks against their network , dismissing such common-looking spam as β just another crimeware spam run β , allowing the campaign to , in essence , hide in the masses .
The CozyDuke activity continues one of the long-running trends of the Dukes operations , the use of multiple malware toolsets against a single target .
In this case , the Dukes first attempted to infect large numbers of potential targets with CozyDuke ( and in a more obvious manner than previously seen ) .
They would then use the toolset to gather initial information on the victims , before deciding which ones to pursue further .
For the victims deemed interesting enough , the Dukes would then deploy a different toolset .
We believe the primary purpose of this tactic is an attempt at evading detection in the targeted network .
Even if the noisy initial CozyDuke campaign is noticed by the victim organization , or by someone else who then makes it publicly known , defenders will begin by first looking for indicators of compromise ( IOCs ) related to the CozyDuke toolset .
If however by that time the Dukes are already operating within the victim βs network , using an another toolset with different IOCs , then it is reasonable to assume that it will take much longer for the victim organization to notice the infiltration .
In previous cases , the group used their malware toolsets interchangeably , as either the initial or a later-stage toolset in a campaign .
For these CozyDuke campaigns however , the Dukes appear to have employed two particular later-stage toolsets , SeaDuke and HammerDuke , that were purposely designed to leave a persistent backdoor on the compromised network .
HammerDuke is a set of backdoors that was first seen in the wild in February 2015 , while SeaDuke is a crossplatform backdoor that was , according to Symantec , first spotted in the wild in October 2014 .
Both toolsets were originally spotted being deployed by CozyDuke to its victims .
What makes SeaDuke special is that it was written in Python and designed to work on both Windows and Linux systems ; it is the first cross-platform tool we have seen from the Dukes .
One plausible reason for developing such a flexible malware might be that the group were increasingly encountering victim environments where users were using Linux as their desktop operating system .
Meanwhile , HammerDuke is a Windows only malware ( written in .NET ) and comes in two variants .
The simpler one will connect to a hardcoded C&C server over HTTP or HTTPS to download commands to execute .
The more advanced variant , on the other hand , will use an algorithm to generate a periodically-changing Twitter account name and will then attempt to find tweets from that account containing links to the actual download location of the commands to execute .
In this way , the advanced HammerDuke variant attempts to hide its network traffic in more legitimate use of Twitter .
This method is not unique to HammerDuke , as MiniDuke , OnionDuke , and CozyDuke all support similar use of Twitter ( image 9 , page 18 ) to retrieve links to additional payloads or commands .
2015 : CloudDuke .
In the beginning of July 2015 , the Dukes embarked on yet another large-scale phishing campaign .
The malware toolset used for this campaign was the previously unseen CloudDuke and we believe that the July campaign marks the first time that this toolset was deployed by the Dukes , other than possible small-scale testing .
The CloudDuke toolset consists of at least a loader , a downloader , and two backdoor variants .
Both backdoors ( internally referred to by their authors as β BastionSolution β and β OneDriveSolution β ) essentially allow the operator to remotely execute commands on the compromised machine .
The way in which each backdoor does so however is significantly different .
While the BastionSolution variant simply retrieves commands from a hard-coded C&C server controlled by the Dukes , the OneDriveSolution utilizes Microsoft βs OneDrive cloud storage service for communicating with its masters , making it significantly harder for defenders to notice the traffic and block the communication channel .
What is most significant about the July 2015 CloudDuke campaign is the timeline .
The campaign appeared to consist of two distinct waves of spear-phishing , one during the first days of July and the other starting from the 20th of the month .
Details of the first wave , including a thorough technical analysis of CloudDuke , was published by Palo Alto Networks on 14th July .
This was followed by additional details from Kaspersky in a blog post published on 16th July .
Both publications happened before the second wave took place and received notable publicity .
Despite the attention and public exposure of the toolset βs technical details ( including IOCs ) to defenders , the Dukes still continued with their second wave of spear-phishing , including the continued use of CloudDuke .
The group did change the contents of the spear-phishing emails they sent , but they didnβt switch to a new email format ; instead , they reverted to the same efaxthemed format that they had previously employed , even to the point of reusing the exact same decoy document that they had used in the CozyDuke campaign a year earlier ( July 2014 ) .
This once more highlights two crucial behavioral elements of the Dukes group .
Firstly , as with the MiniDuke campaigns of February 2013 and CosmicDuke campaigns in the summer of 2014 , again the group clearly prioritized the continuation of their operations over maintaining stealth .
Secondly , it underlines their boldness , arrogance and self-confidence ; they are clearly confident in both their ability to compromise their targets even when their tools and techniques are already publicly known , and critically , they appear to be extremely confident in their ability to act with impunity .
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2015 : Continuing surgical strikes with CosmicDuke .
In addition to the notably overt and large-scale campaigns with CozyDuke and CloudDuke , the Dukes also continued to engage in more covert , surgical campaigns using CosmicDuke .
The latest of these campaigns that we are aware of occurred during the spring and early summer of 2015 .
As their infection vectors , these campaigns used malicious documents exploiting recently fixed vulnerabilities .
Two of these campaigns were detailed in separate blog posts by the Polish security company Prevenity , who said that both campaigns targeted Polish entities with spear- phishing emails containing malicious attachments with relevant Polish language names .
A third , similar , CosmicDuke campaign was observed presumably targeting Georgian entities since it used an attachment with a Georgian-language name that translates to β NATO consolidates control of the Black Sea.docx β .
Based on this , we do not believe that the Dukes are replacing their covert and targeted campaigns with the overt and opportunistic CozyDuke and CloudDuke style of campaigns .
Instead , we believe that they are simply expanding their activities by adding new tools and techniques .
A XENOTIME to Remember : Veles in the Wild .
FireEye recently published a blog covering the tactics , techniques , and procedures ( TTPs ) for the β TRITON actor β when preparing to deploy the TRITON / TRISIS malware framework in 2017 .
Overall , the post does a commendable job in making public findings previously only privately shared ( presumably by FireEye , and in several reports I authored for my employer , Dragos ) to threat intelligence customers .
As such , the blog continues to push forward the narrative of how ICS attacks are enabled through prepositioning and initial intrusion operations β an item I have discussed at length .
Yet one point of confusion in the blog comes at the very start : referring to the entity responsible for TRITON as the β TRITON actor β .
This seems confusing as FireEye earlier publicly declared the β TRITON actor β as a discrete entity , linked to a Russian research institution , and christened it as β TEMP.Veles β .
In the 2018 public posting announcing TEMP.Veles , FireEye researchers noted that the institute in question at least supported TEMP.Veles activity in deploying TRITON , with subsequent public presentations at Cyberwarcon and the Kaspersky Lab sponsored Security Analyst Summit essentially linking TRITON and the research institute ( and therefore TEMP.Veles ) as one in the same .
Yet the most-recent posting covering TTPs from initial access through prerequisites to enable final delivery of effects on target ( deploying TRITON / TRISIS ) avoids the use of the TEMP.Veles term entirely .
In subsequent discussion , FireEye personnel indicate that there was not β an avalanche of evidence to substantiate β anything more than β TRITON actor β β summing matters by indicating this term β is the best we βve got for the public for now β .
Meanwhile , parallel work at Dragos ( my employer , where I have performed significant work on the activity described above ) uncovered similar conclusions concerning TTPs and behaviors , for both the 2017 event and subsequent activity in other industrial sectors .
Utilizing Diamond Model methodology for characterizing activity by behaviors attached to victims , we began tracking TRITON / TRISIS and immediate enabling activity as a distinct activity group ( collection of behaviors , infrastructure , and victimology ) designated XENOTIME .
Based on information gained from discussion with the initial TRITON / TRISIS responders and subsequent work on follow-on activity by this entity , Dragos developed a comprehensive ( public ) picture of adversary activity roughly matching FireEye βs analysis published in April 2019 , described in various media .
At this stage , we have two similar , parallel constructions of events β the how behind the immediate deployment and execution of TRITON / TRISIS β yet dramatically different responses in terms of attribution and labeling .
Since late 2018 , based upon the most-recent posting , FireEye appears to have β walked back β the previously-used terminology of TEMP.Veles and instead refers rather cryptically to the β TRITON actor β , while Dragos leveraged identified behaviors to consistently refer to an activity group , XENOTIME .
Given that both organizations appear to describe similar ( if not identical ) activity , any reasonable person could ( and should ) ask β why the inconsistency in naming and identification .
Aside from the competitive vendor naming landscape ( which I am not a fan of in cases on direct overlap , but which has more to say for itself when different methodologies are employed around similar observations ) , the distinction between FireEye and Dragos β approaches with respect to the β TRITON actor β comes down to fundamental philosophical differences in methodology .
As wonderfully described in a recent public posting , FireEye adheres to a naming convention based upon extensive data collection and activity comparison , designed to yield the identification of a discrete , identifiable entity responsible for a given collection of activity .
