January 30, 2025

Reimagining Your SOC: Overcoming Alert Fatigue with AI-Led Investigations

Reimagining your SOC Part 2/3: This blog explores how the challenges facing the modern SOC can be addressed by transforming the investigation process, unlocking efficiency and scalability in SOC operations with AI.

Written by

Brittany Woodsmall

Product Marketing Manager, AI & Attack Surface

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

Brittany Woodsmall

Product Marketing Manager, AI & Attack Surface

Jan 2025

The efficiency of a Security Operations Center (SOC) hinges on its ability to detect, analyze and respond to threats effectively. With advancements in AI and automation, key early SOC team metrics such as Mean Time to Detect (MTTD) have seen significant improvements:

‍96% of defenders believing AI-powered solutions significantly boost the speed and efficiency of prevention, detection, response, and recovery.
Organizations leveraging AI and automation can shorten their breach lifecycle by an average of 108 days compared to those without these technologies.

While tool advances have improved performance and effectiveness in the detection phase, this has not been as beneficial to the next step of the process where initial alerts are investigated further to determine their relevance and how they relate to other activities. This is often measured with the metric Mean Time to Analysis (MTTA), although some SOC teams operate a two-level process with teams for initial triage to filter out more obviously uninteresting alerts and for more detailed analysis of the remainder. SOC teams continue to grapple with alert fatigue, overwhelmed analysts, and inefficient triage processes, preventing them from achieving the operational efficiency necessary for a high-performing SOC.

Addressing this core inefficiency requires extending AI's capabilities beyond detection to streamline and optimize the following investigative workflows that underpin effective analysis.

Challenges with SOC alert investigation

Detecting cyber threats is only the beginning of a much broader challenge of SOC efficiency. The real bottleneck often lies in the investigation process.

Detection tools and techniques have evolved significantly with the use of machine learning methods, improving early threat detection. However, after a detection pops up, human analysts still typically step in to evaluate the alert, gather context, and determine whether it’s a true threat or a false alarm and why. If it is a threat, further investigation must be performed to understand the full scope of what may be a much larger problem. This phase, measured by the mean time to analysis, is critical for swift incident response.

Challenges with manual alert investigation:

Too many alerts
Alerts lack context
Cognitive load sits with analysts
Insufficient talent in the industry
Fierce competition for experienced analysts

For many organizations, investigation is where the struggle of efficiency intensifies. Analysts face overwhelming volumes of alerts, a lack of consolidated context, and the mental strain of juggling multiple systems. With a worldwide shortage of 4 million experienced level two and three SOC analysts, the cognitive burden placed on teams is immense, often leading to alert fatigue and missed threats.

Even with advanced systems in place not all potential detections are investigated. In many cases, only a quarter of initial alerts are triaged (or analyzed). However, the issue runs deeper. Triaging occurs after detection engineering and alert tuning, which often disable many alerts that could potentially reveal true threats but are not accurate enough to justify the time and effort of the security team. This means some potential threats slip through unnoticed.

Understanding alerts in the SOC: Stopping cyber incidents is hard

Let’s take a look at the cyber-attack lifecycle and the steps involved in detecting and stopping an attack:

First we need a trace of an attack…

The attack will produce some sort of digital trace. Novel attacks, insider threats, and attacker techniques such as living-off-the-land can make attacker activities extremely hard to distinguish.

A detection is created…

Then we have to detect the trace, for example some beaconing to a rare domain. Initial detection alerts being raised underpin the MTTD (mean time to detection). Reducing this initial unseen duration is where we have seen significant improvement with modern threat detection tools.

When it comes to threat detection, the possibilities are vast. Your initial lead could come from anything: an alert about unusual network activity, a potential known malware detection, or an odd email. Once that lead comes in, it’s up to your security team to investigate further and determine if this is this a legitimate threat or a false alarm and what the context is behind the alert.

Investigation begins…

It doesn’t just stop at a detection. Typically, humans also need to look at the alert, investigate, understand, analyze, and conclude whether this is a genuine threat that needs a response. We normally measure this as MTTA (mean time to analyze).

