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August 9, 2022

Cyber Tactics in the Russo-Ukrainian Conflict

The conflict between Russia and Ukraine has led to fears of a full-scale cyberwar. Learn the cyber attack tactics used, hacking groups involved, and more!
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
Rosa Jong
OSINT Analyst
Written by
Taisiia Garkava
Security Analyst
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09
Aug 2022

Introduction

Since the beginning of the Russian invasion of Ukraine in February 2022, cyber communities around the world have been witnessing what can be called a ‘renaissance of cyberwarfare' [1]. Rather than being financially motivated, threat actors are being guided by political convictions to defend allies or attack their enemies. This blog reviews some of the main threat actors involved in this conflict and their ongoing tactics, and advises on how organizations can best protect themselves. Darktrace’s preliminary assessments predicted that attacks would be observed globally with a focus on pro-Ukrainian nations such as North Atlantic Treaty Organization (NATO) members and that identified Advanced Persistent Threat (APT) groups would develop new and complex malware deployed through increasingly sophisticated attack vectors. This blog will show that many of these assessments had unexpected outcomes.

Context for Conflict 

Cyber confrontation between Russia and Ukraine dates back to 2013, when Viktor Yanukovych, (former President of Ukraine) rejected an EU trade pact in favour of an agreement with Russia. This sparked mass protests leading to his overthrow, and shortly after, Russian troops annexed Crimea and initiated the beginning of Russian-Ukrainian ground and cyber warfare. Since then, Russian threat actors have been periodically targeting Ukrainian infrastructure. One of the most notable examples of this, an attack against their national power grid in December 2015, resulted in power outages for approximately 255,000 people in Ukraine and was later attributed to the Russian hacking group Sandworm [2 & 3]. 

Another well-known attack in June 2017 overwhelmed the websites of hundreds of Ukrainian organizations using the infamous NotPetya malware. This attack is still considered the most damaging cyberattack in history, with more than €10 billion euros in financial damage [4]. In February 2022, countries witnessed the next stage of cyberwar against Ukraine with both new and familiar actors deploying various techniques to target their rival’s critical infrastructure. 

Tactic 1: Ransomware

Although some sources suggest US ransomware incidents and expectations of ransom may have declined during the conflict, ransomware still remained a significant tactic deployed globally across this period [5] [6] [7]. A Ukrainian hacking group, Network Battalion 65 (NB65), used ransomware to attack the Russian state-owned television and radio broadcasting network VGTRK. NB65 managed to steal 900,000 emails and 4000 files, and later demanded a ransom which they promised to donate to the Ukrainian army. This attack was unique because the group used the previously leaked source code of Conti, another infamous hacker group that had pledged its support to the Russian government earlier in the conflict. NB65 modified the leaked code to make unique ransomware for each of its targets [5]. 

Against expectations, Darktrace’s customer base appeared to deviate from these ransom trends. Analysts have seen relatively unsophisticated ransomware attacks during the conflict period, with limited evidence to suggest they were connected to any APT activity. Between November 2021 and June 2022, there were 51 confirmed ransomware compromises across the Darktrace customer base. This represents an increase of 43.16% compared to the same period the year before, accounting for relative customer growth. Whilst this suggests an overall growth in ransom cases, many of these confirmed incidents were unattributed and did not appear to be targeting any particular verticals or regions. While there was an increase in the energy sector, this could not be explicitly linked to the conflict. 

The Darktrace DETECT family has a variety of models related to ransomware visibility:

Darktrace Detections for T1486 (Data Encrypted for Impact):

- Compromise / Ransomware / Ransom or Offensive Words Written to SMB

- Compromise / Ransomware / Suspicious SMB Activity

- Anomalous Connection / Sustained MIME Type Conversion

- Unusual Activity / Sustained Anomalous SMB Activity

- Compromise / Ransomware / Suspicious SMB File Extension

- Unusual Activity / Anomalous SMB Read & Write

- Unusual Activity / Anomalous SMB Read & Write from New Device

- SaaS / Resource / SaaS Resources with Additional Extensions

- Compromise / Ransomware / Possible Ransom Note Read

- [If RESPOND is enabled] Antigena / Network / External Threat / Antigena Ransomware Block

Tactic 2: Wipers

One of the largest groups of executables seen during the conflict were wipers. On the eve of the invasion, Ukrainian organizations were targeted by a new wiper malware given the name “HermeticWiper”. Hermetic refers to the name of the Cyprian company “Hermetica Digital Ltd.” which was used by attackers to request a code signing certificate [6]. Such a digital certificate is used to verify the ownership of the code and that it has not been altered. The 24-year-old owner of Hermetica Digital says he had no idea that his company was abused to retrieve a code signing certificate [7]. 