This technique is precise and praiseworthy β yet at the same time , appears so rigorous as to impose limitations on the ability to dynamically adjust and adapt to emerging adversary activity .
( Or for that matter , even categorize otherwise well-known historical actors operating to the present day , such as Turla .
) FireEye βs methodology may have particular limitations in instances where adversaries ( such as XENOTIME and presumably TEMP.Veles ) rely upon extensive use of publicly-available , commonly-used tools with limited amounts of customization .
In such cases , utilizing purely technical approaches for differentiation ( an issue I lightly touched on in a recent post ) becomes problematic , especially when trying to define attribution to specific , β who-based β entities ( such as a Russian research institute ) .
My understanding is FireEye labels entities where definitive attribution is not yet possible with the β TEMP β moniker ( hence , TEMP.Veles ) β yet in this case FireEye developed and deployed the label , then appeared to move away from it in subsequent reporting .
Based on the public blog post β which also indicated that FireEye is responding to an intrusion at a second facility featuring the same or similar observations β this is presumably not for lack of evidence , yet the β downgrade β occurs all the same .
In comparison , XENOTIME was defined based on principles of infrastructure ( compromised third-party infrastructure and various networks associated with several Russian research institutions ) , capabilities ( publicly- and commercially-available tools with varying levels of customization ) and targeting ( an issue not meant for discussion in this blog ) .
In personally responding to several incidents across multiple industry sectors since early 2018 matching TTPs from the TRITON / TRISIS event , these items proved consistent and supported the creation of the XENOTIME activity group .
This naming decision was founded upon the underlying methodology described in the Diamond Model of intrusion analysis .
As such , this decision does not necessarily refer to a specific institution , but rather a collection of observations and behaviors observed across multiple , similarly-situated victims .
Of note , this methodology of naming abstracts away the β who β element β XENOTIME may represent a single discrete entity ( such as a Russian research institution ) or several entities working in coordination in a roughly repeatable , similar manner across multiple events .
Ultimately , the epistemic foundation of the behavior-based naming approach makes this irrelevant for tracking ( and labeling for convenience sake ) observations .
Much like the observers watching the shadows of objects cast upon the wall of the cave , these two definitions ( XENOTIME and TEMP.Veles , both presumably referring to β the TRITON actor β ) describe the same phenomena , yet at the same time appear different .
This question of perception and accuracy rests upon the underlying epistemic framework and the goal conceived for that framework in defining an adversary : FireEye βs methodology follows a deductive approach requiring the collection of significant evidence over time to yield a conclusion that will be necessary given the premises ( the totality of evidence suggests APTxx ) ; the Dragos approach instead seeks an inductive approach , where premises may all be true but the conclusion need not necessarily follow from them given changes in premises over time or other observations not contained within the set ( thus , identified behaviors strongly suggests an activity group , defined as X ) .
From an external analysts β point of view , the wonder is , which is superior to the other .
And my answer for this is : neither is perfect , but both are useful β depending upon your goals and objectives .
But rather than trying to pursue some comparison between the two for identification of superiority ( an approach that will result in unproductive argument and social media warring ) , the point of this post is to highlight the distinctions between these approaches and how β in the case of β the TRITON actor β β they result in noticeably different conclusions from similar datasets .
One reason for the distinction may be differences in evidence , as FireEye βs public reporting notes two distinct events of which they are aware of and have responded to related to β the TRITON actor β while Dragos has been engaged several instances β thus , Dragos would possess more evidence to cement the definition of an activity group , while FireEye βs data collection-centric approach would require far more observations to yield an β APT β .
Yet irrespective of this , it is confusing why the previously-declared β TEMP β category was walked back as this has led to not small amount of confusion β in both technical and non-technical audiences β as to just what FireEye βs blog post refers .
Thus respected journalists ( at least by me ) conflate the β TRITON actor is active at another site β with β TRITON malware was identified at another site β .
In this case , we βre seeing a definite problem with the overly-conservative naming approach used as it engenders confusion in a significant subset of the intended audience .
While some may dismiss adversary or activity naming as so much marketing , having a distinct label for something allows for clearer communication and more accurate discussion .
Furthermore , conflating adversaries with tools , since tools can be repurposed or used by other entities than those first observed deploying them , leads to further potential confusion as the β X actor β is quickly compressed in the minds of some to refer to any and all instantiations of tool β X β .
Overall , the discussion above may appear so much splitting of hairs or determining how many angels can dance on the head of a pin β yet given the communicative impacts behind different naming and labeling conventions , this exploration seems not merely useful but necessary .
Understanding the β how β and β why β behind different entity classifications of similar ( or even the same ) activity allows us to move beyond the dismissive approach of β everyone has their names for marketing purposes β to a more productive mindset that grasps the fundamental methodologies that ( should ) drive these decisions .
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Malware Testing Environment Tied to TEMP.Veles .
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Malware Testing Environment Tied to TEMP.Veles .
We identified a malware testing environment that we assess with high confidence was used to refine some TEMP.Veles tools .
At times , the use of this malware testing environment correlates to in-network activities of TEMP.Veles , demonstrating direct operational support for intrusion activity .
Four files tested in 2014 are based on the open-source project , cryptcat .
Analysis of these cryptcat binaries indicates that the actor continually modified them to decrease AV detection rates .
One of these files was deployed in a TEMP.Veles target βs network .
The compiled version with the least detections was later re-tested in 2017 and deployed less than a week later during TEMP.Veles activities in the target environment .
TEMP.Veles β lateral movement activities used a publicly-available PowerShell based tool , WMImplant .
On multiple dates in 2017 , TEMP.Veles struggled to execute this utility on multiple victim systems , potentially due to AV detection .
Soon after , the customized utility was again evaluated in the malware testing environment .
The following day , TEMP.Veles again tried the utility on a compromised system .
The user has been active in the malware testing environment since at least 2013 , testing customized versions of multiple open-source frameworks , including Metasploit , Cobalt Strike , PowerSploit , and other projects .
The user βs development patterns appear to pay particular attention to AV evasion and alternative code execution techniques .
Custom payloads utilized by TEMP.Veles in investigations conducted by Mandiant are typically weaponized versions of legitimate open-source software , retrofitted with code used for command and control .
Testing , Malware Artifacts , and Malicious Activity Suggests Tie to CNIIHM .
Multiple factors suggest that this activity is Russian in origin and associated with CNIIHM .
A PDB path contained in a tested file contained a string that appears to be a unique handle or user name .
This moniker is linked to a Russia based person active in Russian information security communities since at least 2011 .
The handle has been credited with vulnerability research contributions to the Russian version of Hacker Magazine ( Ρ
Π°ΠΊΠ΅Ρ ) .
According to a now-defunct social media profile , the same individual was a professor at CNIIHM , which is located near Nagatinskaya Street in the Nagatino-Sadovniki district of Moscow .
Another profile using the handle on a Russian social network currently shows multiple photos of the user in proximity to Moscow for the entire history of the profile .
Suspected TEMP.Veles incidents include malicious activity originating from 87.245.143.140 , which is registered to CNIIHM .
This IP address has been used to monitor open-source coverage of TRITON , heightening the probability of an interest by unknown subjects , originating from this network , in TEMP.Veles related activities .
It also has engaged in network reconnaissance against targets of interest to TEMP.Veles .
The IP address has been tied to additional malicious activity in support of the TRITON intrusion .
Multiple files have Cyrillic names and artifacts .
Adversary behavioral artifacts further suggest the TEMP.Veles operators are based in Moscow , lending some further support to the scenario that CNIIHM , a Russian research organization in Moscow , has been involved in TEMP.Veles activity .
We identified file creation times for numerous files that TEMP.Veles created during lateral movement on a target βs network .
These file creation times conform to a work schedule typical of an actor operating within a UTC+3 time zone supporting a proximity to Moscow .
Additional language artifacts recovered from TEMP.Veles toolsets are also consistent with such a regional nexus .
A ZIP archive recovered during our investigations , schtasks.zip , contained an installer and uninstaller of CATRUNNER that includes two versions of an XML scheduled task definitions for a masquerading service β ProgramDataUpdater .
β The malicious installation version has a task name and description in English , and the clean uninstall version has a task name and description in Cyrillic .
The timeline of modification dates within the ZIP also suggest the actor changed the Russian version to English in sequential order , heightening the possibility of a deliberate effort to mask its origins .
While we know that TEMP.Veles deployed the TRITON attack framework , we do not have specific evidence to prove that CNIIHM did ( or did not ) develop the tool .
We infer that CNIIHM likely maintains the institutional expertise needed to develop and prototype TRITON based on the institute βs self-described mission and other public information .
CNIIHM has at least two research divisions that are experienced in critical infrastructure , enterprise safety , and the development of weapons/military equipment :The Center for Applied Research creates means and methods for protecting critical infrastructure from destructive information and technological impacts .
