March 12, 2025

Darktrace's Detection of State-Linked ShadowPad Malware

In 2024, Darktrace identified a cluster of intrusions involving the state-linked malware, ShadowPad. This blog will detail ShadowPad and the associated activities detected by Darktrace.

Written by

Sam Lister

Specialist Security Researcher

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

Sam Lister

Specialist Security Researcher

Mar 2025

An integral part of cybersecurity is anomaly detection, which involves identifying unusual patterns or behaviors in network traffic that could indicate malicious activity, such as a cyber-based intrusion. However, attribution remains one of the ever present challenges in cybersecurity. Attribution involves the process of accurately identifying and tracing the source to a specific threat actor(s).

Given the complexity of digital networks and the sophistication of attackers who often use proxies or other methods to disguise their origin, pinpointing the exact source of a cyberattack is an arduous task. Threat actors can use proxy servers, botnets, sophisticated techniques, false flags, etc. Darktrace’s strategy is rooted in the belief that identifying behavioral anomalies is crucial for identifying both known and novel threat actor campaigns.

The ShadowPad cluster

Between July 2024 and November 2024, Darktrace observed a cluster of activity threads sharing notable similarities. The threads began with a malicious actor using compromised user credentials to log in to the target organization's Check Point Remote Access virtual private network (VPN) from an attacker-controlled, remote device named 'DESKTOP-O82ILGG'. In one case, the IP from which the initial login was carried out was observed to be the ExpressVPN IP address, 194.5.83[.]25. After logging in, the actor gained access to service account credentials, likely via exploitation of an information disclosure vulnerability affecting Check Point Security Gateway devices. Recent reporting suggests this could represent exploitation of CVE-2024-24919 [27,28]. The actor then used these compromised service account credentials to move laterally over RDP and SMB, with files related to the modular backdoor, ShadowPad, being delivered to the ‘C:\PerfLogs\’ directory of targeted internal systems. ShadowPad was seen communicating with its command-and-control (C2) infrastructure, 158.247.199[.]185 (dscriy.chtq[.]net), via both HTTPS traffic and DNS tunneling, with subdomains of the domain ‘cybaq.chtq[.]net’ being used in the compromised devices’ TXT DNS queries.

Figure 1: Darktrace’s Advanced Search data showing the VPN-connected device initiating RDP connections to a domain controller (DC). The device subsequently distributes likely ShadowPad-related payloads and makes DRSGetNCChanges requests to a second DC.

Figure 2: Event Log data showing a DC making DNS queries for subdomains of ‘cbaq.chtq[.]net’ to 158.247.199[.]185 after receiving SMB and RDP connections from the VPN-connected device, DESKTOP-O82ILGG.

Darktrace observed these ShadowPad activity threads within the networks of European-based customers in the manufacturing and financial sectors. One of these intrusions was followed a few months later by likely state-sponsored espionage activity, as detailed in the investigation of the year in Darktrace’s Annual Threat Report 2024.

[related-resource]

Related ShadowPad activity

Additional cases of ShadowPad were observed across Darktrace’s customer base in 2024. In some cases, common C2 infrastructure with the cluster discussed above was observed, with dscriy.chtq[.]net and cybaq.chtq[.]net both involved; however, no other common features were identified. These ShadowPad infections were observed between April and November 2024, with customers across multiple regions and sectors affected. Darktrace’s observations align with multiple other public reports that fit the timeframe of this campaign.

Darktrace has also observed other cases of ShadowPad without common infrastructure since September 2024, suggesting the use of this tool by additional threat actors. ‍

The data theft thread

One of the Darktrace customers impacted by the ShadowPad cluster highlighted above was a European manufacturer. A distinct thread of activity occurred within this organization’s network several months after the ShadowPad intrusion, in October 2024.

The thread involved the internal distribution of highly masqueraded executable files via Sever Message Block (SMB) and WMI (Windows Management Instrumentation), the targeted collection of sensitive information from an internal server, and the exfiltration of collected information to a web of likely compromised sites. This observed thread of activity, therefore, consisted of three phrases: lateral movement, collection, and exfiltration.

The lateral movement phase began when an internal user device used an administrative credential to distribute files named ‘ProgramData\Oracle\java.log’ and 'ProgramData\Oracle\duxwfnfo' to the c$ share on another internal system.

