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October 26, 2022

Strategies to Prolong Quantum Ransomware Attacks

Learn more about how Darktrace combats Quantum Ransomware changing strategy for cyberattacks. Explore the power of AI-driven network cyber security!
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
Nicole Wong
Cyber Security Analyst
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26
Oct 2022

Within science and engineering, the word ‘quantum’ may spark associations with speed and capability, referencing a superior computer that can perform tasks a classical computer cannot. In cyber security, some may recognize ‘quantum’ in relation to cryptography or, more recently, as the name of a new ransomware group, which achieved network-wide encryption a mere four hours after an initial infection.   

Although this group now has a reputation for carrying out fast and efficient attacks, speed is not their only tactic. In August 2022, Darktrace detected a Quantum Ransomware incident where attackers remained in the victim’s network for almost a month after the initial signs of infection, before detonating ransomware. This was a stark difference to previously reported attacks, demonstrating that as motives change, so do threat actors’ strategies. 

The Quantum Group

Quantum was first identified in August 2021 as the latest of several rebrands of MountLocker ransomware [1]. As part of this rebrand, the extension ‘.quantum’ is appended to filenames that are encrypted and the associated ransom notes are named ‘README_TO_DECRYPT.html’ [2].  

From April 2022, media coverage of this group has increased following a DFIR report detailing an attack that progressed from initial access to domain-wide ransomware within four hours [3]. To put this into perspective, the global median dwell time for ransomware in 2020 and 2021 is 5 days [4]. In the case of Quantum, threat actors gained direct keyboard access to devices merely 2 hours after initial infection. The ransomware was staged on the domain controller around an hour and a half later, and executed 12 minutes after that.   

Quantum’s behaviour bears similarities to other groups, possibly due to their history and recruitment. Several members of the disbanded Conti ransomware group are reported to have joined the Quantum and BumbleBee operations. Security researchers have also identified similarities in the payloads and C2 infrastructure used by these groups [5 & 6].  Notably, these are the IcedID initial payload and Cobalt Strike C2 beacon used in this attack. Darktrace has also observed and prevented IcedID and Cobalt Strike activity from BumbleBee across several customer environments.

The Attack

From 11th July 2022, a device suspected to be patient zero made repeated DNS queries for external hosts that appear to be associated with IcedID C2 traffic [7 & 8]. In several reported cases [9 & 10], this banking trojan is delivered through a phishing email containing a malicious attachment that loads an IcedID DLL. As Darktrace was not deployed in the prospect’s email environment, there was no visibility of the initial access vector, however an example of a phishing campaign containing this payload is presented below. It is also possible that the device was already infected prior to joining the network. 

Figure 1- An example phishing email used to distribute IcedID. If configured, Darktrace/Email would be able to detect that the email was sent from an anomalous sender, was part of a fake reply chain, and had a suspicious attachment containing compressed content of unusual mime type [11].    

 

Figure 2- The DNS queries to endpoints associated with IcedID C2 servers, taken from the infected device’s event log.  Additional DNS queries made to other IcedID C2 servers are in the list of IOCs in the appendices.  The repeated DNS queries are indicative of beaconing.


It was not until 22nd July that activity was seen which indicated the attack had progressed to the next stage of the kill chain. This contrasts the previously seen attacks where the progression to Cobalt Strike C2 beaconing and reconnaissance and lateral movement occurred within 2 hours of the initial infection [12 & 13]. In this case, patient zero initiated numerous unusual connections to other internal devices using a compromised account, connections that were indicative of reconnaissance using built-in Windows utilities:

·      DNS queries for hostnames in the network

·      SMB writes to IPC$ shares of those hostnames queried, binding to the srvsvc named pipe to enumerate things such as SMB shares and services on a device, client access permissions on network shares and users logged in to a remote session

·      DCE-RPC connections to the endpoint mapper service, which enables identification of the ports assigned to a particular RPC service

These connections were initiated using an existing credential on the device and just like the dwelling time, differed from previously reported Quantum group attacks where discovery actions were spawned and performed automatically by the IcedID process [14]. Figure 3 depicts how Darktrace detected that this activity deviated from the device’s normal behaviour.  

Figure 3- This figure displays the spike in active internal connections initiated by patient zero. The coloured dots represent the Darktrace models that were breached, detecting this unusual reconnaissance and lateral movement activity.

