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Emotet is a trojan known for delivering follow-on payloads, including TrickBot, Qbot, and, in some cases, Ryuk ransomware. After a hiatus in early 2020, Emotet made a comeback over the summer and remained steady until the January 2021 takedown.

Pairs with this song

Editors’ note: While the analysis and detection opportunities remain applicable, this threat page was written for a previous Threat Detection Report and has not been updated in 2022.


Emotet is an advanced, modular banking trojan that primarily functions as a downloader or dropper of other malware. It’s disseminated through malicious email links or attachments that use branding familiar to the recipient. Emotet focuses on stealing user data and banking credentials, and opportunistically deploys itself to victims. Emotet is polymorphic, meaning it often evades typical signature-based detection, making it more challenging to detect. Emotet is also virtual machine aware and can generate false indicators if run in a virtual environment, further frustrating defenders. Emotet has been active and evolving since 2014.

An eventful year

In the latter half of 2020 we observed Emotet detections transition from execution via an executable on disk to a dynamically linked library (DLL) executed via rundll32. This is an evolution we have seen other malware, like Qbot, adopt in 2020 as well, as it gives the operator flexibility and additional defense evasion opportunities. We also observed Emotet adopt techniques to break the parent-child relationship in process telemetry. This is likely an effort to evade detection analytics designed to alert on unusual child processes. These processes often spawn from common phishing lures, often incorporating Microsoft Office products.

Emotet had multiple dormant periods throughout the year, which is consistent with previous patterns of going dark for several months at a time. The malware started 2020 strong as we observed a significant number of detections in January, but it gradually decreased until we observed no Emotet detections in June. Emotet returned with significant detection volume in July—a pattern others noticed as well—and based on our visibility, remained consistent through October before another quiet month in November.

It’s unclear why Emotet went dormant for part of 2020; potential explanations include possible retooling and transitioning to new affiliations to drop follow-on payloads. It’s also important to note that the patterns we observe don’t present a complete picture of what’s happening in the wild. For example, the lack of Emotet activity we observed in November could be due to an increase in it being caught by perimeter defenses and not making it to the endpoints we monitor.

Payload patterns

In addition to changes in Emotet’s activity level throughout the year, we also observed patterns in the follow-on malware families it dropped. Throughout 2020, Emotet continued the years-long pattern of dropping TrickBot as follow-on malware, which sometimes led to Ryuk ransomware. Notably, after Emotet returned in July, it also began delivering Qbot in some campaigns—but didn’t abandon delivering TrickBot entirely. In mid-October, CrowdStrike reported that they observed Emotet resuming delivery of TrickBot in a likely attempt to replenish the adversaries’ victim base following disruption by industry and law enforcement.

Looking ahead

On January 27, 2021, Europol announced a major international takedown effort of the Emotet botnet. Only time will tell if we see a reorganization and resurgence of Emotet, or if the criminals behind the operation will pivot to a different toolkit or business model. Until then, we can still learn from previous Emotet behaviors and implement detection analytics to help address it as well as other threats. Should Emotet return, its ties to ransomware make rapid response to infections a high priority. If organizations are able to detect and respond to the early stages of an infection chain, whether it uses Emotet or another family, the chances of receiving follow-on ransomware decrease significantly.

Detection opportunities

Detection opportunity 1

PowerShell string obfuscation
ATT&CK technique(s): T1059.001 Command and Scripting Interpreter: PowerShell, T1027 Obfuscated Files or Information
ATT&CK tactic(s): Execution

Details on detection opportunity: Emotet was primarily delivered through malicious documents that executed heavily obfuscated PowerShell. Though obfuscation is meant to deter defenders, we can use it to create detection analytics. One way to detect Emotet’s obfuscated code is to look for a PowerShell process executing commands that use the format operator -f to concatenate strings. To further refine the analytic, you can also look for the format indexes {0} and {1}. In many malicious instances of PowerShell, the format indices will be out of order, as we see in the following decoded PowerShell string used by Emotet, {3}{1}{0}{2}. Such an analytic may require additional tuning for other normal-format index strings that are common in your environment.

