December 8, 2017

Darktrace: Investigating Widespread Trojan Infections

Discover how Darktrace expedites the investigation of widespread Trojan infections, enhancing cybersecurity and response times.

Written by

Max Heinemeyer

Global Field CISO

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

Max Heinemeyer

Global Field CISO

Dec 2017

This blog post outlines how Darktrace helps security operations centre (SOC) teams become more efficient by drastically cutting down the time needed to investigate incidents. This is illustrated by an example encountered in a recent Proof of Value where over 350 client devices had been infected by a stealthy banking trojan.

Identifying and investigating a compromise of this size would usually take a SOC team several hours if not days using disparate traditional security tools. Employing Darktrace, the most important questions were answered within 90 minutes. The main reason for this is that Darktrace provides full visibility and context into network activity for all devices monitored on a single, unified platform.

Alert fatigue & the cyber security skill gap

Getting cyber security right is difficult and time-consuming. Complexity is one of the main challenges the cyber security community is facing. These days, networks are only vaguely defined with digital supply chains, outsourcing, the push into the cloud and the advent of micro-virtualisation like Docker. The amount of data stored, devices connected to internal networks, connections made by devices and the heterogeneity in IT adds to this complexity. Managing it is difficult at best and securing it with traditional tools can be a daunting task.

Our industry is struggling with what has been labelled the ‘cyber security skill gap’. The demand for skilled, experienced security practitioners consistently outstrips supply. SOC teams struggle to find the right people for the job and to keep their analysts motivated in the face of a rapidly evolving threat landscape. Alert fatigue and burnout are common symptoms for SOC analysts working long hours and graveyard shifts.

Investigation methodology

Any incident responder will always begin by asking some high-level questions concerning the incident under investigation – regardless of it being an adware infection, a banking trojan, ransomware, an active intrusion or any other form of cyber security incident.

The most important questions usually are:

How did the infection occur? (To prevent the same initial infection vector in the future)
What behavior is the infected device exhibiting? (To understand the threat and the risk of the infection)
What Indicators of Compromise (IoC) are seen? (To update other security tools and to use for further investigation)
Are other devices infected as well? (To assess the extent of the infection)

We did a recent Proof of Value with an IT service provider in EMEA. Darktrace entered an environment which had already succumbed to a widespread compromise – over 350 client devices had been infected with banking trojans. Let’s walk through how we identified, triaged and investigated this infection using Darktrace.

Identifying the incident

Darktrace came into the environment after the initial infection had taken place already. Darktrace instantly identified several devices exhibiting unexpected HTTP beaconing to unusual, rare external IP addresses. The devices made HTTP POST requests without prior GET requests along other suspicious behavior. Darktrace created several high-severity alerts for this, e.g. ‘Compromise / Suspicious HTTP Beacons to Dotted Quad’ and ‘Compromise / Possible Malware HTTP Comms’:

Figure 1: Example Darktrace alert.

Triaging the incident

Darktrace then provides context around this alert - e.g. the external IP the beaconing was made to, the internal device including the associated user, and the suspicious behavior:

Figure 2: Detection context and C2 IP.

A quick investigation of the external IP reveals that it is a recently discovered command and control (C2) IP address for the Dridex banking trojan.

Drilling deeper into this, Darktrace provides PCAPs for every connection seen. A PCAP for the C2 connection above confirms this incident as active, successful, encoded beaconing to a malicious C2 IP:

Figure 3: PCAP and encoded HTTP POSTs.

Investigating the incident

At this stage, we want to further examine the behavior of the infected device around the time of the incident. Darktrace provides full visibility into past activity, including all network connection made by any device - regardless of whether the incident occurred on the device or not.

We attend to all external connections made by the infected device around the time of the incident and immediately identify more suspicious C2 communication:

Figure 4: More device behavior; further C2 IPs.

By now we have identified 6 different C2 IP addresses.

We can use Darktrace’s ‘External Sites Summary’ to view all devices that have connected to a specific IP or domain in the recent past. Doing this for the initial C2 IP yields the following result (excerpt):

Figure 5: External Sites Summary; further infections.

We immediately identify 5 additional devices that made successful connections to the C2 IP address. In fact, the list above is abridged as we actually saw over 350 devices connecting to this and other C2 IP addresses. Notably, all observed devices appear to have a similar naming structure - this will become important in the next part of the analysis.