*Figure 3: Darktrace model alert highlighting an SMB write of a file named ‘ProgramData\Oracle\java.log’ to the c$ share on another device.*

Over the next few days, Darktrace detected several other internal systems using administrative credentials to upload files with the following names to the c$ share on internal systems:

ProgramData\Adobe\ARM\webservices.dll

ProgramData\Adobe\ARM\wksprt.exe

ProgramData\Oracle\Java\wksprt.exe

ProgramData\Oracle\Java\webservices.dll

ProgramData\Microsoft\DRM\wksprt.exe

ProgramData\Microsoft\DRM\webservices.dll

ProgramData\Abletech\Client\webservices.dll

ProgramData\Abletech\Client\client.exe

ProgramData\Adobe\ARM\rzrmxrwfvp

ProgramData\3Dconnexion\3DxWare\3DxWare.exe

ProgramData\3Dconnexion\3DxWare\webservices.dll

ProgramData\IDMComp\UltraCompare\updater.exe

ProgramData\IDMComp\UltraCompare\webservices.dll

ProgramData\IDMComp\UltraCompare\imtrqjsaqmm

*Figure 4: Cyber AI Analyst highlighting an SMB write of a file named ‘ProgramData\Adobe\ARM\webservices.dll’ to the c$ share on an internal system.*

The threat actor appears to have abused the Microsoft RPC (MS-RPC) service, WMI, to execute distributed payloads, as evidenced by the ExecMethod requests to the IWbemServices RPC interface which immediately followed devices’ SMB uploads.

*Figure 5: Cyber AI Analyst data highlighting a thread of activity starting with an SMB data upload followed by ExecMethod requests.*

Several of the devices involved in these lateral movement activities, both on the source and destination side, were subsequently seen using administrative credentials to download tens of GBs of sensitive data over SMB from a specially selected server. The data gathering stage of the threat sequence indicates that the threat actor had a comprehensive understanding of the organization’s system architecture and had precise objectives for the information they sought to extract.

Immediately after collecting data from the targeted server, devices went on to exfiltrate stolen data to multiple sites. Several other likely compromised sites appear to have been used as general C2 infrastructure for this intrusion activity. The sites used by the threat actor for C2 and data exfiltration purport to be sites for companies offering a variety of service, ranging from consultancy to web design.

Screenshot of one of the likely compromised sites used in the intrusion. — *Figure 6: Screenshot* *of one of the likely compromised sites used in the intrusion.*

At least 16 sites were identified as being likely data exfiltration or C2 sites used by this threat actor in their operation against this organization. The fact that the actor had such a wide web of compromised sites at their disposal suggests that they were well-resourced and highly prepared.

*Figure 7: Darktrace model alert highlighting an internal device slowly exfiltrating data to the external endpoint, yasuconsulting[.]com.*

Figure 8: Darktrace model alert highlighting an internal device downloading nearly 1 GB of data from an internal system just before uploading a similar volume of data to another suspicious endpoint, www.tunemmuhendislik[.]com

Cyber AI Analyst spotlight

*Figure 9: Cyber AI Analyst identifying and piecing together the various steps of a ShadowPad intrusion.*

*Figure 10: Cyber AI Analyst Incident identifying and piecing together the various steps of the data theft activity.*

As shown in the above figures, Cyber AI Analyst’s ability to thread together the different steps of these attack chains are worth highlighting.

In the ShadowPad attack chains, Cyber AI Analyst was able to identify SMB writes from the VPN subnet to the DC, and the C2 connections from the DC. It was also able to weave together this activity into a single thread representing the attacker’s progression.

Similarly, in the data exfiltration attack chain, Cyber AI Analyst identified and connected multiple types of lateral movement over SMB and WMI and external C2 communication to various external endpoints, linking them in a single, connected incident.

These Cyber AI Analyst actions enabled a quicker understanding of the threat actor sequence of events and, in some cases, faster containment.

Attribution puzzle

Publicly shared research into ShadowPad indicates that it is predominantly used as a backdoor in People’s Republic of China (PRC)-sponsored espionage operations [5][6][7][8][9][10]. Most publicly reported intrusions involving ShadowPad are attributed to the China-based threat actor, APT41 [11][12]. Furthermore, Google Threat Intelligence Group (GTIG) recently shared their assessment that ShadowPad usage is restricted to clusters associated with APT41 [13]. Interestingly, however, there have also been public reports of ShadowPad usage in unattributed intrusions [5].

