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May 28, 2024

Stemming the Citrix Bleed Vulnerability with Darktrace’s ActiveAI Security Platform

This blog delves into Darktrace’s investigation into the exploitation of the Citrix Bleed vulnerability on the network of a customer in late 2023. Darktrace’s Self-Learning AI ensured the customer was well equipped to track the post-compromise activity and identify affected devices.
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
Vivek Rajan
Cyber Analyst
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28
May 2024

What is Citrix Bleed?

Since August 2023, cyber threat actors have been actively exploiting one of the most significant critical vulnerabilities disclosed in recent years: Citrix Bleed. Citrix Bleed, also known as CVE-2023-4966, remained undiscovered and even unpatched for several months, resulting in a wide range of security incidents across business and government sectors [1].

How does Citrix Bleed vulnerability work?

The vulnerability, which impacts the Citrix Netscaler Gateway and Netscaler ADC products, allows for outside parties to hijack legitimate user sessions, thereby bypassing password and multifactor authentication (MFA) requirements.

When used as a means of initial network access, the vulnerability has resulted in the exfiltration of sensitive data, as in the case of Xfinity, and even the deployment of ransomware variants including Lockbit [2]. Although Citrix has released a patch to address the vulnerability, slow patching procedures and the widespread use of these products has resulted in the continuing exploitation of Citrix Bleed into 2024 [3].

How Does Darktrace Handle Citrix Bleed?

Darktrace has demonstrated its proficiency in handling the exploitation of Citrix Bleed since it was disclosed back in 2023; its anomaly-based approach allows it to efficiently identify and inhibit post-exploitation activity as soon as it surfaces.  Rather than relying upon traditional rules and signatures, Darktrace’s Self-Learning AI enables it to understand the subtle deviations in a device’s behavior that would indicate an emerging compromise, thus allowing it to detect anomalous activity related to the exploitation of Citrix Bleed.

In late 2023, Darktrace identified an instance of Citrix Bleed exploitation on a customer network. As this customer had subscribed to the Proactive Threat Notification (PTN) service, the suspicious network activity surrounding the compromise was escalated to Darktrace’s Security Operation Center (SOC) for triage and investigation by Darktrace Analysts, who then alerted the customer’s security team to the incident.

Darktrace’s Coverage

Initial Access and Beaconing of Citrix Bleed

Darktrace’s initial detection of indicators of compromise (IoCs) associated with the exploitation of Citrix Bleed actually came a few days prior to the SOC alert, with unusual external connectivity observed from a critical server. The suspicious connection in question, a SSH connection to the rare external IP 168.100.9[.]137, lasted several hours and utilized the Windows PuTTY client. Darktrace also identified an additional suspicious IP, namely 45.134.26[.]2, attempting to contact the server. Both rare endpoints had been linked with the exploitation of the Citrix Bleed vulnerability by multiple open-source intelligence (OSINT) vendors [4] [5].

Darktrace model alert highlighting an affected device making an unusual SSH connection to 168.100.9[.]137 via port 22.
Figure 1: Darktrace model alert highlighting an affected device making an unusual SSH connection to 168.100.9[.]137 via port 22.

As Darktrace is designed to identify network-level anomalies, rather than monitor edge infrastructure, the initial exploitation via the typical HTTP buffer overflow associated with this vulnerability fell outside the scope of Darktrace’s visibility. However, the aforementioned suspicious connectivity likely constituted initial access and beaconing activity following the successful exploitation of Citrix Bleed.

Command and Control (C2) and Payload Download

Around the same time, Darktrace also detected other devices on the customer’s network conducting external connectivity to various endpoints associated with remote management and IT services, including Action1, ScreenConnect and Fixme IT. Additionally, Darktrace observed devices downloading suspicious executable files, including “tniwinagent.exe”, which is associated with the tool Total Network Inventory. While this tool is typically used for auditing and inventory management purposes, it could also be leveraged by attackers for the purpose of lateral movement.

Defense Evasion

In the days surrounding this compromise, Darktrace observed multiple devices engaging in potential defense evasion tactics using the ScreenConnect and Fixme IT services. Although ScreenConnect is a legitimate remote management tool, it has also been used by threat actors to carry out C2 communication [6]. ScreenConnect itself was the subject of a separate critical vulnerability which Darktrace investigated in early 2024. Meanwhile, CISA observed that domains associated with Fixme It (“fixme[.]it”) have been used by threat actors attempting to exploit the Citrix Bleed vulnerability [7].

