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July 14, 2021

Darktrace Detects Egregor Ransomware in Customer Environment

See how Darktrace managed to detect and eliminate an Egregor ransomware extortion attack in a customer environment without the use of any signatures.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Justin Fier
SVP, Red Team Operations
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14
Jul 2021

Ransomware groups are coming and going faster than ever. In June alone we saw Avaddon release its decryption keys unprompted and disappear from sight, while members of CLOP were arrested in Ukraine. The move follows increasing pressure from the US intelligence community and Ukrainian authorities, who took down Egregor ransomware back in February. Egregor had only been around since September 2020. It survived less than six months.

But these gangs aren’t going away – they are simply going underground. Despite ‘closures’, cases of ransomware continue to rise and new threat actors and independent hackers pop up on the Dark Web every day.

As malware actors lay low and resurface with new variants, keeping up with the stream of signatures and new strains has become untenable. This blog studies the techniques, tools and procedures (TTPs) observed from a real-life Egregor intrusion last autumn, which showcases how Self-Learning AI detected the attack without relying on signatures.

Egregor: Maze reloaded

150 companies
worldwide have fallen victim to Egregor.

Law enforcement authorities have been busy this year. Aside from Egregor and CLOP, actions were taken against Netwalker in Bulgaria and the US, while Europol announced that an international operation had disrupted the core infrastructure of Emotet, one of the most prominent botnets of the past decade.

All parties – from governments down to individual businesses – are taking the threat of ransomware more seriously. In response to this added pressure, cyber-criminals often prefer to shut up shop rather than hang around long enough to be arrested.

DarkSide famously closed down after the Colonial Pipeline attacks, only nine months after it had been created. An admin from the Ziggy gang announced that it would issue refunds and was looking for a job as a threat hunter.

“Hi. I am Ziggy ransomware administrator. We decided to publish all decryption keys.

We are very sad about what we did. As soon as possible, all the keys will be published in this channel.”

Take this apology with a pinch of salt. The players which have ‘closed down’ have not had a change of heart, they’ve just changed tack. Different names and new infrastructure can help keep the heat off and circumvent US sanctions or federal scrutiny. PayloadBIN (a new ransomware which cropped up last month), WastedLocker, Dridex, Hades, Phoenix, Indrik Spider… all just aliases for one single group: Evil Corp.

The FBI are becoming more aggressive in their methods of infiltration and disruption, so it is likely we will see more of these U-turns and guerrilla-style tactics. Temporary pop-up gangs are an emerging trend in place of large, established enterprises like REvil, whose websites also vanished following the attack against Kaseya. And there is no doubt we will continue to witness these ‘exit scams’, where groups retire and re-brand, like Maze did last September, when it came back as Egregor.

Darktrace detects malware regardless of the name or strain. It stopped Maze last year, and, as we shall see below, it stopped its successor Egregor, even though the code and C2 endpoints used in the intrusion had never been seen before.

30%
of ransom profits are taken by Egregor developers.

Egregor ransomware attack

Back in November 2020, Egregor was in full bloom, targeting major organizations and exfiltrating data in ‘double extortion’ attacks. At a logistics company in Europe with around 20,000 active devices, during a Darktrace Proof of Value (POV) trial, Egregor struck.

Figure 1: Timeline of the attack. The overall dwell time — from first C2 connection to encryption — was five days.

As a Ransomware-as-a-Service (RaaS) gang, it appears Egregor had partnered with botnet providers to facilitate initial access. In this case, the compromised device carried signs of prior infection. It was seen connecting to an apparent Webex endpoint, before connecting to the Akamai doppelganger, amajai-technologies[.]network. This activity was followed by a number of command and control (C2) and exfiltration-related breaches.

Three days later, Darktrace observed lateral movement over HTTPS. Another device – a server – was seen connecting to the amajai host. This server wrote unusual numeric exectuables to shared SMB drives and took new service control. A third host then made a ~50GB upload to a rare IP.

Figure 2: Cyber AI Analyst summarizes the initial C2 and unusual SMB writes in a similar incident, followed later by a large upload to a rare external endpoint.

After two days, encryption began. This triggered multiple hosts breaches. On the final day, the attacker made large uploads to various endpoints, all from ostensibly compromised hosts.

Retrospective analysis

$4m
is the highest recorded cost of an Egregor ransom.

If the attack had not been neutralized at this point, it could have resulted in significant financial loss and reputational damage for the company. The two-pronged attack enabled Egregor both to encrypt critical resources and to exfiltrate them, with a view to publicizing sensitive data if the victims refused to pay up.

The affiliates who deployed the ransomware in this case were highly skilled. They leveraged a number of sophisticated techniques including the use of a large number of C2 endpoints, with doppelgangers and off-the-shelf tools.