The Center for Experimental Mechanical Engineering develops weapons as well as military and special equipment .
It also researches methods for enabling enterprise safety in emergency situations .
CNIIHM officially collaborates with other national technology and development organizations , including :The Moscow Institute of Physics and Technology ( PsyTech ) , which specializes in applied physics , computing science , chemistry , and biology .
The Association of State Scientific Centers β Nauka , β which coordinates 43 Scientific Centers of the Russian Federation ( SSC RF ) .
Some of its main areas of interest include nuclear physics , computer science and instrumentation , robotics and engineering , and electrical engineering , among others .
The Federal Service for Technical and Export Control ( FTEC ) which is responsible for export control , intellectual property , and protecting confidential information .
The Russian Academy of Missile and Artillery Sciences ( PAPAH ) which specializes in research and development for strengthening Russia βs defense industrial complex .
Information from a Russian recruitment website , linked to CNIIHM βs official domain , indicates that CNIIHM is also dedicated to the development of intelligent systems for computer-aided design and control , and the creation of new information technologies .
Some possibility remains that one or more CNIIHM employees could have conducted the activity linking TEMP.Veles to CNIIHM without their employer βs approval .
However , this scenario is highly unlikely .
In this scenario , one or more persons β likely including at least one CNIIHM employee , based on the moniker discussed above β would have had to conduct extensive , high-risk malware development and intrusion activity from CNIIHM βs address space without CNIIHM βs knowledge and approval over multiple years .
CNIIHM βs characteristics are consistent with what we might expect of an organization responsible for TEMP.Veles activity .
TRITON is a highly specialized framework whose development would be within the capability of a low percentage of intrusion operators .
Release_Time : unknownReport_URL : https://dragos.com/resource/xenotime/XENOTIME is easily the most dangerous threat activity publicly known .
It is the only activity group intentionally compromising and disrupting industrial safety instrumented systems , which can lead to scenarios involving loss of life and environmental damage .
Dragos identified several compromises of ICS vendors and manufacturers in 2018 by activity associated with XENOTIME , providing potential supply chain threat opportunities and vendor-enabled access to asset owner and operator ICS networks .
XENOTIME rose to prominence in December 2017 when Dragos and FireEye jointly published details of TRISIS destructive malware targeting Schneider Electric βs Triconex safety instrumented system .
The multi-step malware framework caused industrial systems in a Middle Eastern industrial facility to shut down .
The incident represented a shift in the capabilities and consequences of ICS malware .
TRISIS was an escalation of the type of attacks historically targeting ICS systems .
Targeting a safety system indicates significant damage and loss of human life were either intentional or acceptable goals of the attack , a consequence not seen in previous disruptive attacks such as the 2016 CRASHOVERRIDE malware that caused a power loss in Ukraine .
Note : Industrial safety instrumented systems comprise part of a multi-layer engineered process control framework to protect life and environment .
Industrial safety systems are highly redundant and separate controls which override and manage industrial processes if they approach unsafe conditions such as over-pressurization , overspeed , or over-heating .
They enable engineers and operators to safely control and possibly shutdown processes before a major incident occurs .
They βre a critical component of many dangerous industrial environments such as electric power generation and oil and gas processing .
XENOTIME configured TRISIS based on the specifics and functions of the Triconex system within the industrial control ( ICS ) environment .
XENOTIME used credential capture and replay to move between networks , Windows commands , standard command-line tools such as PSExec , and proprietary tools for operations on victim hosts .
( Full reports detailing XENOTIME βs tool techniques , and procedures are available to Dragos WorldView customers .
) Because the TRISIS malware framework was highly tailored , it would have required specific knowledge of the Triconex βs infrastructure and processes within a specific plant .
This means it βs not easy to scaleβhowever , the malware provides a blueprint of how to target safety instrumented systems .
This tradecraft is thus scalable and available to others even if the malware itself changes .
Dragos β data indicates XENOTIME remains active .
Furthermore , Dragos β analysis of the TRISIS event continues as we recover additional data surrounding the incident .
Dragos assesses with moderate confidence that XENOTIME intends to establish required access and capability to cause a potential , future disruptiveβor even destructiveβevent .
Compromising safety systems provides little value outside of disrupting operations .
The group created a custom malware framework and tailormade credential gathering tools , but an apparent misconfiguration prevented the attack from executing properly .
As XENOTIME matures , it is less likely that the group will make this mistake in the future .
XENOTIME operates globally , impacting regions far outside of the Middle East , their initial target .
Intelligence suggests the group has been active since at least 2014 and is presently operating in multiple facilities targeting safety systems beyond Triconex .
This group has no known associations to other activity groups .
Dragos threat intelligence leverages the Dragos Platform , our threat operations center , and other sources to provide comprehensive insight into threats affecting industrial control security and safety worldwide .
Dragos does not corroborate nor conduct political attribution to threat activity .
Dragos instead focuses on threat behaviors and appropriate detection and response .
Read more about Dragos β approach to categorizing threat activity and attribution .
Dragos does not publicly describe ICS activity group technical details except in extraordinary circumstances in order to limit tradecraft proliferation .
However , full details on XENOTIME and other group tools , techniques , procedures , and infrastructure is available to network defenders via Dragos WorldView .
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Threat Group 3390 Cyberespionage .
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Threat Group 3390 Cyberespionage .
Dell SecureWorks Counter Threat Unit (TM ) ( CTU ) researchers investigated activities associated with Threat Group-3390 ( TG-3390 ) .
Analysis of TG-3390 's operations , targeting , and tools led CTU researchers to assess with moderate confidence the group is located in the People's Republic of China .
The threat actors target a wide range of organizations : CTU researchers have observed TG-3390 actors obtaining confidential data on defense manufacturing projects , but also targeting other industry verticals and attacking organizations involved in international relations .
The group extensively uses long-running strategic web compromises ( SWCs ) , and relies on whitelists to deliver payloads to select victims .
In comparison to other threat groups , TG-3390 is notable for its tendency to compromise Microsoft Exchange servers using a custom backdoor and credential logger .
CTU researchers divided the threat intelligence about TG-3390 into two sections : strategic and tactical .
Strategic threat intelligence includes an assessment of the ongoing threat posed by the threat group .
Executives can use this assessment to determine how to reduce risk to their organization's mission and critical assets .
Tactical threat intelligence is based on incident response investigations and research , and is mapped to the kill chain .
Computer network defenders can use this information to reduce the time and effort associated with responding to TG-3390 .
CTU researchers assess with moderate confidence that TG-3390 is based in the People's Republic of China .
CTU researchers have evidence that the threat group compromised U.S. and UK organizations in the following verticals : manufacturing ( specifically aerospace ( including defense contractors ) , automotive , technology , energy , and pharmaceuticals ) , education , and legal , as well as organizations focused on international relations .
Based on analysis of the group's SWCs , TG-3390 operations likely affect organizations in other countries and verticals .
TG-3390 operates a broad and long-running campaign of SWCs and has compromised approximately 100 websites as of this publication .
Through an IP address whitelisting process , the threat group selectively targets visitors to these websites .
After the initial compromise , TG-3390 delivers the HttpBrowser backdoor to its victims .
The threat actors then move quickly to compromise Microsoft Exchange servers and to gain complete control of the target environment .
The threat actors are adept at identifying key data stores and selectively exfiltrating all of the high-value information associated with their goal .
CTU researchers recommend the following practices to prevent or detect TG-3390 intrusions :Search web log files for evidence of web server scanning using the URIs listed in the Exploitation section and evidence of Exfiltration using the User-Agent in the Actions on objective section .
Require two-factor authentication for all remote access solutions , including OWA .
Audit ISAPI filters and search for web shells on Microsoft Exchange servers .
CTU researchers infer intent by aggregating observations , analyzing a threat group's activity , and placing the information in a wider context .
Like many threat groups , TG-3390 conducts strategic web compromises ( SWCs ) , also known as watering hole attacks , on websites associated with the target organization's vertical or demographic to increase the likelihood of finding victims with relevant information .
CTU researchers assess with high confidence that TG-3390 uses information gathered from prior reconnaissance activities to selectively compromise users who visit websites under its control .
Most websites compromised by TG-3390 actors are affiliated with five types of organizations around the world :large manufacturing companies , particularly those supplying defense organizations , energy companies , embassies in Washington , DC representing countries in the Middle East , Europe , and Asia , likely to target U.S. based users involved in international relations , non-governmental organizations ( NGOs ) , particularly those focused on international relations and defense , government organizations .
Based on this information , CTU researchers assess that TG-3390 aims to collect defense technology and capability intelligence , other industrial intelligence , and political intelligence from governments and NGOs .
To assess attribution , CTU researchers analyze observed activity , third-party reporting , and contextual intelligence .