HermeticWiper consists of three components: a worm, decoy ransomware and the wiper malware. The custom worm designed for HermeticWiper was used to spread the malware across the network of its infected machines. ESET researchers discovered that the decoy ransomware and the wiper were released at the same time [8]. The decoy ransomware was used to make it look like the machine was hit by ransomware, when in reality the wiper was already permanently wiping data from the machines. In the attack’s initial stage, it bypasses Windows security features designed to prevent overwriting boot records by installing a separate driver. After wiping data from the machine, HermeticWiper prevents that data from being re-fragmented and overwrites the files to fragment it further. This is done to make it more challenging to reconstruct data for post-compromise forensics [9]. Overall, the function and purpose of HermeticWiper seems similar to that of NotPetya ransomware. 

HermeticWiper is not the only conflict-associated wiper malware which has been observed. In January 2022, Microsoft warned Ukrainian customers that they detected wiper intrusion activity against several European organizations. One example of this was the MBR (Master Boot Record) wiper. This type of wiper overwrites the MBR, the disk sector that instructs a computer on how to load its operating system, with a ransomware note. In reality, the note is a misdirection and the malware destroys the MBR and targeted files [10].  

One of the most notable groups that used wiper malware was Sandworm. Sandworm is an APT attributed to Russia’s foreign military intelligence agency, GRU. The group has been active since 2009 and has used a variety of TTPs within their attacks. They have a history of targeting Ukraine including attacks in 2015 on Ukraine’s energy distribution companies and in 2017 when they used the aforementioned NotPetya malware against several Ukrainian organizations [11]. Another Russian (or pro-Russian) group using wiper malware to target Ukraine is DEV-0586. This group targeted various Ukrainian organizations in January 2022 with Whispergate wiper malware. This type of wiper malware presents itself as ransomware by displaying a file instructing the victim to pay Bitcoin to have their files decrypted [12].  

Darktrace did not observe any confirmed cases of HermeticWiper nor other conflict-associated wipers (e.g IsaacWiper and CaddyWiper) within the customer base over this period. Despite this, Darktrace DETECT has a variety of models related to wipers and data destruction:

Darktrace Detections for T1485 (Data Destruction)- this is the main technique exploited during wiper attacks

- Unusual Activity / Anomalous SMB Delete Volume

- IaaS / Unusual Activity / Anomalous AWS Resources Deleted

- IaaS / Storage / S3 Bucket Delete

- SaaS / Resource / Mass Email Deletes from Rare Location

- SaaS / Resource / Anomalous SaaS Resources Deleted

- SaaS / Resource / Resource Permanent Delete

- [If RESPOND is enabled] Antigena / Network / Manual / Enforce Pattern of Life

- [If RESPOND is enabled] Antigena / SaaS / Antigena Unusual Activity Block

Tactic 3: Spear-Phishing

Another strategy that some threat actors employ is spear-phishing. Targeting can be done using email, social media, messaging, or other platforms.

The hacking group Armageddon (also known as Gamaredon) has been responsible for several spear-phishing attacks during the crisis, primarily targeting individuals involved in the Ukrainian Government [13]. Since the beginning of the war, the group has been sending out a large volume of emails containing an HTML file which, if opened, downloads and launches a RAR payload. Those who click the attached link download an HTA with a PowerShell script which obtains the final Armageddon payload. Using the same strategy, the group is also targeting governmental agencies in the European Union [14]. With high-value targets, the need to improve teaching around phishing identification to minimize the chance of being caught in an attacker's net is higher than ever. 

In comparison to the wider trends, Darktrace analysts again saw little-to-no evidence of conflict-associated phishing campaigns affecting customers. Those phishing attempts which did target customers were largely not conflict-related. In some cases, the conflict was used opportunistically, such as when one customer was targeted with a phishing email referencing Russian bank exclusions from the SWIFT payment system (Figures 1 and 2). The email was identified by Darktrace/Email as a probable attempt at financial extortion and inducement - in this case the company received a spoofed email from a major bank’s remittance department.  

Figure 1- Screencap of targeted phishing email sent to Darktrace customer
Figure 2- Attached file contains soliciting reference to SWIFT, a money payment system which select Russian banks were removed from because of the conflict [15]

 Although the conflict was used as a reference in some examples, in most of Darktrace’s observed phishing cases during the conflict period there was little-to-no evidence to suggest that the company being targeted nor the threat actor behind the phishing attempt was associated with or attributable to the Russia-Ukraine conflict.