The adoption of HTTPS for lateral movement and reconnaissance reduced lateral noise for scans and enumeration. The complex C2 had numerous endpoints, some of which were doppelgangers of legitimate sites. Furthermore, some malware was downloaded as masqueraded files: the mimetype Octet Streams were downloaded as ‘g.pixel’. These three tactics helped obfuscate the attacker’s movements and trick traditional security tools.

Ransomware attacks are occurring at a speed that even five years ago was unimaginable. In this case, the overall dwell time was less than a week, and part of the attack happened out of office hours. This highlights the need for Autonomous Response, which can keep up with novel threats and does not rely on humans being in the loop to contain cyber-attacks.

Gone today, here tomorrow

Egregor was busted in February, but we may well see it resurface under a different name and with modified code. If and when this happens, signatures will be of no use. Catching never-before-seen ransomware, which employs novel methods of intrusion and extortion, requires a different approach.

The endpoint in the case study above is now associated via open-source intelligence (OSINT) with Cobalt Strike. But at the time of the investigation, the C2 was unlisted. Similarly, the malware was unknown to OSINT and thus evaded signature-based tools.

Despite this, Self-Learning AI detected every single stage of the in-progress attack. No action was taken as it was only a trial POV so Darktrace had no remote access in the environment. However, after seeing the power of the technology, the organization decided to implement Darktrace across its digital estate.

Thanks to Darktrace analyst Roberto Romeu for his insights on the above threat find.

Learn how Darktrace stops Egregor and all forms of ransomware

Darktrace model detections:

  • Agent Beacon to New Endpoint
  • Agent Beacon (Long Period)
  • Agent Beacon (Medium Period)
  • Agent Beacon (Short Period)
  • Anomalous Octet Stream
  • Anomalous Server Activity / Outgoing from Server
  • Anomalous SMB Followed By Multiple Model Breaches
  • Anomalous SSL without SNI to New External
  • Beaconing Activity To External Rare
  • Beacon to Young Endpoint
  • Data Sent To New External Device
  • Data Sent to Rare Domain
  • DGA Beacon
  • Empire Python Activity Pattern
  • EXE from Rare External Location
  • High Volume of Connections with Beacon Score
  • High Volume of New or Uncommon Service Control
  • HTTP Beaconing to Rare Destination
  • Large Number of Model Breaches
  • Long Agent Connection to New Endpoint
  • Low and Slow Exfiltration
  • Multiple C2 Model Breaches
  • Multiple Connections to New External TCP Port
  • Multiple Failed Connections to Rare Endpoint
  • Multiple Lateral Movement Model Breaches
  • Network Scan
  • New Failed External Connections
  • New or Uncommon Service Control
  • Numeric Exe in SMB Write
  • Rare External SSL Self-Signed
  • Slow Beaconing Activity To External Rare
  • SMB Drive Write
  • SMB Enumeration
  • SSL Beaconing to Rare Destination
  • SSL or HTTP Beacon
  • Suspicious Beaconing Behaviour
  • Suspicious Self-Signed SSL
  • Sustained SSL or HTTP Increase
  • Quick and Regular Windows HTTP Beaconing
  • Uncommon 1 GiB Outbound
  • Unusual BITS Activity
  • Unusual Internal Connections
  • Unusual SMB Version 1 Connectivity
  • Zip or Gzip from Rare External Location

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Justin Fier
SVP, Red Team Operations

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July 10, 2025

Crypto Wallets Continue to be Drained in Elaborate Social Media Scam

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Overview

Continued research by Darktrace has revealed that cryptocurrency users are being targeted by threat actors in an elaborate social engineering scheme that continues to evolve. In December 2024, Cado Security Labs detailed a campaign targeting Web 3 employees in the Meeten campaign. The campaign included threat actors setting up meeting software companies to trick users into joining meetings and installing the information stealer Realst disguised as video meeting software.

The latest research from Darktrace shows that this campaign is still ongoing and continues to trick targets to download software to drain crypto wallets. The campaign features:

  • Threat actors creating fake startup companies with AI, gaming, video meeting software, web3 and social media themes.
  • Use of compromised X (formerly Twitter) accounts for the companies and employees - typically with verification to contact victims and create a facade of a legitimate company.
  • Notion, Medium, Github used to provide whitepapers, project roadmaps and employee details.
  • Windows and macOS versions.
  • Stolen software signing certificates in Windows versions for credibility and defense evasion.
  • Anti-analysis techniques including obfuscation, and anti-sandboxing.

To trick as many victims as possible, threat actors try to make the companies look as legitimate as possible. To achieve this, they make use of sites that are used frequently with software companies such as Twitter, Medium, Github and Notion. Each company has a professional looking website that includes employees, product blogs, whitepapers and roadmaps. X is heavily used to contact victims, and to increase the appearance of legitimacy. Some of the observed X accounts appear to be compromised accounts that typically are verified and have a higher number of followers and following, adding to the appearance of a real company.