The data theft activity that later occurred in the same Darktrace customer network as one of these ShadowPad compromises appeared to be the targeted collection and exfiltration of sensitive data. Such an objective indicates the activity may have been part of a state-sponsored operation. The tactics, techniques, and procedures (TTPs), artifacts, and C2 infrastructure observed in the data theft thread appear to resemble activity seen in previous Democratic People’s Republic of Korea (DPRK)-linked intrusion activities [15] [16] [17] [18] [19].

The distribution of payloads to the following directory locations appears to be a relatively common behavior in DPRK-sponsored intrusions.

Observed examples:

C:\ProgramData\Oracle\Java\

C:\ProgramData\Adobe\ARM\

C:\ProgramData\Microsoft\DRM\

C:\ProgramData\Abletech\Client\

C:\ProgramData\IDMComp\UltraCompare\

C:\ProgramData\3Dconnexion\3DxWare\

Additionally, the likely compromised websites observed in the data theft thread, along with some of the target URI patterns seen in the C2 communications to these sites, resemble those seen in previously reported DPRK-linked intrusion activities.

No clear evidence was found to link the ShadowPad compromise to the subsequent data theft activity that was observed on the network of the manufacturing customer. It should be noted, however, that no clear signs of initial access were found for the data theft thread – this could suggest the ShadowPad intrusion itself represents the initial point of entry that ultimately led to data exfiltration.

Motivation-wise, it seems plausible for the data theft thread to have been part of a DPRK-sponsored operation. DPRK is known to pursue targets that could potentially fulfil its national security goals and had been publicly reported as being active in months prior to this intrusion [21]. Furthermore, the timing of the data theft aligns with the ratification of the mutual defense treaty between DPRK and Russia and the subsequent accused activities [20].

Darktrace assesses with medium confidence that a nation-state, likely DPRK, was responsible, based on our investigation, the threat actor applied resources, patience, obfuscation, and evasiveness combined with external reporting, collaboration with the cyber community, assessing the attacker’s motivation and world geopolitical timeline, and undisclosed intelligence.

Conclusion

When state-linked cyber activity occurs within an organization’s environment, previously unseen C2 infrastructure and advanced evasion techniques will likely be used. State-linked cyber actors, through their resources and patience, are able to bypass most detection methods, leaving anomaly-based methods as a last line of defense.

Two threads of activity were observed within Darktrace’s customer base over the last year: The first operation involved the abuse of Check Point VPN credentials to log in remotely to organizations’ networks, followed by the distribution of ShadowPad to an internal domain controller. The second operation involved highly targeted data exfiltration from the network of one of the customers impacted by the previously mentioned ShadowPad activity.

Despite definitive attribution remaining unresolved, both the ShadowPad and data exfiltration activities were detected by Darktrace’s Self-Learning AI, with Cyber AI Analyst playing a significant role in identifying and piecing together the various steps of the intrusion activities.

Credit to Sam Lister (R&D Detection Analyst), Emma Foulger (Principal Cyber Analyst), Nathaniel Jones (VP), and the Darktrace Threat Research team.

Appendices

Darktrace / NETWORK model alerts

User / New Admin Credentials on Client

Anomalous Connection / Unusual Admin SMB Session

Compliance / SMB Drive Write

Device / Anomalous SMB Followed By Multiple Model Breaches

Anomalous File / Internal / Unusual SMB Script Write

User / New Admin Credentials on Client

Anomalous Connection / Unusual Admin SMB Session

Compliance / SMB Drive Write

Device / Anomalous SMB Followed By Multiple Model Breaches

Anomalous File / Internal / Unusual SMB Script Write

Device / New or Uncommon WMI Activity

Unusual Activity / Internal Data Transfer

Anomalous Connection / Download and Upload

Anomalous Server Activity / Rare External from Server

Compromise / Beacon to Young Endpoint

Compromise / Agent Beacon (Short Period)

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Connection / POST to PHP on New External Host

Compromise / Sustained SSL or HTTP Increase

Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Device / Multiple C2 Model Alerts

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Download and Upload

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Low and Slow Exfiltration

Anomalous Connection / Uncommon 1 GiB Outbound

MITRE ATT&CK mapping

(Technique name – Tactic ID)

ShadowPad malware threads

Initial Access - Valid Accounts: Domain Accounts (T1078.002)

Initial Access - External Remote Services (T1133)

