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November 25, 2024

Why Artificial Intelligence is the Future of Cybersecurity

This blog explores the impact of AI on the threat landscape, the benefits of AI in cybersecurity, and the role it plays in enhancing security practices and tools.
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
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25
Nov 2024

Introduction: AI & Cybersecurity

In the wake of artificial intelligence (AI) becoming more commonplace, it’s no surprise to see that threat actors are also adopting the use of AI in their attacks at an accelerated pace. AI enables augmentation of complex tasks such as spear-phishing, deep fakes, polymorphic malware generation, and advanced persistent threat (APT) campaigns, which significantly enhances the sophistication and scale of their operations. This has put security professionals in a reactive state, struggling to keep pace with the proliferation of threats.

As AI reshapes the future of cyber threats, defenders are also looking to integrate AI technologies into their security stack. Adopting AI-powered solutions in cybersecurity enables security teams to detect and respond to these advanced threats more quickly and accurately as well as automate traditionally manual and routine tasks. According to research done by Darktrace in the 2024 State of AI Cybersecurity Report improving threat detection, identifying exploitable vulnerabilities, and automating low level security tasks were the top three ways practitioners saw AI enhancing their security team’s capabilities [1], underscoring the wide-ranging capabilities of AI in cyber.  

In this blog, we will discuss how AI has impacted the threat landscape, the rise of generative AI and AI adoption in security tools, and the importance of using multiple types of AI in cybersecurity solutions for a holistic and proactive approach to keeping your organization safe.  

The impact of AI on the threat landscape

The integration of AI and cybersecurity has brought about significant advancements across industries. However, it also introduces new security risks that challenge traditional defenses.  Three major concerns with the misuse of AI being leveraged by adversaries are: (1) the increase of novel social engineering attacks that are harder to detect and able to bypass traditional security tools,  (2) the ease of access for less experienced threat actors to now deliver advanced attacks at speed and scale and (3) the attacking of AI itself, to include machine learning models, data corpuses and APIs or interfaces.

In the context of social engineering, AI can be used to create more convincing phishing emails, conduct advanced reconnaissance, and simulate human-like interactions to deceive victims more effectively. Generative AI tools, such as ChatGPT, are already being used by adversaries to craft these sophisticated phishing emails, which can more aptly mimic human semantics without spelling or grammatical error and include personal information pulled from internet sources such as social media profiles. And this can all be done at machine speed and scale. In fact, Darktrace researchers observed a 135% rise in ‘novel social engineering attacks’ across Darktrace / EMAIL customers in 2023, corresponding to the widespread adoption and use of ChatGPT [2].  

Furthermore, these sophisticated social engineering attacks are now able to circumvent traditional security tools. In between December 21, 2023, and July 5, 2024, Darktrace / EMAIL detected 17.8 million phishing emails across the fleet, with 62% of these phishing emails successfully bypassing Domain-based Message Authentication, Reporting, and Conformance (DMARC) verification checks [2].  

And while the proliferation of novel attacks fueled by AI is persisting, AI also lowers the barrier to entry for threat actors. Publicly available AI tools make it easy for adversaries to automate complex tasks that previously required advanced technical skills. Additionally, AI-driven platforms and phishing kits available on the dark web provide ready-made solutions, enabling even novice attackers to execute effective cyber campaigns with minimal effort.

The impact of adversarial use of AI on the ever-evolving threat landscape is important for organizations to understand as it fundamentally changes the way we must approach cybersecurity. However, while the intersection of cybersecurity and AI can have potentially negative implications, it is important to recognize that AI can also be used to help protect us.

A generation of generative AI in cybersecurity

When the topic of AI in cybersecurity comes up, it’s typically in reference to generative AI, which became popularized in 2023. While it does not solely encapsulate what AI cybersecurity is or what AI can do in this space, it’s important to understand what generative AI is and how it can be implemented to help organizations get ahead of today’s threats.  

Generative AI (e.g., ChatGPT or Microsoft Copilot) is a type of AI that creates new or original content. It has the capability to generate images, videos, or text based on information it learns from large datasets. These systems use advanced algorithms and deep learning techniques to understand patterns and structures within the data they are trained on, enabling them to generate outputs that are coherent, contextually relevant, and often indistinguishable from human-created content.

For security professionals, generative AI offers some valuable applications. Primarily, it’s used to transform complex security data into clear and concise summaries. By analyzing vast amounts of security logs, alerts, and technical data, it can contextualize critical information quickly and present findings in natural, comprehensible language. This makes it easier for security teams to understand critical information quickly and improves communication with non-technical stakeholders. Generative AI can also automate the creation of realistic simulations for training purposes, helping security teams prepare for various cyberattack scenarios and improve their response strategies.  