Example of a compromised X account to create a “BuzzuAI” employee.
Figure 1: Example of a compromised X account to create a “BuzzuAI” employee.

The threat actors are active on these accounts while the campaign is active, posting about developments in the software, and product marketing. One of the fake companies part of this campaign, “Eternal Decay”, a blockchain-powered game, has created fake pictures pretending to be presenting at conferences to post on social media, while the actual game doesn’t exist.

From the Eternal Decay X account, threat actors have altered a photo from an Italian exhibition (original on the right) to make it look like Eternal Decay was presented.
Figure 2: From the Eternal Decay X account, threat actors have altered a photo from an Italian exhibition (original on the right) to make it look like Eternal Decay was presented.

In addition to X, Medium is used to post blogs about the software. Notion has been used in various campaigns with product roadmap details, as well as employee lists.

Notion project team page for Swox.
Figure 3: Notion project team page for Swox.

Github has been used to detail technical aspects of the software, along with Git repositories containing stolen open-source projects with the name changed in order to make the code look unique. In the Eternal Decay example, Gitbook is used to detail company and software information. The threat actors even include company registration information from Companies House, however they have linked to a company with a similar name and are not a real registered company.

 From the Eternal Decay Gitbook linking to a company with a similar name on Companies House.
Figure 4: From the Eternal Decay Gitbook linking to a company with a similar name on Companies House.
Gitbook for “Eternal Decay” listing investors.
Figure 5: Gitbook for “Eternal Decay” listing investors.
Gameplay images are stolen from a different game “Zombie Within” and posted pretending to be Eternal Decay gameplay.
Figure 6: Gameplay images are stolen from a different game “Zombie Within” and posted pretending to be Eternal Decay gameplay.

In some of the fake companies, fake merchandise stores have even been set up. With all these elements combined, the threat actors manage to create the appearance of a legitimate start-up company, increasing their chances of infection.

Each campaign typically starts with a victim being contacted through X messages, Telegram or Discord. A fake employee of the company will contact a victim asking to test out their software in exchange for a cryptocurrency payment. The victim will be directed to the company website download page, where they need to enter a registration code, provided by the employee to download a binary. Depending on their operating system, the victim will be instructed to download a macOS DMG (if available) or a Windows Electron application.

Example of threat actor messaging a victim on X with a registration code.
Figure 7: Example of threat actor messaging a victim on X with a registration code.

Windows Version

Similar to the aforementioned Meeten campaign, the Windows version being distributed by the fake software companies is an Electron application. Electron is an open-source framework used to run Javascript apps as a desktop application. Once the user follows directions sent to them via message, opening the application will bring up a Cloudflare verification screen.

Cloudflare verification screen.
Figure 8: Cloudflare verification screen.

The malware begins by profiling the system, gathering information like the username, CPU and core count, RAM, operating system, MAC address, graphics card, and UUID.

Code from the Electron app showing console output of system profiling.
Figure 9: Code from the Electron app showing console output of system profiling.

A verification process occurs with a captcha token extracted from the app-launcher URL and sent along with the system info and UUID. If the verification is successful, an executable or MSI file is downloaded and executed quietly. Python is also retrieved and stored in /AppData/Temp, with Python commands being sent from the command-and-control (C2) infrastructure.

Code from the Electron app looping through Python objects.
Figure 10: Code from the Electron app looping through Python objects.

As there was no valid token, this process did not succeed. However, based on previous campaigns and reports from victims on social media, an information stealer targeting crypto wallets is executed at this stage. A common tactic in the observed campaigns is the use of stolen code signing certificates to evade detection and increase the appearance of legitimate software. The certificates of two legitimate companies Jiangyin Fengyuan Electronics Co., Ltd. and Paperbucketmdb ApS (revoked as of June 2025) were used during this campaign.

MacOS Version

For companies that have a macOS version of the malware, the user is directed to download a DMG. The DMG contains a bash script and a multiarch macOS binary. The bash script is obfuscated with junk, base64 and is XOR’d.

Obfuscated Bash script.
Figure 11: Obfuscated Bash script.

After decoding, the contents of the script are revealed showing that AppleScript is being used. The script looks for disk drives, specifically for the mounted DMG “SwoxApp” and moves the hidden .SwoxApp binary to /tmp/ and makes it executable. This type of AppleScript is commonly used in macOS malware, such as Atomic Stealer.

AppleScript used to mount the malware and make it executable.
Figure 12: AppleScript used to mount the malware and make it executable.