Reconnaissance and Lateral Movement

A few days after the detection of the initial beaconing communication, Darktrace identified several devices on the customer’s network carrying out reconnaissance and lateral movement activity. This included SMB writes of “PSEXESVC.exe”, network scanning, DCE-RPC binds of numerous internal devices to IPC$ shares and the transfer of compromise-related tools. It was at this point that Darktrace’s Self-Learning AI deemed the activity to be likely indicative of an ongoing compromise and several Enhanced Monitoring models alerted, triggering the aforementioned PTNs and investigation by Darktrace’s SOC.

Darktrace observed a server on the network initiating a wide range of connections to more than 600 internal IPs across several critical ports, suggesting port scanning, as well as conducting unexpected DCE-RPC service control (svcctl) activity on multiple internal devices, amongst them domain controllers. Additionally, several binds to server service (srvsvc) and security account manager (samr) endpoints via IPC$ shares on destination devices were detected, indicating further reconnaissance activity. The querying of these endpoints was also observed through RPC commands to enumerate services running on the device, as well as Security Account Manager (SAM) accounts.  

Darktrace also identified devices performing SMB writes of the WinRAR data compression tool, in what likely represented preparation for the compression of data prior to data exfiltration. Further SMB file writes were observed around this time including PSEXESVC.exe, which was ultimately used by attackers to conduct remote code execution, and one device was observed making widespread failed NTLM authentication attempts on the network, indicating NTLM brute-forcing. Darktrace observed several devices using administrative credentials to carry out the above activity.

In addition to the transfer of tools and executables via SMB, Darktrace also identified numerous devices deleting files through SMB around this time. In one example, an MSI file associated with the patch management and remediation service, Action1, was deleted by an attacker. This legitimate security tool, if leveraged by attackers, could be used to uncover additional vulnerabilities on target networks.

A server on the customer’s network was also observed writing the file “m.exe” to multiple internal devices. OSINT investigation into the executable indicated that it could be a malicious tool used to prevent antivirus programs from launching or running on a network [8].

Impact and Data Exfiltration

Following the initial steps of the breach chain, Darktrace observed numerous devices on the customer’s network engaging in data exfiltration and impact events, resulting in additional PTN alerts and a SOC investigation into data egress. Specifically, two servers on the network proceeded to read and download large volumes of data via SMB from multiple internal devices over the course of a few hours. These hosts sent large outbound volumes of data to MEGA file storage sites using TLS/SSL over port 443. Darktrace also identified the use of additional file storage services during this exfiltration event, including 4sync, file[.]io, and easyupload[.]io. In total the threat actor exfiltrated over 8.5 GB of data from the customer’s network.

Darktrace Cyber AI Analyst investigation highlighting the details of a data exfiltration attempt.
Figure 2: Darktrace Cyber AI Analyst investigation highlighting the details of a data exfiltration attempt.

Finally, Darktrace detected a user account within the customer’s Software-as-a-Service (SaaS) environment conducting several suspicious Office365 and AzureAD actions from a rare IP for the network, including uncommon file reads, creations and the deletion of a large number of files.

Unfortunately for the customer in this case, Darktrace RESPOND™ was not enabled on the network and the post-exploitation activity was able to progress until the customer was made aware of the attack by Darktrace’s SOC team. Had RESPOND been active and configured in autonomous response mode at the time of the attack, it would have been able to promptly contain the post-exploitation activity by blocking external connections, shutting down any C2 activity and preventing the download of suspicious files, blocking incoming traffic, and enforcing a learned ‘pattern of life’ on offending devices.

Conclusion

Given the widespread use of Netscaler Gateway and Netscaler ADC, Citrix Bleed remains an impactful and potentially disruptive vulnerability that will likely continue to affect organizations who fail to address affected assets. In this instance, Darktrace demonstrated its ability to track and inhibit malicious activity stemming from Citrix Bleed exploitation, enabling the customer to identify affected devices and enact their own remediation.

Darktrace’s anomaly-based approach to threat detection allows it to identify such post-exploitation activity resulting from the exploitation of a vulnerability, regardless of whether it is a known CVE or a zero-day threat. Unlike traditional security tools that rely on existing threat intelligence and rules and signatures, Darktrace’s ability to identify the subtle deviations in a compromised device’s behavior gives it a unique advantage when it comes to identifying emerging threats.

