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April 27, 2022

How Darktrace AI Blocked Emotet Malspam

Explore Darktrace AI's success in combating Emotet malspam, enhancing security and minimizing risks with cutting-edge artificial intelligence.
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
Zoe Tilsiter
Cyber Analyst
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27
Apr 2022


In January 2021, it was lauded that an international collaborative law enforcement operation had successfully dismantled Emotet’s infrastructure. This was one of the most prolific malware and banking Trojans which led to sensitive data loss, significant financial loss and reputational damage for its victims since early deployment in 2014.1

However, since November 2021, there have been signs of Emotet’s resurgence. Emotet has supposedly leveraged its former partner operators such as Trickbot, also discussed in another Darktrace blog, to rebuild its infrastructure by using already infected machines to download the new Emotet binary.2

Early signs of Emotet’s return appear to be synonymous with its original kill chain and attack vectors. Malware is deployed, compromising a device as a zombie machine. This device is then used to send outbound malspam campaigns. These campaigns can be masked as application installer packages or fake reply email chains to give the spam credibility. Once the malware spreads through this spam, it then attempts to infect other devices – both internally and outbound in other networks.3

In February 2022, Darktrace detected elements of this kill chain in a customer’s environment, notably observing the large volume of SMTP connections which are characteristic of an outbound spam campaign.

Figure 1: Timeline of attack showing the Emotet intrusion progress along the kill chain
Figure 2: A screenshot from VirusTotal, showing that the rare endpoint has been flagged as malicious by other security vendors


Bypassing the rest of the security stack

The attack used Living-off-the-Land techniques by making PowerShell connections via pre-existing user agents within the network. As PowerShell connections can be used for legitimate reasons, this activity appeared to bypass the rest of the customer’s security stack and was likely seen as approved by their tools. However, Darktrace detected that the device was using the PowerShell user agent to connect to an external location. This is rare in comparison to wider network behavior.

The customer’s pre-existing security did not block the outgoing SMTP connections made by the compromised device on unusual ports. However, Darktrace Antigena blocked 71% of outgoing connections on mail ports 25 and 587, significantly reducing the scale of the spam dissemination.

Darktrace insights and services

Darktrace quickly detected a range of anomalous behaviors from the new PowerShell use, uptake in C2 beaconing activity and spam. This can be highlighted via the spike in model breaches (Figure 3). Darktrace’s Cyber AI Analyst also launched an investigation into the device’s suspicious network scanning activity. This was essential for generating an incident summary which outlined the investigation process and technical details needed for the organization’s security team to act quickly (Figure 4).

Throughout the incident, Antigena autonomously responded to the initial breach device to enforce its ‘pattern of life’ without interrupting business processes. This significantly reduced the scope of the compromise by halting further lateral movement. In response to the malicious outbound email spam, Antigena enforced the device’s usual ‘pattern of life’ for thirty minutes and blocked connections to ports 25, 80 and 587 for one hour (Figure 5). Against the command-and-control activity, connections to 91.207.181[.]106 via port 8080 were also blocked for three hours.

The customer’s subscription to Darktrace’s Proactive Threat Notification (PTN) and Ask the Expert (ATE) services meant that this compromise was assisted by additional triage and alerting. PTN ensured that the Darktrace SOC team were quickly alerted to the breach, enabling analysts to perform a detailed investigation alongside the customer’s own security team. Simultaneously, the ATE service ensured the customer was provided with additional information to ensure the threat was less likely to happen again. This equipped the team with the vital information needed for them to act, and to restore quickly and precisely.

Figure 3: Darktrace reveals an anomalous spike in the device’s activity and associated model breaches during the attack period, represented by the dots on the graph


Figure 4: Excerpt of the AI Analyst report of the breach device’s network scanning activity
Figure 5: Antigena Network blocking external connection activity and enforcing the device’s ‘pattern of life’


The resurgence of Emotet shows how email continues to act as a crucial attack vector and source of compromise. In particular, widespread malspam campaigns remain adaptable and effective. The incident in this blog is yet another example highlighting the alarming mutability and networked nature of malware organizations. This allows them to return, even long after their dismantling. Fortunately, in this incident, Autonomous Response enabled this Emotet compromise to be minimized, while PTN and ATE services alerted and further supported the security team throughout.

