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April 20, 2022

Email Compromise To Mass Phishing Campaign

Read Darktrace's in-depth analysis on the shift from business email compromise to mass phishing campaigns. Gain the knowledge to safeguard your business.
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
Shuh Chin Goh
Written by
Sam Lister
Specialist Security Researcher
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20
Apr 2022

It is common for attackers to send large volumes of malicious emails from the email accounts which they compromise. Before carrying out this mass-mailing activity, there are predictable, preparatory steps which attackers take, such as registering mass-mailing applications and creating new inbox rules. In this blog, we will provide details of an attack observed in February 2022 in which a threat actor conducted a successful mass-mailing attack at a financial company based in Africa.

Attack summary

In February 2022, an attacker attempted to infiltrate the email environment of a financial services company based in Africa. At the beginning of February, the attacker likely gained a foothold in the company’s email environment by tricking an internal user into entering the credentials of their corporate email account into a phishing page. Over the following week, the attacker used the compromised account credentials to conduct a variety of activities, such as registering a mass-mailing application and creating a new inbox rule.

After taking these preparatory steps, the attacker went on to send out large volumes of phishing emails from the internal user’s email account. The attacker consequently obtained the credentials of several further internal corporate accounts. They used the credentials of one of these accounts to carry out similar preparatory steps (registering a mass-mailing application and creating a new inbox rule). After taking these steps, the attacker again sent large volumes of phishing emails from the account. At this point, the customer requested assistance from Darktrace’s SOC to aid investigation, and the intrusion was consequently contained by the company.

Since the attacker carried out their activities using a VPN and an Amazon cloud service, the endpoints from which the activities took place did not serve as particularly helpful indicators of an attack. However, prior to sending out phishing emails from internal users’ accounts, the attacker did carry out other predictable, preparatory activities. One of the main goals of this blog is to highlight that these behaviors serve as valuable signs of preparation for mass-mailing activity.

Attack timeline

Figure 1: Timeline of the intrusion

On February 3, the attacker sent a phishing email to the corporate account of an employee. The email was sent from the corporate account of an employee at a company with business ties to the victim enterprise. It is likely that the attacker had compromised this account prior to sending the phishing email from it. The phishing email in question claimed to be an overdue payment reminder. Within the email, there was a link hidden behind the display text “view invoice”. The hostname of the phishing link’s URL was a subdomain of questionpro[.]eu — an online survey platform. The page referred to by the URL was a fake Microsoft Outlook login page.

Figure 2: Destination of phishing link within the email sent by the attacker

Antigena Email, Darktrace’s email security solution, identified the highly unusual linguistic structure of the email, given its understanding of ‘normal’ for that sender. This was reflected in an inducement shift score of 100. However, in this case, the original URL of the phishing link was rewritten by Mimecast’s URL protection service in a way which made the full URL impossible to extract. Consequently, Antigena Email did not know what the original URL of the link was. Since the link was rewritten by Mimecast’s URL protection service, the email’s recipient will have received a warning notification in their browser upon clicking the link. It seems that the recipient ignored the warning, and consequently divulged their email account credentials to the attacker.

For Antigena Email to hold an email from a user’s mailbox, it must judge with high confidence that the email is malicious. In cases where the email contains no suspicious attachments or links, it is difficult for Antigena Email to obtain such high degrees of confidence, unless the email displays clear payload-independent malicious indicators, such as indicators of spoofing or indicators of extortion. In this case, the email, as seen by Antigena Email, didn’t contain any suspicious links or attachments (since Mimecast had rewritten the suspicious link) and the email didn’t contain any indicators of spoofing or extortion.

Figure 3: The email’s high inducement shift score highlights that the email’s linguistic content and structure were unusual for the email’s sender

Shortly after receiving the email, the internal user’s corporate device was observed making SSL connections to the questionpro[.]eu phishing endpoint. It is likely that the user divulged their email account credentials during these connections.

Figure 4: The above screenshot — obtained from Advanced Search — depicts the connections made by the account owner’s device on February 3

Between February 3 and February 7, the attacker logged into the user’s email account several times. Since these logins were carried out using a common VPN service, they were not identified as particularly unusual by Darktrace. However, during their login sessions, the attacker exhibited behavior which was highly unusual for the email account’s owner. The attacker was observed creating an inbox rule called “ _ ” on the user’s email account,[1] as well as registering and granting permissions to a mass-mailing application called Newsletter Software SuperMailer. These steps were taken by the attacker in preparation for their subsequent mass-mailing activity.