Privilege Escalation - Exploitation for Privilege Escalation (T1068)

Privilege Escalation - Valid Accounts: Default Accounts (T1078.001)

Defense Evasion - Masquerading: Match Legitimate Name or Location (T1036.005)

Lateral Movement - Remote Services: Remote Desktop Protocol (T1021.001)

Lateral Movement - Remote Services: SMB/Windows Admin Shares (T1021.002)

Command and Control - Proxy: Internal Proxy (T1090.001)

Command and Control - Application Layer Protocol: Web Protocols (T1071.001)

Command and Control - Encrypted Channel: Asymmetric Cryptography (T1573.002)

Command and Control - Application Layer Protocol: DNS (T1071.004)

Data theft thread

Resource Development - Compromise Infrastructure: Domains (T1584.001)

Privilege Escalation - Valid Accounts: Default Accounts (T1078.001)

Privilege Escalation - Valid Accounts: Domain Accounts (T1078.002)

Execution - Windows Management Instrumentation (T1047)

Defense Evasion - Masquerading: Match Legitimate Name or Location (T1036.005)

Defense Evasion - Obfuscated Files or Information (T1027)

Lateral Movement - Remote Services: SMB/Windows Admin Shares (T1021.002)

Collection - Data from Network Shared Drive (T1039)

Command and Control - Application Layer Protocol: Web Protocols (T1071.001)

Command and Control - Encrypted Channel: Asymmetric Cryptography (T1573.002)

Command and Control - Proxy: External Proxy (T1090.002)

Exfiltration - Exfiltration Over C2 Channel (T1041)

Exfiltration - Data Transfer Size Limits (T1030)

List of indicators of compromise (IoCs)

IP addresses and/or domain names (Mid-high confidence):

ShadowPad thread

- dscriy.chtq[.]net • 158.247.199[.]185 (endpoint of C2 comms)

- cybaq.chtq[.]net (domain name used for DNS tunneling)

Data theft thread

- yasuconsulting[.]com (45.158.12[.]7)

- hobivan[.]net (94.73.151[.]72)

- mediostresbarbas.com[.]ar (75.102.23[.]3)

- mnmathleague[.]org (185.148.129[.]24)

- goldenborek[.]com (94.138.200[.]40)

- tunemmuhendislik[.]com (94.199.206[.]45)

- anvil.org[.]ph (67.209.121[.]137)

- partnerls[.]pl (5.187.53[.]50)

- angoramedikal[.]com (89.19.29[.]128)

- awork-designs[.]dk (78.46.20[.]225)

- digitweco[.]com (38.54.95[.]190)

- duepunti-studio[.]it (89.46.106[.]61)

- scgestor.com[.]br (108.181.92[.]71)

- lacapannadelsilenzio[.]it (86.107.36[.]15)

- lovetamagotchith[.]com (203.170.190[.]137)

- lieta[.]it (78.46.146[.]147)

File names (Mid-high confidence):

ShadowPad thread:

- perflogs\1.txt

- perflogs\AppLaunch.exe

- perflogs\F4A3E8BE.tmp

- perflogs\mscoree.dll

Data theft thread

- ProgramData\Oracle\java.log

- ProgramData\Oracle\duxwfnfo

- ProgramData\Adobe\ARM\webservices.dll

- ProgramData\Adobe\ARM\wksprt.exe

- ProgramData\Oracle\Java\wksprt.exe

- ProgramData\Oracle\Java\webservices.dll

- ProgramData\Microsoft\DRM\wksprt.exe

- ProgramData\Microsoft\DRM\webservices.dll

- ProgramData\Abletech\Client\webservices.dll

- ProgramData\Abletech\Client\client.exe

- ProgramData\Adobe\ARM\rzrmxrwfvp

- ProgramData\3Dconnexion\3DxWare\3DxWare.exe

- ProgramData\3Dconnexion\3DxWare\webservices.dll

- ProgramData\IDMComp\UltraCompare\updater.exe

- ProgramData\IDMComp\UltraCompare\webservices.dll

- ProgramData\IDMComp\UltraCompare\imtrqjsaqmm

- temp\HousecallLauncher64.exe

Attacker-controlled device hostname (Mid-high confidence)

- DESKTOP-O82ILGG

References

[1] https://www.kaspersky.com/about/press-releases/shadowpad-how-attackers-hide-backdoor-in-software-used-by-hundreds-of-large-companies-around-the-world

