The latest escalation in the cyber arms race sees attackers choosing stealth over speed and cunning over chaos.
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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.
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02
Dec 2018
Introduction
The speed of today’s most advanced threats can be devastating. In the few minutes it takes a security analyst to step away from her screen to grab a coffee, ransomware can take down thousands of computers before human teams or traditional tools have the chance to respond. And while big, fast threats are more likely to grab the headlines, cyber-attacks which do the opposite can be just as dangerous. The latest escalation in the cyber arms race sees attackers choosing stealth over speed and cunning over chaos.
As defenders work to rapidly deploy new security and detection technologies, malware authors have been similarly innovative, working to find a means of evading them. New ‘low and slow’ attacks are able to bypass traditional security tools because each individual action compiling the larger threat is too small to detect. These attacks are designed to operate over a longer period of time – and by minimizing disruption to any data transfer or connectivity levels, they blend into legitimate traffic.
For advanced and well-resourced actors like nation states in search of valuable intellectual property or sensitive political records, subtle and prolonged exposure to the systems they attack is a significant benefit. When it comes to the most sophisticated threats, slow and steady really can win the race.
Nevertheless, detection of low and slow attacks is possible with advanced machine learning techniques. To do so, contextual knowledge is critical; by modeling the subtle and unique ‘patterns of life’ of every user, device, and the network as a whole, AI-powered defenses are, for the first time, winning this battle.
This blog explores how attackers use low and slow techniques during multiple stages of the kill chain to achieve their eventual goal. We examine three real-world case studies, drawn from over 7,000 deployments of the Enterprise Immune System, to demonstrate how cyber AI detects low and slow reconnaissance, data exfiltration, and command-and-control activity.
Low and slow reconnaissance
By monitoring the behavioral pattern of devices and users, Darktrace AI is able to learn an evolving profile for expected activity. Armed with this understanding of ‘normal’ for the network, it can then identify significant anomalies indicative of a threat. It does all this without relying on training sets of historical data, enabling the technology to spot threats that other tools miss.
On the network of a European financial services firm, Darktrace discovered a server conducting port scans of various internal computers. This type of network scanning is regularly performed for legitimate testing purposes by administrative devices, but it is also a tactic for attackers to identify vulnerabilities and points of compromise – an early stage of an attack.
Over a duration of 7 days, the server made around 214,000 failed connections to 276 unique devices. However, only a small number of ports were targeted per day. The attack was sequential, but slow over time. Measured in one day, the level of disturbance was minimal enough to evade all rules-based defenses. Nevertheless, by learning ‘self’ across the entire digital business over time, cyber AI can detect even the subtlest deviation from ‘normal’ relative to the individual device, user, or network. Darktrace recognized the longer pattern of network scanning and alerted the customer immediately.
Advanced search view showing regular connections to closed ports over the scanning period.
Low and slow data exfiltration
At an industrial manufacturing company, a desktop was identified establishing over 2,000 connections to a rare host over a 7-day period. During this time, a total of 9.15GB of data was transferred externally. No single connection transmitted more than a few MB of data – an amount which, if viewed in isolation, would not be cause for concern. However, the destination for these connections was 100% rare for the network and maintained that level of rarity for the entire period of exfiltration. This not only flagged the activity as initially suspicious, but also prevented it from being absorbed into legitimate traffic. Combined with the accumulated volume of data leaving the network, Darktrace AI identified this as significant deviation in the device’s behavior, indicating a threat in progress.
Steady exfiltration of data over a 7-day period.
A series of model breaches (orange circles) occurring throughout the period of steady external data exfiltration (blue line).
Low and slow command and control
Darktrace is extremely successful in finding malware infections before they appear on open-source threat lists, a crucial ability when stopping the most serious, never-before-seen threats. This is achieved in large part by detecting beaconing patterns rather than relying on signatures. Beaconing occurs when a malicious program attempts to establish contact with its online infrastructure. Similar to network scanning, it creates a surge in outgoing connections.
Darktrace was deployed in a corporate network where a device was found making connections at steady intervals to a malicious browser extension. The average rate of connection was 11 connections every 4 hours – a low activity level which could easily have blended into legitimate internet traffic. Having identified the regularity of these connections, Darktrace’s AI assigned a high beaconing score, which indicated that they were likely initiated by an automated process. If we include the fact that the destination was rare, it became clear that this was caused by a malicious background program that was running unbeknownst to the user.