Credit to Vivek Rajan, Cyber Analyst, Adam Potter, Cyber Analyst

Appendices

Darktrace Model Coverage

Device / Suspicious SMB Scanning Activity

Device / ICMP Address Scan

Device / Possible SMB/NTLM Reconnaissance

Device / Network Scan

Device / SMB Lateral Movement

Device / Possible SMB/NTLM Brute Force

Device / Suspicious Network Scan Activity

User / New Admin Credentials on Server

Anomalous File / Internal::Unusual Internal EXE File Transfer

Compliance / SMB Drive Write

Device / New or Unusual Remote Command Execution

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / Rare WinRM Incoming

Anomalous Connection / Unusual Admin SMB Session

Device / Unauthorised Device

User / New Admin Credentials on Server

Anomalous Server Activity / Outgoing from Server

Device / Long Agent Connection to New Endpoint

Anomalous Connection / Multiple Connections to New External TCP Port

Device / New or Uncommon SMB Named Pipe

Device / Multiple Lateral Movement Model Breaches

Device / Large Number of Model Breaches

Compliance / Remote Management Tool On Server

Device / Anomalous RDP Followed By Multiple Model Breaches

Device / SMB Session Brute Force (Admin)

Device / New User Agent

Compromise / Large Number of Suspicious Failed Connections

Unusual Activity / Unusual External Data Transfer

Unusual Activity / Enhanced Unusual External Data Transfer

Device / Increased External Connectivity

Unusual Activity / Unusual External Data to New Endpoints

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Uncommon 1 GiB Outbound

Anomalous Connection / Active Remote Desktop Tunnel

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Compliance / Possible Unencrypted Password File On Server

Anomalous Connection / Suspicious Read Write Ratio and Rare External

Device / Reverse DNS Sweep]

Unusual Activity / Possible RPC Recon Activity

Anomalous File / Internal::Executable Uploaded to DC

Compliance / SMB Version 1 Usage

Darktrace AI Analyst Incidents

Scanning of Multiple Devices

Suspicious Remote Service Control Activity

SMB Writes of Suspicious Files to Multiple Devices

Possible SSL Command and Control to Multiple Devices

Extensive Suspicious DCE-RPC Activity

Suspicious DCE-RPC Activity

Internal Downloads and External Uploads

Unusual External Data Transfer

Unusual External Data Transfer to Multiple Related Endpoints

MITRE ATT&CK Mapping

Technique – Tactic – ID – Sub technique of

Network Scanning – Reconnaissance - T1595 - T1595.002

Valid Accounts – Defense Evasion, Persistence, Privilege Escalation, Initial Access – T1078 – N/A

Remote Access Software – Command and Control – T1219 – N/A

Lateral Tool Transfer – Lateral Movement – T1570 – N/A

Data Transfers – Exfiltration – T1567 – T1567.002

Compressed Data – Exfiltration – T1030 – N/A

NTLM Brute Force – Brute Force – T1110 - T1110.001

AntiVirus Deflection – T1553 - NA

Ingress Tool Transfer   - COMMAND AND CONTROL - T1105 - NA

Indicators of Compromise (IoCs)