[2] https://media.kasperskycontenthub.com/wp-content/uploads/sites/43/2017/08/07172148/ShadowPad_technical_description_PDF.pdf

[3] https://blog.avast.com/new-investigations-in-ccleaner-incident-point-to-a-possible-third-stage-that-had-keylogger-capacities

[4] https://securelist.com/operation-shadowhammer-a-high-profile-supply-chain-attack/90380/

[5] https://assets.sentinelone.com/c/Shadowpad?x=P42eqA

[6] https://www.cyfirma.com/research/the-origins-of-apt-41-and-shadowpad-lineage/

[7] https://www.csoonline.com/article/572061/shadowpad-has-become-the-rat-of-choice-for-several-state-sponsored-chinese-apts.html

[8] https://global.ptsecurity.com/analytics/pt-esc-threat-intelligence/shadowpad-new-activity-from-the-winnti-group

[9] https://cymulate.com/threats/shadowpad-privately-sold-malware-espionage-tool/

[10] https://www.secureworks.com/research/shadowpad-malware-analysis

[11] https://blog.talosintelligence.com/chinese-hacking-group-apt41-compromised-taiwanese-government-affiliated-research-institute-with-shadowpad-and-cobaltstrike-2/

[12] https://hackerseye.net/all-blog-items/tails-from-the-shadow-apt-41-injecting-shadowpad-with-sideloading/

[13] https://cloud.google.com/blog/topics/threat-intelligence/scatterbrain-unmasking-poisonplug-obfuscator

[14] https://www.domaintools.com/wp-content/uploads/conceptualizing-a-continuum-of-cyber-threat-attribution.pdf

[15] https://www.nccgroup.com/es/research-blog/north-korea-s-lazarus-their-initial-access-trade-craft-using-social-media-and-social-engineering/

[16] https://www.microsoft.com/en-us/security/blog/2021/01/28/zinc-attacks-against-security-researchers/

[17] https://www.microsoft.com/en-us/security/blog/2022/09/29/zinc-weaponizing-open-source-software/

[18] https://www.welivesecurity.com/en/eset-research/lazarus-luring-employees-trojanized-coding-challenges-case-spanish-aerospace-company/

[19] https://blogs.jpcert.or.jp/en/2021/01/Lazarus_malware2.html

[20] https://usun.usmission.gov/joint-statement-on-the-unlawful-arms-transfer-by-the-democratic-peoples-republic-of-korea-to-russia/

[21] https://media.defense.gov/2024/Jul/25/2003510137/-1/-1/1/Joint-CSA-North-Korea-Cyber-Espionage-Advance-Military-Nuclear-Programs.PDF

[22] https://kyivindependent.com/first-north-korean-troops-deployed-to-front-line-in-kursk-oblast-ukraines-military-intelligence-says/

[23] https://www.microsoft.com/en-us/security/blog/2024/12/04/frequent-freeloader-part-i-secret-blizzard-compromising-storm-0156-infrastructure-for-espionage/

[24] https://www.microsoft.com/en-us/security/blog/2024/12/11/frequent-freeloader-part-ii-russian-actor-secret-blizzard-using-tools-of-other-groups-to-attack-ukraine/

[25] https://www.sentinelone.com/labs/chamelgang-attacking-critical-infrastructure-with-ransomware/

[26] https://thehackernews.com/2022/06/state-backed-hackers-using-ransomware.html/

[27] https://blog.checkpoint.com/security/check-point-research-explains-shadow-pad-nailaolocker-and-its-protection/

[28] https://www.orangecyberdefense.com/global/blog/cert-news/meet-nailaolocker-a-ransomware-distributed-in-europe-by-shadowpad-and-plugx-backdoors

[related-resource]

AI Cybersecurity: Insights for 2025

We surveyed 1,500+ cybersecurity professionals globally to explore their views, knowledge, and priorities on AI cybersecurity in 2025.

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Written by

Sam Lister

Specialist Security Researcher

Inside the SOC

Written by

Sam Lister

Specialist Security Researcher

•

October 20, 2025

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

•

October 15, 2025

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October 20, 2025

Salty Much: Darktrace’s view on a recent Salt Typhoon intrusion

What is Salt Typhoon?‍

Salt Typhoon represents one of the most persistent and sophisticated cyber threats targeting global critical infrastructure today. Believed to be linked to state-sponsored actors from the People’s Republic of China (PRC), this advanced persistent threat (APT) group has executed a series of high-impact campaigns against telecommunications providers, energy networks, and government systems—most notably across the United States.

