Dentro del SOC

Identifying the Imposter: Darktrace’s Detection of Simulated Malware vs the Real Thing

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Mar 2024
Mar 2024
This blog explores how Darktrace is able to differentiate simulated malware from genuine threats, offering advanced anomaly detection and autonomous response in the ever-evolving cyber security landscape.

Distinguishing attack simulations from the real thing

In an era marked by the omnipresence of digital technologies and the relentless advancement of cyber threats, organizations face an ongoing battle to safeguard their digital environment. Although red and blue team exercises have long served as cornerstones in evaluating organizational defenses, their reliance on manual processes poses significant constraints [1]. Led by seasoned security professionals, these tests offer invaluable insights into security readiness but can be marred by their resource-intensive and infrequent testing cycles. The gaps between assessments leave organizations open to undetected vulnerabilities, compromising the true state of their security environment. In response to the ever-changing threat landscape, organizations are adopting a proactive stance towards cyber security to fortify their defenses.

At the forefront, these efforts tend to revolve around simulated attacks, a process designed to test an organization's security posture against both known and emerging threats in a safe and controlled environment [2]. These meticulously orchestrated simulations imitate the tactics, techniques, and procedures (TTPs) employed by actual adversaries and provide organizations with invaluable insights into their security resilience and vulnerabilities. By immersing themselves in simulated attack scenarios, security teams can proactively probe for vulnerabilities, adopt a more aggressive defense posture, and stay ahead of evolving cyber threats.

Distinguishing between simulated malware observations and authentic malware activities stands as a critical imperative for organizations bolstering their cyber defenses. While simulated platforms offer controlled scenarios for testing known attack patterns, Darktrace’s Self-Learning AI can detect known and unknown threats, identify zero-day threats, and previously unseen malware variants, including attack simulations. Whereas simulated platforms focus on specific known attack vectors, Darktrace DETECT™ and Darktrace RESPOND™ can identify and contain both known and unknown threats across the entire attack surface, providing unparalleled protection of the cyber estate.

Darktrace’s Coverage of Simulated Attacks

In January 2024, the Darktrace Security Operations Center (SOC) received a high volume of alerts relating to an unspecified malware strain that was affecting multiple customers across the fleet, raising concerns, and prompting the Darktrace Analyst team to swiftly investigate the multitude of incident. Initially, these activities were identified as malicious, exhibiting striking resemblance to the characteristics of Remcos, a sophisticated remote access trojan (RAT) that can be used to fully control and monitor any Windows computer from XP and onwards [3]. However, further investigation revealed that these activities were intricately linked to a simulated malware provider.

This discovery underscores a pivotal insight into Darktrace’s capabilities. To this point, leveraging advanced AI, Darktrace operates with a sophisticated framework that extends beyond conventional threat detection. By analyzing network behavior and anomalies, Darktrace not only discerns between simulated threats, such as those orchestrated by breach and attack simulation platforms and genuine malicious activities but can also autonomously respond to these threats with RESPOND. This showcases Darktrace’s advanced capabilities in effectively mitigating cyber threats.

Attack Simulation Process: Initial Access and Intrusion

Darktrace initially observed devices breaching several DETECT models relating to the hostname “new-tech-savvy[.]com”, an endpoint that was flagged as malicious by multiple open-source intelligence (OSINT) vendors [4].

In addition, multiple HTML Application (HTA) file downloads were observed from the malicious endpoint, “new-tech-savvy[.]com/5[.]hta”. HTA files are often seen as part of the UAC-0050 campaign, known for its cyber-attacks against Ukrainian targets, which tends to leverage the Remcos RAT with advanced evasion techniques [5] [6]. Such files are often critical components of a malware operation, serving as conduits for the deployment of malicious payloads onto a compromised system. Often, within the HTA file resides a VBScript which, upon execution, triggers a PowerShell script. This PowerShell script is designed to facilitate the download of a malicious payload, namely “word_update.exe”, from a remote server. Upon successful execution, “word_update.exe” is launched, invoking cmd.exe and initiating the sharing of malicious data. This process results in the execution of explorer.exe, with the malicious RemcosRAT concealed within the memory of explorer.exe. [7].