204.155.149[.]37 – IP – Possible Malicious Endpoint

199.80.53[.]177 – IP – Possible Malicious Endpoint

168.100.9[.]137 – IP – Malicious Endpoint

45.134.26[.]2 – IP – Malicious Endpoint

13.35.147[.]18 – IP – Likely Malicious Endpoint

13.248.193[.]251 – IP – Possible Malicious Endpoint

76.223.1[.]166 – IP – Possible Malicious Endpoint

179.60.147[.]10 – IP – Likely Malicious Endpoint

185.220.101[.]25 – IP – Likely Malicious Endpoint

141.255.167[.]250 – IP – Malicious Endpoint

106.71.177[.]68 – IP – Possible Malicious Endpoint

cat2.hbwrapper[.]com – Hostname – Likely Malicious Endpoint

aj1090[.]online – Hostname – Likely Malicious Endpoint

dc535[.]4sync[.]com – Hostname – Likely Malicious Endpoint

204.155.149[.]140 – IP - Likely Malicious Endpoint

204.155.149[.]132 – IP - Likely Malicious Endpoint

204.155.145[.]52 – IP - Likely Malicious Endpoint

204.155.145[.]49 – IP - Likely Malicious Endpoint

References

  1. https://www.axios.com/2024/01/02/citrix-bleed-security-hacks-impact
  2. https://www.csoonline.com/article/1267774/hackers-steal-data-from-millions-of-xfinity-customers-via-citrix-bleed-vulnerability.html
  3. https://www.cybersecuritydive.com/news/citrixbleed-security-critical-vulnerability/702505/
  4. https://www.virustotal.com/gui/ip-address/168.100.9.137
  5. https://www.virustotal.com/gui/ip-address/45.134.26.2
  6. https://www.trendmicro.com/en_us/research/24/b/threat-actor-groups-including-black-basta-are-exploiting-recent-.html
  7. https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-325a
  8. https://www.file.net/process/m.exe.html
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
Vivek Rajan
Cyber Analyst

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May 19, 2026

State of AI Cybersecurity 2026: 77% of security stacks include AI, but trust is lagging

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Findings in this blog are taken from Darktrace’s annual State of AI Cybersecurity Report 2026.

AI is a contributing member of nearly every modern cybersecurity team. As we discussed earlier in this blog series, rapid AI adoption is expanding the attack surface in ways that security professionals have never before experienced while also empowering attackers to operate at unprecedented speed and scale. It’s only logical that defenders are harnessing the power of AI to fight back.

After all, AI can help cybersecurity teams spot the subtle signs of novel threats before humans can, investigate events more quickly and thoroughly, and automate response. But although AI has been widely adopted, this technology is also frequently misunderstood, and occasionally viewed with suspicion.

For CISOs, the cybersecurity marketplace can be noisy. Making sense of competing vendors’ claims to distinguish the solutions that truly deliver on AI’s full potential from those that do not isn’t always easy. Without a nuanced understanding of the different types of AI used across the cybersecurity stack, it is difficult to make informed decisions about which vendors to work with or how to gain the most value from their solutions. Many security leaders are turning to Managed Security Service Providers (MSSPs) for guidance and support.

The right kinds of AI in the right places?

Back in 2024, when we first conducted this annual survey, more than a quarter of respondents were only vaguely familiar with generative AI or hadn’t heard of it at all. Today, GenAI plays a role in 77% of security stacks. This percentage marks a rapid increase in both awareness and adoption over a relatively short period of time.

According to security professionals, different types of AI are widely integrated into cybersecurity tooling:

  • 67% report that their organization’s security stack uses supervised machine learning
  • 67% report that theirs uses agentic AI
  • 58% report that theirs uses natural language processing (NLP)
  • 35% report that theirs uses unsupervised machine learning

But their responses suggest that organizations aren’t always using the most valuable types of AI for the most relevant use cases.

Despite all the recent attention AI has gotten, supervised machine learning isn’t new. Cybersecurity vendors have been experimenting with models trained on hand-labeled datasets for over a decade. These systems are fed large numbers of examples of malicious activity – for instance, strains of ransomware – and use these examples to generalize common indicators of maliciousness – such as the TTPs of multiple known ransomware strains – so that the models can identify similar attacks in the future. This approach is more effective than signature-based detection, since it isn’t tied to an individual byte sequence or file hash. However, supervised machine learning models can miss patterns or features outside the training data set. When adversarial behavior shifts, these systems can’t easily pivot.

Unsupervised machine learning, by contrast, can identify key patterns and trends in unlabeled data without human input. This enables it to classify information independently and detect anomalies without needing to be taught about past threats. Unsupervised learning can continuously learn about an environment and adapt in real time.

One key distinction between supervised and unsupervised machine learning is that supervised learning algorithms require periodic updating and re-training, whereas unsupervised machine learning trains itself while it works.

The question of trust

Even as AI moves into the mainstream, security professionals are eyeing it with a mix of enthusiasm and caution. Although 89% say they have good visibility into the reasoning behind AI-generated outputs, 74% are limiting AI’s ability to take autonomous action in their SOC until explainability improves. 86% do not allow AI to take even small remediation actions without human oversight.

This model, commonly known as “human in the loop,” is currently the norm across the industry. It seems like a best-of-both-worlds approach that allows teams to experience the benefits of AI-accelerated response without relinquishing control – or needing to trust an AI system.