The SwoxApp binary is the prominent macOS information stealer Atomic Stealer. Once executed the malware performs anti-analysis checks for QEMU, VMWare and Docker-OSX, the script exits if these return true.  The main functionality of Atomic Stealer is to steal data from stores including browser data, crypto wallets, cookies and documents. This data is compressed into /tmp/out.zip and sent via POST request to 45[.]94[.]47[.]167/contact. An additional bash script is retrieved from 77[.]73[.]129[.]18:80/install.sh.

Additional Bash script ”install.sh”.
Figure 13: Additional Bash script ”install.sh”.

Install.sh, as shown in Figure 13, retrieves another script install_dynamic.sh from the server https://mrajhhosdoahjsd[.]com. Install_dynamic.sh downloads and extracts InstallerHelper.app, then sets up persistence via Launch Agent to run at login.

Persistence added via Plist configuration.
Figure 14: Persistence added via Plist configuration.

This plist configuration installs a macOS LaunchAgent that silently runs the app at user login. RunAtLoad and KeepAlive keys are used to ensure the app starts automatically and remains persistent.

The retrieved binary InstallerHelper is an Objective-C/Swift binary that logs active application usage, window information, and user interaction timestamps. This data is written to local log files and periodically transmits the contents to https://mrajhhoshoahjsd[.]com/collect-metrics using scheduled network requests.

List of known companies

Darktrace has identified a number of the fake companies used in this scam. These can be found in the list below:

Pollens AI
X: @pollensapp, @Pollens_app
Website: pollens.app, pollens.io, pollens.tech
Windows: 02a5b35be82c59c55322d2800b0b8ccc
Notes: Posing as an AI software company with a focus on “collaborative creation”.

Buzzu
X: @BuzzuApp, @AI_Buzzu, @AppBuzzu, @BuzzuApp
Website: Buzzu.app, Buzzu.us, buzzu.me, Buzzu.space
Windows: 7d70a7e5661f9593568c64938e06a11a
Mac: be0e3e1e9a3fda76a77e8c5743dd2ced
Notes: Same as Pollens including logo but with a different name.

Cloudsign
X: @cloudsignapp
Windows: 3a3b13de4406d1ac13861018d74bf4b2
Notes: Claims to be a document signing platform.

Swox
X: @SwoxApp, @Swox_AI, @swox_app, @App_Swox, @AppSwox, @SwoxProject, @ProjectSwox
Website: swox.io, swox.app, swox.cc, swoxAI.com, swox.us
Windows: d50393ba7d63e92d23ec7d15716c7be6
Mac: 81996a20cfa56077a3bb69487cc58405ced79629d0c09c94fb21ba7e5f1a24c9
Notes: Claims to be a “Next gen social network in the WEB3”. Same GitHub code as Pollens.

KlastAI
X: Links to Pollens X account
Website: Links to pollens.tech
Notes: Same as Pollens, still shows their branding on its GitHub readme page.

Wasper
X: @wasperAI, @WasperSpace
Website: wasper.pro, wasper.app, wasper.org, wasper.space
Notes: Same logo and GitHub code as Pollens.

Lunelior
Website: lunelior.net, Lunelior.app, lunelior.io, lunelior.us
Windows: 74654e6e5f57a028ee70f015ef3a44a4
Mac: d723162f9197f7a548ca94802df74101

BeeSync
X: @BeeSyncAI, @AIBeeSync
Website: beesync.ai, beesync.cc
Notes: Previous alias of Buzzu, Git repo renamed January 2025.

Slax
X: @SlaxApp, @Slax_app, @slaxproject
Website: slax.tech, slax.cc, slax.social, slaxai.app

Solune
X: @soluneapp
Website: solune.io, solune.me
Windows: 22b2ea96be9d65006148ecbb6979eccc

Eternal Decay
X: @metaversedecay
Website: eternal-decay.xyz
Windows: 558889183097d9a991cb2c71b7da3c51
Mac: a4786af0c4ffc84ff193ff2ecbb564b8

Dexis
X: @DexisApp
Website: dexis.app
Notes: Same branding as Swox.

NexVoo
X: @Nexvoospace
Website: nexvoo.app, Nexvoo.net, Nexvoo.us

NexLoop
X: @nexloopspace
Website: nexloop.me

NexoraCore
Notes: Rename of the Nexloop Git repo.

YondaAI
X: @yondaspace
Website: yonda.us

Traffer Groups

A “traffer” malware group is an organized cybercriminal operation that specializes in directing internet users to malicious content typically information-stealing malware through compromised or deceptive websites, ads, and links. They tend to operate in teams with hierarchical structures with administrators recruiting “traffers” (or affiliates) to generate traffic and malware installs via search engine optimization (SEO), YouTube ads, fake software downloads, or owned sites, then monetize the stolen credentials and data via dedicated marketplaces.

