- We have discovered a global intrusion campaign. We are
tracking the actors behind this campaign as UNC2452.
- FireEye discovered a supply chain attack trojanizing SolarWinds
Orion business software updates in order to distribute malware we
- The attacker’s post compromise activity
leverages multiple techniques to evade detection and obscure their
activity, but these efforts also offer some opportunities for
- The campaign is widespread, affecting public and
private organizations around the world.
- FireEye is
releasing signatures to detect this threat actor and supply chain
attack in the wild. These are found on our public GitHub
page. FireEye products and services can help customers detect
and block this attack.
FireEye has uncovered a widespread campaign, that we are tracking as
UNC2452. The actors behind this campaign gained access to numerous
public and private organizations around the world. They gained access
to victims via trojanized updates to SolarWind’s Orion IT monitoring
and management software. This campaign may have begun as early as
Spring 2020 and is currently ongoing. Post compromise activity
following this supply chain compromise has included lateral movement
and data theft. The campaign is the work of a highly skilled actor and
the operation was conducted with significant operational security.
SolarWinds.Orion.Core.BusinessLayer.dll is a SolarWinds
digitally-signed component of the Orion software framework that
contains a backdoor that communicates via HTTP to third party servers.
We are tracking the trojanized version of this SolarWinds Orion
plug-in as SUNBURST.
After an initial dormant period of up to two weeks, it retrieves and
executes commands, called “Jobs”, that include the ability to transfer
files, execute files, profile the system, reboot the machine, and
disable system services. The malware masquerades its network traffic
as the Orion Improvement Program (OIP) protocol and stores
reconnaissance results within legitimate plugin configuration files
allowing it to blend in with legitimate SolarWinds activity. The
backdoor uses multiple obfuscated blocklists to identify forensic and
anti-virus tools running as processes, services, and drivers.
Figure 1: SolarWinds digital signature on
software with backdoor
Multiple trojanzied updates were digitally signed from March – May
2020 and posted to the SolarWinds updates website, including:
The trojanized update file is a standard Windows Installer Patch
file that includes compressed resources associated with the update,
including the trojanized SolarWinds.Orion.Core.BusinessLayer.dll
component. Once the update is installed, the malicious DLL will be
loaded by the legitimate SolarWinds.BusinessLayerHost.exe or
SolarWinds.BusinessLayerHostx64.exe (depending on system
configuration). After a dormant period of up to two weeks, the malware
will attempt to resolve a subdomain of avsvmcloud[.]com. The DNS
response will return a CNAME record that points to a Command and
Control (C2) domain. The C2 traffic to the malicious domains is
designed to mimic normal SolarWinds API communications. The list of
known malicious infrastructure is available on FireEye’s GitHub page.
Worldwide Victims Across Multiple Verticals
FireEye has detected this activity at multiple entities worldwide.
The victims have included government, consulting, technology, telecom
and extractive entities in North America, Europe, Asia and the Middle
East. We anticipate there are additional victims in other countries
and verticals. FireEye has notified all entities we are aware of being affected.
Post Compromise Activity and Detection Opportunities
We are currently tracking the software supply chain compromise and
related post intrusion activity as UNC2452. After gaining initial
access, this group uses a variety of techniques to disguise their
operations while they move laterally (Figure 2). This actor prefers to
maintain a light malware footprint, instead preferring legitimate
credentials and remote access for access into a victim’s environment.
Figure 2: Post-compromise tactics
This section will detail the notable techniques and outline
potential opportunities for detection.
TEARDROP and BEACON Malware Used
Multiple SUNBURST samples have been recovered, delivering different
payloads. In at least one instance the attackers deployed a previously
unseen memory-only dropper we’ve dubbed TEARDROP to deploy Cobalt
TEARDROP is a memory only dropper that runs as a service, spawns a
thread and reads from the file “gracious_truth.jpg”, which likely has
a fake JPG header. Next it checks that HKUSOFTWAREMicrosoftCTF
exists, decodes an embedded payload using a custom rolling XOR
algorithm and manually loads into memory an embedded payload using a
custom PE-like file format. TEARDROP does not have code overlap with
any previously seen malware. We believe that this was used to execute
a customized Cobalt Strike BEACON.
