September 3, 2025

From PowerShell to Payload: Darktrace’s Detection of a Novel Cryptomining Malware

Cryptojacking attacks are rising as threat actors exploit hard-to-detect cryptomining malware. Learn how Darktrace detected and contained a cryptojacking attempt in its early stages using Autonomous Response, with expert analysis of the malware itself revealing insights into a novel cryptomining strain.

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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.

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Sep 2025

What is Cryptojacking?

Cryptojacking remains one of the most persistent cyber threats in the digital age, showing no signs of slowing down. It involves the unauthorized use of a computer or device’s processing power to mine cryptocurrencies, often without the owner’s consent or knowledge, using cryptojacking scripts or cryptocurrency mining (cryptomining) malware [1].

Unlike other widespread attacks such as ransomware, which disrupt operations and block access to data, cryptomining malware steals and drains computing and energy resources for mining to reduce attacker’s personal costs and increase “profits” earned from mining [1]. The impact on targeted organizations can be significant, ranging from data privacy concerns and reduced productivity to higher energy bills.

As cryptocurrency continues to grow in popularity, as seen with the ongoing high valuation of the global cryptocurrency market capitalization (almost USD 4 trillion at time of writing), threat actors will continue to view cryptomining as a profitable venture [2]. As a result, illicit cryptominers are being used to steal processing power via supply chain attacks or browser injections, as seen in a recent cryptojacking campaign using JavaScript [3][4].

Therefore, security teams should maintain awareness of this ongoing threat, as what is often dismissed as a "compliance issue" can escalate into more severe compromises and lead to prolonged exposure of critical resources.

While having a security team capable of detecting and analyzing hijacking attempts is essential, emerging threats in today’s landscape often demand more than manual intervention.

This blog will discuss Darktrace’s successful detection of the malicious activity, the role of Autonomous Response in halting the cryptojacking attack, include novel insights from Darktrace’s threat researchers on the cryptominer payload, showing how the attack chain was initiated through the execution of a PowerShell-based payload.

Darktrace’s Coverage of Cryptojacking via PowerShell

In July 2025, Darktrace detected and contained an attempted cryptojacking incident on the network of a customer in the retail and e-commerce industry.

The threat was detected when a threat actor attempted to use a PowerShell script to download and run NBMiner directly in memory.

The initial compromise was detected on July 22, when Darktrace / NETWORK observed the use of a new PowerShell user agent during a connection to an external endpoint, indicating an attempt at remote code execution.

Specifically, the targeted desktop device established a connection to the rare endpoint, 45.141.87[.]195, over destination port 8000 using HTTP as the application-layer protocol. Within this connection, Darktrace observed the presence of a PowerShell script in the URI, specifically ‘/infect.ps1’.

Darktrace’s analysis of this endpoint (45.141.87[.]195[:]8000/infect.ps1) and the payload it downloaded indicated it was a dropper used to deliver an obfuscated AutoIt loader. This attribution was further supported by open-source intelligence (OSINT) reporting [5]. The loader likely then injected NBMiner into a legitimate process on the customer’s environment – the first documented case of NBMiner being dropped in this way.

Figure 1: Darktrace’s detection of a device making an HTTP connection with new PowerShell user agent, indicating PowerShell abuse for command-and-control (C2) communications.

Script files are often used by malicious actors for malware distribution. In cryptojacking attacks specifically, scripts are used to download and install cryptomining software, which then attempts to connect to cryptomining pools to begin mining operations [6].

Inside the payload: Technical analysis of the malicious script and cryptomining loader

To confidently establish that the malicious script file dropped an AutoIt loader used to deliver the NBMiner cryptominer, Darktrace’s threat researchers reverse engineered the payload. Analysis of the file ‘infect.ps1’ revealed further insights, ultimately linking it to the execution of a cryptominer loader.

Figure 2: Screenshot of the ‘infect.ps1’ PowerShell script observed in the attack.