Active since at least 2019, the group—also tracked as Earth Estries, GhostEmperor, and UNC2286—has demonstrated advanced capabilities in exploiting edge devices, maintaining deep persistence, and exfiltrating sensitive data across more than 80 countries. While much of the public reporting has focused on U.S. targets, Salt Typhoon’s operations have extended into Europe, the Middle East, and Africa (EMEA) where it has targeted telecoms, government entities, and technology firms. Its use of custom malware and exploitation of high-impact vulnerabilities (e.g., Ivanti, Fortinet, Cisco) underscores the strategic nature of its campaigns, which blend intelligence collection with geopolitical influence [1].

Leveraging zero-day exploits, obfuscation techniques, and lateral movement strategies, Salt Typhoon has demonstrated an alarming ability to evade detection and maintain long-term access to sensitive environments. The group’s operations have exposed lawful intercept systems, compromised metadata for millions of users, and disrupted essential services, prompting coordinated responses from intelligence agencies and private-sector partners worldwide. As organizations reassess their threat models, Salt Typhoon serves as a stark reminder of the evolving nature of nation-state cyber operations and the urgent need for proactive defense strategies.

Darktrace’s coverage

In this case, Darktrace observed activity in a European telecommunications organisation consistent with Salt Typhoon’s known tactics, techniques and procedures (TTPs), including dynamic-link library (DLL) sideloading and abuse of legitimate software for stealth and execution.

Initial access

The intrusion likely began with exploitation of a Citrix NetScaler Gateway appliance in the first week of July 2025. From there, the actor pivoted to Citrix Virtual Delivery Agent (VDA) hosts in the client’s Machine Creation Services (MCS) subnet. Initial access activities in the intrusion originated from an endpoint potentially associated with the SoftEther VPN service, suggesting infrastructure obfuscation from the outset.

Tooling

Darktrace subsequently observed the threat actor delivering a backdoor assessed with high confidence to be SNAPPYBEE (also known as Deed RAT) [2][3] to multiple Citrix VDA hosts. The backdoor was delivered to these internal endpoints as a DLL alongside legitimate executable files for antivirus software such as Norton Antivirus, Bkav Antivirus, and IObit Malware Fighter. This pattern of activity indicates that the attacker relied on DLL side-loading via legitimate antivirus software to execute their payloads. Salt Typhoon and similar groups have a history of employing this technique [4][5], enabling them to execute payloads under the guise of trusted software and bypassing traditional security controls.

Command-and-Control (C2)

The backdoor delivered by the threat actor leveraged LightNode VPS endpoints for C2, communicating over both HTTP and an unidentified TCP-based protocol. This dual-channel setup is consistent with Salt Typhoon’s known use of non-standard and layered protocols to evade detection. The HTTP communications displayed by the backdoor included POST requests with an Internet Explorer User-Agent header and Target URI patterns such as “/17ABE7F017ABE7F0”. One of the C2 hosts contacted by compromised endpoints was aar.gandhibludtric[.]com (38.54.63[.]75), a domain recently linked to Salt Typhoon [6].

Detection timeline

Darktrace produced high confidence detections in response to the early stages of the intrusion, with both the initial tooling and C2 activities being strongly covered by both investigations by Darktrace Cyber AI Analyst^TM investigations and Darktrace models. Despite the sophistication of the threat actor, the intrusion activity identified and remediated before escalating beyond these early stages of the attack, with Darktrace’s timely high-confidence detections likely playing a key role in neutralizing the threat.

Cyber AI Analyst observations

Darktrace’s Cyber AI Analyst autonomously investigated the model alerts generated by Darktrace during the early stages of the intrusion. Through its investigations, Cyber AI Analyst discovered the initial tooling and C2 events and pieced them together into unified incidents representing the attacker’s progression.

Figure 1: Cyber AI Analyst weaved together separate events from the intrusion into broader incidents summarizing the attacker’s progression.