As the customers were subscribed to Darktrace’s Proactive Threat Notification (PTN) service, an Enhanced Monitoring model was breached upon detection of the malicious HTA file. Enhanced Monitoring models are high-fidelity DETECT models designed to identify activity likely to be indicative of compromise. These PTN alerts were swiftly investigated by Darktrace’s round the clock SOC team.

Following this successful detection, Darktrace RESPOND took immediate action by autonomously blocking connections to the malicious endpoint, effectively preventing additional download attempts. Similar activity may be seen in the case of a legitimate malware attack; however, in this instance, the hostname associated with the download confirmed the detected malicious activity was the result of an attack simulation.

Figure 1: The Breach Log displays the model breach, “Anomalous File/Incoming HTA File”, where a device was detected downloading the HTA file, “5.hta” from the endpoint, “new-tech-savvy[.]com”.
Figure 2: The Model Breach Event Log shows a device making connections to the endpoint, “new-tech-savvy[.]com”. As a result, theRESPOND model, “Antigena/Network/External Threat/Antigena File then New Outbound Block", breached and connections to this malicious endpoint were blocked.
Figure 3: The Breach Log further showcases another RESPOND model, “Antigena/Network/External Threat/Antigena Suspicious File Block", which was triggered when the device downloaded a  HTA file from the malicious endpoint, “new-tech-savvy[.]com".

In other cases, Darktrace observed SSL and HTTP connections also attributed to the same simulated malware provider, highlighting Darktrace’s capability to distinguish between legitimate and simulated malware attack activity.

Figure 4: The Model Breach “Anomalous Connection/Low and Slow Exfiltration" displays the hostname of a simulated malware provider, confirming the detected malicious activity as the result of an attack simulation.
Figure 5: The Model Breach Event Log shows the SSL connections made to an endpoint associated with the simulated malware provider.
Figure 6: Darktrace’s Advanced Search displays SSL connection logs to the endpoint of the simulated malware provider around the time the simulation activity was observed.

Upon detection of the malicious activity occurring within affected customer networks, Darktrace’s Cyber AI Analyst™ investigated and correlated the events at machine speed. Figure 8 illustrates the synopsis and additional technical information that AI Analyst generated on one customer’s environment, detailing that over 220 HTTP queries to 18 different endpoints for a single device were seen. The investigation process can also be seen in the screenshot, showcasing Darktrace’s ability to provide ‘explainable AI’ detail. AI Analyst was able to autonomously search for all HTTP connections made by the breach device and identified a single suspicious software agent making one HTTP request to the endpoint, 45.95.147[.]236.

Furthermore, the malicious endpoints, 45.95.147[.]236, previously observed in SSH attacks using brute-force or stolen credentials, and “tangible-drink.surge[.]sh”, associated with the Androxgh0st malware [8] [9] [10], were detected to have been requested by another device.

This highlights Darktrace’s ability to link and correlate seemingly separate events occurring on different devices, which could indicate a malicious attack spreading across the network.  AI Analyst was also able to identify a username associated with the simulated malware prior to the activity through Kerberos Authentication Service (AS) requests. The device in question was also tagged as a ‘Security Device’ – such tags provide human analysts with valuable context about expected device activity, and in this case, the tag corroborates with the testing activity seen. This exemplifies how Darktrace’s Cyber AI Analyst takes on the labor-intensive task of analyzing thousands of connections to hundreds of endpoints at a rapid pace, then compiling results into a single pane that provides customer security teams with the information needed to evaluate activities observed on a device.

All in all, this demonstrates how Darktrace’s Self-Learning AI is capable of offering an unparalleled level of awareness and visibility over any anomalous and potentially malicious behavior on the network, saving security teams and administrators a great deal of time.

Figure 7: Cyber AI Analyst Incident Log containing a summary of the attack simulation activity,, including relevant technical details, and the AI investigation process.