Detection opportunity 2

Rundll32 execution by ordinal
ATT&CK technique(s): T1218.011 Signed Binary Proxy Execution: Rundll32
ATT&CK tactic(s): Defense Evasion

Details: In the latter half of 2020, we observed Emotet begin using execution by ordinal via rundll32.exe. An ordinal is the numeric position of the exported function in the DLL Export Address table. We have had success detecting this by looking for rundll32.exe executing DLL export functions by ordinal, which are denoted by #. In the example below, the DLL is Chpieog.dll and the ordinal is #1. We detect this simply by looking for rundll32 process execution with command lines matching a regular expression for ordinal calls. While this is a legitimate way to execute a DLL, it’s fairly rare, and our strategy has proven successful in identifying the early stages of Emotet execution.

Detection opportunity 3

PowerShell executing processes using wmiclass
ATT&CK technique(s): T1059.001 Command and Scripting Interpreter: PowerShell, T1047 Windows Management Instrumentation
ATT&CK tactic(s): Execution

Details: In some Emotet campaigns we observed the WMI Provider Host (wmiprvse.exe) spawning PowerShell with an encoded command. After decoding the first layer, we noticed use of the wmiclass .NET class to call the Create method of the Win32_Process class in order to execute the Emotet payload. To detect this behavior we look for PowerShell processes with a decoded command line containing references to wmiclass and win32_process. PowerShell command-line detection analytics are always at risk of evasion through obfuscation, but we found this analytic to be reliable in finding Emotet in 2020.

Bonus forensic analysis opportunity

Identifying Emotet maldocs with a broken parent-child process chain

Details: Emotet campaigns sometimes feature the intentional circumvention of the creation of a direct child process of an Office application. Subsequent malicious Emotet processes spawn as child processes of wmiprvse.exe by proxying execution through COM and WMI. Generally speaking, processes that spawn as a child of an Office application are less frequent and can be subject to more defender scrutiny. By spawning indirectly as a child of wmiprvse.exe, this behavior offers an adversary two distinct potential advantages:

  1. Many security products are unable to reconstruct the broken process chain caused by proxying execution through COM, so it can be difficult to enrich data sources based on context alone
  2. Child processes of wmiprvse.exe are common. For example, in SCCM environments, WMI and COM are used heavily to remotely spawn processes


Even though adversaries try to evade defenses by breaking process chains, we can still detect and investigate their behavior. When we observed Emotet using this technique, we still wanted to identify the offending malicious document that executed the processes, so we figured out a regular procedure to find the original maldoc. We thought it would be useful to share the steps we use to find the maldoc in case you find yourself in a similar situation.

  1. Search within a time window of execution of the first detected process. For example, if we detected wmiprvse.exe spawning powershell.exe to execute an encoded command to download the Emotet payload, and powershell.exe started at 13:00 hours UTC (UTC or GTFO), we would search between 12:59-13:01. We would gradually expand our search to 12:55-13:05 hours and beyond if we didn’t find the maldoc in the first search
  2. Because we suspect a malicious document, filter the process search results for Microsoft Office products
  3. Narrow the search even further by filtering the resulting Office processes for module loads of VBA-related DLLs, including vbeui.dll and vbe7.dll. The presence of these DLLs being loaded is a potential indicator of macro use
  4. Check the file modifications and command line of the remaining processes for malicious documents
Kyle Rainey
Kyle has been providing proactive and reactive incident response and forensics services to Fortune 500 companies for over five years. As an intelligence analyst at Red Canary, he leverages his years of experience conducting investigations and building detections in order to engineer impactful, scalable intelligence products. Kyle is passionate about solving hard problems and constantly learning.
Kyle has been providing proactive and reactive incident response and forensics services to Fortune 500 companies for over five years. As an intelligence analyst at Red Canary, he leverages his years of experience conducting investigations and building detections in order to engineer impactful, scalable intelligence products. Kyle is passionate about solving hard problems and constantly learning.
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