Conducting the investigation effectively requires a high degree of skill and efficiency, as every second counts in mitigating potential damage. Security teams must analyze the available data, correlate it across multiple sources, and piece together the timeline of events to understand the full scope of the incident. This process involves navigating through vast amounts of information, identifying patterns, and discerning relevant details. All while managing the pressure of minimizing downtime and preventing further escalation.

Containment begins…

Once we confirm something as a threat, and the human team determines a response is required and understand the scope, we need to contain the incident. That's normally the MTTC (mean time to containment) and can be further split into immediate and more permanent measures.

For more about how AI-led solutions can help in the containment stage read here: Autonomous Response: Streamlining Cybersecurity and Business Operations

The challenge is not only in 1) detecting threats quickly, but also 2) triaging and investigating them rapidly and with precision, and 3) prioritizing the most critical findings to avoid missed opportunities. Effective investigation demands a combination of advanced tools, robust workflows, and the expertise to interpret and act on the insights they generate. Without these, organizations risk delaying critical containment and response efforts, leaving them vulnerable to greater impacts.

While there are further steps (remediation, and of course complete recovery) here we will focus on investigation.

Developing an AI analyst: How Darktrace replicates human investigation

Darktrace has been working on understanding the investigative process of a skilled analyst since 2017. By conducting internal research between Darktrace expert SOC analysts and machine learning engineers, we developed a formalized understanding of investigative processes. This understanding formed the basis of a multi-layered AI system that systematically investigates data, taking advantage of the speed and breadth afforded by machine systems.

With this research we found that the investigative process often revolves around iterating three key steps: hypothesis creation, data collection, and results evaluation.

All these details are crucial for an analyst to determine the nature of a potential threat. Similarly, they are integral components of our Cyber AI Analyst which is an integral component across our product suite. In doing so, Darktrace has been able to replicate the human-driven approach to investigating alerts using machine learning speed and scale.

Here’s how it works:

When an initial or third-party alert is triggered, the Cyber AI Analyst initiates a forensic investigation by building multiple hypotheses and gathering relevant data to confirm or refute the nature of suspicious activity, iterating as necessary, and continuously refining the original hypothesis as new data emerges throughout the investigation.
Using a combination of machine learning including supervised and unsupervised methods, NLP and graph theory to assess activity, this investigation engine conducts a deep analysis with incidents raised to the human team only when the behavior is deemed sufficiently concerning.
After classification, the incident information is organized and processed to generate the analysis summary, including the most important descriptive details, and priority classification, ensuring that critical alerts are prioritized for further action by the human-analyst team.
If the alert is deemed unimportant, the complete analysis process is made available to the human team so that they can see what investigation was performed and why this conclusion was drawn.

Darktrace cyber ai analyst workflow, how it works

To illustrate this via example, if a laptop is beaconing to a rare domain, the Cyber AI Analyst would create hypotheses including whether this could be command and control traffic, data exfiltration, or something else. The AI analyst then collects data, analyzes it, makes decisions, iterates, and ultimately raises a new high-level incident alert describing and detailing its findings for human analysts to review and follow up.

Learn more about Darktrace's Cyber AI Analyst

Cost savings: Equivalent to adding up to 30 full-time Level 2 analysts without increasing headcount
Minimize business risk: Takes on the busy work from human analysts and elevates a team’s overall decision making
Improve security outcomes: Identifies subtle, sophisticated threats through holistic investigations

‍

Unlocking an efficient SOC

To create a mature and proactive SOC, addressing the inefficiencies in the alert investigation process is essential. By extending AI's capabilities beyond detection, SOC teams can streamline and optimize investigative workflows, reducing alert fatigue and enhancing analyst efficiency.

This holistic approach not only improves Mean Time to Analysis (MTTA) but also ensures that SOCs are well-equipped to handle the evolving threat landscape. Embracing AI augmentation and automation in every phase of threat management will pave the way for a more resilient and proactive security posture, ultimately leading to a high-performing SOC that can effectively safeguard organizational assets.

