mrmoor/cti-corpus-raw · Datasets at Hugging Face

text stringlengths 1 38.9k
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 —–BEGIN CERTIFICATE—– to the beginning of the base64 encoded payload and appends —–END CERTIFICATE—– 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 ’s 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 “ C:\Users\user\AppData\Local\cdnver.dll ” .
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 ’s 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 “ .txt ” and “ .exe ” files within the command “ certutil -decode ” , as the Sofacy document used “ C:\Programdata\ ” 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 ’s signature GAMEFISH malware .
The malicious document – Hotel_Reservation_Form.doc ( MD5 : 9b10685b774a783eabfecdb6119a8aa3 ) , contains a macro that base64 decodes a dropper that then deploys APT28 ’s 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 ’s 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 ’s 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 ’s 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 isn’t 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 ’s 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 – especially to foreign countries – 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 .
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 ‘ Cannon ’ .
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 .

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 —–BEGIN CERTIFICATE—– to the beginning of the base64 encoded payload and appends —–END CERTIFICATE—– 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 ’s 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 “ C:\Users\user\AppData\Local\cdnver.dll ” .

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 ’s 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 “ .txt ” and “ .exe ” files within the command “ certutil -decode ” , as the Sofacy document used “ C:\Programdata\ ” 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 ’s signature GAMEFISH malware .

The malicious document – Hotel_Reservation_Form.doc ( MD5 : 9b10685b774a783eabfecdb6119a8aa3 ) , contains a macro that base64 decodes a dropper that then deploys APT28 ’s 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 ’s 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 ’s 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 ’s 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 isn’t 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 ’s 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 – especially to foreign countries – 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 .

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 ‘ Cannon ’ .

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 .