Keeping humans somewhat in the loop is essential for getting the best out of AI. Analysts will always need to review alerts, make judgement calls, and set guardrails for AI's behavior. Their input helps AI models better understand what “normal” looks like, improving their accuracy over time.

However, relying on human confirmation has real costs – it delays response, increases the cognitive burden analysts must bear, and creates potential coverage gaps when security teams are overwhelmed or unavailable. The traditional model, in which humans monitor and act on every alert, is no longer workable at scale.

If organizations depend too heavily on in-the-loop humans, they risk recreating the very problem AI is meant to solve: backlogs of alerts waiting for analyst review. Removing the human from the loop can buy back valuable time, which analysts can then invest in building a proactive security posture. They can also focus more closely on the most critical incidents, where human attention is truly needed.

Allowing AI to operate autonomously requires trust in its decision-making. This trust can be built gradually over time, with autonomous operations expanding as trust grows. But it also requires knowledge and understanding of AI — what it is, how it works, and how best to deploy it at enterprise scale.

Looking for help in all the right places

To gain access to these capabilities in a way that’s efficient and scalable, growing numbers of security leaders are looking for outsourced support. In fact, 85% of security professionals prefer to obtain new SOC capabilities in the form of a managed service.

This makes sense: Managed Security Service Providers (MSSPs) can deliver deep, continuously available expertise without the cost and complexity of building an in-house team. Outsourcing also allows organizations to scale security coverage up or down as needs change, stay current with evolving threats and regulatory requirements, and leverage AI-native detection and response without needing to manage the AI tools themselves.

Preferences for MSSP-delivered security operations are particularly strong in the education, energy (87%), and healthcare sectors. This makes sense: all are high-value targets for threat actors, and all tend to have limited cybersecurity budgets, so the need for a partner who can deliver affordable access to expertise at scale is strong. Retailers also voiced a strong preference for MSSP-delivered services. These companies are tasked with managing large volumes of consumer personal and financial data, and with transforming an industry traditionally thought of as a late adopter to a vanguard of cyber defense. Technology companies, too, have a marked preference for SOC capabilities delivered by MSSPs. This may simply be because they understand the complexity of the threat landscape – and the advantages of specialized expertise — so well.

In order to help as many organizations as possible – from major enterprises to small and midmarket companies – benefit from enterprise-grade, AI-native security, Darktrace is making it easier for MSSPs to deliver its technology. The ActiveAI Security Portal introduces an alert dashboard designed to increase the speed and efficiency of alert triage, while a new AI-powered managed email security solution is giving MSSPs an edge in the never-ending fight against advanced phishing attacks – helping partners as well as organizations succeed on the frontlines of cyber defense.

Explore the full State of AI Cybersecurity 2026 report for deeper insights into how security leaders are responding to AI-driven risks.

Learn more about securing AI in your enterprise.

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May 19, 2026

When Open Source Is Weaponized: Analysis of a Trojanized 7 Zip Installer

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Background of the malicious 7-Zip installer, and assessing its Impact

Early in 2026, external researchers disclosed a malicious distribution campaign leveraging a trojanized installer masquerading itself as a legitimate 7‑Zip utility. Evidence suggests the campaign was active as of January 2026, during which victims were served a fake installer from 7zip[.]com, a highly convincing typo-squatted domain impersonating the official 7‑Zip distribution site (7-zip[.]org).

Initial access is typically achieved through social engineering and search‑engine abuse, including YouTube tutorial content that explicitly referenced the impersonated domain as the download source. Notably, several reports observed the installer delivered a modified but functional build of 7‑Zip (7zfm.exe) to reduce suspicion and preserve expected user behavior.

However, the installer also dropped additional payloads, such as Uphero.exe, hero.exe, and hero.dll, which are not part of the legitimate 7‑Zip software package. Once installed and executed, these payloads allow the attacker to establish persistence and configure the infected host as a proxy node under their control. This facilitates malicious activities such as traffic relaying, anonymizing infrastructure, and the delivery of secondary payloads [1] [2].

Overall, this attack illustrates a proxyware-style attack that abuses implicit trust in widely deployed third‑party tools while exploiting unconventional delivery vectors such as instructional media. By closely imitating legitimate software behavior and branding, the threat actors significantly reduced user suspicion and increased the likelihood of widespread, undetected compromise.