On February 7, the attacker sent out phishing emails from the user’s account. The emails were sent to hundreds of internal and external mailboxes. The email claimed to be an overdue payment reminder and it contained a questionpro[.]eu link hidden behind the display text “view invoice”. It is likely that the inbox rule created by the attacker caused all responses to this phishing email to be deleted. Attackers regularly create inbox rules on the email accounts which they compromise to ensure that responses to the malicious emails which they distribute are hidden from the accounts’ owners.[2]

Since Antigena Email does not have visibility of internal-to-internal emails, the phishing email was delivered fully weaponized to hundreds of internal mailboxes. On February 7, after the phishing email was sent from the compromised internal account, more than twenty internal devices were observed making SSL connections to the relevant questionpro[.]eu endpoint, indicating that many internal users had clicked the phishing link and possibly revealed their account credentials to the attacker.

Figure 5: The above screenshot — obtained from Advanced Search — depicts the large volume of connections made by internal devices to the phishing endpoint

Over the next five days, the attacker was observed logging into the corporate email accounts of at least six internal users. These logins were carried out from the same VPN endpoints as the attacker’s original logins. On February 11, the attacker was observed creating an inbox rule named “ , ” on one of these accounts. Shortly after, the attacker went on to register and grant permissions to the same mass-mailing application, Newsletter Software SuperMailer. As with the other account, these steps were taken by the attacker in preparation for subsequent mass-mailing activity.

Figure 6: The above screenshot — obtained from Advanced Search — outlines all of the actions involving the mass-mailing application that were taken by the attacker (accounts have been redacted)

On February 11, shortly after 08:30 (UTC), the attacker widely distributed a phishing email from this second user’s account. The phishing email was distributed to hundreds of internal and external mailboxes. Unlike the other phishing emails used by the attacker, this one claimed to be a purchase order notification, and it contained an HTML file named PurchaseOrder.html. Within this file, there was a link to a suspicious page on the public relations (PR) news site, everything-pr[.]com. After the phishing email was sent from the compromised internal account, more than twenty internal devices were observed making SSL connections to the relevant everything-pr[.]com endpoint, indicating that many internal users had opened the malicious attachment.

Figure 7: The above screenshot — obtained from Advanced Search — depicts the connections made by internal devices to the endpoint referenced in the malicious attachment

On February 11, the customer submitted an Ask the Expert (ATE) request to Darktrace’s SOC team. The guidance provided by the SOC helped the security team to contain the intrusion. The attacker managed to maintain a presence within the organization’s email environment for eight days. During these eight days, the attacker sent out large volumes of phishing emails from two corporate accounts. Before sending out these phishing emails, the attacker carried out predictable, preparatory actions. These actions included registering a mass-mailing application with Azure AD and creating an inbox rule.

Darktrace guidance

There are many learning points for this particular intrusion. First, it is important to be mindful of signs of preparation for malicious mass-mailing activity. After an attacker compromises an email account, there are several actions which they will likely perform before they send out large volumes of malicious emails. For example, they may create an inbox rule on the account, and they may register a mass-mailing application with Azure AD. The Darktrace models SaaS / Compliance / New Email Rule and SaaS / Admin / OAuth Permission Grant are designed to pick up on these behaviors.

Second, in cases where an attacker succeeds in sending out phishing emails from an internal, corporate account, it is advised that customers make use of Darktrace’s Advanced Search to identify users that may have divulged account credentials to the attacker. The phishing email sent from the compromised account will likely contain a suspicious link. Once the hostname of the link has been identified, it is possible to ask Advanced Search to display all HTTP or SSL connections to the host in question. If the hostname is www.example.com, you can get Advanced Search to display all SSL connections to the host by using the Advanced Search query, @fields.server_name:"www.example.com", and you can get Advanced Search to display all HTTP connections to the host by using the query, @fields.host:"www.example.com".

Third, it is advised that customers make use of Darktrace’s ‘watched domains’ feature[3] in cases where an attacker succeeds in sending out malicious emails from the accounts they compromise. If a hostname is added to the watched domains list, then a model named Compromise / Watched Domain will breach whenever an internal device is observed connecting to it. If Antigena Network is configured, then observed attempts to connect to the relevant host will be blocked if the hostname is added to the watched domains list with the ‘flag for Antigena’ toggle switched on. If an attacker succeeds in sending out a malicious email from an internal, corporate account, it is advised that customers add hostnames of phishing links within the email to the watched domains list and enable the Antigena flag. Doing so will cause Darktrace to identify and thwart any attempts to connect to the relevant phishing endpoints.

Figure 8: The above screenshot — obtained from the Model Editor — shows that Antigena Network prevented ten internal devices from connecting to phishing endpoints after the relevant phishing hostnames were added to the watched domains list on February 11

For Darktrace customers who want to find out more about phishing detection, refer here for an exclusive supplement to this blog.

MITRE ATT&CK techniques observed

Thanks to Paul Jennings for his contributions.

Footnotes

1. https://docs.microsoft.com/en-us/powershell/module/exchange/new-inboxrule?view=exchange-ps

2. https://www.fireeye.com/current-threats/threat-intelligence-reports/rpt-fin4.html

3. https://customerportal.darktrace.com/product-guides/main/watched-domains

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
Shuh Chin Goh
Written by
Sam Lister
Specialist Security Researcher

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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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