At this point we have answered all but the first question: ‘How did the infection occur?’

Darktrace started monitoring the network after the initial infection occurred and spread. Further research into the C2 IP addresses shows that they are associated with the Emotet trojan. This sophisticated malware often precedes banking trojan (e.g. Dridex) infections and is spread via phishing. We can thus assume that phishing was a likely initial infection vector.

How then did the infection manage to spread to so many devices?

Surely not all users clicked on suspicious phishing emails? Recent versions of Emotet have limited lateral movement capabilities. They mainly propagate via SMB brute forcing - trying administrative accounts and hard-coded password lists. The naming convention on the infected devices is very similar - this could indicate a similar build-process and setup of the devices. If a vulnerability - such as an administrative account with a weak password - existed on one of the devices, it might be present in all of the devices with a similar build.

Using Darktrace, the security team has now a solid understanding of the nature and size of the infection, the IoCs available to update firewalls and other preventive security controls and outstanding remediation-activities.

What would this investigation look like with traditional tools, not using Darktrace?

Detecting these covert banking trojans in the first place, let alone triaging them fully, can be a difficult challenge in itself. Current banking Trojan strains such as Dridex, Fedeo or Vawtrak keep updating the malware with new C2 addresses to avoid blacklisting. Initial detection could be at any stage of the attack lifecycle – likely it will be in the latter stages though, when considerable damage has already been done.

An analyst will have to log into various security devices to get close to the same level of visibility provided in Darktrace – web proxy logs, anti-virus logs, running PCAPs on infected hosts, SIEM logs. Having to switch between all those disparate security tools is not time-efficient and produces a fragmentary picture of what actually transpired.

Conclusion

A working hypothesis is that a single device was initially infected via phishing, allowing Emotet to spread to over 350 internal devices via SMB brute forcing. It took no longer than 90 minutes to come from an initial detection of the incident to this conclusion, which forms the basis for an actionable report.

The last thing a SOC needs is yet another tool producing a profusion of alerts. Using Darktrace’s machine learning and unrivalled network visibility, you can focus on the small set of relevant alerts and rapidly investigate those incidents according to their severity and priority.

Darktrace can reduce costs even if you bring in a third-party incident response team. You will be able to significantly speed up their ongoing investigation if they have access to Darktrace. Third-party incident response teams are expensive – their daily rates ranging between £2,000 and £3,000 per day. Cutting their work down from days to hours will result in cost and efforts saved.

Written by

Max Heinemeyer

Global Field CISO

Inside the SOC

Written by

Max Heinemeyer

Global Field CISO

•

August 3, 2026

Nathaniel Jones

SVP, Global Threat Intelligence

•

August 4, 2026

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August 4, 2026

Extending AI Security Visibility with Darktrace and Microsoft Agent 365

AI agents are rapidly becoming embedded in everyday business operations, helping employees automate workflows, access information, and accelerate decision-making. As organizations embrace agentic AI, security teams face a growing challenge: understanding how AI is being used, what agents can access, and where risk may emerge.

As agents take on more business-critical work, security teams often need to move across multiple portals to understand risks spanning identity, data, and threat activity. This fragmented view can make it difficult to assess an agent's overall risk posture and determine where attention is needed. Organizations need a way to bring these signals together without disrupting existing security investments or workflows.

Today, Darktrace is announcing an integration between Darktrace / SECURE AI and Microsoft Agent 365 that brings Darktrace's Adaptive AI-driven risk signals directly into the Microsoft 365 Admin Center. By extending the visibility and risk understanding provided by Darktrace / SECURE AI into the Microsoft ecosystem, organizations can gain a more unified understanding of AI agent risk across their environments.

As one of the first security companies to partner with Microsoft to contribute third-party risk signals to the Agent Registry, Darktrace is helping shape how organizations understand and manage AI agent risk.

Extending visibility into the Microsoft Agent 365 experience

Microsoft Agent 365 provides administrators with a centralized registry of AI agents operating within their environment. As organizations expand their use of AI agents, this centralized visibility becomes increasingly important for governance and oversight.

This new integration extends that visibility by allowing Darktrace-generated risk signals to be surfaced directly within the Microsoft Agent 365 experience. By combining Microsoft's agent management and security capabilities with Darktrace's AI-powered risk analysis, organizations gain greater awareness of potential security concerns associated with AI agents operating across their environments.