As cyber security advances, attackers will develop increasingly sophisticated methods to operate under the radar. Traditional cyber security tools which work in binary ways based on historical data – either the upload exceeded a predefined limit or not – cannot keep up. This new era will see AI proven crucial because of its ability to learn a constantly-evolving ‘pattern of life’ for a network over the duration of its deployment. This allows Darktrace AI to effectively locate the disturbances in connectivity levels – no matter how small – that have been caused by malicious or non-compliant activity. Fundamentally, this enables Darktrace to discover in-progress attacks and then autonomously respond, neutralizing them before they become a crisis.
High-profile, fast-moving attacks like NotPetya and WannaCry have encouraged some organizations to focus on preventing certain types of threat, at the expense of others – and hackers are catching on. By leveraging powerful AI, Darktrace empowers customers to prevent not just the fastest-moving attacks, but also the slowest and subtlest.
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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.
Darktrace Named the Only 2025 Gartner® Peer Insights™ Customers’ Choice for Network Detection and Response
Darktrace: The only Customers’ Choice for NDR in 2025
In a year defined by rapid change across the threat landscape, recognition from those who use and rely on security technology every day means the most.
That’s why we’re proud to share that Darktrace has been named the only Customers’ Choice in the 2025 Gartner® Peer Insights™ Voice of the Customer for Network Detection and Response (NDR).
Out of 11 leading NDR vendors evaluated, Darktrace stood alone as the sole Customers’ Choice, a recognition that we feel reflects not just our innovation, but the trust and satisfaction of the customers who secure their networks with Darktrace every day.
What the Gartner® Peer Insights™ Voice of the Customer means
“Voice of the Customer” is a document that synthesizes Gartner Peer Insights reviews into insights for buyers of technology and services. This aggregated peer perspective, along with the individual detailed reviews, is complementary to Gartner expert research and can play a key role in your buying process. Peers are verified reviewers of a technology product or service, who not only rate the offering, but also provide valuable feedback to consider before making a purchase decision. Vendors placed in the upper-right “Customers’ Choice” quadrant of the “Voice of the Customer” have scores that meet or exceed the market average for both axes (User Interest and Adoption, and Overall Experience).It’s not just a rating. We feel it’s a reflection of genuine customer sentiment and success in the field.
In our view, Customers consistently highlight Darktrace’s ability to:
Detect and respond to unknown threats in real time
Deliver unmatched visibility across IT, OT, and cloud environments
Automate investigations and responses through AI-driven insights
We believe this recognition reinforces what our customers already know: that Darktrace helps them see, understand, and stop attacks others miss.
A rare double: recognized by customers and analysts alike
This distinction follows another major recogniton. Darktrace’s placement as a Leader in the Gartner® Magic Quadrant™ for Network Detection and Response earlier this year.
That makes Darktrace the only vendor to achieve both:
A Leader status in the Gartner Magic Quadrant for NDR, and
A Customers’ Choice in Gartner Peer Insights 2025
It’s a rare double that we feel reflects both industry leadership and customer trust, two perspectives that, together, define what great cybersecurity looks like.
A Customers’ Choice across the network and the inbox
To us, this recognition also builds on Darktrace’s momentum across multiple domains. Earlier this year, Darktrace was also named a Customers’ Choice for Email Security Platforms in the Gartner® Peer Insights™ report.
With more than 1,000 verified reviews across Network Detection and Response, Email Security Platforms, and Cyber Physical Systems (CPS), we at Darktrace are proud to be trusted across the full attack surface, from the inbox to the industrial network.
Thank you to our customers
We’re deeply grateful to every customer who shared their experience with Darktrace on Gartner Peer Insights. Your insights drive our innovation and continue to shape how we protect complex, dynamic environments across the world.
Gartner® Peer Insights™ content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.
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 and Peer Insights are registered trademarks of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.
Gartner, Voice of the Customer for Network Detection and Response, By Peer Community Contributor, 30 October 2025
Tracking a Dragon: Investigating a DragonForce-affiliated ransomware attack with Darktrace
What is DragonForce?