Simulated cyber-attacks represent the ever-present challenge of testing and validating security defenses, while the threat of legitimate compromise exemplifies the constant risk of cyber threats in today’s digital landscape. Darktrace emerges as the solution to this conflict, offering real-time detection and response capabilities that identify and mitigate simulated and authentic threats alike.

While simulations are crafted to mimic legitimate threats within predefined parameters and controlled environments, the capabilities of Darktrace DETECT transcend these limitations. Even in scenarios where intent is not malicious, Darktrace’s ability to identify anomalies and raise alerts remains unparalleled. Moreover, Darktrace’s AI Analyst and autonomous response technology, RESPOND, underscore Darktrace’s indispensable role in safeguarding organizations against emerging threats.

Credit to Priya Thapa, Cyber Analyst, Tiana Kelly, Cyber Analyst & Analyst Team Lead


Model Breaches

Darktrace DETECT Model Breach Coverage

Anomalous File / Incoming HTA File

Anomalous Connection / Low and Slow Exfiltration

Darktrace RESPOND Model Breach Coverage

§  Antigena / Network/ External Threat/ Antigena File then New Outbound Block

Cyber AI Analyst Incidents

• Possible HTTP Command and Control

• Suspicious File Download

List of IoCs

IP Address

38.52.220[.]2 - Malicious Endpoint

46.249.58[.]40 - Malicious Endpoint

45.95.147[.]236 - Malicious Endpoint


tangible-drink.surge[.]sh - Malicious Endpoint

new-tech-savvy[.]com - Malicious Endpoint












Darktrace son expertos de talla mundial en inteligencia de amenazas, caza de amenazas y respuesta a incidentes, y proporcionan apoyo al SOC las 24 horas del día a miles de clientes de Darktrace en todo el mundo. Inside the SOC está redactado exclusivamente por estos expertos y ofrece un análisis de los ciberincidentes y las tendencias de las amenazas, basado en la experiencia real sobre el terreno.
Priya Thapa
Cyber Analyst
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How to Protect your Organization Against Microsoft Teams Phishing Attacks

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May 2024

The problem: Microsoft Teams phishing attacks are on the rise

Around 83% of Fortune 500 companies rely on Microsoft Office products and services1, with Microsoft Teams and Microsoft SharePoint in particular emerging as critical platforms to the business operations of the everyday workplace. Researchers across the threat landscape have begun to observe these legitimate services being leveraged more and more by malicious actors as an initial access method.

As Teams becomes a more prominent feature of the workplace many employees rely on it for daily internal and external communication, even surpassing email usage in some organizations. As Microsoft2 states, "Teams changes your relationship with email. When your whole group is working in Teams, it means you'll all get fewer emails. And you'll spend less time in your inbox, because you'll use Teams for more of your conversations."

However, Teams can be exploited to send targeted phishing messages to individuals either internally or externally, while appearing legitimate and safe. Users might receive an external message request from a Teams account claiming to be an IT support service or otherwise affiliated with the organization. Once a user has accepted, the threat actor can launch a social engineering campaign or deliver a malicious payload. As a primarily internal tool there is naturally less training and security awareness around Teams – due to the nature of the channel it is assumed to be a trusted source, meaning that social engineering is already one step ahead.

Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)
Figure 1: Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)

Microsoft Teams Phishing Examples

Microsoft has identified several major phishing attacks using Teams within the past year.

In July 2023, Microsoft announced that the threat actor known as Midnight Blizzard – identified by the United States as a Russian state-sponsored group – had launched a series of phishing campaigns via Teams with the aim of stealing user credentials. These attacks used previously compromised Microsoft 365 accounts and set up new domain names that impersonated legitimate IT support organizations. The threat actors then used social engineering tactics to trick targeted users into sharing their credentials via Teams, enabling them to access sensitive data.  

At a similar time, threat actor Storm-0324 was observed sending phishing lures via Teams containing links to malicious SharePoint-hosted files. The group targeted organizations that allow Teams users to interact and share files externally. Storm-0324’s goal is to gain initial access to hand over to other threat actors to pursue more dangerous follow-on attacks like ransomware.