By integrating Darktrace telemetry into Agent 365, customers can:

Surface Darktrace-detected risks and signals alongside Microsoft-native signals in a single interface

Identify potentially compromised or anomalous AI agents more quickly

Gain unified understanding of context and agent behavior

This approach reinforces a single control plane for AI security while allowing organizations to continue leveraging existing investments across both platforms.

Why unified visibility of AI agent risk signals matters

As AI adoption accelerates across Microsoft environments, organizations must manage new forms of behavior, access patterns, and risk. Security teams need more than inventories and permissions. They need visibility into how AI systems operate and how risk evolves over time.

This integration addresses a critical gap: how to bring behavioral AI security insights into the same control plane as identity, access, and agent management.

With Darktrace and Microsoft Agent 365 together, organizations benefit from:

Unified visibility: A single pane of glass for understanding AI agent risk signals across Microsoft and Darktrace signals

Faster detection of abnormal agent behavior: Darktrace's Adaptive AI highlights deviations that may not be captured by static controls

Operational efficiency: Security teams can triage and prioritize risk signals without switching between systems

Stronger trust in AI deployments: Clear attribution, context, and investigation pathways improve confidence in AI agent usage

Extending Microsoft's AI security model, not replacing it

Securing AI requires a layered approach that combines governance, visibility, threat detection, and risk management. This integration is designed to complement Microsoft's security capabilities, not duplicate them.

Through Darktrace / SECURE AI, Darktrace contributes:

Identification of risk via advanced prompt analysis

Behavioral anomaly detection across AI agents

Cross-environment threat correlation

Autonomous insight into emerging or unknown risks

Microsoft provides:

Centralized agent management

Identity and access governance

Native detection of risk signals and enforcement capabilities

Together, these capabilities create a more complete, layered approach to securing AI-driven enterprises. Organizations gain the governance and policy controls needed to manage AI adoption while benefiting from continuous visibility into how AI is used across the business.

Building the future of secure AI

As AI agents become more deeply embedded in business processes, organizations need more than inventories and static controls. They need to understand how AI is being used, how agents behave, and where risk is emerging across the enterprise.

Darktrace / SECURE AI delivers that understanding through continuous visibility into AI activity, helping security teams assess intent, identify behavioral drift, and uncover emerging risk across both human and agent-driven workflows. Powered by Adaptive AI, it provides the context needed to secure AI as it evolves.

The integration with Microsoft Agent 365 extends those insights into the workflows organizations already use. Agent 365 provides a unified control plane for governing and securing AI agents, while Darktrace contributes complementary behavioral risk signals that can be surfaced within the Agent 365 experience. Together, they give customers broader context on agent activity and risk while preserving the value of their existing Microsoft and Darktrace investments.

As enterprises move from AI experimentation to AI-powered execution, Microsoft and Darktrace help bring together governance, compliance, behavioral understanding, and oversight in a unified approach to AI security. For organizations adopting Microsoft 365 E7, Darktrace / SECURE AI further strengthens that foundation by providing continuous visibility into AI activity, agent behavior, and emerging risk as AI adoption scales.

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August 3, 2026

Why Trust is the New Attack Surface: Darktrace’s Mid-Year Threat Update 2026

In early 2026, a React2Shell honeypot purpose-built by Darktrace analysts was compromised in less than two hours after deployment. That single data point captures the pace of the threat landscape in the first half of 2026, but speed tells only part of the story.

The shift over the past six months has moved away from traditional malware and vulnerability-centric attacks and toward the abuse of trusted identities, platforms, and infrastructure. Identities, Software-as-a-Service (SaaS) platforms, cloud entitlements, automation frameworks, and non-human identities have become the preferred attack paths as organizations adopt AI at scale.

Attackers are increasingly operating inside the relationships, services, and authenticated channels that defenders and users are conditioned to rely on, rather than breaking in from the outside.

What has changed since 2025?

In 2025, identity became the new perimeter as attackers increasingly bypassed traditional exploitation in favor of trusted accounts, SaaS platforms, and emerging AI-enabled tradecraft. The first half of 2026 marks the next stage of that evolution. Identity remains central, but the trust challenge now extends far beyond accounts to email authentication, cloud entitlements, software supply chains, AI gateways, remote administration tooling, and non-human identities.