Every relevant alert is investigated

The Cyber AI Analyst is not a generative AI system, or an XDR or SEIM aggregator that simply prompts you on what to do next. It uses a multi-layered combination of many different specialized AI methods to investigate every relevant alert from across your enterprise, native, 3^rd party, and manual triggers, operating at machine speed and scale. This also positively affects detection engineering and alert tuning, because it does not suffer from fatigue when presented with low accuracy but potentially valuable alerts.

Retain and improve analyst skills

Transferring most analysis processes to AI systems can risk team skills if they don't maintain or build them and if the AI doesn't explain its process. This can reduce the ability to challenge or build on AI results and cause issues if the AI is unavailable. The Cyber AI Analyst, by revealing its investigation process, data gathering, and decisions, promotes and improves these skills. Its deep understanding of cyber incidents can be used for skill training and incident response practice by simulating incidents for security teams to handle.

Create time for cyber risk reduction

Human cybersecurity professionals excel in areas that require critical thinking, strategic planning, and nuanced decision-making. With alert fatigue minimized and investigations streamlined, your analysts can avoid the tedious data collection and analysis stages and instead focus on critical decision-making tasks such as implementing recovery actions and performing threat hunting.

‍

Stay tuned for part 3/3

Part 3/3 in the Reimagine your SOC series explores the preventative security solutions market and effective risk management strategies.

Coming soon!

Written by

Brittany Woodsmall

Product Marketing Manager, AI & Attack Surface

Inside the SOC

Written by

Brittany Woodsmall

Product Marketing Manager, AI & Attack Surface

Senior Product Marketing Manager, Email

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December 5, 2025

Atomic Stealer: Darktrace’s Investigation of a Growing macOS Threat

The Rise of Infostealers Targeting Apple Users

In a threat landscape historically dominated by Windows-based threats, the growing prevalence of macOS information stealers targeting Apple users is becoming an increasing concern for organizations. Infostealers are a type of malware designed to steal sensitive data from target devices, often enabling attackers to extract credentials and financial data for resale or further exploitation. Recent research identified infostealers as the largest category of new macOS malware, with an alarming 101% increase in the last two quarters of 2024 [1].

What is Atomic Stealer?

Among the most notorious is Atomic macOS Stealer (or AMOS), first observed in 2023. Known for its sophisticated build, Atomic Stealer can exfiltrate a wide range of sensitive information including keychain passwords, cookies, browser data and cryptocurrency wallets.

Originally marketed on Telegram as a Malware-as-a-Service (MaaS), Atomic Stealer has become a popular malware due to its ability to target macOS. Like other MaaS offerings, it includes services like a web panel for managing victims, with reports indicating a monthly subscription cost between $1,000 and $3,000 [2]. Although Atomic Stealer’s original intent was as a standalone MaaS product, its unique capability to target macOS has led to new variants emerging at an unprecedented rate

Even more concerning, the most recent variant has now added a backdoor for persistent access [3]. This backdoor presents a significant threat, as Atomic Stealer campaigns are believed to have reached an around 120 countries. The addition of a backdoor elevates Atomic Stealer to the rare category of backdoor deployments potentially at a global scale, something only previously attributed to nation-state threat actors [4].

This level of sophistication is also evident in the wide range of distribution methods observed since its first appearance; including fake application installers, malvertising and terminal command execution via the ClickFix technique. The ClickFix technique is particularly noteworthy: once the malware is downloaded onto the device, users are presented with what appears to be a legitimate macOS installation prompt. In reality, however, the user unknowingly initiates the execution of the Atomic Stealer malware.

This blog will focus on activity observed across multiple Darktrace customer environments where Atomic Stealer was detected, along with several indicators of compromise (IoCs). These included devices that successfully connected to endpoints associated with Atomic Stealer, those that attempted but failed to establish connections, and instances suggesting potential data exfiltration activity.