Mitigation: FireEye has provided two Yara rules to detect
TEARDROP available on our GitHub.
Defenders should look for the following alerts from FireEye HX:
MalwareGuard and WindowsDefender:
Window’s defender Exploit Guard log entries:
(Microsoft-Windows-Security-Mitigations/KernelMode event ID 12)
(PID XXXXX) would have been blocked from loading the
Attacker Hostnames Match Victim Environment
The actor sets the hostnames on their command and control
infrastructure to match a legitimate hostname found within the
victim’s environment. This allows the adversary to blend into the
environment, avoid suspicion, and evade detection.
The attacker infrastructure leaks its configured hostname in RDP SSL
certificates, which is identifiable in internet-wide scan data. This
presents a detection opportunity for defenders — querying
internet-wide scan data sources for an organization’s hostnames can
uncover malicious IP addresses that may be masquerading as the
organization. (Note: IP Scan history often shows IPs switching between
default (WIN-*) hostnames and victim’s hostnames) Cross-referencing
the list of IPs identified in internet scan data with remote access
logs may identify evidence of this actor in an environment. There is
likely to be a single account per IP address.
IP Addresses located in Victim’s Country
The attacker’s choice of IP addresses was also optimized to evade
detection. The attacker primarily used only IP addresses originating
from the same country as the victim, leveraging Virtual Private Servers.
This also presents some detection opportunities, as geolocating IP
addresses used for remote access may show an impossible rate of travel
if a compromised account is being used by the legitimate user and the
attacker from disparate IP addresses. The attacker used multiple IP
addresses per VPS provider, so once a malicious login from an unusual
ASN is identified, looking at all logins from that ASN can help detect
additional malicious activity. This can be done alongside baselining
and normalization of ASN’s used for legitimate remote access to help
identify suspicious activity.
Lateral Movement Using Different Credentials
Once the attacker gained access to the network with compromised
credentials, they moved laterally using multiple different
credentials. The credentials used for lateral movement were always
different from those used for remote access.
Organizations can use HX’s LogonTracker module to graph all logon
activity and analyze systems displaying a one-to-many relationship
between source systems and accounts. This will uncover any single
system authenticating to multiple systems with multiple accounts, a
relatively uncommon occurrence during normal business operations.
Temporary File Replacement and Temporary Task Modification
The attacker used a temporary file replacement technique to remotely
execute utilities: they replaced a legitimate utility with theirs,
executed their payload, and then restored the legitimate original
file. They similarly manipulated scheduled tasks by updating an
existing legitimate task to execute their tools and then returning the
scheduled task to its original configuration. They routinely removed
their tools, including removing backdoors once legitimate remote
access was achieved.
Defenders can examine logs for SMB sessions that show access to
legitimate directories and follow a
delete-create-execute-delete-create pattern in a short amount of time.
Additionally, defenders can monitor existing scheduled tasks for
temporary updates, using frequency analysis to identify anomalous
modification of tasks. Tasks can also be monitored to watch for
legitimate Windows tasks executing new or unknown binaries.
This campaign’s post compromise activity was conducted with a high
regard for operational security, in many cases leveraging dedicated
infrastructure per intrusion. This is some of the best operational
security that FireEye has observed in a cyber attack, focusing on
evasion and leveraging inherent trust. However, it can be
detected through persistent defense.