Theme	2025 (Mid-Year / Annual)	H1 2026
Identity	Credentials remained the weak link; identity emerged as the new perimeter.	Identity remains the entry point, but trust has become the new attack surface.
Cloud & SaaS	SaaS-targeted ransomware continued to rise.	Cloud and SaaS became the attacker's preferred operating environment.
AI	Large Language Models (LLMs) were suspected of influencing phishing shifts.	LLM-generated malware, compromised AI proxies, and the abuse of AI identities emerged.
Attack Surface Scale & Speed	Exponential growth of Common Vulnerabilities and Exposures (CVEs), with public proof-of-concepts appearing faster.	Cloud and AI adoption expanded the attack surface, while AI accelerated exploitation. One honeypot was compromised in under two hours.
Supply Chain	Legitimate services were increasingly abused.	Trusted maintainers and CI/CD workflows were weaponized.

Identity and email: trust signals under pressure

Email remains the most reliable route to a trusted identity, and the data shows attackers investing in quality over noise. In the first half of 2026, 67% of phishing emails passed DMARC. Authentication alone is no longer sufficient to stop most phishing attempts. VIP users were targeted in 25.8% of phishing, consistent with 2025's “over 25%” figure, but drifting upward throughout the period. Crucially, phishing sophistication continued to increase: 37% of phishing contained a high volume of text, up from 32% in the first half of 2025, while 39% featured novel social engineering techniques, suggesting attackers are further customizing to specific targets.

The most prevalent threats affecting Darktrace customers were also among the most identity-centric: information stealers, with dedicated StealC and AMOS campaigns running through the half-year. Their prevalence is, fundamentally, an identity story. Credentials harvested by infostealers often become the initial access vector for far higher-impact intrusions later in the attack chain. Crucially, the delivery method rarely requires exploitation of a technical weakness. ClickFix social engineering, which tricks users into running malicious code themselves, remained a common distribution route. One recent campaign impacted Darktrace customers across 17 countries, with the United States the most affected. The compromise did not begin with a software flaw, but with a trusted user taking a trusted action.

Supply chain: Trust weaponized at scale

March and April reinforced the same lesson: trust has become a supply-chain vulnerability. The Axios compromise abused trust in a widely used maintainer, while the Trivy campaign leveraged trusted CI/CD infrastructure, release artifacts, and container images to push malicious code through legitimate development workflows.

The clearest example was a February–March campaign in which devices downloaded malicious payloads while using Hola VPN, later linked to an issue within Hola's own delivery pipeline. Darktrace's Threat Research team identified associated activity through recurring anomalous behavior across multiple customers before a public advisory was released.

More recently, attackers abused legitimate blockchain infrastructure to distribute infostealers, including AMOS and Phexia. Popular tools like VPNs, often used by users with limited security resources, combined with legitimate command-and-control (C2) infrastructure enables attackers to reach a far wider victim base while frustrating defenders who cannot simply block the associated endpoints.

For defenders, the challenge is no longer identifying malicious infrastructure, but recognizing when trusted infrastructure begins behaving maliciously.

Cloud and SaaS: from target to terrain

Through May and June, activity involving device registration, cloud data theft, SaaS abuse, RDP expansion, and remote management tooling suggested that attackers increasingly view cloud and SaaS not simply as targets, but as their preferred operating environment.

In one Darktrace case a single compromised SaaS account triggered activity across email, SaaS, and network layers, including inbox rule changes, phishing propagation, and connections to suspicious infrastructure. None of these indicators were decisive in isolation, but together they revealed a clear intrusion. Increasingly, attackers do not need to bypass trust controls in these environments; they inherit them through compromised identities, delegated access, and legitimate administration tools. This is the natural progression of 2025's SaaS-targeted ransomware trend: the platforms on which businesses operate are increasingly the same platforms on which adversaries operate.

AI: accelerant, attack surface, and trusted but risky actor

If trust is the attack surface, AI is where that surface is expanding fastest. Across the Darktrace customer base, AI service connections per deployment rose 13% in the first half of 2026, surpassing 16 million connections, while the typical organization now interacts with seven different AI providers. AI is no longer at the edge of the enterprise; it is embedded in day-to-day business operations. That shift creates three distinct problems, all of which were observed by Darktrace in the first half of 2026.