A prominent traffer group “CrazyEvil” was identified by Recorded Future in early 2025. The group, who have been active since at least 2021, specialize in social engineering attacks targeted towards cryptocurrency users, influencers, DeFi professionals, and gaming communities. As reported by Recorded Future, CrazyEvil are estimated to have made millions of dollars in revenue from their malicious activity. CrazyEvil and their sub teams create fake software companies, similar to the ones described in this blog, making use of Twitter and Medium to target victims. As seen in this campaign, CrazyEvil instructs users to download their software which is an info stealer targeting both macOS and Windows users.

While it is unclear if the campaigns described in this blog can be attributed to CrazyEvil or any sub teams, the techniques described are similar in nature. This campaign highlights the efforts that threat actors will go to make these fake companies look legitimate in order to steal cryptocurrency from victims, in addition to use of newer evasive versions of malware.

Indicators of Compromise (IoCs)

Manboon[.]com

https://gaetanorealty[.]com

Troveur[.]com

Bigpinellas[.]com

Dsandbox[.]com

Conceptwo[.]com

Aceartist[.]com

turismoelcasco[.]com

Ekodirect[.]com

https://mrajhhosdoahjsd[.]com

https://isnimitz.com/zxc/app[.]zip

http://45[.]94[.]47[.]112/contact

45[.]94[.]47[.]167/contact

77[.]73[.]129[.]18:80

Domain Keys associated with the C2s

YARA Rules

rule Suspicious_Electron_App_Installer

{

  meta:

      description = "Detects Electron apps collecting HWID, MAC, GPU info and executing remote EXEs/MSIs"

      date = "2025-06-18"

  strings:

      $electron_require = /require\(['"]electron['"]\)/

      $axios_require = /require\(['"]axios['"]\)/

      $exec_use = /exec\(.*?\)/

      $url_token = /app-launcher:\/\/.*token=/

      $getHWID = /(Get-CimInstance Win32_ComputerSystemProduct).UUID/

      $getMAC = /details\.mac && details\.mac !== '00:00:00:00:00:00'/

      $getGPU = /wmic path win32_VideoController get name/

      $getInstallDate = /InstallDate/

      $os_info = /os\.cpus\(\)\[0\]\.model/

      $downloadExe = /\.exe['"]/

      $runExe = /msiexec \/i.*\/quiet \/norestart/

      $zipExtraction = /AdmZip\(.*\.extractAllTo/

  condition:

      (all of ($electron_require, $axios_require, $exec_use) and

       3 of ($getHWID, $getMAC, $getGPU, $getInstallDate, $os_info) and

       2 of ($downloadExe, $runExe, $zipExtraction, $url_token))

}

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About the author
Tara Gould
Threat Researcher

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July 9, 2025

Defending the Cloud: Stopping Cyber Threats in Azure and AWS with Darktrace

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Real-world intrusions across Azure and AWS

As organizations pursue greater scalability and flexibility, cloud platforms like Microsoft Azure and Amazon Web Services (AWS) have become essential for enabling remote operations and digitalizing corporate environments. However, this shift introduces a new set of security risks, including expanding attack surfaces, misconfigurations, and compromised credentials frequently exploited by threat actors.

This blog dives into three instances of compromise within a Darktrace customer’s Azure and AWS environment which Darktrace.

  1. The first incident took place in early 2024 and involved an attacker compromising a legitimate user account to gain unauthorized access to a customer’s Azure environment.
  2. The other two incidents, taking place in February and March 2025, targeted AWS environments. In these cases, threat actors exfiltrated corporate data, and in one instance, was able to detonate ransomware in a customer’s environment.

Case 1 - Microsoft Azure

Simplified timeline of the attack on a customer’s Azure environment.
Figure 1: Simplified timeline of the attack on a customer’s Azure environment.

In early 2024, Darktrace identified a cloud compromise on the Azure cloud environment of a customer in the Europe, the Middle East and Africa (EMEA) region.

Initial access

In this case, a threat actor gained access to the customer’s cloud environment after stealing access tokens and creating a rogue virtual machine (VM). The malicious actor was found to have stolen access tokens belonging to a third-party external consultant’s account after downloading cracked software.

With these stolen tokens, the attacker was able to authenticate to the customer’s Azure environment and successfully modified a security rule to allow inbound SSH traffic from a specific IP range (i.e., securityRules/AllowCidrBlockSSHInbound). This was likely performed to ensure persistent access to internal cloud resources.

Detection and investigation of the threat

Darktrace / IDENTITY recognized that this activity was highly unusual, triggering the “Repeated Unusual SaaS Resource Creation” alert.

Cyber AI Analyst launched an autonomous investigation into additional suspicious cloud activities occurring around the same time from the same unusual location, correlating the individual events into a broader account hijack incident.