In-Depth Malware Analysis
(b91ce2fa41029f6955bff20079468448) is a SolarWinds-signed plugin
component of the Orion software framework that contains an obfuscated
backdoor which communicates via HTTP to third party servers. After an
initial dormant period of up to two weeks, it retrieves and executes
commands, called “Jobs”, that include the ability to transfer and
execute files, profile the system, and disable system services. The
backdoor’s behavior and network protocol blend in with legitimate
SolarWinds activity, such as by masquerading as the Orion Improvement
Program (OIP) protocol and storing reconnaissance results within
plugin configuration files. The backdoor uses multiple blocklists to
identify forensic and anti-virus tools via processes, services, and drivers.
- Subdomain DomainName Generation Algorithm (DGA) is performed
to vary DNS requests
- CNAME responses point to the C2 domain
for the malware to connect to
- The IP block of A record
responses controls malware behavior
- DGA encoded machine
domain name, used to selectively target victims
- CNAME responses point to the C2 domain
- Command and control traffic masquerades as the legitimate Orion
- Code hides in plain site by using fake
variable names and tying into legitimate components
Delivery and Installation
Authorized system administrators fetch and install updates to
SolarWinds Orion via packages distributed by SolarWinds’s website. The
(02af7cec58b9a5da1c542b5a32151ba1) contains the
SolarWinds.Orion.Core.BusinessLayer.dll described in this report.
After installation, the Orion software framework executes the .NET
program SolarWinds.BusinessLayerHost.exe to load plugins, including
SolarWinds.Orion.Core.BusinessLayer.dll. This plugin contains many
legitimate namespaces, classes, and routines that implement
functionality within the Orion framework. Hidden in plain sight, the
implements an HTTP-based backdoor. Code within the logically unrelated
invokes the backdoor code when the Inventory Manager plugin is loaded.
SolarWinds.Orion.Core.BusinessLayer.dll is signed by SolarWinds,
using the certificate with serial number
0f:e9:73:75:20:22:a6:06:ad:f2:a3:6e:34:5d:c0:ed. The file was signed
on March 24, 2020.
On execution of the malicious
method the sample verifies that its lower case process name hashes to
the value 17291806236368054941. This hash value is calculated as the
standard FNV-1A 64-bit hash with an additional XOR by
6605813339339102567 after computing the FNV-1A. This hash matches a
process named “solarwinds.businesslayerhost”.
The sample only executes if the filesystem write time of the
assembly is at least 12 to 14 days prior to the current time; the
exact threshold is selected randomly from an interval. The sample
continues to check this time threshold as it is run by a legitimate
recurring background task. Once the threshold is met, the sample
creates the named pipe 583da945-62af-10e8-4902-a8f205c72b2e to act as
a guard that only one instance is running before reading
SolarWinds.Orion.Core.BusinessLayer.dll.config from disk and
retrieving the XML field appSettings. The appSettings fields’ keys are
legitimate values that the malicious logic re-purposes as a persistent
configuration. The key ReportWatcherRetry must be any value other than
3 for the sample to continue execution.
The sample checks that the machine is domain joined and retrieves
the domain name before execution continues. A userID is generated by
computing the MD5 of a network interface MAC address that is up and
not a loopback device, the domain name, and the registry value
userID is encoded via a custom XOR scheme after the MD5 is calculated.
The ReportWatcherPostpone key of appSettings is then read from
SolarWinds.Orion.Core.BusinessLayer.dll.config to retrieve the
initial, legitimate value. This operation is performed as the sample
later bit packs flags into this field and the initial value must be
known in order to read out the bit flags. The sample then invokes the
method Update which is the core event loop of the sample.
DGA and Blocklists
The backdoor determines its C2 server using a Domain Generation
Algorithm (DGA) to construct and resolve a subdomain of
avsvmcloud[.]com. The Update method is responsible for initializing
cryptographic helpers for the generation of these random C2
subdomains. Subdomains are generated by concatenating a victim userId
with a reversible encoding of the victims local machine domain name.