1. AI as an attack multiplier

Darktrace identified AI-generated malware exploiting React2Shell, in which an attacker used an LLM to produce working exploit code and deploy it at scale. Similar activity is increasingly appearing across the wider threat landscape, suggesting that the barrier to effective offensive operations is collapsing. As demonstrated by the recent JadePuffer case, in which an agentic threat actor exploited a vulnerability in an internet-facing server before launching a fully automated ransomware attack, AI is accelerating the path from vulnerability disclosure to operational exploitation [1].

2. AI as an attack surface

The AI layer itself is now worth probing. At an automation technology manufacturer, a compromised LLM proxy was used as a steppingstone toward additional AI services; when that failed, the attacker pivoted to cryptomining. Darktrace’s Cyber AI Analyst pieced the intrusion together and Darktrace’s Managed Threat Detection service alerted the customer, containing it before it could progress further. The practitioner lesson is clear: treat AI gateways, proxies, and model endpoints as production cloud workloads because attackers already do.

3. AI as a trusted but potentially risky actor

Darktrace / SECURE AI observations suggest the most common real-world risk is quieter still: employees entering personal identifiable information (PII), tax records, identity documents, company financial data, HR records, and personal medical data into LLM prompts, alongside widespread shadow AI use and increased AI usage from mobile devices. Across nearly 280,000 prompts submitted by almost 28,000 users over 28 days, Darktrace identified that approximately 1% of these prompts (or 2,945 instances) contained sensitive data*.

_{*Prompt data was analyzed in aggregate and anonymized form to protect user privacy.}

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For defenders, the challenge is context: knowing when legitimate business use crosses into material risk without breaking privacy or user trust. As organizations increasingly trust AI systems to access, process, and share sensitive information at machine speed, AI must be secured and monitored alongside identities, applications, and cloud infrastructure.

Speed and geopolitics: faster operations, longer-term objectives

Several investigations in the first half of the year showed how quickly attackers operationalize newly disclosed vulnerabilities, validating exploitation through Out-of-Band Application Security Testing (OAST) infrastructure and trusted cloud services before patching cycles can be completed. React2Shell was compromised in two hours, while BeyondTrust exploitation followed in less than a day. Against this backdrop, state-aligned actors continue to prioritize long-term access, intelligence collection, and pre-positioning through legitimate services, cloud infrastructure, and trusted relationships. Operations linked to China, Russia, Iran, and the Democratic People’s Republic of Korea (DPRK) shared a common characteristic: a focus on persistence and strategic positioning rather than immediate disruption.

China: Darktrace observed Chinese-nexus actors prioritizing long-term access through trusted services, dynamic-link library (DLL) sideloading, and modular intrusion chains consistent with activity documented in Crimson Echo reporting and associated with Twill Typhoon tradecraft.

Iran: Darktrace's ZionSiphon investigation highlighted Iranian-linked interest in operational technology (OT) environments, blending espionage objectives with infrastructure disruption capabilities.

Russia: Darktrace investigations, alongside wider industry reporting, highlighted Russian reliance on trusted relationships and supply-chain targeting for long-term intelligence on Ukraine related support [2].

DPRK: Darktrace observed DPRK-linked activity combining rapid vulnerability weaponization with persistent access techniques, including Axios supply-chain compromise, React2Shell exploitation and stealthy macOS intrusions

While objectives differed across actors, the tradecraft was remarkably consistent: trusted services, legitimate infrastructure, and persistent access remained more valuable than immediate disruption.

The defender shift

Across identity compromise, supply-chain attacks, SaaS abuse, AI infrastructure targeting, and state-aligned operations, attackers increasingly succeed by operating through trusted systems rather than breaking through defensive controls. Trusted users, trusted software, trusted infrastructure, and increasingly trusted AI systems all became viable attack paths.

For defenders, the challenge is no longer simply determining whether an action is allowed; it is determining whether that action makes sense in its wider context. Authentication, reputation, and provenance remain important, but they are no longer sufficient on their own. As attackers increasingly operate within trusted systems, the strongest signal is often a behavioral deviation: identifying when trusted activity no longer aligns with expected behavior.