Appendix

Darktrace model breaches

·    Device / Multiple Lateral Movement Model Breaches

·    Device / Large Number of Model Breaches

·    Device / Suspicious Network Scan Activity

·    Device / Network Scan

·    Device / External Address Scan

·    Device / Multiple C2 Model Breaches

·    Device / Large Number of Connections to New Endpoints

·    Device / Increased External Connectivity

·    Device / New User Agent and New IP

·    Device / New PowerShell User Agent

·    Compromise / Suspicious Beaconing Behavior

·    Compromise / Beacon to Young Endpoint

·    Compromise / Agent Beacon to New Endpoint

·    Compromise / Sustained SSL or HTTP Increase

·    Compromise / Suspicious Spam Activity

·    Anomalous Connection / Possible Outbound Spam

·    Anomalous Connection / Suspicious Expired SSL

·    Anomalous Connection / Rare External SSL Self-Signed

·    Anomalous Connection / Suspicious Self-Signed SSL

·    Anomalous Connection / Anomalous SSL without SNI to New External

·    Anomalous Connection / PowerShell to Rare External

·    AI Analyst / AI Analyst Investigation

·    Unusual Activity / Unusual External Activity

IoCs

MITRE ATT&CK Techniques Observed

Footnotes

1. https://www.cisa.gov/uscert/ncas/alerts/TA18-201A

2. https://blog.malwarebytes.com/threat-intelligence/2021/11/trickbot-helps-emotet-come-back-from-the-dead/

3. https://www.kaspersky.com/resource-center/threats/emotet

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
Zoe Tilsiter
Cyber Analyst

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December 22, 2025

The Year Ahead: AI Cybersecurity Trends to Watch in 2026

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Introduction: 2026 cyber trends

Each year, we ask some of our experts to step back from the day-to-day pace of incidents, vulnerabilities, and headlines to reflect on the forces reshaping the threat landscape. The goal is simple:  to identify and share the trends we believe will matter most in the year ahead, based on the real-world challenges our customers are facing, the technology and issues our R&D teams are exploring, and our observations of how both attackers and defenders are adapting.  

In 2025, we saw generative AI and early agentic systems moving from limited pilots into more widespread adoption across enterprises. Generative AI tools became embedded in SaaS products and enterprise workflows we rely on every day, AI agents gained more access to data and systems, and we saw glimpses of how threat actors can manipulate commercial AI models for attacks. At the same time, expanding cloud and SaaS ecosystems and the increasing use of automation continued to stretch traditional security assumptions.

Looking ahead to 2026, we’re already seeing the security of AI models, agents, and the identities that power them becoming a key point of tension – and opportunity -- for both attackers and defenders. Long-standing challenges and risks such as identity, trust, data integrity, and human decision-making will not disappear, but AI and automation will increase the speed and scale of the cyber risk.  

Here's what a few of our experts believe are the trends that will shape this next phase of cybersecurity, and the realities organizations should prepare for.  

Agentic AI is the next big insider risk

In 2026, organizations may experience their first large-scale security incidents driven by agentic AI behaving in unintended ways—not necessarily due to malicious intent, but because of how easily agents can be influenced. AI agents are designed to be helpful, lack judgment, and operate without understanding context or consequence. This makes them highly efficient—and highly pliable. Unlike human insiders, agentic systems do not need to be socially engineered, coerced, or bribed. They only need to be prompted creatively, misinterpret legitimate prompts, or be vulnerable to indirect prompt injection. Without strong controls around access, scope, and behavior, agents may over-share data, misroute communications, or take actions that introduce real business risk. Securing AI adoption will increasingly depend on treating agents as first-class identities—monitored, constrained, and evaluated based on behavior, not intent.

-- Nicole Carignan, SVP of Security & AI Strategy

Prompt Injection moves from theory to front-page breach

We’ll see the first major story of an indirect prompt injection attack against companies adopting AI either through an accessible chatbot or an agentic system ingesting a hidden prompt. In practice, this may result in unauthorized data exposure or unintended malicious behavior by AI systems, such as over-sharing information, misrouting communications, or acting outside their intended scope. Recent attention on this risk—particularly in the context of AI-powered browsers and additional safety layers being introduced to guide agent behavior—highlights a growing industry awareness of the challenge.  