Threat overview

Darktrace observed multiple customers affected by the malicious 7‑Zip installer between January 12 and January 22, impacting organizations across the Americas (AMS), Asia‑Pacific & Japan (APJ), and Europe, the Middle East, and Africa (EMEA) regions. The activity targeted customers across various sectors, including Human health and social work activities, Manufacturing, Education, and Information and communication.

The following use case highlights a device on one customer network making external connections associated with malicious 7-Zip update activity observed between  January 7 and January 18, 2026.  This behavior included connectivity to the malicious domain 7zip[.]com, followed by command-and control (C2) activity involving "smshero"-themed domains, as well as outbound proxy connections over ports 1000 and 1002.  

Initial Connectivity to 'update[.]7zip[.]com':

Initial Beaconing to Young Endpoint alert behavior, involving the known tunnel/proxy endpoint ‘79.127.221[.]47’.
Figure 1: Initial Beaconing to Young Endpoint alert behavior, involving the known tunnel/proxy endpoint ‘79.127.221[.]47’.

Starting on January 7, Darktrace / NETWORK detected the device making repeated beaconing connections to the endpoint 79.127.221[.]47 over the destination port 1000. The use of this port aligns with open-source intelligence (OSINT) reporting that hero[.]exe establishes outbound proxy connections via non-standard ports such as 1000 and 1002 [1].

Darktrace observed TLS beaconing alerts to the known trojanized installer, update[.]7zip[.]com · 98.96.229[.]19, over port 443 on January 7th.
Figure 2: Darktrace observed TLS beaconing alerts to the known trojanized installer, update[.]7zip[.]com · 98.96.229[.]19, over port 443 on January 7th.

Later the same day, the device initiated TLS beaconing to the endpoint update.7zip[.]com. This is more than likely a common source of compromise, where victims unknowingly installed a modified build of the tool alongside additional malicious components. The campaign then progressed into the next attack phase, marked by established connectivity to various C2 domains.

Beaconing Activity to "smshero"-themed domains

Darktrace subsequently observed the same infected device connecting to various C2 domains used to retrieve configuration data. As such, these external hostnames were themed around the string “smshero”, for example ‘smshero[.]co’.

On January 8th, Darktrace observed SSL beaconing to a rare destination which was attributed to a known ‘config/control domain’, nova[.]smshero[.]ai.
Figure 3: On January 8th, Darktrace observed SSL beaconing to a rare destination which was attributed to a known ‘config/control domain’, nova[.]smshero[.]ai.

The following day, on January 8, the device exhibited its first connectivity to a "smshero"-themed endpoint, which has since been identified as being associated with rotating C2 servers [1] [3]. Similar beaconing activity continued over the following days, with Darktrace identifying C2 connectivity to update[.]7zip[.]com over port 443, alongside additional connections to “smshero”‑themed endpoints such as zest.hero-sms[.]ai, flux.smshero[.]cc, and glide.smshero[.]cc between January 9 and January 15.

Darktrace later observed continued beaconing alerts over a 4-day interval to additional rare destinations attributed to a known ‘config/control domain’, zest[.]hero-sms[.]ai & glide[.]smshero[.]cc.
Figure 4: Darktrace later observed continued beaconing alerts over a 4-day interval to additional rare destinations attributed to a known ‘config/control domain’, zest[.]hero-sms[.]ai & glide[.]smshero[.]cc.

Proxied connectivity over destination ports

The primary objective of this campaign is believed to be proxyware, whereby third-party traffic is routed through victim devices to potentially obfuscate malicious activity. Devices were also observed communicating with rare external IPs hosted on Cloudflare and DataCamp Limited ASNs, establishing outbound proxy connections over the non-standard ports 1000 and 1002 [1].

OSINT sources also indicate that connections over these ports leveraged an XOR-encoded protocol (key 0x70) designed to obscure control messages. While the end goal of the campaign remains unclear, residential proxy networks can be abused to evade security rules and facilitate further unauthorized activities, including phishing and malware distribution [1][3].

Specifically, on January 8, Darktrace observed the device engaging in low-and-slow data exfiltration to the IP 79.127.221[.]47, which had first been observed the previous day, over port 1000. Proxyware typically installs an agent that routes third‑party traffic through an end-user’s device, effectively  turning it into a residential proxy exit node. This activity likely represents the system actively communicating outbound data to an entity that controls its behavior.