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Credit to Nathaniel Jones (SVP, Global Threat Intelligence), Emma Foulger (Global Threat Research Operations Lead), Justin Torres (Senior Cyber Analyst), Daniel Levy (Threat Hunting Data Scientist)

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Edited by Ryan Traill (Content Manager)

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Appendix 1: Threat Research Methodology

Darktrace’s Threat Research team conducts extensive research across customer deployments to identify active threats, pinpoint key Indicators of Compromise (IoCs), and provide relevant threat intelligence. This research leverages Darktrace’s anomaly-based detection and involves thorough analysis and contextualization by the Threat Research team. Detected threats are promptly reported to the relevant customer security teams. When a customer has Darktrace’s Autonomous Response technology enabled, these threats are swiftly mitigated to prevent escalation.

Between January 1 and June 30, 2026, Darktrace investigated a wide range of cyber threats across its customer base. Many were identified as campaign-like activities targeting multiple customers, where clusters of similar tactics, techniques, and procedures (TTPs) and IoCs were seen affecting a significant number of customers within a short timeframe.

Statistics related to email are derived from aggregated Darktrace / EMAIL data across all cloud-hosted customer deployments between January 1 and June 30, 2026. Standard data-quality filtering was applied to exclude anomalous observations prior to aggregation. Regional statistics are based on relevant subsets of this dataset.

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Appendix 2: Campaigns - Regional and Sector Trends

While the above broad themes defined the threat landscape over the last six months, campaign clustering across the Darktrace customer base revealed how they manifested differently across sectors, regions, and industries.

Darktrace’s Threat Research team investigates a range of threats affecting its customer base. Through this research, campaign-like clusters of activity have been identified, in which common tactics, techniques, and procedures (TTPs), as well as infrastructure, are observed impacting a significant number of customers within a short timeframe.

Sectors and industries are classified using the Standard Industrial Classification (SIC) system to ensure consistent categorization. While the sector and regional insights in this report reflect broader global trends, they are also influenced by the distribution of Darktrace's customer base. For example, Finance, Manufacturing, and Education are strongly represented among Darktrace customers, which may result in a higher number of observed cases in these sectors. This reflects customer distribution rather than necessarily indicating elevated sector-specific risk. Similarly, regional trends may be influenced by the geographic distribution of Darktrace customers.

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Analysis of campaign clusters identified by the Darktrace Threat Research team during the first half of 2026 revealed distinct regional trends.

Europe, Middle East & Africa (EMEA) dominated with 60% of all campaign cluster cases targeting this region.
The Americas (AMS) was the next most affected region, with 30% of campaign cluster cases.
The Asia-Pacific and Japan (APJ) region was less affected by campaign clusters, potentially indicating that threat actors placed a lower priority on the region and instead focused their efforts elsewhere.

Sector targeting also varied considerably by region:

In EMEA, the Information and Communication was the most affected by a significant margin, representing 25% of all cases.
In contrast, AMS targeting was more evenly distributed, with the Education, Public administration and defence, and Financial Insurance activities sectors all forming over 20% of AMS regional cases.
Across APJ, campaign activity was spread more equally, with no single sector emerging as a dominant target.

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Several countries also stood out within their respective regions:

The United States accounted for 60% of all campaign clusters within AMS.
Japan represented 40% of campaign customer cases across APJ.
In EMEA, the United Kingdom and Zimbabwe each accounted for 23% of identified cases, both being involved in a variety of campaign types.

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Inside the SOC & Threat Research 2026 Monthly Progression: From Access to Impact

Month	Dominant Themes
January	Voice phishing, VPS infrastructure, WebSocket C2, RMM abuse, ransomware, infostealers (StealC), and trojanized installers (7-Zip).
February	Voice phishing, VPN intrusion, edge infrastructure compromise (BeyondTrust), and RMM abuse.
March	Sustained supply chain compromise (Hola VPN, Axios, Trivy), malicious browser extensions, phishing, and discovery tools.
April	Account creation abuse, payload delivery, VPN credential abuse, Fortinet exploitation, and botnet activity.
May	PowerShell, EtherHiding, data exfiltration, VPN access, business email compromise (BEC), ClickFix, and infostealers (AMOS).
June	RDP abuse, device registration, RMM usage, voice phishing, cloud data theft, botnet activity, blockchain abuse, ClickFix, and infostealers (AMOS).