Four days later, on the 26th of July, patient zero performed SMB writes of DLL and MSI executables to the C$ shares of internal devices including domain controllers, using a privileged credential not previously seen on the patient zero device. The deviation from normal behaviour that this represents is also displayed in Figure 3. Throughout this activity, patient zero made DNS queries for the external Cobalt Strike C2 server shown in Figure 4. Cobalt Strike has often been seen as a secondary payload delivered via IcedID, due to IcedID’s ability to evade detection and deploy large scale campaigns [15]. It is likely that reconnaissance and lateral movement was performed under instructions received by the Cobalt Strike C2 server.   

Figure 4- This figure is taken from Darktrace’s Advanced Search interface, showing a DNS query for a Cobalt Strike C2 server occurring during SMB writes of .dll files and DCE-RPC requests to the epmapper service, demonstrating reconnaissance and lateral movement.


The SMB writes to domain controllers and usage of a new account suggests that by this stage, the attacker had achieved domain dominance. The attacker also appeared to have had hands-on access to the network via a console; the repetition of the paths ‘programdata\v1.dll’ and ‘ProgramData\v1.dll’, in lower and title case respectively, suggests they were entered manually.  

These DLL files likely contained a copy of the malware that injects into legitimate processes such as winlogon, to perform commands that call out to C2 servers [16]. Shortly after the file transfers, the affected domain controllers were also seen beaconing to external endpoints (‘sezijiru[.]com’ and ‘gedabuyisi[.]com’) that OSINT tools have associated with these DLL files [17 & 18]. Moreover, these SSL connections were made using a default client fingerprint for Cobalt Strike [19], which is consistent with the initial delivery method. To illustrate the beaconing nature of these connections, Figure 5 displays the 4.3 million daily SSL connections to one of the C2 servers during the attack. The 100,000 most recent connections were initiated by 11 unique source IP addresses alone.

Figure 5- The Advanced Search interface, querying for external SSL connections from devices in the network to an external host that appears to be a Cobalt Strike C2 server. 4.3 million connections were made over 8 days, even after the ransomware was eventually detonated on 2022-08-03.


Shortly after the writes, the attack progressed to the penultimate stage. The next day, on the 27th of July, the attackers moved to achieve their first objective: data exfiltration. Data exfiltration is not always performed by the Quantum ransomware gang. Researchers have noted discrepancies between claims of data theft made in their ransom notes versus the lack of data seen leaving the network, although this may have been missed due to covert exfiltration via a Cobalt Strike beacon [20]. 

In contrast, this attack displayed several gigabytes of data leaving internal devices including servers that had previously beaconed to Cobalt Strike C2 servers. This data was transferred overtly via FTP, however the attacker still attempted to conceal the activity using ephemeral ports (FTP in EPSV mode). FTP is an effective method for attackers to exfiltrate large files as it is easy to use, organizations often neglect to monitor outbound usage, and it can be shipped through ports that will not be blocked by traditional firewalls [21].   

Figure 6 displays an example of the FTP data transfer to attacker-controlled infrastructure, in which the destination share appears structured to identify the organization that the data was stolen from, suggesting there may be other victim organizations’ data stored. This suggests that data exfiltration was an intended outcome of this attack. 

Figure 6- This figure is from Darktrace’s Advanced Search interface, displaying some of the data transferred from an internal device to the attacker’s FTP server.

 
Data was continuously exfiltrated until a week later when the final stage of the attack was achieved and Quantum ransomware was detonated. Darktrace detected the following unusual SMB activity initiated from the attacker-created account that is a hallmark for ransomware (see Figure 7 for example log):

·      Symmetric SMB Read to Write ratio, indicative of active encryption

·      Sustained MIME type conversion of files, with the extension ‘.quantum’ appended to filenames

·      SMB writes of a ransom note ‘README_TO_DECRYPT.html’ (see Figure 8 for an example note)

Figure 7- The Model Breach Event Log for a device that had files encrypted by Quantum ransomware, showing the reads and writes of files with ‘.quantum’ appended to encrypted files, and an HTML ransom note left where the files were encrypted.

 

Figure 8- An example of the ransom note left by the Quantum gang, this one is taken from open-sources [22].


The example in Figure 8 mentions that the attacker also possessed large volumes of victim data.  It is likely that the gigabytes of data exfiltrated over FTP were leveraged as blackmail to further extort the victim organization for payment.  