Figure 5: Darktrace later observed a ‘Low and Slow Exfiltration to IP’ alert, involving the known tunnel/proxy endpoint ‘79.127.221[.]47’.

Similar activity continued between January 10 and January 18, with Darktrace detecting threat actors attempting to exfiltrate significant volumes of data to 79.127.221[.]47 over destination port 1000.

Throughout the course of this incident, Darktrace’s Cyber AI Analyst launched several autonomous investigations, analyzing each anomalous event and ultimately painting a detailed picture of the attack timeline. These investigations correlated multiple incidents based on Darktrace detections observed between January 7 and January 19. Cyber AI Analyst identified anomalous variables such as repeated connections to unusual endpoints involving data uploads and downloads, with particular emphasis on HTTP and SSL connectivity.

Darktrace AI Analyst Coverage, showcasing multiple incident events that occurred on January 7th & 8th, highlighting associated malicious 7-zip behaviors.
Figure 6: Darktrace AI Analyst Coverage, showcasing multiple incident events that occurred on January 7th & 8th, highlighting associated malicious 7-zip behaviors.
Darktrace AI Analyst Endpoint Details from the given ‘Unusual Repeated Connections’ Incident Event, including the known tunnel/proxy endpoint.
Figure 7: Darktrace AI Analyst Endpoint Details from the given ‘Unusual Repeated Connections’ Incident Event, including the known tunnel/proxy endpoint.
 Darktrace AI Analyst Coverage, showcasing additional incident events that occurred on January 12th through 18th, highlighting malicious 7-zip behaviors and SSL connectivity.
Figure 8: Darktrace AI Analyst Coverage, showcasing additional incident events that occurred on January 12th through 18th, highlighting malicious 7-zip behaviors and SSL connectivity.

Darktrace’s Autonomous Response

At several stages throughout the attack, Darktrace implemented Autonomous Response actions to help contain the suspicious activity as soon as it was identified, providing the customer’s security team with additional time to investigate and remediate. Between January 7 and January 18, Darktrace blocked a wide range of malicious activity, including beaconing connections to unusual endpoints, small data exfiltration attempts, and larger egress efforts, ultimately preventing the attacker from progressing through multiple stages of the attack or achieving their objectives.

Darktrace Autonomous Response Action Coverage showcasing connection block connection events including various endpoints that occurred on January 7th.
Figure 9: Darktrace Autonomous Response Action Coverage showcasing connection block connection events including various endpoints that occurred on January 7th.
Darktrace Antigena (Autonomous Response) Model Alert Coverage, showcasing a Antigena Suspicious Activity Block alert occurred on January 10th as a result of the Low and Slow Exfiltration to IP model alert.
Figure 10: Darktrace Antigena (Autonomous Response) Model Alert Coverage, showcasing a Antigena Suspicious Activity Block alert occurred on January 10th as a result of the Low and Slow Exfiltration to IP model alert.
Figure 11: Additional Darktrace Antigena (Autonomous Response) Model Alert Coverage, showcasing a Antigena Large Data Volume Outbound Block alert occurred on January 18th as a result of the Uncommon 1 GiB Outbound model alert.

Conclusion

The malicious 7‑Zip installer underscores how attackers continue to weaponize trust in widely used, legitimate software to gain initial access while evading user suspicion. By exploiting familiar and commonly installed services, this type of attack demonstrates that even routine actions, such as installing compression software, can become high‑risk events when defenses or user awareness are insufficient.

This campaign further emphasizes the urgent need for strict software validation and continuous network monitoring. Modern threats no longer rely solely on obscure tools or overtly malicious behavior. Instead, they increasingly blend seamlessly into everyday operations, making detection more challenging.

In this case, Darktrace / NETWORK was able to identify the anomalous activity and Autonomous Response actions in a timely manner, enabling the customer to be quickly notified and providing crucial additional time to investigate further.

In summary, the abuse of a trojanized 7‑Zip installer highlights a concerning shift in modern threat tactics, where trusted and widely deployed tools can serve as primary delivery mechanisms for system compromise. This reality reinforces that proactive detection, continuous monitoring, and strong security awareness are not optional but essential.