The ‘infect.ps1’ script is a heavily obfuscated PowerShell script that contains multiple variables of Base64 and XOR encoded data. The first data blob is XOR’d with a value of 97, after decoding, the data is a binary and stored in APPDATA/local/knzbsrgw.exe. The binary is AutoIT.exe, the legitimate executable of the AutoIt programming language. The script also performs a check for the existence of the registry key HKCU:\\Software\LordNet.

The second data blob ($cylcejlrqbgejqryxpck) is written to APPDATA\rauuq, where it will later be read and XOR decoded. The third data blob ($tlswqbblxmmr)decodes to an obfuscated AutoIt script, which is written to %LOCALAPPDATA%\qmsxehehhnnwioojlyegmdssiswak. To ensure persistence, a shortcut file named xxyntxsmitwgruxuwqzypomkhxhml.lnk is created to run at startup.

Figure 3: Screenshot of second stage AutoIt script.

The observed AutoIt script is a process injection loader. It reads an encrypted binary from /rauuq in APPDATA, then XOR-decodes every byte with the key 47 to reconstruct the payload in memory. Next, it silently launches the legitimate Windows app ‘charmap.exe’ (Character Map) and obtains a handle with full access. It allocates executable and writable memory inside that process, writes the decrypted payload into the allocated region, and starts a new thread at that address. Finally, it closes the thread and process handles.

The binary that is injected into charmap.exe is 64-bit Windows binary. On launch, it takes a snapshot of running processes and specifically checks whether Task Manager is open. If Task Manager is detected, the binary kills sigverif.exe; otherwise, it proceeds. Once the condition is met, NBMiner is retrieved from a Chimera URL (https://api[.]chimera-hosting[.]zip/frfnhis/zdpaGgLMav/nbminer[.]exe) and establishes persistence, ensuring that the process automatically restarts if terminated. When mining begins, it spawns a process with the arguments ‘-a kawpow -o asia.ravenminer.com:3838 -u R9KVhfjiqSuSVcpYw5G8VDayPkjSipbiMb.worker -i 60’ and hides the process window to evade detection.

The program includes several evasion measures. It performs anti-sandboxing by sleeping to delay analysis and terminates sigverif.exe (File Signature Verification). It checks for installed antivirus products and continues only when Windows Defender is the sole protection. It also verifies whether the current user has administrative rights. If not, it attempts a User Account Control (UAC) bypass via Fodhelper to silently elevate and execute its payload without prompting the user. The binary creates a folder under %APPDATA%, drops rtworkq.dll extracted from its own embedded data, and copies ‘mfpmp.exe’ from System32 into that directory to side-load ‘rtworkq.dll’. It also looks for the registry key HKCU\Software\kap, creating it if it does not exist, and reads or sets a registry value it expects there.

Zooming Out: Darktrace Coverage of NBMiner

Darktrace’s analysis of the malicious PowerShell script provides clear evidence that the payload downloaded and executed the NBMiner cryptominer. Once executed, the infected device is expected to attempt connections to cryptomining endpoints (mining pools). Darktrace initially observed this on the targeted device once it started making DNS requests for a cryptominer endpoint, “gulf[.]moneroocean[.]stream” [7], one minute after the connection involving the malicious script.

Figure 5: Darktrace Advanced Search logs showcasing the affected device making a DNS request for a Monero mining endpoint.

Though DNS requests do not necessarily mean the device connected to a cryptominer-associated endpoint, Darktrace detected connections to the endpoint specified in the DNS Answer field: monerooceans[.]stream, 152.53.121[.]6. The attempted connections to this endpoint over port 10001 triggered several high-fidelity model alerts in Darktrace related to possible cryptomining mining activity. The IP address and destination port combination (152.53.121[.]6:10001) has also been linked to cryptomining activity by several OSINT security vendors [8][9].

Figure 6: Darktrace’s detection of a device establishing connections with the Monero Mining-associated endpoint, monerooceans[.]stream over port 10001.

Darktrace / NETWORK grouped together the observed indicators of compromise (IoCs) on the targeted device and triggered an additional Enhanced Monitoring model designed to identify activity indicative of the early stages of an attack. These high-fidelity models are continuously monitored and triaged by Darktrace’s SOC team as part of the Managed Threat Detection service, ensuring that subscribed customers are promptly notified of malicious activity as soon as it emerges.