The attacker likely utilizes the DGA subdomain to vary the DNS
response to victims as a means to control the targeting of the
malware. These subdomains are concatenated with one of the following
to create the hostname to resolve:
Process name, service name, and driver path listings are obtained,
and each value is hashed via the FNV-1a + XOR algorithm as described
previously and checked against hardcoded blocklists. Some of these
hashes have been brute force reversed as part of this analysis,
showing that these routines are scanning for analysis tools and
antivirus engine components. If a blocklisted process is found the
Update routine exits and the sample will continue to try executing the
routine until the blocklist passes. Blocklisted services are stopped
by setting their
registry entries to value 4 for disabled. Some entries in the service
list if found on the system may affect the DGA algorithms behavior in
terms of the values generated. The list of stopped services is then
bit-packed into the ReportWatcherPostpone key of the appSettings entry
for the samples’ config file. If any service was transitioned to
disabled the Update method exits and retries later. The sample
retrieves a driver listing via the WMI query Select * From
Win32_SystemDriver. If any blocklisted driver is seen the Update
method exits and retries. If all blocklist tests pass, the sample
tries to resolve api.solarwinds.com to test the network for connectivity.
Network Command and Control (C2)
If all blocklist and connectivity checks pass, the sample starts
generating domains in a while loop via its DGA. The sample will delay
for random intervals between the generation of domains; this interval
may be any random value from the ranges 1 to 3 minutes, 30 to 120
minutes, or on error conditions up to 420 to 540 minutes (9 hours).
The DNS A record of generated domains is checked against a hardcoded
list of IP address blocks which control the malware’s behavior.
Records within the following ranges will terminate the malware and
update the configuration key ReportWatcherRetry to a value that
prevents further execution:
- fc00:: – fe00::
- fec0:: – ffc0::
- ff00:: – ff00::
Once a domain has been successfully retrieved in a CNAME DNS
response the sample will spawn a new thread of execution invoking the
method HttpHelper.Initialize which is responsible for all C2
communications and dispatching. The HTTP thread begins by delaying for
a configurable amount of time that is controlled by the SetTime
command. The HTTP thread will delay for a minimum of 1 minute between
callouts. The malware uses HTTP GET or HTTP POST requests. If the
sample is attempting to send outbound data the content-type HTTP
header will be set to “application/octet-stream” otherwise
A JSON payload is present for all HTTP POST and PUT requests and
contains the keys “userId”, “sessionId”, and “steps”. The “steps”
field contains a list of objects with the following keys: “Timestamp”,
“Index”, “EventType”, “EventName”, “DurationMs”, “Succeeded”, and
“Message”. The JSON key “EventType” is hardcoded to the value “Orion”,
and the “EventName” is hardcoded to “EventManager”. Malware response
messages to send to the server are DEFLATE compressed and
single-byte-XOR encoded, then split among the “Message” fields in the
“steps” array. Each “Message” value is Base64 encoded separately. Not
all objects in the “steps” array contribute to the malware message –
the integer in the “Timestamp” field must have the 0x2 bit set to
indicate that the contents of the “Message” field are used in the
malware message. Step objects whose bit 0x2 is clear in the Timestamp
field contain random data and are discarded when assembling the
In observed traffic these HTTP response bodies attempt to appear
like benign XML related to .NET assemblies, but command data is
actually spread across the many GUID and HEX strings present. Commands
are extracted from HTTP response bodies by searching for HEX strings
using the following regular expression:
Command data is spread across multiple strings that are disguised as
GUID and HEX strings. All matched substrings in the response are
filtered for non HEX characters, joined together, and HEX-decoded. The
first DWORD value shows the actual size of the message, followed
immediately with the message, with optional additional junk bytes
following. The extracted message is single-byte XOR decoded using the
first byte of the message, and this is then DEFLATE decompressed. The
first character is an ASCII integer that maps to the JobEngine enum,
with optional additional command arguments delimited by space characters.
Commands are then dispatched to a JobExecutionEngine based upon the
command value as described next.
Terminate the current thread.
Profile the local system including hostname,
Perform a HTTP request to the specified URL,
Starts a new process with the given file path
Returns a process listing. If no arguments are
Terminate the given process, by PID.