Darktrace’s Coverage of Atomic Stealer

As this evolving threat began to spread across the internet in June 2025, Darktrace observed a surge in Atomic Stealer activity, impacting numerous customers in 24 different countries worldwide. Initially, most of the cases detected in 2025 affected Darktrace customers within the Europe, Middle East, and Africa (EMEA) region. However, later in the year, Darktrace began to observe a more even distribution of cases across EMEA, the Americas (AMS), and Asia Pacific (APAC). While multiple sectors were impacted by Atomic Stealer, Darktrace customers in the education sector were the most affected, particularly during September and October, coinciding with the return to school and universities after summer closures. This spike likely reflects increased device usage as students returned and reconnected potentially compromised devices to school and campus environments.

Starting from June, Darktrace detected multiple events of suspicious HTTP activity to external connections to IPs in the range 45.94.47.0/24. Investigation by Darktrace’s Threat Research team revealed several distinct patterns ; HTTP POST requests to the URI “/contact”, identical cURL User Agents and HTTP requests to “/api/tasks/[base64 string]” URIs.

Within one observed customer’s environment in July, Darktrace detected two devices making repeated initiated HTTP connections over port 80 to IPs within the same range. The first, Device A, was observed making GET requests to the IP 45.94.47[.]158 (AS60781 LeaseWeb Netherlands B.V.), targeting the URI “/api/tasks/[base64string]” using the “curl/8.7.2” user agent. This pattern suggested beaconing activity and triggered the ‘Beaconing Activity to External Rare' model alert in Darktrace / NETWORK, with Device A’s Model Event Log showing repeated connections. The IP associated with this endpoint has since been flagged by multiple open-source intelligence (OSINT) vendors as being associated with Atomic Stealer [5].

Figure 1: Darktrace’s detection of Device A showing repeated connections to the suspicious IP address over port 80, indicative of beaconing behavior.

Darktrace’s Cyber AI Analyst subsequently launched an investigation into the activity, uncovering that the GET requests resulted in a ‘503 Service Unavailable’ response, likely indicating that the server was temporarily unable to process the requests.

Figure 2: Cyber AI Analyst Incident showing the 503 Status Code, indicating that the server was temporarily unavailable.

This unusual activity prompted Darktrace’s Autonomous Response capability to recommend several blocking actions for the device in an attempt to stop the malicious activity. However, as the customer’s Autonomous Response configuration was set to Human Confirmation Mode, Darktrace was unable to automatically apply these actions. Had Autonomous Response been fully enabled, these connections would have been blocked, likely rendering the malware ineffective at reaching its malicious command-and-control (C2) infrastructure.

Figure 3: Autonomous Response’s suggested actions to block suspicious connectivity on Device A in the first customer environment.

In another customer environment in August, Darktrace detected similar IoCs, noting a device establishing a connection to the external endpoint 45.94.47[.]149 (ASN: AS57043 Hostkey B.V.). Shortly after the initial connections, the device was observed making repeated requests to the same destination IP, targeting the URI /api/tasks/[base64string] with the user agent curl/8.7.1, again suggesting beaconing activity. Further analysis of this endpoint after the fact revealed links to Atomic Stealer in OSINT reporting [6].

Figure 4: Cyber AI Analyst investigation finding a suspicious URI and user agent for the offending device within the second customer environment.

As with the customer in the first case, had Darktrace’s Autonomous Response been properly configured on the customer’s network, it would have been able to block connectivity with 45.94.47[.]149. Instead, Darktrace suggested recommended actions that the customer’s security team could manually apply to help contain the attack.

Figure 5: Autonomous Response’s suggested actions to block suspicious connectivity to IP 45.94.47[.]149 for the device within the second customer environment.

In the most recent case observed by Darktrace in October, multiple instances of Atomic Stealer activity were seen across one customer’s environment, with two devices communicating with Atomic Stealer C2 infrastructure. During this incident, one device was observed making an HTTP GET request to the IP 45.94.47[.]149 (ASN: AS60781 LeaseWeb Netherlands B.V.). These connections targeted the URI /api/tasks/[base64string, using the user agent curl/8.7.1.