Credit to Justin Torres, Senior Cyber Analyst, David Moreira da Silva, Cyber Analyst, Emma Foulger, Global Threat Research Operations Lead.

Edited by Ryan Traill (Content Manager)

Appendices

References

1. https://www.malwarebytes.com/blog/threat-intel/2026/02/fake-7-zip-downloads-are-turning-home-pcs-into-proxy-nodes

2. https://www.tomshardware.com/tech-industry/cyber-security/unofficial-7-zip-com-website-served-up-malware-for-10-days-files-turned-pcs-into-a-proxy-botnet

3. https://blog.lukeacha.com/2026/01/beware-of-fake-7zip-installer-upstage.html

4. https://www.bleepingcomputer.com/news/security/malicious-7-zip-site-distributes-installer-laced-with-proxy-tool/

5. https://customerportal.darktrace.com/guides/antigena-network-model-actions

Darktrace Model Detections

·      Anomalous Connection / Data Sent to Rare Domain

·      Anomalous Connection / Low and Slow Exfiltration to IP

·      Anomalous Connection / Multiple Failed Connections to Rare Endpoint

·      Anomalous Connection / Uncommon 1 GiB Outbound

·      Anomalous Server Activity / Rare External from Server

·      Compromise / Agent Beacon (Long Period)

·      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 / Large Number of Suspicious Failed Connections

·      Compromise / Large Number of Suspicious Successful Connections

·      Compromise / Repeating Connections Over 4 Days

·      Compromise / SSL Beaconing to Rare Destination

·      Compromise / Suspicious TLS Beaconing To Rare External

·      Device / Large Number of Model Alerts

·      Unusual Activity / Unusual External Activity

Cyber AI Analyst Coverage

·      Unusual Repeated Connections

·      Unusual Repeated Connections to Multiple Endpoints

·      Possible HTTP Command and Control

·      Possible HTTP Command and Control to Multiple Endpoints

·      Suspicious Remote Service Control Activity

·      Possible SSL Command and Control to Multiple Endpoints

Indicators of Compromise

IoC - Type - Description + Confidence

·      7zip[.]com – Hostname – C2 Endpoint

·      flux[.]smshero[.]co - Hostname - C2 Endpoint

·      neo[.]herosms[.]co - Hostname - C2 Endpoint

·      nova[.]smshero[.]ai - Hostname - C2 Endpoint

·      zest[.]hero-sms[.]ai -  Hostname - C2 Endpoint

·      soc[.]hero-sms[.]co - Hostname - C2 Endpoint

·      pulse[.]herosms[.]cc - Hostname - C2 Endpoint

·      glide[.]smshero[.]cc - Hostname - C2 Endpoint

·      prime[.]herosms[.]vip - Hostname - C2 Endpoint

·      172.96.115[.]226 - IP Address - C2 Endpoint

·      79.127.221[.]47:1002 – IP Address/Port - Proxy Endpoint

·      84.17.37[.]1:1002 - IP Address/Port - Proxy Endpoint

MITRE ATT&CK Mapping

Technique Name - Tactic - ID - Sub-Technique of

·      Exfiltration Over C2 Channel - EXFILTRATION - T1041

·      Scheduled Transfer - EXFILTRATION - T1029

·      Automated Exfiltration - EXFILTRATION - T1020

·      Data Transfer Size Limits - EXFILTRATION - T1030

·      External Proxy - COMMAND AND CONTROL - T1090.002 - T1090

·      Non-Application Layer Protocol - COMMAND AND CONTROL - T1095

·      Non-Standard Port - COMMAND AND CONTROL - T1571

·      Exfiltration to Cloud Storage - EXFILTRATION - T1567.002 - T1567

·      Exploit Public-Facing Application - INITIAL ACCESS - T1190

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

·      Application Layer Protocol - COMMAND AND CONTROL - T1071

·      Man in the Browser - COLLECTION - T1185

·      Browser Extensions - PERSISTENCE - T1176

·      Encrypted Channel - COMMAND AND CONTROL - T1573

·      Fallback Channels - COMMAND AND CONTROL - T1008

·      Multi-Stage Channels - COMMAND AND CONTROL - T1104

·      Supply Chain Compromise - INITIAL ACCESS ICS - T0862

·      Commonly Used Port - COMMAND AND CONTROL ICS - T0885

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About the author
Justin Torres
Cyber Analyst
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