Darktrace Coverage

 

Figure 9- Timeline of Quantum ransomware incident


If Darktrace/Email was deployed in the prospect’s environment, the initial payload (if delivered through a phishing email) could have been detected and held from the recipient’s inbox. Although DETECT identified anomalous network behaviour at each stage of the attack, since the incident occurred during a trial phase where Darktrace could only detect but not respond, the attack was able to progress through the kill chain. If RESPOND/Network had been configured in the targeted environment, the unusual connections observed during the initial access, C2, reconnaissance and lateral movement stages of the attack could have been blocked. This would have prevented the attackers from delivering the later stage payloads and eventual ransomware into the target network.

It is often thought that a properly implemented backup strategy is sufficient defense against ransomware [23], however as discussed in a previous Darktrace blog, the increasing frequency of double extortion attacks in a world where ‘data is the new oil’ demonstrates that backups alone are not a mitigation for the risk of a ransomware attack [24]. Equally, the lack of preventive defenses in the target’s environment enabled the attacker’s riskier decision to dwell in the network for longer and allowed them to optimize their potential reward. 

Recent crackdowns from law enforcement on ransomware groups have shifted these groups’ approaches to aim for a balance between low risk and significant financial rewards [25]. However, given the Quantum gang only have a 5% market share in Q2 2022, compared to the 13.2% held by LockBit and 16.9% held by BlackCat [26], a riskier strategy may be favourable, as a longer dwell time and double extortion outcome offers a ‘belt and braces’ approach to maximizing the rewards from carrying out this attack. Alternatively, the gaps in-between the attack stages may imply that more than one player was involved in this attack, although this group has not been reported to operate a franchise model before [27]. Whether assisted by others or driving for a risk approach, it is clear that Quantum (like other actors) are continuing to adapt to ensure their financial success. They will continue to be successful until organizations dedicate themselves to ensuring that the proper data protection and network security measures are in place. 

Conclusion 

Ransomware has evolved over time and groups have merged and rebranded. However, this incident of Quantum ransomware demonstrates that regardless of the capability to execute a full attack within hours, prolonging an attack to optimize potential reward by leveraging double extortion tactics is sometimes still the preferred action. The pattern of network activity mirrors the techniques used in other Quantum attacks, however this incident lacked the continuous progression of the group’s attacks reported recently and may represent a change of motives during the process. Knowing that attacker motives can change reinforces the need for organizations to invest in preventative controls- an organization may already be too far down the line if it is executing its backup contingency plans. Darktrace DETECT/Network had visibility over both the early network-based indicators of compromise and the escalation to the later stages of this attack. Had Darktrace also been allowed to respond, this case of Quantum ransomware would also have had a very short dwell time, but a far better outcome for the victim.

Thanks to Steve Robinson for his contributions to this blog.

Appendices

References

[1] https://community.ibm.com/community/user/security/blogs/tristan-reed/2022/07/13/ibm-security-reaqta-vs-quantum-locker-ransomware

 

[2] https://www.bleepingcomputer.com/news/security/quantum-ransomware-seen-deployed-in-rapid-network-attacks/

 

[3], [12], [14], [16], [20] https://thedfirreport.com/2022/04/25/quantum-ransomware/

 

[4] https://www.mandiant.com/sites/default/files/2022-04/M-Trends%202022%20Executive%20Summary.pdf

 

[5] https://cyware.com/news/over-650-healthcare-organizations-affected-by-the-quantum-ransomware-attack-d0e776bb/

 

[6] https://www.kroll.com/en/insights/publications/cyber/bumblebee-loader-linked-conti-used-in-quantum-locker-attacks

 

[7] https://github.com/pan-unit42/tweets/blob/master/2022-06-28-IOCs-for-TA578-IcedID-Cobalt-Strike-and-DarkVNC.txt 

 

[8] https://github.com/stamparm/maltrail/blob/master/trails/static/malware/icedid.txt

 

[9], [15] https://www.cynet.com/blog/shelob-moonlight-spinning-a-larger-web-from-icedid-to-conti-a-trojan-and-ransomware-collaboration/

 

[10] https://www.microsoft.com/security/blog/2021/04/09/investigating-a-unique-form-of-email-delivery-for-icedid-malware/

 

[11] https://twitter.com/0xToxin/status/1564289244084011014

 

[13], [27] https://cybernews.com/security/quantum-ransomware-gang-fast-and-furious/

 

[17] https://www.virustotal.com/gui/domain/gedabuyisi.com/relations

 

[18] https://www.virustotal.com/gui/domain/sezijiru.com/relations.