For the following reasons , CTU researchers assess with moderate confidence that TG-3390 has a Chinese nexus :The SWC of a Uyghur cultural website suggests intent to target the Uyghur ethnic group , a Muslim minority group primarily found in the Xinjiang region of China .
Threat groups outside of China are unlikely to target the Uyghur people .
TG-3390 uses the PlugX remote access tool .
The menus for PlugX 's server-side component are written exclusively in Standard Chinese ( Mandarin ) , suggesting that PlugX operators are familiar with this language .
CTU researchers have observed TG-3390 activity between 04:00 and 09:00 UTC , which is 12:00 to 17:00 local time in China ( UTC +8 ) .
The timeframe maps to the second half of the workday in China .
The threat actors have used the Baidu search engine , which is only available in Chinese , to conduct reconnaissance activities .
CTU researchers have observed the threat group obtaining information about specific U.S. defense projects that would be desirable to those operating within a country with a manufacturing base , an interest in U.S. military capability , or both .
CTU researchers recognize that the evidence supporting this attribution is circumstantial .
It is possible that TG-3390 is false-flag operation by a threat group outside of China that is deliberately planting indications of a Chinese origin .
TG-3390 has access to proprietary tools , some of which are used exclusively by TG-3390 and others that are shared among a few Chinese threat groups .
The complexity and continual development of these tools indicates a mature development process .
TG-3390 can quickly leverage compromised network infrastructure during an operation and can conduct simultaneous intrusions into multiple environments .
This ability is further demonstrated by analysis of interactions between TG-3390 operators and a target environment .
CTU researchers found no evidence of multiple operators working simultaneously against a single organization .
This efficiency of operation ( a 1:1 ratio of operator to observed activity ) suggests that TG-3390 can scale to conduct the maximum number of simultaneous operations .
These characteristics suggest that the threat group is well resourced and has access to a tools development team and a team focused on SWCs .
TG-3390 's obfuscation techniques in SWCs complicate detection of malicious web traffic redirects .
Malware used by the threat group can be configured to bypass network-based detection ; however , the threat actors rarely modify host-based configuration settings when deploying payloads .
CTU researchers have observed the threat actors installing a credential logger and backdoor on Microsoft Exchange servers , which requires a technical grasp of Internet Information Services ( IIS ) .
TG-3390 uses older exploits to compromise targets , and CTU researchers have not observed the threat actors using zero-day exploits as of this publication .
The threat actors demonstrated the ability to adapt when reentering a network after an eviction , overcoming technical barriers constructed by network defenders .
In addition to using SWCs to target specific types of organizations , TG-3390 uses spearphishing emails to target specific victims .
CTU researchers assess with high confidence that the threat actors follow an established playbook during an intrusion .
They quickly move away from their initial access vector to hide their entry point and then target Exchange servers as a new access vector .
As of this publication , CTU researchers have not discovered how TG-3390 keeps track of the details associated with its compromised assets and credentials .
However , the threat actors' ability to reuse these assets and credentials , sometimes weeks or months after the initial compromise , indicates the group is disciplined and well organized .
After gaining access to a target network in one intrusion analyzed by CTU researchers , TG-3390 actors identified and exfiltrated data for specific projects run by the target organization , indicating that they successfully obtained the information they sought .
TG-3390 : american.blackcmd.com .
TG-3390 : api.apigmail.com .
TG-3390 : apigmail.com .
TG-3390 : backup.darkhero.org .
TG-3390 : bel.updatawindows.com .
TG-3390 : binary.update-onlines.org .
TG-3390 : blackcmd.com .
TG-3390 : castle.blackcmd.com .
TG-3390 : ctcb.blackcmd.com .
TG-3390 : darkhero.org .
TG-3390 : 208.115.242.36 .
TG-3390 : 208.115.242.37 .
TG-3390 : 208.115.242.38 .
TG-3390 : 66.63.178.142 .
TG-3390 : 72.11.148.220 .
TG-3390 : 72.11.141.133 .
TG-3390 : 74.63.195.236 .
TG-3390 : 74.63.195.237 .
1cb4b74e9d030afbb18accf6ee2bfca1 MD5 hash HttpBrowser RAT dropper .
b333b5d541a0488f4e710ae97c46d9c2 MD5 hash HttpBrowser RAT dropper .
86a05dcffe87caf7099dda44d9ec6b48 MD5 hash HttpBrowser RAT dropper .
93e40da0bd78bebe5e1b98c6324e9b5b MD5 hash HttpBrowser RAT dropper .
f43d9c3e17e8480a36a62ef869212419 MD5 hash HttpBrowser RAT dropper .
57e85fc30502a925ffed16082718ec6c MD5 hash HttpBrowser RAT dropper .
4251aaf38a485b08d5562c6066370f09 MD5 hash HttpBrowser RAT dropper .
bbfd1e703f55ce779b536b5646a0cdc1 MD5 hash HttpBrowser RAT dropper .
12a522cb96700c82dc964197adb57ddf MD5 hash HttpBrowser RAT dropper .
728e5700a401498d91fb83159beec834 MD5 hash HttpBrowser RAT dropper .
2bec1860499aae1dbcc92f48b276f998 MD5 hash HttpBrowser RAT dropper .
014122d7851fa8bf4070a8fc2acd5dc5 MD5 hash HttpBrowser RAT .
0ae996b31a2c3ed3f0bc14c7a96bea38 MD5 hash HttpBrowser RAT .
1a76681986f99b216d5c0f17ccff2a12 MD5 hash HttpBrowser RAT .
380c02b1fd93eb22028862117a2f19e3 MD5 hash HttpBrowser RAT .
40a9a22da928cbb70df48d5a3106d887 MD5 hash HttpBrowser RAT .
46cf2f9b4a4c35b62a32f28ac847c575 MD5 hash HttpBrowser RAT .
5436c3469cb1d87ea404e8989b28758d MD5 hash HttpBrowser RAT .
692cecc94ac440ec673dc69f37bc0409 MD5 hash HttpBrowser RAT .
Living Off the Land .
Release_Time : 2015-05-28Report_URL : https://www.secureworks.com/blog/living-off-the-landIn over half of the targeted threat response engagements performed by the Dell SecureWorks Counter Threat Unit Special Operations ( CTU-SO ) team in the past year , the threat actors accessed the target environment using compromised credentials and the companies' own virtual private network ( VPN ) or other remote access solutions .
Detecting threat actors who are " living off the land , " using credentials , systems , and tools they collect along the way instead of backdoors , can be challenging for organizations that focus their instrumentation and controls primarily on the detection of malware and indicators such as command and control IP addresses , domains , and protocols .
With their gaps in visibility , these organizations can have a very difficult time distinguishing adversary activity from that of legitimate users , pushing detection times out to weeks , months , or even years .
Recently , CTU researchers responded to an intrusion perpetrated by Threat Group-1314 ( TG-1314 ) , one of numerous threat groups that employ the " living off the land " technique to conduct their intrusions .
In this case , the threat actors used compromised credentials to log into an Internet-facing Citrix server to gain access to the network .
CTU researchers discovered evidence that the threat actors were not only leveraging the company 's remote access infrastructure , but were also using the company 's endpoint management platform , Altiris , to move laterally through the network .
Memory collection and analysis can be an extremely valuable component of an incident response plan and in this case proved crucial in identifying TG-1314 's actions on objective .
Memory collected from systems involved in the intrusion was analyzed using the Volatility framework .
First , Volatility 's pstree plugin , which lists running processes in a tree view , was executed .
The result immediately revealed signs of a suspicious cmd.exe process running as a child of the ACLIENT.EXE process .
CTU researchers immediately recognized suspicious commands , such as changing the working directory to recycler and executing commands from that location , that were unlikely to have been connected to legitimate system administrator operations .
The results also revealed indications that PsExec , a popular system administration tool for executing commands on remote systems , was run against several target hosts to spawn shells on them .
To better understand how the adversary was operating and what other actions they had performed , CTU researchers examined cmd.exe and its supporting processes to uncover additional command line artifacts .
While cmd.exe is a console application , it still requires GUI like functionality and other support to interact with the operating system .
On the Windows XP platform , this support is provided by the csrss.exe process .
Because commands run from cmd.exe are acted on by csrss.exe , additional evidence of command history and responses sent to the cmd console window are often discoverable by analyzing the csrss.exe process 's memory .
The output in Figure 3 shows the Process ID ( PID ) of the csrss.exe process to be 716 .
Running Volatility 's vaddump plugin on this process allowed CTU researchers to obtain the Virtual Address Descriptor ( VAD ) sections .
The relevant strings inside the VAD sections were UTF-16 encoded and revealed additional insights once extracted .
TG-1314 was mapping network drives using a compromised Altiris account to connect to additional systems .
After identifying compromised credentials and executed commands , CTU researchers shifted focus to determine how the threat actors were obtaining the shell and executing their commands on the compromised host .