Shortly afterward, the device began making repeated connections over port 80 to the same external IP, 45.94.47[.]149. This activity continued for several days until Darktrace detected the device making an HTTP POST request to a new IP, 45.94.47[.]211 (ASN: AS57043 Hostkey B.V.), this time targeting the URI /contact, again using the curl/8.7.1 user agent. Similar to the other IPs observed in beaconing activity, OSINT reporting later linked this one to information stealer C2 infrastructure [7].

Figure 6: Darktrace’s detection of suspicious beaconing connectivity with the suspicious IP 45.94.47.211.

Further investigation into this customer’s network revealed that similar activity had been occurring as far back as August, when Darktrace detected data exfiltration on a second device. Cyber AI Analyst identified this device making a single HTTP POST connection to the external IP 45.94.47[.]144, another IP with malicious links [8], using the user agent curl/8.7.1 and targeting the URI /contact.

Figure 7: Cyber AI Analyst investigation finding a successful POST request to 45.94.47[.]144 for the device within the third customer environment.

A deeper investigation into the technical details within the POST request revealed the presence of a file named “out.zip”, suggesting potential data exfiltration.

Figure 8: Advanced Search log in Darktrace / NETWORK showing “out.zip”, indicating potential data exfiltration for a device within the third customer environment.

Similarly, in another environment, Darktrace was able to collect a packet capture (PCAP) of suspected Atomic Stealer activity, which revealed potential indicators of data exfiltration. This included the presence of the “out.zip” file being exfiltrated via an HTTP POST request, along with data that appeared to contain details of an Electrum cryptocurrency wallet and possible passwords.

Read more about Darktrace’s full deep dive into a similar case where this tactic was leveraged by malware as part of an elaborate cryptocurrency scam.

Figure 9: PCAP of an HTTP POST request showing the file “out.zip” and details of Electrum Cryptocurrency wallet.

Although recent research attributes the “out.zip” file to a new variant named SHAMOS [9], it has also been linked more broadly to Atomic Stealer [10]. Indeed, this is not the first instance where Darktrace has seen the “out.zip” file in cases involving Atomic Stealer either. In a previous blog detailing a social engineering campaign that targeted cryptocurrency users with the Realst Stealer, the macOS version of Realst contained a binary that was found to be Atomic Stealer, and similar IoCs were identified, including artifacts of data exfiltration such as the “out.zip” file.

Conclusion‍

The rapid rise of Atomic Stealer and its ability to target macOS marks a significant shift in the threat landscape and should serve as a clear warning to Apple users who were traditionally perceived as more secure in a malware ecosystem historically dominated by Windows-based threats.

Atomic Stealer’s growing popularity is now challenging that perception, expanding its reach and accessibility to a broader range of victims. Even more concerning is the emergence of a variant embedded with a backdoor, which is likely to increase its appeal among a diverse range of threat actors. Darktrace’s ability to adapt and detect new tactics and IoCs in real time delivers the proactive defense organizations need to protect themselves against emerging threats before they can gain momentum.

Credit to Isabel Evans (Cyber Analyst), Dylan Hinz (Associate Principal Cyber Analyst)
Edited by Ryan Traill (Analyst Content Lead)

Appendices

References

1. https://www.scworld.com/news/infostealers-targeting-macos-jumped-by-101-in-second-half-of-2024

2. https://www.kandji.io/blog/amos-macos-stealer-analysis

3. https://www.broadcom.com/support/security-center/protection-bulletin/amos-stealer-adds-backdoor

4. https://moonlock.com/amos-backdoor-persistent-access

5. https://www.virustotal.com/gui/ip-address/45.94.47.158/detection

6. https://www.trendmicro.com/en_us/research/25/i/an-mdr-analysis-of-the-amos-stealer-campaign.html

7. https://www.virustotal.com/gui/ip-address/45.94.47.211/detection

8. https://www.virustotal.com/gui/ip-address/45.94.47.144/detection

9. https://securityaffairs.com/181441/malware/over-300-entities-hit-by-a-variant-of-atomic-macos-stealer-in-recent-campaign.html