Figure 7: Darktrace’s correlation of the initial PowerShell-related activity with the cryptomining endpoint, showcasing a pattern indicative of an initial attack chain.

Darktrace’s Cyber AI Analyst launched an autonomous investigation into the ongoing activity and was able to link the individual events of the attack, encompassing the initial connections involving the PowerShell script to the ultimate connections to the cryptomining endpoint, likely representing cryptomining activity. Rather than viewing these seemingly separate events in isolation, Cyber AI Analyst was able to see the bigger picture, providing comprehensive visibility over the attack.

Figure 8: Darktrace’s Cyber AI Analyst view illustrating the extent of the cryptojacking attack mapped against the Cyber Kill Chain.

Darktrace’s Autonomous Response

Fortunately, as this customer had Darktrace configured in Autonomous Response mode, Darktrace was able to take immediate action by preventing the device from making outbound connections and blocking specific connections to suspicious endpoints, thereby containing the attack.

Specifically, these Autonomous Response actions prevented the outgoing communication within seconds of the device attempting to connect to the rare endpoints.

Figure 10: Darktrace’s Autonomous Response blocked connections to the mining-related endpoint within a second of the initial connection.

Additionally, the Darktrace SOC team was able to validate the effectiveness of the Autonomous Response actions by analyzing connections to 152.53.121[.]6 using the Advanced Search feature. Across more than 130 connection attempts, Darktrace’s SOC confirmed that all were aborted, meaning no connections were successfully established.

Figure 11: Advanced Search logs showing all attempted connections that were successfully prevented by Darktrace’s Autonomous Response capability.

Conclusion

Cryptojacking attacks will remain prevalent, as threat actors can scale their attacks to infect multiple devices and networks. What’s more, cryptomining incidents can often be difficult to detect and are even overlooked as low-severity compliance events, potentially leading to data privacy issues and significant energy bills caused by misused processing power.

Darktrace’s anomaly-based approach to threat detection identifies early indicators of targeted attacks without relying on prior knowledge or IoCs. By continuously learning each device’s unique pattern of life, Darktrace can detect subtle deviations that may signal a compromise.

In this case, the cryptojacking attack was quickly identified and mitigated during the early stages of malware and cryptomining activity. Darktrace's Autonomous Response was able to swiftly contain the threat before it could advance further along the attack lifecycle, minimizing disruption and preventing the attack from potentially escalating into a more severe compromise.

Credit to Keanna Grelicha (Cyber Analyst) and Tara Gould (Threat Research Lead)

Appendices

Darktrace Model Detections

NETWORK Models:

· Compromise / High Priority Crypto Currency Mining (Enhanced Monitoring Model)

· Device / Initial Attack Chain Activity (Enhanced Monitoring Model)

· Compromise / Suspicious HTTP and Anomalous Activity (Enhanced Monitoring Model)

· Compromise / Monero Mining

· Anomalous File / Script from Rare External Location

· Device / New PowerShell User Agent

· Anomalous Connection / New User Agent to IP Without Hostname

· Anomalous Connection / Powershell to Rare External

· Device / Suspicious Domain

Cyber AI Analyst Incident Events:

· Detect \ Event \ Possible HTTP Command and Control

· Detect \ Event \ Cryptocurrency Mining Activity

Autonomous Response Models:

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

· Antigena / Network::External Threat::Antigena Suspicious Activity Block

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

· Antigena / Network::External Threat::Antigena Crypto Currency Mining Block

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

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

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

List of Indicators of Compromise (IoCs)

(IoC - Type - Description + Confidence)

· 45.141.87[.]195:8000/infect.ps1 - IP Address, Destination Port, Script - Malicious PowerShell script