Despite its advantages, generative AI also has limitations that organizations must consider. One challenge is the potential for generating false positives, where benign activities are mistakenly flagged as threats, which can overwhelm security teams with unnecessary alerts. Moreover, implementing generative AI requires significant computational resources and expertise, which may be a barrier for some organizations. It can also be susceptible to prompt injection attacks and there are risks with intellectual property or sensitive data being leaked when using publicly available generative AI tools.  In fact, according to the MIT AI Risk Registry, there are potentially over 700 risks that need to be mitigated with the use of generative AI.

Generative AI impact on cyber attacks screenshot data sheet

For more information on generative AI's impact on the cyber threat landscape download the Darktrace Data Sheet

Beyond the Generative AI Glass Ceiling

Generative AI has a place in cybersecurity, but security professionals are starting to recognize that it’s not the only AI organizations should be using in their security tool kit. In fact, according to Darktrace’s State of AI Cybersecurity Report, “86% of survey participants believe generative AI alone is NOT enough to stop zero-day threats.” As we look toward the future of AI in cybersecurity, it’s critical to understand that different types of AI have different strengths and use cases and choosing the technologies based on your organization’s specific needs is paramount.

There are a few types of AI used in cybersecurity that serve different functions. These include:

Supervised Machine Learning: Widely used in cybersecurity due to its ability to learn from labeled datasets. These datasets include historical threat intelligence and known attack patterns, allowing the model to recognize and predict similar threats in the future. For example, supervised machine learning can be applied to email filtering systems to identify and block phishing attempts by learning from past phishing emails. This is human-led training facilitating automation based on known information.  

Large Language Models (LLMs): Deep learning models trained on extensive datasets to understand and generate human-like text. LLMs can analyze vast amounts of text data, such as security logs, incident reports, and threat intelligence feeds, to identify patterns and anomalies that may indicate a cyber threat. They can also generate detailed and coherent reports on security incidents, summarizing complex data into understandable formats.

Natural Language Processing (NLP): Involves the application of computational techniques to process and understand human language. In cybersecurity, NLP can be used to analyze and interpret text-based data, such as emails, chat logs, and social media posts, to identify potential threats. For instance, NLP can help detect phishing attempts by analyzing the language used in emails for signs of deception.

Unsupervised Machine Learning: Continuously learns from raw, unstructured data without predefined labels. It is particularly useful in identifying new and unknown threats by detecting anomalies that deviate from normal behavior. In cybersecurity, unsupervised learning can be applied to network traffic analysis to identify unusual patterns that may indicate a cyberattack. It can also be used in endpoint detection and response (EDR) systems to uncover previously unknown malware by recognizing deviations from typical system behavior.

Types of AI in cybersecurity
Figure 1: Types of AI in cybersecurity

Employing multiple types of AI in cybersecurity is essential for creating a layered and adaptive defense strategy. Each type of AI, from supervised and unsupervised machine learning to large language models (LLMs) and natural language processing (NLP), brings distinct capabilities that address different aspects of cyber threats. Supervised learning excels at recognizing known threats, while unsupervised learning uncovers new anomalies. LLMs and NLP enhance the analysis of textual data for threat detection and response and aid in understanding and mitigating social engineering attacks. By integrating these diverse AI technologies, organizations can achieve a more holistic and resilient cybersecurity framework, capable of adapting to the ever-evolving threat landscape.

A Multi-Layered AI Approach with Darktrace

AI-powered security solutions are emerging as a crucial line of defense against an AI-powered threat landscape. In fact, “Most security stakeholders (71%) are confident that AI-powered security solutions will be better able to block AI-powered threats than traditional tools.” And 96% agree that AI-powered solutions will level up their organization’s defenses.  As organizations look to adopt these tools for cybersecurity, it’s imperative to understand how to evaluate AI vendors to find the right products as well as build trust with these AI-powered solutions.  

Darktrace, a leader in AI cybersecurity since 2013, emphasizes interpretability, explainability, and user control, ensuring that our AI is understandable, customizable and transparent. Darktrace’s approach to cyber defense is rooted in the belief that the right type of AI must be applied to the right use cases. Central to this approach is Self-Learning AI, which is crucial for identifying novel cyber threats that most other tools miss. This is complemented by various AI methods, including LLMs, generative AI, and supervised machine learning, to support the Self-Learning AI.  

Darktrace focuses on where AI can best augment the people in a security team and where it can be used responsibly to have the most positive impact on their work. With a combination of these AI techniques, applied to the right use cases, Darktrace enables organizations to tailor their AI defenses to unique risks, providing extended visibility across their entire digital estates with the Darktrace ActiveAI Security Platform™.

Credit to: Ed Metcalf, Senior Director Product Marketing, AI & Innovations - Nicole Carignan VP of Strategic Cyber AI for their contribution to this blog.

CISOs guide to buying AI white paper cover

To learn more about Darktrace and AI in cybersecurity download the CISO’s Guide to Cyber AI here.

Download the white paper to learn how buyers should approach purchasing AI-based solutions. It includes:

  • Key steps for selecting AI cybersecurity tools
  • Questions to ask and responses to expect from vendors
  • Understand tools available and find the right fit
  • Ensure AI investments align with security goals and needs
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

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November 6, 2025

Darktrace Named the Only 2025 Gartner® Peer Insights™ Customers’ Choice for Network Detection and Response

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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.