10. https://binhex.ninja/malware-analysis-blogs/amos-stealer-atomic-stealer-malware.html

Darktrace Model Detections

Darktrace / NETWORK

Compromise / Beaconing Activity To External Rare
Compromise / HTTP Beaconing to New IP
Compromise / HTTP Beaconing to Rare Destination
Anomalous Connection / New User Agent to IP Without Hostname
Device / New User Agent
Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
Compromise / Slow Beaconing Activity To External Rare
Anomalous Connection / Posting HTTP to IP Without Hostname
Compromise / Quick and Regular Windows HTTP Beaconing

Autonomous Response

Antigena / Network / Significant Anomaly::Antigena Alerts Over Time Block
Antigena / Network / Significant Anomaly::Antigena Significant Anomaly from Client Block
Antigena / Network / External Threat::Antigena Suspicious Activity Block

List of IoCs

45.94.47[.]149 – IP – Atomic C2 Endpoint
45.94.47[.]144 – IP – Atomic C2 Endpoint
45.94.47[.]158 – IP – Atomic C2 Endpoint
45.94.47[.]211 – IP – Atomic C2 Endpoint
out.zip - File Output – Possible ZIP file for Data Exfiltration

MITRE ATT&CK Mapping:

Tactic –Technique – Sub-Technique

Execution - T1204.002 - User Execution: Malicious File

Credential Access - T1555.001 - Credentials from Password Stores: Keychain

Credential Access - T1555.003 - Credentials from Web Browsers

Command & Control - T1071 - Application Layer Protocol

Exfiltration - T1041 - Exfiltration Over C2 Channel

About the author

Isabel Evans

Cyber Analyst

Blog

Email

December 3, 2025

Darktrace Named as a Leader in 2025 Gartner® Magic Quadrant™ for Email Security Platforms

Darktrace is proud to be named as a Leader in the Gartner® Magic Quadrant™ for Email Security Platforms (ESP). We believe this recognition reflects what our customers already know: our product is exceptional – and so is the way we deliver it.

In July 2025, Darktrace was named a Customers’ Choice in the Gartner® Peer Insights™ Voice of the Customer for Email Security, a distinction given to vendors who have scores that meet or exceed the market average for both axes (User Interest and Adoption, and Overall Experience). To us, both achievements are testament to the customer-first approach that has fueled our rapid growth. We feel this new distinction from Gartner validates the innovation, efficacy, and customer-centric delivery that set Darktrace apart.

A Gartner Magic Quadrant is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors. CIOs and CISOs can use this research to make informed decisions about which email security platform can best accomplish their goals. We encourage our customers to read the full report to get the complete picture.

This acknowledgement follows the recent recognition of Darktrace / NETWORK, also designated a Leader in the Gartner Magic Quadrant for Network Detection & Response and named the only Customers’ Choice in its category.

Leaders are recognized for strong market adoption, financial stability, and established integrations with major collaboration platforms.

Why do we believe Darktrace is leading in the email security market?

Our relentless innovation which drives proven results

At Darktrace we continue to push the frontier of email security, with industry-first AI-native detection and response capabilities that go beyond traditional SEG approaches. How do we do it?

With a proven approach that gets results. Darktrace’s unique business-centric anomaly detection catches advanced phishing, supply chain compromises, and BEC attacks – detecting them on average 13 days earlier than attack-centric solutions. That’s why 75% of our customers have removed their SEG and now rely on their native email security provider combined with Darktrace.
By offering comprehensive protection beyond the inbox. Darktrace / EMAIL goes further than traditional inbound filtering, delivering account and messaging protection, DLP, and DMARC capabilities, ensuring best-in-class security across inbound, outbound, and domain protection scenarios.
Continuous innovation. We are ranked second highest in the Gartner Critical Capabilities research for core email security function, likely thanks to our product strategy and rapid pace of innovation. We’ve release major capabilities twice a year for nearly five years, including advanced AI models and expanded coverage for collaboration platforms.