This exploration required a look at the suspect cmd.exe 's parent process , shown earlier in the investigation to be ACLIENT.EXE .
Volatility 's procdump command was used to dump the executable from memory .
Running the strings utility against the dumped ACLIENT.EXE binary revealed evidence that the file was the Altiris agent .
These results indicated that the threat actors leveraged the Altiris management platform installed at the client site , along with compromised domain credentials associated with the Altiris system , to move laterally within the compromised environment .
Threat groups often follow a path of least resistance to achieve their objective .
They will leverage legitimate remote access solutions for entry and valid system administrator tools for lateral movement , if possible .
To help disrupt this tactic , it is important that organizations implement two-factor authentication for all remote access solutions and consider doing the same for internal , high-value assets like their internal system management consoles .
CTU researchers assess with high confidence that threat groups like TG-1314 will continue to live off of the land to avoid detection and conduct their operations .
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APT Targets Financial Analysts with CVE-2017-0199 .
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APT Targets Financial Analysts with CVE-2017-0199 .
On April 20 , Proofpoint observed a targeted campaign focused on financial analysts working at top global financial firms operating in Russia and neighboring countries .
These analysts were linked by their coverage of the telecommunications industry , making this targeting very similar to , and likely a continuation of , activity described in our β In Pursuit of Optical Fibers and Troop Intel β blog .
This time , however , attackers opportunistically used spear-phishing emails with a Microsoft Word attachment exploiting the recently patched CVE-2017-0199 to deploy the ZeroT Trojan , which in turn downloaded the PlugX Remote Access Trojan ( RAT ) .
Proofpoint is tracking this attacker , believed to operate out of China , as TA459 .
The actor typically targets Central Asian countries , Russia , Belarus , Mongolia , and others .
TA549 possesses a diverse malware arsenal including PlugX , NetTraveler , and ZeroT .
In this blog , we also document other 2017 activity so far by this attack group , including their distribution of ZeroT malware and secondary payloadsIn this campaign , attackers used a Microsoft Word document called 0721.doc , which exploits CVE-2017-0199 .
This vulnerability was disclosed and patched days prior to this attack .
The document uses the logic flaw to first download the file power.rtf from http://122.9.52.215/news/power.rtf .
The payload is actually an HTML Application ( HTA ) file , not an RTF document .
The HTA βs VBScript changes the window size and location and then uses PowerShell to download yet another script : power.ps1 .
This is a PowerShell script that downloads and runs the ZeroT payload cgi.exe .
The attack group has made incremental changes to ZeroT since our last analysis .
While they still use RAR SFX format for the initial payloads , ZeroT now uses a the legitimate McAfee utility ( SHA256 3124fcb79da0bdf9d0d1995e37b06f7929d83c1c4b60e38c104743be71170efe ) named mcut.exe instead of the Norman Safeground AS for sideloading as they have in the past .
The encrypted ZeroT payload , named Mctl.mui , is decoded in memory revealing a similarly tampered PE header and only slightly modified code when compared to ZeroT payloads we analyzed previously .
Once ZeroT is running , we observed that the fake User-Agent used in the requests changed from β Mozilla/6.0 ( compatible ; MSIE 10.0 ; Windows NT 6.2 ; Tzcdrnt/6.0 ) β to β Mozilla/6.0 ( compatible ; MSIE 11.0 ; Windows NT 6.2 ) β , thus removing the β Tzcdrnt β typo observed in previous versions .
The initial beacon to index.php changed to index.txt but ZeroT still expects an RC4 encrypted response using a static key : β (*^GF (9042&* β .
Next , ZeroT uses HTTP beacons to transmit information about the infected system to the command and control ( C&C ) .
All posts are encrypted , unlike the last time we analyzed a sample from this actor , when the first POST was accidentally not encrypted .
After that , stage 2 payloads are still retrieved as Bitmap ( BMP ) images that use Least Significant Bit ( LSB ) Steganography to hide the real payloads .
These images appear normal in image viewers .
The stage 2 payload was PlugX that beaconed to C&C servers www.icefirebest.com and www.icekkk.net .
Throughout 2017 we observed this threat actor actively attempting to compromise victims with various malware payloads .
ZeroT remained the primary stage 1 payload , but the stage 2 payloads varied .
One such interesting example was β ΠΠΠΠ_Π ΠΠΠΠΠΠΠ¦ΠΠ_ΠΠ ΠΠΠΠ’Π.rar β ( SHA256 b5c208e4fb8ba255883f771d384ca85566c7be8adcf5c87114a62efb53b73fda ) .
Translated from Russian , this file is named β PROJECT_REALIZATION_PLAN.rar β and contains a compressed .scr executable .
This ZeroT executable communicated with the C&C domain www.kz-info.net and downloaded PlugX as well as an additionalTrojan which communicated with the www.ruvim.net C&C server .
is a payload that we do not see this group using frequently .
Another interesting ZeroT sample ( SHA256 bc2246813d7267608e1a80a04dac32da9115a15b1550b0c4842b9d6e2e7de374 ) contained the executable 0228.exe and a decoy document 0228.doc in the RAR SFX archive .
Bundling decoy documents is a common tactic by this group .
RAR SFX directives are used to display the decoy while the malicious payload is executed .
We suspect that this specific lure was copied from the news article http://www.cis.minsk.by/news.php?id=7557 .
TA459 is well-known for targeting organizations in Russia and neighboring countries .
However , their strategy , tactics , techniques , and procedures in this particular attack emphasize the importance of rigorous patching regimens for all organizations .
Even as software vulnerabilities often take a back seat to human exploits and social engineering , robust defenses must include protection at the email gateway , proactive patch management , and thoughtful end user education .
Paying attention to the details of past attacks is also an important means of preparing for future attacks .
Noting who is targeted , with what malware , and with what types of lures provide clues with which organizations can improve their security posture .
At the same time , multinational organizations like the financial services firms targeted here must be acutely aware of the threats from state-sponsored actors working with sophisticated malware to compromise users and networks .
Ongoing activity from attack groups like TA459 who consistently target individuals specializing in particular areas of research and expertise further complicate an already difficult security situation for organizations dealing with more traditional malware threats , phishing campaigns , and socially engineered threats every day .
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Suckfly : Revealing the secret life of your code signing certificates .
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Suckfly : Revealing the secret life of your code signing certificates .
Release_Time : 2016-03-15 Report_URL : https://community.broadcom.com/symantecenterprise/communities/community-home/librarydocuments/viewdocument?DocumentKey=62e325ae-f551-4855-b9cf-28a7d52d1534&CommunityKey=1ecf5f55-9545-44d6-b0f4-4e4a7f5f5e68&tab=librarydocumentsIn late 2015 , Symantec identified suspicious activity involving a hacking tool used in a malicious manner against one of our customers .
Normally , this is considered a low-level alert easily defeated by security software .
In this case , however , the hacktool had an unusual characteristic not typically seen with this type of file ; it was signed with a valid code-signing certificate .
Many hacktools are made for less than ethical purposes and are freely available , so this was an initial red flag , which led us to investigate further .
As our investigation continued , we soon realized this was much larger than a few hacktools .
We discovered Suckfly , an advanced threat group , conducting targeted attacks using multiple stolen certificates , as well as hacktools and custom malware .
The group had obtained the certificates through pre-attack operations before commencing targeted attacks against a number of government and commercial organizations spread across multiple continents over a two-year period .
This type of activity and the malicious use of stolen certificates emphasizes the importance of safeguarding certificates to prevent them from being used maliciously .
Suckfly has a number of hacktools and malware varieties at its disposal : Back door , Keylogger , Port scanner , Misc. tool , Exploit , Credential dumper , Privilage escalation .
The first signed hacktool we identified in late 2015 was a digitally signed brute-force server message block ( SMB ) scanner .
The organization associated with this certificate is a South Korean mobile software developer .
While we became initially curious because the hacktool was signed , we became more suspicious when we realized a mobile software developer had signed it , since this is not the type of software typically associated with a mobile application .
Based on this discovery , we began to look for other binaries signed with the South Korean mobile software developer's certificate .
This led to the discovery of three additional hacktools also signed using this certificate .
In addition to being signed with a stolen certificate , the identified hacktools had been used in suspicious activity against a US based health provider operating in India .
This evidence indicates that the certificate βs rightful owner either misused it or it had been stolen from them .
Symantec worked with the certificate owner to confirm that the hacktool was not associated with them .
Following the trail further , we traced malicious traffic back to where it originated from and looked for additional evidence to indicate that the attacker persistently used the same infrastructure .
We discovered the activity originated from three separate IP addresses , all located in Chengdu , China .
In addition to the traffic originating from Chengdu , we identified a selection of hacktools and malware signed using nine stolen certificates .
The nine stolen certificates originated from nine different companies who are physically located close together around the central districts of Seoul , South Korea .
We don't know the exact date Suckfly stole the certificates from the South Korean organizations .