However, Darktrace/Email has several model categories which pick up phishing related threats:

Sample of Darktrace for Email Detections for T1566 (Phishing)- this is the overarching technique exploited during spear-phishing events

Model Categories:

- Inducement

- Internal / External User Spoofing

- Internal / External Domain Spoofing

- Fake Support

- Link to Rare Domains

- Link to File Storage

- Redirect Links

- Anomalous / Malicious Attachments

- Compromised Known Sender

Specific models can be located on the Email Console

 

Tactic 4: Distributed-Denial-of-Service (DDoS)

Another tactic employed by both pro-Russian and pro-Ukrainian threat actors was DDoS (Distributed Denial of Service) attacks. Both pro-Russia and pro-Ukraine actors were seen targeting critical infrastructure, information resources, and governmental platforms with mass DDoS attacks. The Ukrainian Minister of Digital Transformation, Mykhailo Fedorov, called on an IT Army of underground Ukrainian hackers and volunteers to protect Ukraine's critical infrastructure and conduct DDoS attacks against Russia [16]. As of 1 August 2022, more than two hundred thousand people are subscribed to the group's official Telegram channel, where potential DDoS targets are announced [17].

Darktrace observed similar pro-Ukraine DDoS behaviors within a variety of customer environments. These DDoS campaigns appeared to involve low-volume individual support combined with crowd-sourced DDoS activity. They were hosted on a range of public-sourced DDoS sites and seemed to share sentiments of groups such as the IT Army of Ukraine (Figure 3).

Figure 3- Example DDoS outsource domain with unusual TLD 

From the Russian side, one of the prominent newly emerged groups, Killnet, is striking back, launching several massive DDoS attacks against the critical infrastructure of countries that provide weaponry to Ukraine [18 & 19]. Today, the number of supporters of Killnet has grown to eighty-four thousand on their Telegram channel. The group has already launched a number of mass attacks on several NATO states, including Germany, Poland, Italy, Lithuania and Norway. This shows the conflict has attracted new and fast-growing groups with large backing and the capacity to undertake widespread attacks. 

DETECT has several models to identify anomalous DoS/DDoS activity:

Darktrace Detection for T1498 (Network Denial of Service)- this is the main technique exploited during DDoS attacks

- Device / Anomaly Indicators / Denial of Service Activity Indicator

- Anomalous Server Activity / Possible Denial of Service Activity

- [If RESPOND is enabled] Antigena / Network / External Threat / Antigena Suspicious Activity Block

What did Darktrace observe?

Darktrace’s cross-fleet detections were largely contrary to expectations. Analysts did not see large-scale complex conflict-linked attacks utilizing either conflict-associated ransomware, malware, or other TTPs. Instead, cyber incidents observed were largely opportunistic, using malware that could be purchased through Malware-as-a-Service models and other widely available toolkits, (rather than APT or conflict-attributable attacks). Overall, this is not to say there have been no repercussions from the conflict or that opportunistic attacks will cease, but evidence suggests that there were fewer wider cyber consequences beyond the initial APT-based attacks seen in the public forum. 

Another trend expected since the beginning of the conflict was targeted responses to sanction announcements focusing on NATO businesses and governments. Analysts, however, saw the limited reactive actions, with little-to-no direct impact from sanction announcements. Although cyber-attacks on some NATO organizations did take place, they were not as widespread or impactful as expected. Lastly, it was thought that exposure to new and sophisticated exploits would increase and be used to weaken NATO nations - especially corporations in critical industries. However, analysts observed relatively common exploits deployed indiscriminately and opportunistically. Overall, with the wider industry expecting chaos, Darktrace analysts did not see the crisis taken advantage of to target wider businesses outside of Ukraine. Based on this comparison between expectations and reality, the conflict has demonstrated the danger of  falling prey to confirmation bias and the need to remain vigilant and expect the unexpected. It may be possible to say that cyberwar is ‘cold’ right now, however the element of surprise is always present, and it is better to be prepared to protect yourself and your organization.    

What to Expect from the Future

As cyberattacks continue to become less monetarily and physically costly, it is to be expected that they will increase in frequency. Even after a political ceasefire is established, hacking groups can harbour resentment and continue their attacks, though possibly on a smaller scale.  

Additionally, the longer this conflict continues, the more sophisticated hacking groups’s attacks may become. In one of their publications, Killnet shared with subscribers that they had created ‘network weaponry’ powerful enough to simultaneously take down five European countries (Figure 4) [20]. Whether or not this claim is true, it is vital to be prepared. The European Union and the United States have supported Ukraine since the start of the invasion, and the EU has also stated that it is considering providing further assistance to help Ukraine in cyberspace [21].