Discover why customers choose Darktrace for network and email security.

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

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Mikey Anderson
Product Marketing Manager, Network Detection & Response

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November 5, 2025

Tracking a Dragon: Investigating a DragonForce-affiliated ransomware attack with Darktrace

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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.

Darktrace’s detection of administrator credentials being used in Kerberos login events by an infected device.
Figure 1: Darktrace’s detection of administrator credentials being used in Kerberos login events by an infected device.
Darktrace’s detection of administrator credentials being used in SMB sessions 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
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.
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.

Live screenshot of the destination (45.135.232[.]229), captured via OSINT sources, displaying a Microsoft IIS Manager console webpage.
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.

Darktrace’s detection of SMB events (excluding Read events) where the device was seen moving or writing files with the “.df_win” extension.
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.
Darktrace’s detection of a spike in SMB Write events with the filename “readme.txt” on September 9, indicating the start of file encryption.
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.

Edited by Ryan Traill (Analyst Content Lead)

Appendices

References:

1. https://www.infosecurity-magazine.com/news/dragonforce-goup-ms-coop-harrods/

2. https://www.picussecurity.com/resource/blog/dragonforce-ransomware-attacks-retail-giants

3. https://blog.checkpoint.com/security/dragonforce-ransomware-redefining-hybrid-extortion-in-2025/

4. https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/proton66-part-1-mass-scanning-and-exploit-campaigns/

5. https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/proton66-part-2-compromised-wordpress-pages-and-malware-campaigns/

6. https://www.broadcom.com/support/security-center/protection-bulletin/proton66-infrastructure-tied-to-expanding-malware-campaigns-and-c2-operations

7. https://www.virustotal.com/gui/ip-address/45.135.232.229

8. https://spur.us/context/45.135.232.229

9. https://www.group-ib.com/blog/dragonforce-ransomware/

IoC - Type - Description + Confidence

·      45.135.232[.]229 - Endpoint Associated with Data Exfiltration

·      .readme.txt – Ransom Note File Extension

·      .df_win – File Encryption Extension Observed

MITRE ATT&CK Mapping

DragonForce TTPs vs Darktrace Models

Initial Access:

·      Anomalous Connection::Callback on Web Facing Device

Command and Control:

·      Compromise::SSL or HTTP Beacon

·      Compromise::Beacon to Young Endpoint

·      Compromise::Beaconing on Uncommon Port

·      Compromise::Suspicious SSL Activity

·      Anomalous Connection::Devices Beaconing to New Rare IP

·      Compromise::Suspicious HTTP and Anomalous Activity

·      DNS Tunnel with TXT Records

Tooling:

·      Anomalous File::EXE from Rare External Location

·      Anomalous File::Masqueraded File Transfer

·      Anomalous File::Numeric File Download

·      Anomalous File::Script from Rare External Location

·      Anomalous File::Uncommon Microsoft File then Exe

·      Anomalous File::Zip or Gzip from Rare External Location

·      Anomalous File::Uncommon Microsoft File then Exe

·      Anomalous File::Internet Facing System File Download

Reconnaissance:

·      Device::Suspicious SMB Query

·      Device::ICMP Address Scan

·      Anomalous Connection::SMB Enumeration

·      Device::Possible SMB/NTLM Reconnaissance

·      Anomalous Connection::Possible Share Enumeration Activity

·      Device::Possible Active Directory Enumeration

·      Anomalous Connection::Large Volume of LDAP Download

·      Device::Suspicious LDAP Search Operation

Lateral Movement:

·      User::Suspicious Admin SMB Session

·      Anomalous Connection::Unusual Internal Remote Desktop

·      Anomalous Connection::Unusual Long Remote Desktop Session

·      Anomalous Connection::Unusual Admin RDP Session

·      User::New Admin Credentials on Client

·      User::New Admin Credentials on Server

·      Multiple Device Correlations::Spreading New Admin Credentials

·      Anomalous Connection::Powershell to Rare External

·      Device::New PowerShell User Agent

·      Anomalous Active Directory Web Services

·      Compromise::Unusual SVCCTL Activity

Evasion:

·      Unusual Activity::Anomalous SMB Delete Volume

·      Persistence

·      Device::Anomalous ITaskScheduler Activity

·      Device::AT Service Scheduled Task

·      Actions on Objectives

·      Compromise::Ransomware::Suspicious SMB Activity (EM)

·      Anomalous Connection::Sustained MIME Type Conversion

·      Compromise::Ransomware::SMB Reads then Writes with Additional Extensions

·      Compromise::Ransomware::Possible Ransom Note Write

·      Data Sent to Rare Domain

·      Uncommon 1 GiB Outbound

·      Enhanced Unusual External Data Transfer

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.

The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content.

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About the author
Justin Torres
Cyber Analyst
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