· gulf.moneroocean[.]stream - Hostname - Monero Endpoint

· monerooceans[.]stream - Hostname - Monero Endpoint

· 152.53.121[.]6:10001 - IP Address, Destination Port - Monero Endpoint

· 152.53.121[.]6 - IP Address – Monero Endpoint

· https://api[.]chimera-hosting[.]zip/frfnhis/zdpaGgLMav/nbminer[.]exe – Hostname, Executable File – NBMiner

· Db3534826b4f4dfd9f4a0de78e225ebb – Hash – NBMiner loader

MITRE ATT&CK Mapping

(Tactic – Technique – Sub-Technique)

· Vulnerabilities – RESOURCE DEVELOPMENT – T1588.006 - T1588

· Exploits – RESOURCE DEVELOPMENT – T1588.005 - T1588

· Malware – RESOURCE DEVELOPMENT – T1588.001 - T1588

· Drive-by Compromise – INITIAL ACCESS – T1189

· PowerShell – EXECUTION – T1059.001 - T1059

· Exploitation of Remote Services – LATERAL MOVEMENT – T1210

· Web Protocols – COMMAND AND CONTROL – T1071.001 - T1071

· Application Layer Protocol – COMMAND AND CONTROL – T1071

· Resource Hijacking – IMPACT – T1496

· Obfuscated Files - DEFENSE EVASION - T1027

· Bypass UAC - PRIVILEGE ESCALATION – T1548.002

· Process Injection – PRIVILEGE ESCALATION – T055

· Debugger Evasion – DISCOVERY – T1622

· Logon Autostart Execution – PERSISTENCE – T1547.009

References

[1] https://www.darktrace.com/cyber-ai-glossary/cryptojacking#:~:text=Battery%20drain%20and%20overheating,fee%20to%20%E2%80%9Cmine%20cryptocurrency%E2%80%9D.

[2] https://coinmarketcap.com/

[3] https://www.ibm.com/think/topics/cryptojacking

[4] https://thehackernews.com/2025/07/3500-websites-hijacked-to-secretly-mine.html

[5] https://urlhaus.abuse.ch/url/3589032/

[6] https://www.logpoint.com/en/blog/uncovering-illegitimate-crypto-mining-activity/

[7] https://www.virustotal.com/gui/domain/gulf.moneroocean.stream/detection

[8] https://www.virustotal.com/gui/domain/monerooceans.stream/detection

[9] https://any.run/report/5aa8cd5f8e099bbb15bc63be52a3983b7dd57bb92566feb1a266a65ab5da34dd/351eca83-ef32-4037-a02f-ac85a165d74e

^{The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.}

^{Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein. Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.}

^{Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.}

^{The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content without notice.}

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Inside the SOC

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Associate Principal Analyst & Regional Consultancy Lead

•

March 24, 2026

Carlos Gray

Senior Product Marketing Manager, Email

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Blog

Network

March 26, 2026

Phantom Footprints: Tracking GhostSocks Malware

Why are attackers using residential proxies?

In today's threat landscape, blending in to normal activity is the key to success for attackers and the growing reliance on residential proxies shows a significant shift in how threat actors are attempting to bypass IP detection tools.

The increasing dependency on residential proxies has exposed how prevalent proxy services are and how reliant a diverse range of threat actors are on them. From cybercriminal groups to state‑sponsored actors, the need to bypass IP detection tools is fundamental to the success of these groups. One malware that has quietly become notorious for its ability to avoid anomaly detection is GhostSocks, a malware that turns compromised devices into residential proxies.

What is GhostSocks?

Originally marketed on the Russian underground forum xss[.]is as a Malware‑as‑a‑Service (MaaS), GhostSocks enables threat actors to turn compromised devices into residential proxies, leveraging the victim's internet bandwidth to route malicious traffic through it.

How does Ghostsocks malware work?

The malware offers the threat actor a “clean” IP address, making it look like it is coming from a household user. This enables the bypassing of geographic restrictions and IP detection tools, a perfect tool for avoiding anomaly detection. It wasn’t until 2024, when a partnership was announced with the infamous information stealer Lumma Stealer, that GhostSocks surged into widespread adoption and alluded to who may be the author of the proxy malware.