Conclusion

Based on overlaps in TTPs, staging patterns, infrastructure, and malware, Darktrace assesses with moderate confidence that the observed activity was consistent with Salt Typhoon/Earth Estries (ALA GhostEmperor/UNC2286). Salt Typhoon continues to challenge defenders with its stealth, persistence, and abuse of legitimate tools. As attackers increasingly blend into normal operations, detecting behavioral anomalies becomes essential for identifying subtle deviations and correlating disparate signals. The evolving nature of Salt Typhoon’s tradecraft, and its ability to repurpose trusted software and infrastructure, ensures it will remain difficult to detect using conventional methods alone. This intrusion highlights the importance of proactive defense, where anomaly-based detections, not just signature matching, play a critical role in surfacing early-stage activity.

Credit to Nathaniel Jones (VP, Security & AI Strategy, FCISO), Sam Lister (Specialist Security Researcher), Emma Foulger (Global Threat Research Operations Lead), Adam Potter (Senior Cyber Analyst)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Indicators of Compromise (IoCs)

IoC-Type-Description + Confidence

89.31.121[.]101 – IP Address – Possible C2 server

hxxp://89.31.121[.]101:443/WINMM.dll - URI – Likely SNAPPYBEE download

b5367820cd32640a2d5e4c3a3c1ceedbbb715be2 - SHA1 – Likely SNAPPYBEE download

hxxp://89.31.121[.]101:443/NortonLog.txt - URI - Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/123.txt - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/123.tar - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/pdc.exe - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443//Dialog.dat - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/fltLib.dll - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/DisplayDialog.exe - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/DgApi.dll - URI - Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/dbindex.dat - URI - Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/1.txt - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/imfsbDll.dll – Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/imfsbSvc.exe - URI – Likely DLL side-loading activity

aar.gandhibludtric[.]com – Hostname – Likely C2 server

38.54.63[.]75 – IP – Likely C2 server

156.244.28[.]153 – IP – Possible C2 server

hxxp://156.244.28[.]153/17ABE7F017ABE7F0 - URI – Possible C2 activity

MITRE TTPs

Technique | Description

T1190 | Exploit Public-Facing Application - Citrix NetScaler Gateway compromise

T1105 | Ingress Tool Transfer – Delivery of backdoor to internal hosts

T1665 | Hide Infrastructure – Use of SoftEther VPN for C2

T1574.001 | Hijack Execution Flow: DLL – Execution of backdoor through DLL side-loading

T1095 | Non-Application Layer Protocol – Unidentified application-layer protocol for C2 traffic

T1071.001| Web Protocols – HTTP-based C2 traffic

T1571| Non-Standard Port – Port 443 for unencrypted HTTP traffic

Darktrace Model Alerts during intrusion

Anomalous File::Internal::Script from Rare Internal Location

Anomalous File::EXE from Rare External Location

Anomalous File::Multiple EXE from Rare External Locations

Anomalous Connection::Possible Callback URL

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

Antigena::Network::Significant Anomaly::Antigena Significant Server Anomaly Block

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

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

Antigena::Network::External Threat::Antigena File then New Outbound Block

References

[1] https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-239a

[2] https://www.trendmicro.com/en_gb/research/24/k/earth-estries.html

[3] https://www.trendmicro.com/content/dam/trendmicro/global/en/research/24/k/earth-estries/IOC_list-EarthEstries.txt

[4] https://www.trendmicro.com/en_gb/research/24/k/breaking-down-earth-estries-persistent-ttps-in-prolonged-cyber-o.html

[5] https://lab52.io/blog/deedrat-backdoor-enhanced-by-chinese-apts-with-advanced-capabilities/

[6] https://www.silentpush.com/blog/salt-typhoon-2025/

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About the author

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

Blog

AI

October 15, 2025

How a Major Civil Engineering Company Reduced MTTR across Network, Email and the Cloud with Darktrace

Asking more of the information security team

“What more can we be doing to secure the company?” is a great question for any cyber professional to hear from their Board of Directors. After successfully defeating a series of attacks and seeing the potential for AI tools to supercharge incoming threats, a UK-based civil engineering company’s security team had the answer: Darktrace.

“When things are coming at you at machine speed, you need machine speed to fight it off – it’s as simple as that,” said their Information Security Manager. “There were incidents where it took us a few hours to get to the bottom of what was going on. Darktrace changed that.”

Prevention was also the best cure. A peer organization in the same sector was still in business continuity measures 18 months after an attack, and the security team did not want to risk that level of business disruption.

Legacy tools were not meeting the team’s desired speed or accuracy

The company’s native SaaS email platform took between two and 14 days to alert on suspicious emails, with another email security tool flagging malicious emails after up to 24 days. After receiving an alert, responses often took a couple of days to coordinate. The team was losing precious time.