However , by analyzing the dates when we first saw the certificates paired with hacktools or malware , we can gain insight into when the certificates may have been stolen .
Figure 4 details how many times each stolen certificate was used in a given month .
The first sighting of three of the nine stolen certificates being used maliciously occurred in early 2014 .
Those three certificates were the only ones used in 2014 , making it likely that the other six were not compromised until 2015 .
All nine certificates were used maliciously in 2015 .
As noted earlier , the stolen certificates Symantec identified in this investigation were used to sign both hacking tools and malware .
Further analysis of the malware identified what looks like a custom back door .
We believe Suckfly specifically developed the back door for use in cyberespionage campaigns .
Symantec detects this threat as Backdoor.Nidiran .
Analysis of Nidiran samples determined that the back door had been updated three times since early 2014 , which fits the timeline outlined in Figure 4 .
The modifications were minor and likely performed to add capabilities and avoid detection .
While the malware is custom , it only provides the attackers with standard back door capabilities .
Suckfly delivered Nidiran through a strategic web compromise .
Specifically , the threat group used a specially crafted web page to deliver an exploit for the Microsoft Windows OLE Remote Code Execution Vulnerability ( CVE-2014-6332 ) , which affects specific versions of Microsoft Windows .
This exploit is triggered when a potential victim browses to a malicious page using Internet Explorer , which can allow the attacker to execute code with the same privileges as the currently logged-in user .
Once exploit has been achieved , Nidiran is delivered through a self-extracting executable that extracts the components to a .tmp folder after it has been executed .
The threat then executes β svchost.exe β , a PE file , which is actually a clean tool known as OLEVIEW.EXE .
The executable will then load iviewers.dll , which is normally a clean , legitimate file .
Attackers have been known to distribute malicious files masquerading as the legitimate iviewers.dll file and then use DLL load hijacking to execute the malicious code and infect the computer .
This technique is associated with themalware and is frequently used in China based cyberespionage activity .
Suckfly isnβt the only attack group to use certificates to sign malware but they may be the most prolific collectors of them .
After all , Stuxnet , widely regarded as the world βs first known cyberweapon , was signed using stolen certificates from companies based in Taiwan with dates much earlier than Suckfly .
Other cyberespionage groups , including Black Vine and Hidden Lynx , have also used stolen certificates in their campaigns .
In April 2013 , a third-party vendor published a report about a cyberespionage group using custom malware and stolen certificates in their operations .
The report documented an advanced threat group they attributed to China .
Symantec tracks the group behind this activity as Blackfly and detects the malware they use as Backdoor.Winnti .
The Blackfly attacks share some similarities with the more recent Suckfly attacks .
Blackfly began with a campaign to steal certificates , which were later used to sign malware used in targeted attacks .
The certificates Blackfly stole were also from South Korean companies , primarily in the video game and software development industry .
Another similarity is that Suckfly stole a certificate from Company D ( see Figure 4 ) less than two years after Blackfly had stolen a certificate from the same company .
While the stolen certificates were different , and stolen in separate instances , they were both used with custom malware in targeted attacks originating from China .
Signing malware with code-signing certificates is becoming more common , as seen in this investigation and the other attacks we have discussed .
Attackers are taking the time and effort to steal certificates because it is becoming necessary to gain a foothold on a targeted computer .
Attempts to sign malware with code-signing certificates have become more common as the Internet and security systems have moved towards a more trust and reputation oriented model .
This means that untrusted software may not be allowed to run unless it is signed .
As we noted in our previous research on the Apple threat landscape , some operating systems , such as Mac OS X , are configured by default to only allow applications to run if they have been signed with a valid certificate , meaning they are trusted .
However , using valid code-signing certificates stolen from organizations with a positive reputation can allow attackers to piggyback on that company βs trust , making it easier to slip by these defenses and gain access to targeted computers .
Suckfly paints a stark picture of where cyberattack groups and cybercriminals are focusing their attentions .
Our investigation shines a light on an often unknown and seedier secret life of code-signing certificates , which is completely unknown to their owners .
The implications of this study shows that certificate owners need to keep a careful eye on them to prevent them from falling into the wrong hands .
It is important to give certificates the protection they need so they can't be used maliciously .
The certificates are only as secure as the safeguards that organizations put around them .
Once a certificate has been compromised , so has the reputation of the organization who signed it .
An organization whose certificate has been stolen and used to sign malware will always be associated with that activity .
Symantec monitors for this type of activity to help prevent organizations from being tied to malicious actions undertaken with their stolen certificates .
During the course of this investigation , we ensured that all certificates compromised by Suckfly were revoked and the affected companies notified .
Over the past few years , we have seen a number of advanced threats and cybercrime groups who have stolen code-signing certificates .
In all of the cases involving an advanced threat , the certificates were used to disguise malware as a legitimate file or application .
File hashes :05edd53508c55b9dd64129e944662c0d 1cf5ce3e3ea310b0f7ce72a94659ff54 352eede25c74775e6102a095fb49da8c 3b595d3e63537da654de29dd01793059 4709395fb143c212891138b98460e958 50f4464d0fc20d1932a12484a1db4342 96c317b0b1b14aadfb5a20a03771f85f ba7b1392b799c8761349e7728c2656dd de5057e579be9e3c53e50f97a9b1832b e7d92039ffc2f07496fe7657d982c80f e864f32151d6afd0a3491f432c2bb7a2 .
usv0503.iqservs-jp.com aux.robertstockdill.com fli.fedora-dns-update.com bss.pvtcdn.com ssl.microsoft-security-center.com ssl.2upgrades.com 133.242.134.121 fli.fedora-dns-update.com .
Indian organizations targeted in Suckfly attacks .
In March 2016 , Symantec published a blog on Suckfly , an advanced cyberespionage group that conducted attacks against a number of South Korean organizations to steal digital certificates .
Since then we have identified a number of attacks over a two-year period , beginning in April 2014 , which we attribute to Suckfly .
The attacks targeted high-profile targets , including government and commercial organizations .
These attacks occurred in several different countries , but our investigation revealed that the primary targets were individuals and organizations primarily located in India .
While there have been several Suckfly campaigns that infected organizations with the group βs custom malware Backdoor.Nidiran , the Indian targets show a greater amount of post-infection activity than targets in other regions .
This suggests that these attacks were part of a planned operation against specific targets in India .
The first known Suckfly campaign began in April of 2014 .
During our investigation of the campaign , we identified a number of global targets across several industries who were attacked in 2015 .
Many of the targets we identified were well known commercial organizations located in India .
These organizations included :One of India 's largest financial organizations A large e-commerce company The e-commerce company 's primary shipping vendor One of India 's top five IT firms A United States healthcare provider 's Indian business unit Two government organizations .
Suckfly spent more time attacking the government networks compared to all but one of the commercial targets .
Additionally , one of the two government organizations had the highest infection rate of the Indian targets .
Figure 1 shows the infection rate for each of the targets .
Indian government org #2 is responsible for implementing network software for different ministries and departments within India 's central government .
The high infection rate for this target is likely because of its access to technology and information related to other Indian government organizations .
Suckfly 's attacks on government organizations that provide information technology services to other government branches is not limited to India .
It has conducted attacks on similar organizations in Saudi Arabia , likely because of the access that those organizations have .
Suckfly 's targets are displayed in figure 2 by their industry , which provides a clearer view of the group βs operations .
Most of the group 's attacks are focused on government or technology related companies and organizations .
One of the attacks we investigated provided detailed insight into how Suckfly conducts its operations .
In 2015 , Suckfly conducted a multistage attack between April 22 and May 4 against an e-commerce organization based in India .
Similar to its other attacks , Suckfly used the Nidiran back door along with a number of hacktools to infect the victim 's internal hosts .
The tools and malware used in this breach were also signed with stolen digital certificates .
Suckfly 's first step was to identify a user to target so the attackers could attempt their initial breach into the e-commerce company 's internal network .
We don't have hard evidence of how Suckfly obtained information on the targeted user , but we did find a large open-source presence on the initial target .
The target 's job function , corporate email address , information on work related projects , and publicly accessible personal blog could all be freely found online .
On April 22 , 2015 , Suckfly exploited a vulnerability on the targeted employee 's operating system ( Windows ) that allowed the attackers to bypass the User Account Control and install the Nidiran back door to provide access for their attack .
While we know the attackers used a custom dropper to install the back door , we do not know the delivery vector .
Based on the amount of open-source information available on the target , it is feasible that a spear-phishing email may have been used .
After the attackers successfully exploited the employee βs system , they gained access to the e-commerce company 's internal network .
We found evidence that Suckfly used hacktools to move latterly and escalate privileges .
To do this the attackers used a signed credential-dumping tool to obtain the victim 's account credentials .
With the account credentials , the attackers were able to access the victim 's account and navigate the internal corporate network as though they were the employee .