DragonForce is a Ransomware-as-a-Service (RaaS) platform that emerged in late 2023, offering broad-scale capabilities and infrastructure to threat actors. Recently, DragonForce has been linked to attacks targeting the UK retail sector, resulting in several high-profile cases [1][2]. Moreover, the group launched an affiliate program offering a revenue share of roughly 20%, significantly lower than commissions reported across other RaaS platforms [3].
This Darktrace case study examines a DragonForce-linked RaaS infection within the manufacturing industry. The earliest signs of compromise were observed during working hours in August 2025, where an infected device started performing network scans and attempted to brute-force administrative credentials. After eight days of inactivity, threat actors returned and multiple devices began encrypting files via the SMB protocol using a DragonForce-associated file extension. Ransom notes referencing the group were also dropped, suggesting the threat actor is claiming affiliation with DragonForce, though this has not been confirmed.
Despite Darktrace’s detection of the attack in its early stages, the customer’s deployment did not have Darktrace’s Autonomous Response capability configured, allowing the threat to progress to data exfiltration and file encryption.
Darktrace's Observations
While the initial access vector was not clearly defined in this case study, it was likely achieved through common methods previously employed out by DragonForce affiliates. These include phishing emails leveraging social engineering tactics, exploitation of public-facing applications with known vulnerabilities, web shells, and/or the abuse of remote management tools.
Darktrace’s analysis identified internal devices performing internal network scanning, brute-forcing credentials, and executing unusual Windows Registry operations. Notably, Windows Registry events involving "Schedule\Taskcache\Tasks" contain subkeys for individual tasks, storing GUIDs that can be used to locate and analyze scheduled tasks. Additionally, Control\WMI\Security holds security descriptors for WMI providers and Event Tracing loggers that use non-default security settings respectively.
Furthermore, Darktrace identified data exfiltration activity over SSH, including connections to an ASN associated with a malicious hosting service geolocated in Russia.
1. Network Scan & Brute Force
Darktrace identified anomalous behavior in late August to early September 2025, originating from a source device engaging in internal network scanning followed by brute-force attempts targeting administrator credential, including “administrator”, “Admin”, “rdpadmin”, “ftpadmin”.
Upon further analysis, one of the HTTP connections seen in this activity revealed the use of the user agent string “OpenVAS-VT”, suggesting that the device was using the OpenVAS vulnerability scanner. Subsequently, additional devices began exhibiting network scanning behavior. During this phase, a file named “delete.me” was deleted by multiple devices using SMB protocol. This file is commonly associated with network scanning and penetration testing tool NetScan.
2. Windows Registry Key Update
Following the scanning phase, Darktrace observed the initial device then performing suspicious Winreg operations. This included the use of the ”BaseRegOpenKey” function across multiple registry paths.
Additional operations such as “BaseRegOpenKey” and “BaseRegQueryValue” were also seen around this time. These operations are typically used to retrieve specific registry key values and allow write operations to registry keys.
The registry keys observed included “SYSTEM\CurrentControlSet\Control\WMI\Security” and “Software\Microsoft\Windows NT\CurrentVersion\Schedule\Taskcache\Tasks”. These keys can be leveraged by malicious actors to update WMI access controls and schedule malicious tasks, respectively, both of which are common techniques for establishing persistence within a compromised system.
3. New Administrator Credential Usage
Darktrace subsequently detected the device using a highly privileged credential, “administrator”, via a successful Kerberos login for the first time. Shortly after, the same credential was used again for a successful SMB session.
These marked the first instances of authentication using the “administrator” credential across the customer’s environment, suggesting potential malicious use of the credential following the earlier brute-force activity.
Figure 1: Darktrace’s detection of administrator credentials being used in Kerberos login events by an infected device.
Figure 2: Darktrace’s detection of administrator credentials being used in SMB sessions by an infected device.
4. Data Exfiltration
Prior to ransomware deployment, several infected devices were observed exfiltrating data to the malicious IP 45.135.232[.]229 via SSH connections [7][8]. This was followed by the device downloading data from other internal devices and transferring an unusually large volume of data to the same external endpoint.