Cyber AI Analyst’s investigation into unusual cloud activity performed by the compromised account.
Figure 2: Cyber AI Analyst’s investigation into unusual cloud activity performed by the compromised account.
Figure 2: Surrounding resource creation events highlighted by Cyber AI Analyst.
Figure 3: Surrounding resource creation events highlighted by Cyber AI Analyst.
Figure 4: Surrounding resource creation events highlighted by Cyber AI Analyst.

“Create resource service limit” events typically indicate the creation or modification of service limits (i.e., quotas) for a specific Azure resource type within a region. Meanwhile, “Registers the Capacity Resource Provider” events refer to the registration of the Microsoft Capacity resource provider within an Azure subscription, responsible for managing capacity-related resources, particularly those related to reservations and service limits. These events suggest that the threat actor was looking to create new cloud resources within the environment.

Around ten minutes later, Darktrace detected the threat actor creating or modifying an Azure disk associated with a virtual machine (VM), suggesting an attempt to create a rogue VM within the environment.

Threat actors can leverage such rogue VMs to hijack computing resources (e.g., by running cryptomining malware), maintain persistent access, move laterally within the cloud environment, communicate with command-and-control (C2) infrastructure, and stealthily deliver and deploy malware.

Persistence

Several weeks later, the compromised account was observed sending an invitation to collaborate to an external free mail (Google Mail) address.

Darktrace deemed this activity as highly anomalous, triggering a compliance alert for the customer to review and investigate further.

The next day, the threat actor further registered new multi-factor authentication (MFA) information. These actions were likely intended to maintain access to the compromised user account. The customer later confirmed this activity by reviewing the corresponding event logs within Darktrace.

Case 2 – Amazon Web Services

Simplified timeline of the attack on a customer’s AWS environment
Figure 5: Simplified timeline of the attack on a customer’s AWS environment

In February 2025, another cloud-based compromised was observed on a UK-based customer subscribed to Darktrace’s Managed Detection and Response (MDR) service.

How the attacker gained access

The threat actor was observed leveraging likely previously compromised credential to access several AWS instances within customer’s Private Cloud environment and collecting and exfiltrating data, likely with the intention of deploying ransomware and holding the data for ransom.

Darktrace alerting to malicious activity

This observed activity triggered a number of alerts in Darktrace, including several high-priority Enhanced Monitoring alerts, which were promptly investigated by Darktrace’s Security Operations Centre (SOC) and raised to the customer’s security team.

The earliest signs of attack observed by Darktrace involved the use of two likely compromised credentials to connect to the customer’s Virtual Private Network (VPN) environment.

Internal reconnaissance

Once inside, the threat actor performed internal reconnaissance activities and staged the Rclone tool “ProgramData\rclone-v1.69.0-windows-amd64.zip”, a command-line program to sync files and directories to and from different cloud storage providers, to an AWS instance whose hostname is associated with a public key infrastructure (PKI) service.

The threat actor was further observed accessing and downloading multiple files hosted on an AWS file server instance, notably finance and investment-related files. This likely represented data gathering prior to exfiltration.

Shortly after, the PKI-related EC2 instance started making SSH connections with the Rclone SSH client “SSH-2.0-rclone/v1.69.0” to a RockHoster Virtual Private Server (VPS) endpoint (193.242.184[.]178), suggesting the threat actor was exfiltrating the gathered data using the Rclone utility they had previously installed. The PKI instance continued to make repeated SSH connections attempts to transfer data to this external destination.

Darktrace’s Autonomous Response

In response to this activity, Darktrace’s Autonomous Response capability intervened, blocking unusual external connectivity to the C2 server via SSH, effectively stopping the exfiltration of data.

This activity was further investigated by Darktrace’s SOC analysts as part of the MDR service. The team elected to extend the autonomously applied actions to ensure the compromise remained contained until the customer could fully remediate the incident.

Continued reconissance

Around the same time, the threat actor continued to conduct network scans using the Nmap tool, operating from both a separate AWS domain controller instance and a newly joined device on the network. These actions were accompanied by further internal data gathering activities, with around 5 GB of data downloaded from an AWS file server.

The two devices involved in reconnaissance activities were investigated and actioned by Darktrace SOC analysts after additional Enhanced Monitoring alerts had triggered.

Lateral movement attempts via RDP connections

Unusual internal RDP connections to a likely AWS printer instance indicated that the threat actor was looking to strengthen their foothold within the environment and/or attempting to pivot to other devices, likely in response to being hindered by Autonomous Response actions.

This triggered multiple scanning, internal data transfer and unusual RDP alerts in Darktrace, as well as additional Autonomous Response actions to block the suspicious activity.