 

[19] https://github.com/ByteSecLabs/ja3-ja3s-combo/blob/master/master-list.txt 

 

[21] https://www.darkreading.com/perimeter/ftp-hacking-on-the-rise

 

[22] https://www.pcrisk.com/removal-guides/23352-quantum-ransomware

 

[23] https://www.cohesity.com/resource-assets/tip-sheet/5-ways-ransomware-renders-backup-useless-tip-sheet-en.pdf

 

[24] https://www.forbes.com/sites/nishatalagala/2022/03/02/data-as-the-new-oil-is-not-enough-four-principles-for-avoiding-data-fires/ 

 

[25] https://www.bleepingcomputer.com/news/security/access-to-hacked-corporate-networks-still-strong-but-sales-fall/

 

[26] https://www.bleepingcomputer.com/news/security/ransom-payments-fall-as-fewer-victims-choose-to-pay-hackers/ 

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
Nicole Wong
Cyber Security Analyst

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December 4, 2025

How Darktrace is ending email security silos with new capabilities in cross-domain detection, DLP, and native Microsoft integrations

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A new era of reputation-aware, unified email security

Darktrace / EMAIL is redefining email defense with new innovations that close email security silos and empower SOC teams to stop multi-stage attacks – without disrupting business operations.  

By extending visibility across interconnected domains, Darktrace catches the 17% of threats that leading SEGs miss, including multi-stage attacks like email bombing and cloud platform abuse. Its label-free behavioral DLP protects sensitive data without reliance on manual rules or classification, while DMARC strengthens brand trust and authenticity. With native integrations for Microsoft Defender and Security Copilot, SOC teams can now investigate and respond faster, reducing risk and maintaining operational continuity across the enterprise.

Summary of what’s new:

  • Cross-domain AI-native detection unifying email, identity, and SaaS
  • Label-free behavioral DLP for effortless data protection
  • Microsoft Defender and Security Copilot integrations for streamlined investigation and response

Why email security must evolve

Today’s attacks don’t stop at the inbox. They move across domains – email to identity, SaaS, and network – exploiting the blind spots between disconnected tools. Yet most email security solutions still operate in isolation, unable to see or respond beyond the message itself.

In 2024, Darktrace detected over 30 million phishing attempts: 38% targeting high-value individuals and almost a third using novel social engineering, including AI-generated text. Generative AI is amplifying the realism and scale of social engineering, while customers face a wave of new techniques like email bombing, where attackers flood inboxes to distract or manipulate users, and polymorphic malware, which continuously evolves to evade static defenses.

Meanwhile, defenders are exposed to traditional DLP tools that create operational drag with high false positives and rigid policies. Accidental insider breachers remain a major risk to organizations: 6% of all data breaches are caused by misdelivery, and 95% of those incidents involve personal data.

Tool sprawl compounds the issue. The average enterprise manages around 75 security products, and 69% report operational strain as a result. This complexity is counterproductive – and with legacy SEGs failing to adapt to detect threats that exploit human behavior, analysts are left juggling an unwieldy patchwork of fragmented defenses.

The bottom line? Siloed email defenses can’t keep pace with today’s AI-driven, cross domain attacks.

Beyond detection: AI built for modern threats

Darktrace / EMAIL is uniquely designed to catch the threats SEGs miss, powered by Self-Learning AI. It learns the communication patterns of every user – correlating behavioral signals from email, identity, and SaaS – to identify the subtle, context-driven deviations that define advanced social engineering and supply chain attacks.

Unlike tools that rely on static rules or historical attack data, Darktrace’s AI assumes a zero trust posture, treating every interaction as a potential risk. It detects novel threats in real time, including those that exploit trusted relationships or mimic legitimate business processes. And because Darktrace’s technology is natively unified, it delivers precise, coordinated responses that neutralize threats in real time.

Powerful innovations to Darktrace / EMAIL

Improved, multi-domain threat detection and response

With this update, Darktrace reveals multi-domain detection linking behavioral signals across email, identity, and SaaS to uncover advanced attacks. Darktrace leverages its existing agentic platform to understand behavioral deviations in any communication channel and take precise actions regardless of the domain.  

This innovation enables customers to:

  • Correlate behavioral signals across domains to expose cross-channel threats and enable coordinated response
  • Link email and identity intelligence to neutralize multi-stage attacks, including advanced email bombing campaigns

Detection accuracy is further strengthened through layering with traditional threat intelligence:

  • Integrated antivirus verdicts improve detection efficacy by adding traditional file scanning
  • Structured threat intelligence (STIX/TAXII) enriches alerts with global context for faster triage and prioritization

Expanded ecosystem visibility also includes:

  • Salesforce integration, enabling automatic action on potentially malicious tickets auto-created from emails – accelerating threat response and reducing manual burden

Advancements in label-free DLP

Darktrace is delivering the industry’s first label-free data loss prevention (DLP) solution powered by a proprietary domain specific language model (DSLM).  