On April 27 , the attackers scanned the corporate internal network for hosts with ports 8080 , 5900 , and 40 open .
Ports 8080 and 5900 are common ports used with legitimate protocols , but can be abused by attackers when they are not secured .
It isn't clear why the attackers scanned for hosts with port 40 open because there isn't a common protocol assigned to this port .
Based on Suckfly scanning for common ports , it βs clear that the group was looking to expand its foothold on the e-commerce company 's internal network .
The attackers β final step was to exfiltrate data off the victim βs network and onto Suckfly βs infrastructure .
While we know that the attackers used the Nidiran back door to steal information about the compromised organization , we do not know if Suckfly was successful in stealing other information .
These steps were taken over a 13-day period , but only on specific days .
While tracking what days of the week Suckfly used its hacktools , we discovered that the group was only active Monday through Friday .
There was no activity from the group on weekends .
We were able to determine this because the attackers β hacktools are command line driven and can provide insight into when the operators are behind keyboards actively working .
Figure 4 shows the attackers β activity levels throughout the week .
Suckfly made its malware difficult to analyze to prevent their operations from being detected .
However , we were able to successfully analyze Suckfly malware samples and extract some of the communications between the Nidiran back door and the Suckfly command and control ( C&C ) domains .
We analyzed the dropper , which is an executable that contains the following three files :dllhost.exe : The main host for the .dll file .
iviewers.dll : Used to load encrypted payloads and then decrypt them .
msfled : The encrypted payload .
All three files are required for the malware to run correctly .
Once the malware has been executed , it checks to see if it has a connection to the internet before running .
If the connection test is successful , the malware runs and attempts to communicate with the C&C domain over ports 443 and 8443 .
In the samples we analyzed we found the port and C&C information encrypted and hardcoded into the Nidiran malware itself .
The key for the RC4 encryption in this sample is the hardcoded string β h0le β .
Once the cookie data is decoded , Suckfly has the network name , hostname , IP address , and the victim 's operating system information .
Information about the C&C infrastructure identified in our analysis of Suckfly activity can be seen in Table 1 .
Domain Registration IP address Registration dateaux.robertstockdill.com [email protected] Unknown April 1 , 2014 .
ssl.2upgrades.com [email protected] 176.58.96.234 July 5 , 2014 .
bss.pvtcdn.com [email protected] 106.184.1.38 May 19 , 2015 .
ssl.microsoft-security-center.com Whoisguard Unknown July 20 ,[email protected] 133.242.134.121 August 18 , 2014 .
fli.fedora-dns-update.com Whoisguard Unknown Unknown .
Suckfly targeted one of India βs largest e-commerce companies , a major Indian shipping company , one of India βs largest financial organizations , and an IT firm that provides support for India βs largest stock exchange .
All of these targets are large corporations that play a major role in India βs economy .
By targeting all of these organizations together , Suckfly could have had a much larger impact on India and its economy .
While we don't know the motivations behind the attacks , the targeted commercial organizations , along with the targeted government organizations , may point in this direction .
Suckfly has the resources to develop malware , purchase infrastructure , and conduct targeted attacks for years while staying off the radar of security organizations .
During this time they were able to steal digital certificates from South Korean companies and launch attacks against Indian and Saudi Arabian government organizations .
There is no evidence that Suckfly gained any benefits from attacking the government organizations , but someone else may have benefited from these attacks .
The nature of the Suckfly attacks suggests that it is unlikely that the threat group orchestrated these attacks on their own .
We believe that Suckfly will continue to target organizations in India and similar organizations in other countries in order to provide economic insight to the organization behind Suckfly 's operations .
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THE DUKES 7 YEARS OF RUSSIAN CYBERESPIONAGE .
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THE DUKES 7 YEARS OF RUSSIAN CYBERESPIONAGE .
TOOLS AND TECHNIQUES OF THE DUKES .
PINCHDUKE : First known activity November 2008 , Most recent known activity Summer 2010 , C&C communication methods HTTP(S) , Known toolset components Multiple loaders , Information stealer .
The PinchDuke toolset consists of multiple loaders and a core information stealer Trojan .
The loaders associated with the PinchDuke toolset have also been observed being used with CosmicDuke .
The PinchDuke information stealer gathers system configuration information , steals user credentials , and collects user files from the compromised host transferring these via HTTP (S ) to a C&C server .
We believe PinchDuke βs credential stealing functionality is based on the source code of the Pinch credential stealing malware ( also known as LdPinch ) that was developed in the early 2000s and has later been openly distributed on underground forums .
Credentials targeted by PinchDuke include ones associated with the following software or services : The Bat! , Yahoo! , Mail.ru , Passport.Net , Google Talk , Netscape Navigator , Mozilla Firefox , Mozilla Thunderbird , Internet Explorer , Microsoft Outlook , WinInet Credential Cache , Lightweight Directory Access Protocol ( LDAP ) .
PinchDuke will also search for files that have been created within a predefined timeframe and whose file extension is present in a predefined list .
As a curiosity , most PinchDuke samples contain a Russian language error message : β There is an error in the module βs name ! The length of the data section name must be 4 bytes β .
GEMINIDUKE : First known activity January 2009 , Most recent known activity December 2012 , C&C communication methods HTTP(S) , Known toolset components Loader , Information stealer , Multiple persistence components .
The GeminiDuke toolset consists of a core information stealer , a loader and multiple persistencerelated components .
Unlike CosmicDuke and PinchDuke , GeminiDuke primarily collects information on the victim computer βs configuration .
The collected details include : Local user accounts , Network settings , Internet proxy settings , Installed drivers , Running processes , Programs previously executed by users , Programs and services configured to automatically run at startup , Values of environment variables , Files and folders present in any users home folder , Files and folders present in any users My Documents , Programs installed to the Program Files folder , Recently accessed files , folders and programs .
As is common for malware , the GeminiDuke infostealer uses a mutex to ensure that only one instance of itself is running at a time .
What is less common is that the name used for the mutex is often a timestamp .
We believe these timestamps to be generated during the compilation of GeminiDuke from the local time of the computer being used .
Comparing the GeminiDuke compilation timestamps , which always reference the time in the UTC+0 timezone , with the local time timestamps used as mutex names , and adjusting for the presumed timezone difference , we note that all of the mutex names reference a time and date that is within seconds of the respective sample βs compilation timestamp .
Additionally , the apparent timezone of the timestamps in all of the GeminiDuke samples compiled during the winter is UTC+3 , while for samples compiled during the summer , it is UTC+4 .
The observed timezones correspond to the pre-2011 definition of Moscow Standard Time ( MSK ) , which was UTC+3 during the winter and UTC+4 during the summer .
In 2011 MSK stopped following Daylight Saving Time ( DST ) and was set to UTC+4 year-round , then reset to UTC +3 yearround in 2014 .
Some of the observed GeminiDuke samples that used timestamps as mutex names were compiled while MSK still respected DST and for these samples , the timestamps perfectly align with MSK as it was defined at the time .
However , GeminiDuke samples compiled after MSK was altered still vary the timezone between UTC+3 in the winter and UTC+4 during the summer .
While computers using Microsoft Windows automatically adjust for DST , changes in timezone definitions require that an update to Windows be installed .
We therefore believe that the Dukes group simply failed to update the computer they were using to compile GeminiDuke samples , so that the timestamps seen in later samples still appear to follow the old definition of Moscow Standard Time .
The GeminiDuke infostealer has occasionally been wrapped with a loader that appears to be unique to GeminiDuke and has never been observed being used with any of the other Duke toolsets .
GeminiDuke also occasionally embeds additional executables that attempt to achieve persistence on the victim computer .
These persistence components appear to be uniquely customized for use with GeminiDuke , but they use many of the same techniques as CosmicDuke persistence components .
COSMICDUKE : First known activity January 2010 , Most recent known activity Summer 2015 , Other names Tinybaron , BotgenStudios , NemesisGemina , C&C communication methods HTTP(S) , FTP , WebDav , Known toolset components Information stealer , Multiple loaders , Privilege escalation component , Multiple persistence components .
The CosmicDuke toolset is designed around a main information stealer component .
This information stealer is augmented by a variety of components that the toolset operators may selectively include with the main component to provide additional functionalities , such as multiple methods of establishing persistence , as well as modules that attempt to exploit privilege escalation vulnerabilities in order to execute CosmicDuke with higher privileges .
CosmicDuke βs information stealing functionality includes : Keylogging , Taking screenshots , Stealing clipboard contents , Stealing user files with file extensions that match a predefined list , Exporting the users cryptographic certificates including private keys , Collecting user credentials , including passwords , for a variety of popular chat and email programs as well as from web browsers CosmicDuke may use HTTP , HTTPS , FTP or WebDav to exfiltrate the collected data to a hardcoded C&C server .
While we believe CosmicDuke to be an entirely custom- written toolset with no direct sharing of code with other Duke toolsets , the high-level ways in which many of its features have been implemented appear to be shared with other members of the Duke arsenal .