For a more in depth look at how Darktrace stops Microsoft Teams phishing read our blog: Don’t Take the Bait: How Darktrace Keeps Microsoft Teams Phishing Attacks at Bay

The market: Existing Microsoft Teams security solutions are insufficient

Microsoft’s native Teams security focuses on payloads, namely links and attachments, as the principal malicious component of any phishing. These payloads are relatively straightforward to detect with their experience in anti-virus, sandboxing, and IOCs. However, this approach is unable to intervene before the stage at which payloads are delivered, before the user even gets the chance to accept or deny an external message request. At the same time, it risks missing more subtle threats that don’t include attachments or links – like early stage phishing, which is pure social engineering – or completely new payloads.

Equally, the market offering for Teams security is limited. Security solutions available on the market are always payload-focused, rather than taking into account the content and context in which a link or attachment is sent. Answering questions like:

  • Does it make sense for these two accounts to speak to each other?
  • Are there any linguistic indicators of inducement?

Furthermore, they do not correlate with email to track threats across multiple communication environments which could signal a wider campaign. Effectively, other market solutions aren’t adding extra value – they are protecting against the same types of threats that Microsoft is already covering by default.

The other aspect of Teams security that native and market solutions fail to address is the account itself. As well as focusing on Teams threats, it’s important to analyze messages to understand the normal mode of communication for a user, and spot when a user’s Teams activity might signal account takeover.

The solution: How Darktrace protects Microsoft Teams against sophisticated threats

With its biggest update to Darktrace/Email ever, Darktrace now offers support for Microsoft Teams. With that, we are bringing the same AI philosophy that protects your email and accounts to your messaging environment.  

Our Self-Learning AI looks at content and context for every communication, whether that’s sent in an email or Teams message. It looks at actual user behavior, including language patterns, relationship history of sender and recipient, tone and payloads, to understand if a message poses a threat. This approach allows Darktrace to detect threats such as social engineering and payloadless attacks using visibility and forensic capabilities that Microsoft security doesn’t currently offer, as well as early symptoms of account compromise.  

Unlike market solutions, Darktrace doesn’t offer a siloed approach to Teams security. Data and signals from Teams are shared across email to inform detection, and also with the wider Darktrace ActiveAI security platform. By correlating information from email and Teams with network and apps security, Darktrace is able to better identify suspicious Teams activity and vice versa.  

Interested in the other ways Darktrace/Email augments threat detection? Read our latest blog on how improving the quality of end-user reporting can decrease the burden on the SOC. To find our more about Darktrace's enduring partnership with Microsoft, click here.


[1] Essential Microsoft Office Statistics in 2024

[2] Microsoft blog, Microsoft Teams and email, living in harmony, 2024

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About the author
Carlos Gray
Product Manager


Dentro del SOC

Don’t Take the Bait: How Darktrace Keeps Microsoft Teams Phishing Attacks at Bay

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May 2024

Social Engineering in Phishing Attacks

Faced with increasingly cyber-aware endpoint users and vigilant security teams, more and more threat actors are forced to think psychologically about the individuals they are targeting with their phishing attacks. Social engineering methods like taking advantage of the human emotions of their would-be victims, pressuring them to open emails or follow links or face financial or legal repercussions, and impersonating known and trusted brands or services, have become common place in phishing campaigns in recent years.

Phishing with Microsoft Teams

The malicious use of the popular communications platform Microsoft Teams has become widely observed and discussed across the threat landscape, with many organizations adopting it as their primary means of business communication, and many threat actors using it as an attack vector. As Teams allows users to communicate with people outside of their organization by default [1], it becomes an easy entry point for potential attackers to use as a social engineering vector.

In early 2024, Darktrace/Apps™ identified two separate instances of malicious actors using Microsoft Teams to launch a phishing attack against Darktrace customers in the Europe, the Middle East and Africa (EMEA) region. Interestingly, in this case the attackers not only used a well-known legitimate service to carry out their phishing campaign, but they were also attempting to impersonate an international hotel chain.