Written in GoLang, GhostSocks utilizes the SOCKS5 proxy protocol, creating a SOCKS5 connection on infected devices. It uses a relay‑based C2 implementation, where an intermediary server sits in between the real command-and-control (C2) server and the infected device.

How does Ghostsocks malware evade detection?

To further increase evasion, the Ghostsocks malware wraps its SOCKS5 tunnels in TLS encryption, allowing its malicious traffic to blend into normal network traffic.

Early variants of GhostSocks do not implement a persistence mechanism; however, later versions achieve persistence via registry run keys, ensuring sustained proxy operational time [1].

While proxying is its primary purpose, GhostSocks also incorporates backdoor functionality, enabling malicious actors to run arbitrary commands and download and deploy additional malicious payloads. This was evident with the well‑known ransomware group Black Basta, which reportedly used GhostSocks as a way of maintaining long‑term access to victims’ networks [1].

Darktrace’s detection of GhostSocks Malware

Darktrace observed a steady increase in GhostSocks activity across its customer base from late 2025, with its Threat Research team identifying multiple incidents involving the malware. In one notable case from December 2025, Darktrace detected GhostSocks operating alongside Lumma Stealer, reinforcing that the partnership between Lumma and GhostSocks remains active despite recent attempts to disrupt Lumma’s infrastructure.

Darktrace’s first detection of GhostSocks‑related activity came when a device on the network of a customer in the education sector began making connections to an endpoint with a suspicious self‑signed certificate that had never been seen on the network before.

The endpoint in question, 159.89.46[.]92 with the hostname retreaw[.]click, has been flagged by multiple open‑source intelligence (OSINT) sources as being associated with Lumma Stealer’s C2 infrastructure [2], indicating its likely role in the delivery of malicious payloads.

Figure 1: Darktrace’s detection of suspicious SSL connections to retreaw[.]click, indicating an attempted link to Lumma C2 infrastructure.

Less than two minutes later, Darktrace observed the same device downloading the executable (.exe) file “Renewable.exe” from the IP 86.54.24[.]29, which Darktrace recognized as 100% rare for this network.

Figure 2: Darktrace’s detection of a device downloading the unusual executable file “Renewable.exe”.

Both the file MD5 hash and the executable itself have been identified by multiple OSINT vendors as being associated with the GhostSocks malware [3], with the executable likely the backdoor component of the GhostSocks malware, facilitating the distribution of additional malicious payloads [4].

Following this detection, Darktrace’s Autonomous Response capability recommended a blocking action for the device in an early attempt to stop the malicious file download. In this instance, Darktrace was configured in Human Confirmation Mode, meaning the customer’s security team was required to manually apply any mitigative response actions. Had Autonomous Response been fully enabled at the time of the attack, the connections to 86.54.24[.]29 would have been blocked, rendering the malware ineffective at reaching its C2 infrastructure and halting any further malicious communication.

Figure 3: Darktrace’s Autonomous Response capability suggesting blocking the suspicious connections to the unusual endpoint from which the malicious executable was downloaded.

As the attack was able to progress, two days later the device was detected downloading additional payloads from the endpoint www.lbfs[.]site (23.106.58[.]48), including “Setup.exe”, “,.exe”, and “/vp6c63yoz.exe”.

Figure 4: Darktrace’s detection of a malicious payload being downloaded from the endpoint www.lbfs[.]site.

Once again, Darktrace recognized the anomalous nature of these downloads and suggested that a “group pattern of life” be enforced on the offending device in an attempt to contain the activity. By enforcing a pattern of life on a device, Darktrace restricts its activity to connections and behaviors similar to those performed by peer devices within the same group, while still allowing it to carry out its expected activity, effectively preventing deviations indicative of compromise while minimizing disruption. As mentioned earlier, these mitigative actions required manual implementation, so the activity was able to continue. Darktrace proceeded to suggest further actions to contain subsequent malicious downloads, including an attempt to block all outbound traffic to stop the attack from progressing.

Figure 5: An overview of download activity and the Autonomous Response actions recommended by Darktrace to block the downloads.