Specifically , the techniques CosmicDuke uses to extract user credentials from targeted software and to detect the presence of analysis tools appear to be based on the techniques used by PinchDuke .
Likewise , many of CosmicDuke βs persistence components use techniques also used by components associated with GeminiDuke and CozyDuke .
In all of these cases , the techniques are the same , but the code itself has been altered to work with the toolset in question , leading to small differences in the final implementation .
A few of the CosmicDuke samples we discovered also included components that attempt to exploit either of the publicly known CVE-2010-0232 or CVE-2010- 4398 privilege escalation vulnerabilities .
In the case of CVE-2010-0232 , the exploit appears to be based directly on the proof of concept code published by security researcher Tavis Ormandy when he disclosed the vulnerability .
We believe that the exploit for CVE- 2010-4398 was also based on a publicly available proof of concept .
In addition to often embedding persistence or privilege escalation components , CosmicDuke has occasionally embedded PinchDuke , GeminiDuke , or MiniDuke components .
It should be noted that CosmicDuke does not interoperate with the second , embedded malware in any way other than by writing the malware to disk and executing it .
After that , CosmicDuke and the second malware operate entirely independently of each other , including separately contacting their C&C servers .
Sometimes , both malware have used the same C&C server , but in other cases , even the servers have been different .
Finally , it is worth noting that while most of the compilation timestamps for CosmicDuke samples appear to be authentic , we are aware of a few cases of them being forged .
One such case was detailed on page 10 as an apparent evasion attempt .
Another is a loader variant seen during the spring of 2010 in conjunction with both CosmicDuke and PinchDuke .
These loader samples all had compilation timestamps purporting to be from the 24th or the 25th of September , 2001 .
However , many of these loader samples embed CosmicDuke variants that exploit the CVE-2010- 0232 privilege escalation vulnerability thus making it impossible for the compilation timestamps to be authentic .
MINIDUKE : First known activity Loader July 2010 , Backdoor May 2011 Most recent known activity Loader : Spring 2015 , Backdoor : Summer 2014 C&C communication methods HTTP(S) , Twitter , Known toolset components Downloader , Backdoor , Loader .
The MiniDuke toolset consists of multiple downloader and backdoor components , which are commonly referred to as the MiniDuke β stage 1 β , β stage 2 β , and β stage 3 β components as per Kaspersky βs original MiniDuke whitepaper .
Additionally , a specific loader is often associated with the MiniDuke toolset and is referred to as the β MiniDuke loader β .
While the loader has often been used together with other MiniDuke components , it has also commonly been used in conjunction with CosmicDuke and PinchDuke .
In fact , the oldest samples of the loader that we have found were used with PinchDuke .
To avoid confusion however , we have decided to continue referring to the loader as the β MiniDuke loader β .
Two details about MiniDuke components are worth noting .
Firstly , some of the MiniDuke components were written in Assembly language .
While many malware were written in Assembly during the β old days β of curiosity-driven virus writing , it has since become a rarity .
Secondly , some of the MiniDuke components do not contain a hardcoded C&C server address , but instead obtain the address of a current C&C server via Twitter .
The use of Twitter either to initially obtain the address of a C&C server ( or as a backup if no hardcoded primary C&C server responds ) is a feature also found in OnionDuke , CozyDuke , and HammerDuke .
COZYDUKE : First known activity January 2010 , Most recent known activity : Spring 2015 , Other names CozyBear , CozyCar , Cozer , EuroAPT , C&C communication methods HTTP(S) , Twitter ( backup ) , Known toolset components Dropper , Modular backdoor , Multiple persistence components , Information gathering module , Screenshot module , Password stealing module , Password hash stealing module .
CozyDuke is not simply a malware toolset ; rather , it is a modular malware platform formed around a core backdoor component .
This component can be instructed by the C&C server to download and execute arbitrary modules , and it is these modules that provide CozyDuke with its vast array of functionality .
Known CozyDuke modules include : Command execution module for executing arbitrary Windows Command Prompt commands , Password stealer module , NT LAN Manager ( NTLM ) hash stealer module , System information gathering module , Screenshot module .
In addition to modules , CozyDuke can also be instructed to download and execute other , independent executables .
In some observed cases , these executables were self-extracting archive files containing common hacking tools , such as PSExec and Mimikatz , combined with script files that execute these tools .
In other cases , CozyDuke has been observed downloading and executing tools from other toolsets used by the Dukes such as OnionDuke , SeaDuke , and HammerDuke .
ONIONDUKE : First known activity February 2013 , Most recent known activity Spring 2015 , C&C communication methods HTTP(S) , Twitter ( backup ) , Known toolset components Dropper , Loader , Multiple modular core components , Information stealer , Distributed Denial of Service ( DDoS ) module , Password stealing module , Information gathering module , Social network spamming module .
The OnionDuke toolset includes at least a dropper , a loader , an information stealer Trojan and multiple modular variants with associated modules .
OnionDuke first caught our attention because it was being spread via a malicious Tor exit node .
The Tor node would intercept any unencrypted executable files being downloaded and modify those executables by adding a malicious wrapper contained an embedded OnionDuke .
Once the victim finished downloading the file and executed it , the wrapper would infect the victim βs computer with OnionDuke before executing the original legitimate executable .
The same wrapper has also been used to wrap legitimate executable files , which were then made available for users to download from torrent sites .
Again , if a victim downloaded a torrent containing a wrapped executable , they would get infected with OnionDuke .
Finally , we have also observed victims being infected with OnionDuke after they were already infected with CozyDuke .
In these cases , CozyDuke was instructed by its C&C server to download and execute OnionDuke toolset .
SEADUKE : First known activity October 2014 , Most recent known activity Spring 2015 , Other names SeaDaddy , SeaDask , C&C communication methods HTTP(S) , Known toolset components Backdoor .
SeaDuke is a simple backdoor that focuses on executing commands retrieved from its C&C server , such as uploading and downloading files , executing system commands and evaluating additional Python code .
SeaDuke is made interesting by the fact that it is written in Python and designed to be cross-platform so that it works on both Windows and Linux .
The only known infection vector for SeaDuke is via an existing CozyDuke infection , wherein CozyDuke downloads and executes the SeaDuke toolset .
Like HammerDuke , SeaDuke appears to be used by the Dukes group primarily as a secondary backdoor left on CozyDuke victims after that toolset has completed the initial infection and stolen any readily available information from them .
HAMMERDUKE : First known activity January 2015 , Most recent known activity Summer 2015 , Other names HAMMERTOSS , Netduke , C&C communication methods HTTP(S) , Twitter , Known toolset components Backdoor .
HammerDuke is a simple backdoor that is apparently designed for similar use cases as SeaDuke .
Specifically , the only known infection vector for HammerDuke is to be downloaded and executed by CozyDuke onto a victim that has already been compromised by that toolset .
This , together with HammerDuke βs simplistic backdoor functionality , suggests that it is primarily used by the Dukes group as a secondary backdoor left on CozyDuke victims after CozyDuke performed the initial infection and stole any readily available information from them .
HammerDuke is however interesting because it is written in .NET , and even more so because of its occasional use of Twitter as a C&C communication channel .
Some HammerDuke variants only contain a hardcoded C&C server address from which they will retrieve commands , but other HammerDuke variants will first use a custom algorithm to generate a Twitter account name based on the current date .
If the account exists , HammerDuke will then search for tweets from that account with links to image files that contain embedded commands for the toolset to execute .
HammerDuke βs use of Twitter and crafted image files is reminiscent of other Duke toolsets .
Both OnionDuke and MiniDuke also use date-based algorithms to generate Twitter account names and then searched for any tweets from those accounts that linked to image files .
In contrast however , for OnionDuke and MiniDuke the linked image files contain embedded malware to be downloaded and executed , rather than instructions .
Similarly , GeminiDuke may also download image files , but these would contain embedded additional configuration information for the toolset itself .
Unlike HammerDuke however , the URLs for the images downloaded by GeminiDuke are hardcoded in its initial configuration , rather than retrieved from Twitter .
CLOUDDUKE : First known activity June 2015 , Most recent known activity Summer 2015 , Other names MiniDionis , CloudLook , C&C communication methods HTTP(S) , Microsoft OneDrive , Known toolset components Downloader , Loader , Two backdoor variants .
CloudDuke is a malware toolset known to consist of , at least , a downloader , a loader and two backdoor variants .
The CloudDuke downloader will download and execute additional malware from a preconfigured location .
Interestingly , that location may be either a web address or a Microsoft OneDrive account .
Both CloudDuke backdoor variants support simple backdoor functionality , similar to SeaDuke .
While one variant will use a preconfigured C&C server over HTTP or HTTPS , the other variant will use a Microsoft OneDrive account to exchange commands and stolen data with its operators .
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