-- Collin Chapleau, Senior Director of Security & AI Strategy

Humans are even more outpaced, but not broken

When it comes to cyber, people aren’t failing; the system is moving faster than they can. Attackers exploit the gap between human judgment and machine-speed operations. The rise of deepfakes and emotion-driven scams that we’ve seen in the last few years reduce our ability to spot the familiar human cues we’ve been taught to look out for. Fraud now spans social platforms, encrypted chat, and instant payments in minutes. Expecting humans to be the last line of defense is unrealistic.

Defense must assume human fallibility and design accordingly. Automated provenance checks, cryptographic signatures, and dual-channel verification should precede human judgment. Training still matters, but it cannot close the gap alone. In the year ahead, we need to see more of a focus on partnership: systems that absorb risk so humans make decisions in context, not under pressure.

-- Margaret Cunningham, VP of Security & AI Strategy

AI removes the attacker bottleneck—smaller organizations feel the impact

One factor that is currently preventing more companies from breaches is a bottleneck on the attacker side: there’s not enough human hacker capital. The number of human hands on a keyboard is a rate-determining factor in the threat landscape. Further advancements of AI and automation will continue to open that bottleneck. We are already seeing that. The ostrich approach of hoping that one’s own company is too obscure to be noticed by attackers will no longer work as attacker capacity increases.  

-- Max Heinemeyer, Global Field CISO

SaaS platforms become the preferred supply chain target

Attackers have learned a simple lesson: compromising SaaS platforms can have big payouts. As a result, we’ll see more targeting of commercial off-the-shelf SaaS providers, which are often highly trusted and deeply integrated into business environments. Some of these attacks may involve software with unfamiliar brand names, but their downstream impact will be significant. In 2026, expect more breaches where attackers leverage valid credentials, APIs, or misconfigurations to bypass traditional defenses entirely.

-- Nathaniel Jones, VP of Security & AI Strategy

Increased commercialization of generative AI and AI assistants in cyber attacks

One trend we’re watching closely for 2026 is the commercialization of AI-assisted cybercrime. For example, cybercrime prompt playbooks sold on the dark web—essentially copy-and-paste frameworks that show attackers how to misuse or jailbreak AI models. It’s an evolution of what we saw in 2025, where AI lowered the barrier to entry. In 2026, those techniques become productized, scalable, and much easier to reuse.  

-- Toby Lewis, Global Head of Threat Analysis

Conclusion

Taken together, these trends underscore that the core challenges of cybersecurity are not changing dramatically -- identity, trust, data, and human decision-making still sit at the core of most incidents. What is changing quickly is the environment in which these challenges play out. AI and automation are accelerating everything: how quickly attackers can scale, how widely risk is distributed, and how easily unintended behavior can create real impact. And as technology like cloud services and SaaS platforms become even more deeply integrated into businesses, the potential attack surface continues to expand.  

Predictions are not guarantees. But the patterns emerging today suggest that 2026 will be a year where securing AI becomes inseparable from securing the business itself. The organizations that prepare now—by understanding how AI is used, how it behaves, and how it can be misused—will be best positioned to adopt these technologies with confidence in the year ahead.

Learn more about how to secure AI adoption in the enterprise without compromise by registering to join our live launch webinar on February 3, 2026.  

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December 22, 2025

Why Organizations are Moving to Label-free, Behavioral DLP for Outbound Email

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Why outbound email DLP needs reinventing

In 2025, the global average cost of a data breach fell slightly — but remains substantial at USD 4.44 million (IBM Cost of a Data Breach Report 2025). The headline figure hides a painful reality: many of these breaches stem not from sophisticated hacks, but from simple human error: mis-sent emails, accidental forwarding, or replying with the wrong attachment. Because outbound email is a common channel for sensitive data leaving an organization, the risk posed by everyday mistakes is enormous.

In 2025, 53% of data breaches involved customer PII, making it the most commonly compromised asset (IBM Cost of a Data Breach Report 2025). This makes “protection at the moment of send” essential. A single unintended disclosure can trigger compliance violations, regulatory scrutiny, and erosion of customer trust –consequences that are disproportionate to the marginal human errors that cause them.