Suspicious outbound SSH communication to known threat infrastructure

Darktrace subsequently observed the AWS printer instance initiating SSH communication with a rare external endpoint associated with the web hosting and VPS provider Host Department (67.217.57[.]252), suggesting that the threat actor was attempting to exfiltrate data to an alternative endpoint after connections to the original destination had been blocked.

Further investigation using open-source intelligence (OSINT) revealed that this IP address had previously been observed in connection with SSH-based data exfiltration activity during an Akira ransomware intrusion [1].

Once again, connections to this IP were blocked by Darktrace’s Autonomous Response and subsequently these blocks were extended by Darktrace’s SOC team.

The above behavior generated multiple Enhanced Monitoring alerts that were investigated by Darktrace SOC analysts as part of the Managed Threat Detection service.

Enhanced Monitoring alerts investigated by SOC analysts as part of the Managed Detection and Response service.
Figure 5: Enhanced Monitoring alerts investigated by SOC analysts as part of the Managed Detection and Response service.

Final containment and collaborative response

Upon investigating the unusual scanning activity, outbound SSH connections, and internal data transfers, Darktrace analysts extended the Autonomous Response actions previously triggered on the compromised devices.

As the threat actor was leveraging these systems for data exfiltration, all outgoing traffic from the affected devices was blocked for an additional 24 hours to provide the customer’s security team with time to investigate and remediate the compromise.

Additional investigative support was provided by Darktrace analysts through the Security Operations Service, after the customer's opened of a ticket related to the unfolding incident.

Simplified timeline of the attack
Figure 8: Simplified timeline of the attack

Around the same time of the compromise in Case 2, Darktrace observed a similar incident on the cloud environment of a different customer.

Initial access

On this occasion, the threat actor appeared to have gained entry into the AWS-based Virtual Private Cloud (VPC) network via a SonicWall SMA 500v EC2 instance allowing inbound traffic on any port.

The instance received HTTPS connections from three rare Vultr VPS endpoints (i.e., 45.32.205[.]52, 207.246.74[.]166, 45.32.90[.]176).

Lateral movement and exfiltration

Around the same time, the EC2 instance started scanning the environment and attempted to pivot to other internal systems via RDP, notably a DC EC2 instance, which also started scanning the network, and another EC2 instance.  

The latter then proceeded to transfer more than 230 GB of data to the rare external GTHost VPS endpoint 23.150.248[.]189, while downloading hundreds of GBs of data over SMB from another EC2 instance.

Cyber AI Analyst incident generated following the unusual scanning and RDP connections from the initial compromised device.
Figure 7: Cyber AI Analyst incident generated following the unusual scanning and RDP connections from the initial compromised device.

The same behavior was replicated across multiple EC2 instances, whereby compromised instances uploaded data over internal RDP connections to other instances, which then started transferring data to the same GTHost VPS endpoint over port 5000, which is typically used for Universal Plug and Play (UPnP).

What Darktrace detected

Darktrace observed the threat actor uploading a total of 718 GB to the external endpoint, after which they detonated ransomware within the compromised VPC networks.

This activity generated nine Enhanced Monitoring alerts in Darktrace, focusing on the scanning and external data activity, with the earliest of those alerts triggering around one hour after the initial intrusion.

Darktrace’s Autonomous Response capability was not configured to act on these devices. Therefore, the malicious activity was not autonomously blocked and escalated to the point of ransomware detonation.

Conclusion

This blog examined three real-world compromises in customer cloud environments each illustrating different stages in the attack lifecycle.

The first case showcased a notable progression from a SaaS compromise to a full cloud intrusion, emphasizing the critical role of anomaly detection when legitimate credentials are abused.

The latter two incidents demonstrated that while early detection is vital, the ability to autonomously block malicious activity at machine speed is often the most effective way to contain threats before they escalate.

Together, these incidents underscore the need for continuous visibility, behavioral analysis, and machine-speed intervention across hybrid environments. Darktrace's AI-driven detection and Autonomous Response capabilities, combined with expert oversight from its Security Operations Center, give defenders the speed and clarity they need to contain threats and reduce operational disruption, before the situation spirals.