The IP address was first seen on the network on September 2, 2025 - the same date as the observed data exfiltration activity preceding ransomware deployment and encryption.
Further analysis revealed that the endpoint was geolocated in Russia and registered to the malicious hosting provider Proton66. Multiple external researchers have reported malicious activity involving the same Proton66 ASN (AS198953 Proton66 OOO) as far back as April 2025. These activities notably included vulnerability scanning, exploitation attempts, and phishing campaigns, which ultimately led to malware [4][5][6].
Data Exfiltration Endpoint details.
Endpoint: 45.135.232[.]229
ASN: AS198953 Proton66 OOO
Transport protocol: TCP
Application protocol: SSH
Destination port: 22
Figure 3: Darktrace’s summary of the external IP 45.135.232[.]229, first detected on September 2, 2025. The right-hand side showcases model alerts triggered related to this endpoint including multiple data exfiltration related model alerts.
Further investigation into the endpoint using open-source intelligence (OSINT) revealed that it led to a Microsoft Internet Information Services (IIS) Manager console webpage. This interface is typically used to configure and manage web servers. However, threat actors have been known to exploit similar setups, using fake certificate warnings to trick users into downloading malware, or deploying malicious IIS modules to steal credentials.
Figure 4: Live screenshot of the destination (45.135.232[.]229), captured via OSINT sources, displaying a Microsoft IIS Manager console webpage.
5. Ransomware Encryption & Ransom Note
Multiple devices were later observed connecting to internal devices via SMB and performing a range of actions indicative of file encryption. This suspicious activity prompted Darktrace’s Cyber AI Analyst to launch an autonomous investigation, during which it pieced together associated activity and provided concrete timestamps of events for the customer’s visibility.
During this activity, several devices were seen writing a file named “readme.txt” to multiple locations, including network-accessible webroot paths such as inetpub\ and wwwroot\. This “readme.txt” file, later confirmed to be the ransom note, claimed the threat actors were affiliated with DragonForce.
At the same time, devices were seen performing SMB Move, Write and ReadWrite actions involving files with the “.df_win” extension across other internal devices, suggesting that file encryption was actively occurring.
Figure 5: Darktrace’s detection of SMB events (excluding Read events) where the device was seen moving or writing files with the “.df_win” extension.
Figure 6: Darktrace’s detection of a spike in SMB Write events with the filename “readme.txt” on September 9, indicating the start of file encryption.
Conclusion
The rise of Ransomware-as-a-Service (RaaS) and increased attacker customization is fragmenting tactics, techniques, and procedures (TTPs), making it increasingly difficult for security teams to prepare for and defend against each unique intrusion. RaaS providers like DragonForce further complicate this challenge by enabling a wide range of affiliates, each with varying levels of sophistication [9].
In this instance, Darktrace was able to identify several stages of the attack kill chain, including network scanning, the first-time use of privileged credentials, data exfiltration, and ultimately ransomware encryption. Had the customer enabled Darktrace’s Autonomous Response capability, it would have taken timely action to interrupt the attack in its early stages, preventing the eventual data exfiltration and ransomware detonation.
Credit to Justin Torres, Senior Cyber Analyst, Nathaniel Jones, VP, Security & AI Strategy, FCISO, & Emma Foulger, Global Threat Research Operations Lead.
Darktrace Cyber AI Analyst Coverage/Investigation Events:
· Web Application Vulnerability Scanning of Multiple Devices
· Port Scanning
· Large Volume of SMB Login Failures
· Unusual RDP Connections
· Widespread Web Application Vulnerability Scanning
· Unusual SSH Connections
· Unusual Repeated Connections
· Possible Application Layer Reconnaissance Activity
· Unusual Administrative Connections
· Suspicious Remote WMI Activity
· Extensive Unusual Administrative Connections
· Suspicious Directory Replication Service Activity
· Scanning of Multiple Devices
· Unusual External Data Transfer
· SMB Write of Suspicious File
· Suspicious Remote Service Control Activity
· Access of Probable Unencrypted Password Files
· Internal Download and External Upload
· Possible Encryption of Files over SMB
· SMB Writes of Suspicious Files to Multiple Devices
The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.
Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein. Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.
Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.
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