This update expands DLP to protect against both secrets and personally identifiable information (PII), safeguarding sensitive data without relying on status rules or manual classification. The DSLM is tuned for email/DLP semantics so it understands entities, PII patterns, and message context quickly enough to enforce at send time.

Key enhancements include:

  • Behaviorally enhanced PII detection that automatically defines over 35+ new categories, including personal, financial, and health data  
  • Added detail to DLP alerts in the UI, showing exactly how and when DLP policies were applied
  • Enhanced Cyber AI Analyst narratives to explain detection logic, making it easier to investigate and escalate incidents

And for further confidence in outbound mail, discover new updates to DMARC, with support for BIMI logo verification, automatic detection of both MTA-STS and TLS records, and data exports for deeper analysis and reporting. Accessible for all organizations, available now on the Azure marketplace.

Streamlined SOC workflows, with Microsoft-native integrations

This update introduces new integrations that simplify SOC operations, unify visibility, and accelerate response. By embedding directly into the Microsoft ecosystem – with Defender and Security Copilot – analysts gain instant access to correlated insights without switching consoles.

New innovations include:

  • Unified quarantine management with Microsoft Defender, centralizing containment within the native Microsoft interface and eliminating console hopping
  • Ability to surface threat insights directly in Copilot via the Darktrace Email Analysis Agent, eliminating data hunting and simplifying investigations
  • Automatic ticket creation in JIRA when users report suspicious messages
  • Sandbox analysis integration, enabling payload inspection in isolated environments directly from the Darktrace UI

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

  1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.
  2. Redefining NDR with industry-first autonomous threat investigation from network to endpoint  
  3. Innovations to our suite of Exposure Management & Attack Surface Management tools

As attackers exploit gaps between tools, the Darktrace ActiveAI Security Platform delivers unified detection, automated investigation, and autonomous response across cloud, endpoint, email, network, and OT. With full-stack visibility and AI-native workflows, Darktrace empowers security teams to detect, understand, and stop novel threats before they escalate.

Join our Live Launch Event

When? December 9, 2025

What will be covered? Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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December 4, 2025

The 17% of email threats SEGs miss – and how Darktrace catches them

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17%: The figure that changes your risk math

Most organizations deploy a Secure Email Gateway (SEG) assuming it will catch whatever their native email security provider would not be able to. But the data tells a different story. Nearly one in six of the riskiest inbound emails still evade the native + SEG layers on the first pass – 17% is the average SEG miss rate after Microsoft filtering.  

How did we calculate the miss rate? The figure comes from a volume-weighted analysis of real-world enterprise deployments where Darktrace operated alongside a SEG, compared to deployments without a SEG. It’s based on how each security layer treated malicious emails on the first instance – if the SEG missed the email at the initial filtering but caught it minutes or hours later we considered it a miss, because the threat had already been exposed to the user. We computed the mean per category miss count across the top three widely deployed SEGs and divided that by the total number of threats that had already bypassed native filters. The resulting rate is 17.8%, conservatively communicated as “about 17%.”

This result is a powerful directional signal – not a guarantee for every environment – but significant enough to merit a closer look.

What SEGs miss most (and why it matters)

Our analysis shows that SEGs most frequently miss context-driven, low-signal attacks.

Darktrace catches more threats than SEGs across a range of attack vectors

These are the kinds of emails that look convincing to recipients and rely on business context, without overtly malicious indicators, including:

Solicitation and fraudulent requests (~21% miss rate)

Deceptive invoices, vendor “updates,” payment term changes, or urgent favors. These messages often lack obvious payloads and exploit business process mimicry, making them nearly indistinguishable from genuine correspondence in the eyes of static, rule-based filters dependent on payload analysis. 22% of breaches stemming from external actors were a result of social engineering in 2025 (Verizon 2025 Data Breach Investigations Report).

Phishing links (~20% miss rate)

Links to credential harvesters or later-weaponized sites using new or compromised domains, redirects, or shorteners. URL rotation and staging evade list-based controls; the linguistic and workflow context looks routine. This also includes threats that leverage legitimate cloud platforms to disguise their intent and avoid reputation analysis.  Phishing remains one of the most expensive cause of breaches, an average cost of $4.8 million (IBM Cost of a Data Breach Report 2025).