Given a path and an optional match pattern
Given a file path and a Base64 encoded string
Tests whether the given file path exists.
Deletes the specified file path.
Compute the MD5 of a file at a given path and
Arbitrary registry read from one of the
Arbitrary registry write from one of the
Arbitrary registry delete from one of the
Returns listing of subkeys and value
Attempts to immediately trigger a system
Indicators and Detections to Help the Community
To empower the community to detect this supply chain backdoor, we
are publishing indicators and detections to help organizations
identify this backdoor and this threat actor. The signatures are a mix
of Yara, IOC, and Snort formats.
A list of the detections and signatures are available on the FireEye
GitHub repository found here.
We are releasing detections and will continue to update the public
repository with overlapping detections for host and network-based
indicators as we develop new or refine existing ones. We have found
multiple hashes with this backdoor and we will post updates of those hashes.
MITRE ATT&CK Techniques Observed
Obfuscated Files or Information
Application Layer Protocol: DNS
File and Directory Discovery
Ingress Tool Transfer
Compromise Software Supply
Security Software Discovery
Domain Generation Algorithms
Immediate Mitigation Recommendations
Prior to following SolarWind’s recommendation to utilize Orion
Platform release 2020.2.1 HF 1, which is currently available via the
SolarWinds Customer Portal, organizations should consider preserving
impacted devices and building new systems using the latest versions.
Applying an upgrade to an impacted box could potentially overwrite
forensic evidence as well as leave any additional backdoors on the
system. In addition, SolarWinds has released additional mitigation and
hardening instructions here.
In the event you are unable to follow SolarWinds’ recommendations,
the following are immediate mitigation techniques that could be
deployed as first steps to address the risk of trojanized SolarWinds
software in an environment. If attacker activity is discovered in an
environment, we recommend conducting a comprehensive investigation and
designing and executing a remediation strategy driven by the
investigative findings and details of the impacted environment.
- Ensure that SolarWinds servers are isolated / contained until
a further review and investigation is conducted. This should include
blocking all Internet egress from SolarWinds servers.
SolarWinds infrastructure is not isolated, consider taking the
- Restrict scope of connectivity to endpoints
from SolarWinds servers, especially those that would be
considered Tier 0 / crown jewel assets
- Restrict the
scope of accounts that have local administrator privileged on
- Block Internet egress from servers
or other endpoints with SolarWinds software.
- Restrict scope of connectivity to endpoints
- Consider (at a minimum) changing passwords for accounts that
have access to SolarWinds servers / infrastructure. Based upon
further review / investigation, additional remediation measures may
- If SolarWinds is used to managed networking
infrastructure, consider conducting a review of network device
configurations for unexpected / unauthorized modifications. Note,
this is a proactive measure due to the scope of SolarWinds
functionality, not based on investigative findings.
This blog post was the combined effort of numerous personnel and
teams across FireEye coming together. Special thanks to:
Andrew Archer, Doug Bienstock, Chris DiGiamo, Glenn Edwards, Nick
Hornick, Alex Pennino, Andrew Rector, Scott Runnels, Eric Scales,
Nalani Fraser, Sarah Jones, John Hultquist, Ben Read, Jon Leathery,
Fred House, Dileep Jallepalli, Michael Sikorski, Stephen Eckels,
William Ballenthin, Jay Smith, Alex Berry, Nick Richard, Isif
Ibrahima, Dan Perez, Marcin Siedlarz, Ben Withnell, Barry Vengerik,
Nicole Oppenheim, Ian Ahl, Andrew Thompson, Matt Dunwoody, Evan Reese,
Steve Miller, Alyssa Rahman, John Gorman, Lennard Galang, Steve Stone,
Nick Bennett, Matthew McWhirt, Mike Burns, Omer Baig.
Also special thanks to Nick Carr, Christopher Glyer, and Ramin
Nafisi from Microsoft.