Traditional DLP has long attempted to mitigate these impacts, but it relies heavily on perfect labelling and rigid pattern-matching. In reality, data loss rarely presents itself as a neat, well-structured pattern waiting to be caught – it looks like everyday communication, just slightly out of context.

How data loss actually happens

Most data loss comes from frustratingly familiar scenarios. A mistyped name in auto-complete sends sensitive data to the wrong “Alex.” A user forwards a document to a personal Gmail account “just this once.” Someone shares an attachment with a new or unknown correspondent without realizing how sensitive it is.

Traditional, content-centric DLP rarely catches these moments. Labels are missing or wrong. Regexes break the moment the data shifts formats. And static rules can’t interpret the context that actually matters – the sender-recipient relationship, the communication history, or whether this behavior is typical for the user.

It’s the everyday mistakes that hurt the most. The classic example: the Friday 5:58 p.m. mis-send, when auto-complete selects Martin, a former contractor, instead of Marta in Finance.

What traditional DLP approaches offer (and where gaps remain)

Most email DLP today follows two patterns, each useful but incomplete.

  • Policy- and label-centric DLP works when labels are correct — but content is often unlabeled or mislabeled, and maintaining classification adds friction. Gaps appear exactly where users move fastest
  • Rule and signature-based approaches catch known patterns but miss nuance: human error, new workflows, and “unknown unknowns” that don’t match a rule

The takeaway: Protection must combine content + behavior + explainability at send time, without depending on perfect labels.

Your technology primer: The three pillars that make outbound DLP effective

1) Label-free (vs. data classification)

Protects all content, not just what’s labeled. Label-free analysis removes classification overhead and closes gaps from missing or incorrect tags. By evaluating content and context at send time, it also catches misdelivery and other payload-free errors.

  • No labeling burden; no regex/rule maintenance
  • Works when tags are missing, wrong, or stale
  • Detects misdirected sends even when labels look right

2) Behavioral (vs. rules, signatures, threat intelligence)

Understands user behavior, not just static patterns. Behavioral analysis learns what’s normal for each person, surfacing human error and subtle exfiltration that rules can’t. It also incorporates account signals and inbound intel, extending across email and Teams.

  • Flags risk without predefined rules or IOCs
  • Catches misdelivery, unusual contacts, personal forwards, odd timing/volume
  • Blends identity and inbound context across channels

3) Proprietary DSLM (vs. generic LLM)

Optimized for precise, fast, explainable on-send decisions. A DSLM understands email/DLP semantics, avoids generative risks, and stays auditable and privacy-controlled, delivering intelligence reliably without slowing mail flow.

  • Low-latency, on-send enforcement
  • Non-generative for predictable, explainable outcomes
  • Governed model with strong privacy and auditability

The Darktrace approach to DLP

Darktrace / EMAIL – DLP stops misdelivery and sensitive data loss at send time using hold/notify/justify/release actions. It blends behavioral insight with content understanding across 35+ PII categories, protecting both labeled and unlabeled data. Every action is paired with clear explainability: AI narratives show exactly why an email was flagged, supporting analysts and helping end-users learn. Deployment aligns cleanly with existing SOC workflows through mail-flow connectors and optional Microsoft Purview label ingestion, without forcing duplicate policy-building.

Deployment is simple: Microsoft 365 routes outbound mail to Darktrace for real-time, inline decisions without regex or rule-heavy setup.

A buyer’s checklist for DLP solutions

When choosing your DLP solution, you want to be sure that it can deliver precise, explainable protection at the moment it matters – on send – without operational drag.  

To finish, we’ve compiled a handy list of questions you can ask before choosing an outbound DLP solution:

  • Can it operate label free when tags are missing or wrong? 
  • Does it truly learn per user behavior (no shortcuts)? 
  • Is there a domain specific model behind the content understanding (not a generic LLM)? 
  • Does it explain decisions to both analysts and end users? 
  • Will it integrate with your label program and SOC workflows rather than duplicate them? 

For a deep dive into Darktrace’s DLP solution, check out the full solution brief.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email
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