Figure 4- Snapshot of Killnet Telegram announcement

How to Protect Against these Attacks

In the face of wider conflict and cybersecurity tensions, it is crucial that organizations evaluate their security stack and practise the following: 

·       Know what your critical assets are and what software is running on them. 

·       Keep your software up to date. Prioritize patching critical and high vulnerabilities that allow remote code execution. 

·       Enforce Multifactor Authentication (MFA) to the greatest extent possible. 

·       Require the use of a password manager to generate strong and unique passwords for each separate account. 

·       Backup all the essential files on the cloud and external drives and regularly maintain them. 

·       Train your employees to recognize phishing emails, suspicious websites, infected links or other abnormalities to prevent successful compromise of email accounts. 

In order to prevent an organization from suffering damage due to one of the attacks mentioned above, a full-circle approach is needed. This defence starts with a thorough understanding of the attack surface to provide timely mitigation. This can be supported by Darktrace products: 

·       As shown throughout this blog, Darktrace DETECT and Darktrace/Email have several models relating to conflict-associated TTPs and attacks. These help to quickly alert security teams and provide visibility of anomalous behaviors.

·       Darktrace PREVENT/ASM helps to identify vulnerable external-facing assets. By patching and securing these devices, the risk of exploit is drastically reduced.

·       Darktrace RESPOND and RESPOND/Email can make targeted actions to a range of threats such as blocking incoming DDoS connections or locking malicious email links.

Thanks to the Darktrace Threat Intelligence Unit for their contributions to this blog.

Appendices 

Reference List

[1] https://www.atlanticcouncil.org/blogs/ukrainealert/vladimir-putins-ukraine-invasion-is-the-worlds-first-full-scale-cyberwar/ 

[2] https://www.reuters.com/article/us-ukraine-cybersecurity-idUSKCN0VY30K

[3] https://www.reuters.com/article/us-ukraine-cybersecurity-sandworm-idUSKBN0UM00N20160108

[4 & 11] https://www.wired.com/story/notpetya-cyberattack-ukraine-russia-code-crashed-the-world/ 

[5] https://www.scmagazine.com/analysis/ransomware/despite-hopes-for-decline-ransomware-attacks-increased-during-russia-ukraine-conflict

[6] https://ransomware.org/blog/has-the-ukraine-conflict-disrupted-ransomware-attacks/

[7] https://www.cfr.org/blog/financial-incentives-may-explain-perceived-lack-ransomware-russias-latest-assault-ukraine

[8] https://www.bleepingcomputer.com/news/security/hackers-use-contis-leaked-ransomware-to-attack-russian-companies/ 

[9] https://voi.id/en/technology/138937/hermetica-owner-from-cyprus-didnt-know-his-server-was-used-in-malicious-malware-attack-in-ukraine 

[10] https://www.reuters.com/article/ukraine-crisis-cyber-cyprus-idCAKBN2KT2QI 

[11] https://www.eset.com/int/about/newsroom/press-releases/research/eset-research-ukraine-hit-by-destructive-attacks-before-and-during-the-russian-invasion-with-hermet/ 

[12] https://blog.malwarebytes.com/threat-intelligence/2022/03/hermeticwiper-a-detailed-analysis-of-the-destructive-malware-that-targeted-ukraine/ 

[13] https://www.microsoft.com/security/blog/2022/01/15/destructive-malware-targeting-ukrainian-organizations/ 

[15] https://www.cisa.gov/uscert/ncas/alerts/aa22-057a 

[16] https://attack.mitre.org/groups/G0047/ 

[17] https://cyware.com/news/ukraine-cert-warns-of-increasing-attacks-by-armageddon-group-850081f8 

[18] https://www.bbc.co.uk/news/business-60521822

[19] https://foreignpolicy.com/2022/04/11/russia-cyberwarfare-us-ukraine-volunteer-hackers-it-army/

[20] https://t.me/itarmyofukraine2022

[21] https://www.csoonline.com/article/3664859/russian-ddos-attack-on-lithuania-was-planned-on-telegram-flashpoint-says.html

[19 & 20] https://flashpoint.io/blog/killnet-kaliningrad-and-lithuanias-transport-standoff-with-russia/ 

[21] https://presidence-francaise.consilium.europa.eu/en/news/member-states-united-in-supporting-ukraine-and-strengthening-the-eu-s-telecommunications-and-cybersecurity-resilience/ 

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
Rosa Jong
OSINT Analyst
Written by
Taisiia Garkava
Security 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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