Despite these attempts to evade endpoint users and traditional security measures, Darktrace’s anomaly detection enabled it to identify the suspicious phishing messages and bring them to the customer’s attention. Additionally, Darktrace’s autonomous response capability, was able to follow-up these detections with targeted actions to contain the suspicious activity in the first instance.

Darktrace Coverage of Microsoft Teams Phishing

Chats Sent by External User and Following Actions by Darktrace

On February 29, 2024, Darktrace detected the presence of a new external user on the Software-as-a-Service (SaaS) environment of an EMEA customer for the first time. The user, “REDACTED@InternationalHotelChain[.]onmicrosoft[.]com” was only observed on this date and no further activities were detected from this user after February 29.

Later the same day, the unusual external user created its first chat on Microsoft Teams named “New Employee Loyalty Program”. Over the course of around 5 minutes, the user sent 63 messages across 21 different chats to unique internal users on the customer’s SaaS platform. All these chats included the ‘foreign tenant user’ and one of the customer’s internal users, likely in an attempt to remain undetected. Foreign tenant user, in this case, refers to users without access to typical internal software and privileges, indicating the presence of an external user.

Darktrace’s detection of unusual messages being sent by a suspicious external user via Microsoft Teams.
Figure 1: Darktrace’s detection of unusual messages being sent by a suspicious external user via Microsoft Teams.
Advanced Search results showing the presence of a foreign tenant user on the customer’s SaaS environment.
Figure 2: Advanced Search results showing the presence of a foreign tenant user on the customer’s SaaS environment.

Darktrace identified that the external user had connected from an unusual IP address located in Poland, 195.242.125[.]186. Darktrace understood that this was unexpected behavior for this user who had only previously been observed connecting from the United Kingdom; it further recognized that no other users within the customer’s environment had connected from this external source, thereby deeming it suspicious. Further investigation by Darktrace’s analyst team revealed that the endpoint had been flagged as malicious by several open-source intelligence (OSINT) vendors.

External Summary highlighting the rarity of the rare external source from which the Teams messages were sent.
Figure 3: External Summary highlighting the rarity of the rare external source from which the Teams messages were sent.

Following Darktrace’s initial detection of these suspicious Microsoft Teams messages, Darktrace's autonomous response was able to further support the customer by providing suggested mitigative actions that could be applied to stop the external user from sending any additional phishing messages.

Unfortunately, at the time of this attack Darktrace's autonomous response capability was configured in human confirmation mode, meaning any autonomous response actions had to be manually actioned by the customer. Had it been enabled in autonomous response mode, it would have been able promptly disrupt the attack, disabling the external user to prevent them from continuing their phishing attempts and securing precious time for the customer’s security team to begin their own remediation procedures.

Darktrace autonomous response actions that were suggested following the ’Large Volume of Messages Sent from New External User’ detection model alert.
Figure 4: Darktrace autonomous response actions that were suggested following the ’Large Volume of Messages Sent from New External User’ detection model alert.

External URL Sent within Teams Chats

Within the 21 Teams chats created by the threat actor, Darktrace identified 21 different external URLs being sent, all of which included the domain "cloud-sharcpoint[.]com”. Many of these URLs had been recently established and had been flagged as malicious by OSINT providers [3]. This was likely an attempt to impersonate “cloud-sharepoint[.]com”, the legitimate domain of Microsoft SharePoint, with the threat actor attempting to ‘typo-squat’ the URL to convince endpoint users to trust the legitimacy of the link. Typo-squatted domains are commonly misspelled URLs registered by opportunistic attackers in the hope of gaining the trust of unsuspecting targets. They are often used for nefarious purposes like dropping malicious files on devices or harvesting credentials.

Upon clicking this malicious link, users were directed to a similarly typo-squatted domain, “InternatlonalHotelChain[.]sharcpoInte-docs[.]com”. This domain was likely made to appear like the SharePoint URL used by the international hotel chain being impersonated.

Redirected link to a fake SharePoint page attempting to impersonate an international hotel chain.
Figure 5: Redirected link to a fake SharePoint page attempting to impersonate an international hotel chain.