User impersonation (~19% miss rate)

Convincing messages that mimic executives, colleagues, or partners, often with subtle display-name or address manipulation. These attacks rely on social engineering and context, bypassing static detection and reputation checks.

Other notable misses: Credential harvesting lures and forged/abused sender addresses, both typically light on static indicators but heavy on contextual clues. 

Why SEGs miss these emails

Let’s look at some of the reasons SEGs fail to catch more advanced, context-driven attacks.

  1. Attack-centric bias. SEGs excel at recognizing known-bad indicators (spam, commodity malware). But today’s high-impact threats are supercharged by AI and can be hyper-customized with polymorphic malware or personalized social engineering. They mirror normal business communications and weaponize trust, not binary patterns.  
  2. Limited behavioral understanding. Without modeling each user’s “normal” pattern of life, subtle anomalies (timing, tone, counterpart, transaction patterns) can look benign, even if they should be flagged. Some modern solutions have begun to incorporate behavioral analysis into their products, but these are still supplements for additional information rather than integrated into the core threat detection engine.
  3. Assumed trust. Account compromise and attacks that abuse legitimate services exploit trust. SEGs weren’t designed to handle these kinds of threats, in fact, they assume trust in order to minimize false positives, leaving them wide open to attackers.  
  4. Siloed detection. Email rarely tells the whole story. Attacks pivot across email, identity, and SaaS; single-channel tools can’t connect those dots in real time. This issue is exacerbated when email security vendors are only focused on email activity, ignoring activity beyond the inbox like network or cloud account activity.
  5. Adaptive evasion. Fast domain churn, benign-looking links, and clean hosting on trusted platforms routinely outpace static rules and blocklists. No matter how great your threat intelligence or threat research teams may be, there is a reliance on a first victim – which leads to defenders remaining one step behind attackers. 

How Darktrace / EMAIL catches the threats SEGs miss

Everywhere a SEG falters, Darktrace excels. Let’s take a look why.

  • Self-Learning AI: Darktrace learns the unique communication patterns of every user, department, and supplier, flagging the subtle deviations that typify social engineering and impersonation. 
  • A zero trust approach: According to Gartner, many organizations fail to extend their zero-trust strategy to email, leaving a critical gap. Darktrace assumes no trust, applying the zero trust principle across all aspects of email communication.
  • Cross-domain context: Correlates behavior across email, identity, and SaaS, exposing multi-stage campaigns that a siloed SEG can’t piece together. 
  • Better together with native providers: Operates alongside your native email security – not against it – so protection is additive. Darktrace ingests native signals and orchestrate unified quarantine without duplicating policy stacks or forcing you to disable built-in protections. 

For example: one of our customers, a global enterprise saw a surge of “document-share” notifications from a trusted collaboration platform. The domain and authentication looked fine; their SEG allowed it. Darktrace / EMAIL flagged it because the supplier’s sharing behavior and permission scope deviated from normal (volume, recipients, and access level). Follow-up confirmed the supplier account was compromised. Behavioral context – not rules or signatures – made the difference. 

Three steps to building a modern email security stack

Let’s end with three strategic takeaways for ensuring your email security is fit-for-purpose.

  1. Defense-in-depth = diversity, not duplication

Why it matters: Two security layers with the same detection philosophy (e.g. SEG + native email security) create overlapping blind spots. Both native email security providers and SEGs are attack-centric solutions that rely on past threats and threat intelligence. True defense-in-depth ensures you are asking different questions of every email that comes through.

How to apply: Pair your native email security with behavioral AI that learns how your business communicates. Eliminate redundant layers that only add cost and latency. 

  1. Coordinate the layers you keep

Why it matters:  Layers that don’t talk create delays and hand-offs; SEGs often become sole decision-makers by forcing native protections off. 

How to apply:  Favor an ICES approach that ingests native signals and can orchestrate unified quarantine, so detections become actions in one motion. 

  1. Quantify your security gap with a POV

Why it matters:  Every environment is different. You need evidence before making changes to your stack.

How to apply:  Run Darktrace / EMAIL in observe mode next to your current stack to surface exactly what’s still getting through. Use those results to plan your transition and measure improvement. 

Ready to claim 17% more protection? Request a demo with Darktrace / EMAIL to quantify what your SEG is missing, then decide how much of that residual risk you’re willing to accept. We’ll help you plan a clean, staged transition that preserves native protections and streamlines operations.  In the meantime, calculate your potential ROI using Darktrace / EMAIL with our handy calculator.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email
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