Beyond long detection and response times, the old email security platform was no longer performing: 19% of incoming spam was missed. Of even more concern: 6% of phishing emails reached users’ inboxes, and malware and ransomware email was also still getting through, with 0.3% of such email-borne payloads reaching user inboxes.

Choosing Darktrace

“When evaluating tools in 2023, only Darktrace had what I was looking for: an existing, mature, AI-based cybersecurity solution. ChatGPT had just come out and a lot of companies were saying ‘AI this’ and ‘AI that’. Then you’d take a look, and it was all rules- and cases-based, not AI at all,” their Information Security Manager.

The team knew that, with AI-enabled attacks on the horizon, a cybersecurity company that had already built, fielded, and matured an AI-powered cyber defense would give the security team the ability to fend off machine-speed attacks at the same pace as the attackers.

Darktrace accomplishes this with multi-layered AI that learns each organization’s normal business operations. With this detailed level of understanding, Darktrace’s Self-Learning AI can recognize unusual activity that may indicate a cyber-attack, and works to neutralize the threat with precise response actions. And it does this all at machine speed and with minimal disruption.

On the morning the team was due to present its findings, the session was cancelled – for a good reason. The Board didn’t feel further discussion was necessary because the case for Darktrace was so conclusive. The CEO described the Darktrace option as ‘an insurance policy we can’t do without’.

Saving time with Darktrace / EMAIL

Darktrace / EMAIL reduced the discovery, alert, and response process from days or weeks to seconds .

Darktrace / EMAIL automates what was originally a time-consuming and repetitive process. The team has recovered between eight and 10 working hours a week by automating much of this process using / EMAIL.

Today, Darktrace / EMAIL prevents phishing emails from reaching employees’ inboxes. The volume of hostile and unsolicited email fell to a third of its original level after Darktrace / EMAIL was set up.

Further savings with Darktrace / NETWORK and Darktrace / IDENTITY

Since its success with Darktrace / EMAIL, the company adopted two more products from the Darktrace ActiveAI Security Platform – Darktrace / NETWORK and Darktrace / IDENTITY.

These have further contributed to cost savings. An initial plan to build a 24/7 SOC would have required hiring and retaining six additional analysts, rather than the two that currently use Darktrace, costing an additional £220,000 per year in salary. With Darktrace, the existing analysts have the tools needed to become more effective and impactful.

An additional benefit: Darktrace adoption has lowered the company’s cyber insurance premiums. The security team can reallocate this budget to proactive projects.

Detection of novel threats provides reassurance

Darktrace’s unique approach to cybersecurity added a key benefit. The team’s previous tool took a rules-based approach – which was only good if the next attack featured the same characteristics as the ones on which the tool was trained.

“Darktrace looks for anomalous behavior, and we needed something that detected and responded based on use cases, not rules that might be out of date or too prescriptive,” their Information Security Manager. “Our existing provider could take a couple of days to update rules and signatures, and in this game, speed is of the essence. Darktrace just does everything we need - without delay.”

Where rules-based tools must wait for a threat to emerge before beginning to detect and respond to it, Darktrace identifies and protects against unknown and novel threats, speeding identification, response, and recovery, minimizing business disruption as a result.

Looking to the future

With Darktrace in place, the UK-based civil engineering company team has reallocated time and resources usually spent on detection and alerting to now tackle more sophisticated, strategic challenges. Darktrace has also equipped the team with far better and more regularly updated visibility into potential vulnerabilities.

“One thing that frustrates me a little is penetration testing; our ISO accreditation mandates a penetration test at least once a year, but the results could be out of date the next day,” their Information Security Manager. “Darktrace / Proactive Exposure Management will give me that view in real time – we can run it daily if needed - and that’s going to be a really effective workbench for my team.”

As the company looks to further develop its security posture, Darktrace remains poised to evolve alongside its partner.

About the author

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How a Major Civil Engineering Company Reduced MTTR across Network, Email and the Cloud with Darktrace

Asking more of the information security team

Legacy tools were not meeting the team’s desired speed or accuracy

Choosing Darktrace

Saving time with Darktrace / EMAIL

Further savings with Darktrace / NETWORK and Darktrace / IDENTITY

Detection of novel threats provides reassurance

Looking to the future