Around the same time, a third executable download was detected, this time from the hostname hxxp[://]d2ihv8ymzp14lr.cloudfront.net/2021-08-19/udppump[.]exe, along with the file “udppump.exe”.While GhostSocks may have been present only to facilitate the delivery of additional payloads, there is no indication that these CloudFront endpoints or files are functionally linked to GhostSocks. Rather, the evidence points to broader malicious file‑download activity.

Shortly after the multiple executable files had been downloaded, Darktrace observed the device initiating a series of repeated successful connections to several rare external endpoints, behavior consistent with early-stage C2 beaconing activity.

Cyber AI Analyst’s investigation

Figure 7: Darktrace’s detection of additional malicious file downloads from malicious CloudFront endpoints.

Throughout the course of this attack, Darktrace’s Cyber AI Analyst carried out its own autonomous investigation, piecing together seemingly separate events into one wider incident encompassing the first suspicious downloads beginning on December 4, the unusual connectivity to many suspicious IPs that followed, and the successful beaconing activity observed two days later. By analyzing these events in real-time and viewing them as part of the bigger picture, Cyber AI Analyst was able to construct an in‑depth breakdown of the attack to aid the customer’s investigation and remediation efforts.

Figure 8: Cyber AI Analyst investigation detailing the sequence of events on the compromised device, highlighting its extensive connectivity to rare endpoints, the related malicious file‑download activity, and finally the emergence of C2 beaconing behavior.

Conclusion

The versatility offered by GhostSocks is far from new, but its ability to convert compromised devices into residential proxy nodes, while enabling long‑term, covert network access—illustrates how threat actors continue to maximise the value of their victims’ infrastructure. Its growing popularity, coupled with its ongoing partnership with Lumma, demonstrates that infrastructure takedowns alone are insufficient; as long as threat actors remain committed to maintaining anonymity and can rapidly rebuild their ecosystems, related malware activity is likely to persist in some form.

Credit to Isabel Evans (Cyber Analyst), Gernice Lee (Associate Principal Analyst & Regional Consultancy Lead – APJ)
Edited by Ryan Traill (Content Manager)

Appendices

References

1. https://bloo.io/research/malware/ghostsocks

2. https://www.virustotal.com/gui/domain/retreaw.click/community

3. https://synthient.com/blog/ghostsocks-from-initial-access-to-residential-proxy

4. https://www.joesandbox.com/analysis/1810568/0/html

5. https://www.virustotal.com/gui/url/fab6525bf6e77249b74736cb74501a9491109dc7950688b3ae898354eb920413

Darktrace Model Detections

Real-time Detection Models

Anomalous Connection / Suspicious Self-Signed SSL

Anomalous Connection / Rare External SSL Self-Signed

Anomalous File / EXE from Rare External Location

Anomalous File / Multiple EXE from Rare External Locations

Compromise / Possible Fast Flux C2 Activity

Compromise / Large Number of Suspicious Successful Connections

Compromise / Large Number of Suspicious Failed Connections

Compromise / Sustained SSL or HTTP Increase

Autonomous Response Models

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

Antigena / Network / External Threat / Antigena Suspicious File Block

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

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

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

Antigena / Network / External Threat / Antigena Suspicious Activity Block

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

Resource Development – T1588 - Malware

Initial Access - T1189 - Drive-by Compromise

Persistence – T1112 – Modify Registry

Command and Control – T1071 – Application Layer Protocol

Command and Control – T1095 – Non-application Layer Protocol

Command and Control – T1071 – Web Protocols

Command and Control – T1571 – Non-Standard Port

Command and Control – T1102 – One-Way Communication

List of Indicators of Compromise (IoCs)