We deliver exceptional customer experiences worldwide

Darktrace’s leadership isn’t just about excelling in technology, it’s about delivering an outstanding experience that customers value. Let’s dig into what makes our customers tick.

Proven loyalty from our base. Recognition from Gartner Peer Insights as a Customers’ Choice, combined with a 4.8-star rating (based on 340 reviews as of November 2025), demonstrates for us the trust of thousands of organizations worldwide, not just the analysts.
Customer-first support. Darktrace goes beyond ticket-only models with dedicated account teams and award-winning service, backed by significant headcount growth in technical support and analytics roles over the past year.
Local expertise. With offices spanning continents, Darktrace is able to provide regional language support and tailored engagement from teams on the ground, ensuring personalized service and a human-first experience.

Darktrace enhances security stacks with a partner-first architecture

There are plenty of tools out there than encourage a siloed approach. Darktrace / EMAIL plays well with others, enhancing your native security provider and allowing you to slim down your stack. It’s designed to set you up for future growth, with:

A best-in-breed platform approach. Natively built on Self-Learning AI, Darktrace / EMAIL delivers deep integration with our / NETWORK, / IDENTITY, and / CLOUD products as part of a unified platforms – that enables and enhances comprehensive enterprise-wise security.
Optimized workflows. Darktrace integrates tightly with an extended ecosystem of security tools – including a strategic partnership with Microsoft enabling unified threat response and quarantine capabilities – bringing constant innovation to all of your SOC workflows.
A channel-first strategy. Darktrace is making significant investments in partner-driven architectures, enabling integrated ecosystems that deliver maximum value and future-ready security for our customers.

Analyst recognized. Customer approved.

Darktrace / EMAIL is not just another inbound email security tool; it’s an advanced email security platform trusted by thousands of users to protect them against advanced phishing, messaging, and account-level attacks.

As a Leader, we believe we owe our positioning to our customers and partners for supporting our growth. In the upcoming years we will continue to innovate to serve the organizations who depend on Darktrace for threat protection.

To learn more about Darktrace’s position as a Leader, view a complimentary copy of the Magic Quadrant report, register for the Darktrace Innovation Webinar on 9 December, 2025, or simply request a demo.

‍

Gartner, Gartner® Magic Quadrant™ for Email Security Platforms, Max Taggett, Nikul Patel, 3 December 2025

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Darktrace.

[related-resource]

About the author

Carlos Gray

Senior Product Marketing Manager, Email

Your data. Our AI.

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Check out this article by Darktrace: Reimagining Your SOC: Overcoming Alert Fatigue with AI-Led Investigations

Reimagining Your SOC: Overcoming Alert Fatigue with AI-Led Investigations

Challenges with SOC alert investigation

Understanding alerts in the SOC: Stopping cyber incidents is hard

First we need a trace of an attack…

A detection is created…

Investigation begins…

Containment begins…

Developing an AI analyst: How Darktrace replicates human investigation

Here’s how it works:

Unlocking an efficient SOC

Every relevant alert is investigated

Retain and improve analyst skills

Create time for cyber risk reduction

Stay tuned for part 3/3

Atomic Stealer: Darktrace’s Investigation of a Growing macOS Threat

Darktrace Named as a Leader in 2025 Gartner® Magic Quadrant™ for Email Security Platforms

Enjoying the blog?

More in this series

Blog

Network

December 5, 2025

Atomic Stealer: Darktrace’s Investigation of a Growing macOS Threat

The Rise of Infostealers Targeting Apple Users

What is Atomic Stealer?

Darktrace’s Coverage of Atomic Stealer

Appendices

References

Darktrace Model Detections

List of IoCs

Blog

Email

December 3, 2025

Darktrace Named as a Leader in 2025 Gartner® Magic Quadrant™ for Email Security Platforms

Why do we believe Darktrace is leading in the email security market?

Our relentless innovation which drives proven results

We deliver exceptional customer experiences worldwide

Darktrace enhances security stacks with a partner-first architecture

Analyst recognized. Customer approved.