This fake SharePoint page used the branding of the international hotel chain and contained a document named “New Employee Loyalty Program”; the same name given to the phishing messages sent by the attacker on Microsoft Teams. Upon accessing this file, users would be directed to a credential harvester, masquerading as a Microsoft login page, and prompted to enter their credentials. If successful, this would allow the attacker to gain unauthorized access to a user’s SaaS account, thereby compromising the account and enabling further escalation in the customer’s environment.

Figure 6: A fake Microsoft login page that popped-up when attempting to open the ’New Employee Loyalty Program’ document.

This is a clear example of an attacker attempting to leverage social engineering tactics to gain the trust of their targets and convince them to inadvertently compromise their account. Many corporate organizations partner with other companies and well-known brands to offer their employees loyalty programs as part of their employment benefits and perks. As such, it would not necessarily be unexpected for employees to receive such an offer from an international hotel chain. By impersonating an international hotel chain, threat actors would increase the probability of convincing their targets to trust and click their malicious messages and links, and unintentionally compromising their accounts.

In spite of the attacker’s attempts to impersonate reputable brands, platforms, Darktrace/Apps was able to successfully recognize the malicious intent behind this phishing campaign and suggest steps to contain the attack. Darktrace recognized that the user in question had deviated from its ‘learned’ pattern of behavior by connecting to the customer’s SaaS environment from an unusual external location, before proceeding to send an unusually large volume of messages via Teams, indicating that the SaaS account had been compromised.

A Wider Campaign?

Around a month later, in March 2024, Darktrace observed a similar incident of a malicious actor impersonating the same international hotel chain in a phishing attacking using Microsoft Teams, suggesting that this was part of a wider phishing campaign. Like the previous example, this customer was also based in the EMEA region.  

The attack tactics identified in this instance were very similar to the previously example, with a new external user identified within the network proceeding to create a series of Teams messages named “New Employee Loyalty Program” containing a typo-squatted external links.

There were a few differences with this second incident, however, with the attacker using the domain “@InternationalHotelChainExpeditions[.]onmicrosoft[.]com” to send their malicious Teams messages and using differently typo-squatted URLs to imitate Microsoft SharePoint.

As both customers targeted by this phishing campaign were subscribed to Darktrace’s Proactive Threat Notification (PTN) service, this suspicious SaaS activity was promptly escalated to the Darktrace Security Operations Center (SOC) for immediate triage and investigation. Following their investigation, the SOC team sent an alert to the customers informing them of the compromise and advising urgent follow-up.


While there are clear similarities between these Microsoft Teams-based phishing attacks, the attackers here have seemingly sought ways to refine their tactics, techniques, and procedures (TTPs), leveraging new connection locations and creating new malicious URLs in an effort to outmaneuver human security teams and conventional security tools.

As cyber threats grow increasingly sophisticated and evasive, it is crucial for organizations to employ intelligent security solutions that can see through social engineering techniques and pinpoint suspicious activity early.

Darktrace’s Self-Learning AI understands customer environments and is able to recognize the subtle deviations in a device’s behavioral pattern, enabling it to effectively identify suspicious activity even when attackers adapt their strategies. In this instance, this allowed Darktrace to detect the phishing messages, and the malicious links contained within them, despite the seemingly trustworthy source and use of a reputable platform like Microsoft Teams.

Credit to Min Kim, Cyber Security Analyst, Raymond Norbert, Cyber Security Analyst and Ryan Traill, Threat Content Lead


Darktrace Model Detections

SaaS Model

Large Volume of Messages Sent from New External User

SaaS / Unusual Activity / Large Volume of Messages Sent from New External User

Indicators of Compromise (IoCs)

IoC – Type - Description

https://cloud-sharcpoint[.]com/[a-zA-Z0-9]{15} - Example hostname - Malicious phishing redirection link

InternatlonalHotelChain[.]sharcpolnte-docs[.]com – Hostname – Redirected Link

195.242.125[.]186 - External Source IP Address – Malicious Endpoint

MITRE Tactics

Tactic – Technique

Phishing – Initial Access (T1566)





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About the author
Min Kim
Cyber Security Analyst
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