86.54.24[.]29 - IP - Likely GhostSocks C2

http[://]86.54.24[.]29/Renewable[.]exe - Hostname - GhostSocks Distribution Endpoint

http[://]d2ihv8ymzp14lr.cloudfront[.]net/2021-08-19/udppump[.]exe - CDN - Payload Distribution Endpoint

www.lbfs[.]site - Hostname - Likely C2 Endpoint

retreaw[.]click - Hostname - Lumma C2 Endpoint

alltipi[.]com - Hostname - Possible C2 Endpoint

w2.bruggebogeyed[.]site - Hostname - Possible C2 Endpoint

9b90c62299d4bed2e0752e2e1fc777ac50308534 - SHA1 file hash – Likely GhostSocks payload

3d9d7a7905e46a3e39a45405cb010c1baa735f9e - SHA1 file hash - Likely follow-up payload

10f928e00a1ed0181992a1e4771673566a02f4e3 - SHA1 file hash - Likely follow-up payload

About the author

Gernice Lee

Associate Principal Analyst & Regional Consultancy Lead

Blog

Email

March 24, 2026

Darktrace Unites Human Behavior and Threat Detection Across Email, Slack, Teams, and Zoom

Photo of office workers collaborating at a laptop

The communication attack surface is expanding

Modern attackers no longer focus solely on inboxes, they target people and the productivity systems where work actually happens. Meanwhile, the boundary between internal and external usage of tools is becoming blurrier everyday – turning the entire workplace into the attack surface. In 2025, identity compromise emerged as the single most consistent threat across the global threat landscape, as observed by Darktrace research across our entire customer base. Over 70% of incidents in the US involved SaaS/M365 account compromise and phishing or email-based social engineering, making credential abuse the single most effective initial access vector.

Despite this upward trend, investment in existing security awareness training (SAT) isn’t moving the needle on reducing risk. 84% of organizations still measure success through completion rates¹, even though completion of standard training correlates with less than 2% real improvement in risky behavior.² By prioritizing completion, organizations reward time spent rather than meaningful engagement, yet time in training doesn’t translate to retention or real-world decision-making. This compliance-first approach has left the workforce unprepared for the threats they actually face.

At the same time, attacks have evolved. Highly personalized, AI-generated campaigns now move fluidly across email, Slack, Teams, Zoom, and beyond, blending channels and even targeting systems directly through techniques like prompt injection. This new reality demands a different approach: one that treats people and the tools they use as a single ecosystem, where behavior and detection continuously inform and strengthen each other.

Only an adaptive communication security system can keep pace with the speed, creativity, and cross channel nature of today’s threats. 

Ushering in the adaptive era of workplace security

With this release, Darktrace brings together our new behavior-driven training solution with email detection, cross-channel visibility, and platform-level insights. Powered by Self-Learning AI, it delivers protection across both people and the communication tools they rely on every day, including email, Slack, Teams, and Zoom.

Each component learns from the others – training adapts to real user behavior, detection evolves across channels, and response is continuously refined – creating a powerful feedback loop that strengthens resilience and improves accuracy against today’s AI-driven threats.

Introducing: Unified training and email security for a self-improving email defense

Our brand new product, Darktrace / Adaptive Human Defense, closes the gap between human behavior and email security to continuously strengthen both people and defenses. Each user receives personalized training that adapts to their own inbox activity and skill level, with learning delivered directly within the flow of their day-to-day email interactions.

By learning from each user’s interactions with security training, it adapts security responses, creating a closed-loop system where training reinforces detection and detection informs training. Let’s look at some of the benefits.

Reduce successful phishing at the source with contextual Just in Time coaching: Contextual coaching appears directly in real email threads the moment risky behavior is detected, so habits change where mistakes actually happen. Configurable triggers and group policies target the right users, reducing repeated errors and administrative overhead.
Adaptive phishing simulations that progress automatically with each user: Embedded simulations vary in their degree of realism, from generic phishing to generative AI-enabled spear phishing. Users progress through the difficulty levels based on their performance to give an accurate picture of their phishing preparedness.
Native email security integration turns human behavior into quantified risk: The native email security integration allows engagement, links clicked, and question success signals to flow back into / EMAIL recipes and models, so detection and response adapt automatically as users learn.
Actionable risk and trend analytics beyond completion rates: Analytics that surface repeat offenders, high-value targets, and measurable exposure, moving beyond completion metrics to give leaders actionable insights tied to real behavior.