Credit to Alexandra Sentenac (Senior Cyber Analyst) and Dylan Evans (Security Research Lead)

References

[1] https://www.virustotal.com/gui/ip-address/67.217.57.252/community

Case 1

Darktrace / IDENTITY model alerts

IaaS / Compliance / Uncommon Azure External User Invite

SaaS / Resource / Repeated Unusual SaaS Resource Creation

IaaS / Compute / Azure Compute Resource Update

Cyber AI Analyst incidents

Possible Unsecured AzureActiveDirectory Resource

Possible Hijack of Office365 Account

Case 2

Darktrace / NETWORK model alerts

Compromise / SSH Beacon

Device / Multiple Lateral Movement Model Alerts

Device / Suspicious SMB Scanning Activity

Device / SMB Lateral Movement

Compliance / SSH to Rare External Destination

Device / Anomalous SMB Followed By Multiple Model Alerts

Device / Anonymous NTLM Logins

Anomalous Connection / SMB Enumeration

Device / New or Uncommon SMB Named Pipe Device / Network Scan

Device / Suspicious Network Scan Activity

Device / New Device with Attack Tools

Device / RDP Scan Device / Attack and Recon Tools

Compliance / High Priority Compliance Model Alert

Compliance / Outgoing NTLM Request from DC

Compromise / Large Number of Suspicious Successful Connections

Device / Large Number of Model Alerts

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Unusual Activity / Internal Data Transfer

Anomalous Connection / Unusual Internal Connections

Device / Anomalous RDP Followed By Multiple Model Alerts

Unusual Activity / Unusual External Activity

Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Unusual Activity / Unusual External Data to New Endpoint

Anomalous Connection / Multiple Connections to New External TCP Port

Darktrace / Autonomous Response model alerts

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

Antigena / Network / Manual / Quarantine Device

Antigena / MDR / MDR-Quarantined Device

Antigena / MDR / Model Alert on MDR-Actioned Device

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / Insider Threat / Antigena Internal Data Transfer Block

Cyber AI Analyst incidents

Possible Application Layer Reconnaissance Activity

Scanning of Multiple Devices

Unusual Repeated Connections

Unusual External Data Transfer

Case 3

Darktrace / NETWORK model alerts

Unusual Activity / Unusual Large Internal Transfer

Compliance / Incoming Remote Desktop

Unusual Activity / High Volume Server Data Transfer

Unusual Activity / Internal Data Transfer

Anomalous Connection / Unusual Internal Remote Desktop

Anomalous Connection / Unusual Incoming Data Volume

Anomalous Server Activity / Domain Controller Initiated to Client

Device / Large Number of Model Alerts

Anomalous Connection / Possible Flow Device Brute Force

Device / RDP Scan

Device / Suspicious Network Scan Activity

Device / Network Scan

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Connection / Download and Upload

Unusual Activity / Unusual External Data Transfer

Unusual Activity / High Volume Client Data Transfer

Unusual Activity / Unusual External Activity

Anomalous Connection / Uncommon 1 GiB Outbound

Device / Increased External Connectivity

Compromise / Large Number of Suspicious Successful Connections

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Low and Slow Exfiltration to IP

Unusual Activity / Enhanced Unusual External Data Transfer

Anomalous Connection / Multiple Connections to New External TCP Port

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Multiple Connections to New External UDP Port

Anomalous Connection / Possible Data Staging and External Upload

Unusual Activity / Unusual External Data to New Endpoint

Device / Large Number of Model Alerts from Critical Network Device

Compliance / External Windows Communications

Anomalous Connection / Unusual Internal Connections

Cyber AI Analyst incidents

Scanning of Multiple Devices

Extensive Unusual RDP Connections

MITRE ATT&CK mapping

(Technique name – Tactic ID)

Case 1

Defense Evasion - Modify Cloud Compute Infrastructure: Create Cloud Instance

Persistence – Account Manipulation

Case 2

Initial Access - External Remote Services

Execution - Inter-Process Communication

Persistence - External Remote Services

Discovery - System Network Connections Discovery

Discovery - Network Service Discovery

Discovery - Network Share Discovery

Lateral Movement - Remote Desktop Protocol

Lateral Movement - Remote Services: SMB/Windows Admin Shares

Collection - Data from Network Shared Drive

Command and Control - Protocol Tunneling

Exfiltration - Exfiltration Over Asymmetric Encrypted Non-C2 Protocol

Case 3

Initial Access - Exploit Public-Facing Application

Discovery - Remote System Discovery

Discovery - Network Service Discovery

Lateral Movement - Remote Services

Lateral Movement - Remote Desktop Protocol  

Collection - Data from Network Shared Drive

Collection - Data Staged: Remote Data Staging

Exfiltration - Exfiltration Over C2 Channel

Command and Control - Non-Standard Port

Command and Control – Web Service

Impact - Data Encrypted for Impact

List of IoCs

IoC         Type      Description + Probability

193.242.184[.]178 - IP Address - Possible Exfiltration Server  

45.32.205[.]52  - IP Address  - Possible C2 Infrastructure

45.32.90[.]176 - IP Address - Possible C2 Infrastructure

207.246.74[.]166 - IP Address - Likely C2 Infrastructure

67.217.57[.]252 - IP Address - Likely C2 Infrastructure

23.150.248[.]189 - IP Address - Possible Exfiltration Server

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About the author
Alexandra Sentenac
Cyber Analyst
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