Learn more about / Adaptive Human Defense in the product solution brief.

Industry-first cross-channel full-message analysis for email, Slack, Teams, and Zoom

Darktrace now brings full-message analysis to Email, Slack, Teams, Zoom, and even generative AI prompts. The same leading behavioral analysis from EMAIL extends to every message, tracing intent, tone, relationships, and conversation flow across all communication activity for a complete understanding of every user interaction.

By correlating messaging and collaboration activity with email and account environments, cross-channel analysis reveals multi-domain attack paths and follows both users and threats as a single, continuous narrative – delivering better context to improve detection across the entire organization.

Eliminate cross-channel blind spots: Detect phishing, malware, account takeovers, and conversational manipulation across email and collaboration platforms, so attackers can’t exploit Slack, Teams, or Zoom as a new entry point. Unified behavioral analysis gives security teams a coherent, single view, for no more fragmented, channel-specific gaps.
Spot generative AI prompt injection attacks before they manipulate assistants: Dedicated models surface threats targeting corporate AI assistants – like ShadowLeak and Hashjack – before they can silently manipulate workflows, reducing risk before static filters catch up.

Learn more about Darktrace’s messaging security offering in the product solution brief.

Industry-first DMARC with bi-directional ASM and email security integration

Darktrace transforms domain protection by linking DMARC, attack surface intelligence, and email security into a single, continuously evolving workflow. Instead of treating domain authentication and exposure as separate tasks, this unified approach shows not just where domains are vulnerable, but how attackers are actively exploiting them.

Fix authentication weaknesses faster: SPF, DKIM, DMARC configurations, and external exposure data are analyzed together, giving teams clear guidance to correct weaknesses before they can be abused. Deep bidirectional integration with attack surface intelligence reduces impersonation risk at the source.
Accelerate email investigations: DMARC context is embedded directly into email workflows, enriching triage with authentication posture, internal/external sender lists, and seamless pivots between email and domain intelligence for faster, more accurate investigations.

Committed to innovation

These updates are part of a broader Darktrace release, which also includes:

Innovations in cloud security with continuous Kubernetes posture management, as well as native integrations with Proactive Exposure Management (PEM) and Attack Surface Management (ASM).
Innovations to Darktrace / Forensic Acquisition & Investigation, including faster cloud incident investigations, automated and on-demand forensic data capture across hybrid environments, and open forensic coverage for third-party endpoint and XDR ecosystems.
Introduction of a new Alerts Dashboard in the ActiveAI Security Portal, enabling unified alert triage, AI-driven incident correlation, and coordinated investigations across multiple deployments to reduce response times and operational complexity.‍
Innovations in OT security, including Operational Overview Architecture diagrams, Operational Overview reporting, expanded ICS & IoMT device classification, and expanded OT & IIoT Protocol Coverage.
Further updates to / NETWORK, / ENDPOINT, Cyber AI Analyst, and cross-platform products.

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Join our Live Launch Event on April 14, 2026.

Join us for an exclusive announcement event where Darktrace, the leader in AI-native cybersecurity, will be announcing our latest innovations, including  a demo of our new product / Adaptive Human Defense, an exclusive conversation with a Darktrace customer, and a deep dive into the Darktrace ActiveAI Security Portal.

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‍References

[1] 84% of organizations still measure security awareness training success through completion rates, a vanity metric with no correlation to behavior change. (Source: NIST Awareness Effectiveness Study, Forrester 2025)

[2] 'Limited benefit from embedded phishing training. Using randomized controlled trials and statistical modeling, embedded training provides a statistically-significant reduction in average failure rate, but of only 2%.' Ho, G., Mirian, A., Luo, E., Tong, K., Lee, E., Liu, L., Longhurst, C. A., Dameff, C., Savage, S., & Voelker, G. M. (2025). Understanding the Efficacy of Phishing Training in Practice. Proceedings of the 2025 IEEE Symposium on Security and Privacy.

About the author

Carlos Gray

Senior Product Marketing Manager, Email

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