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January 9, 2024

Three Ways AI Secures OT & ICS from Cyber Attacks

Explore the three challenges facing industries that manage OT and ICS Systems, the benefits of adopting AI technology, and Darktrace / OT’s unique role!
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
Oakley Cox
Director of Product
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09
Jan 2024

What is OT and ICS?

Operational technologies and industrial control systems are the networked technologies used for the automation of physical processes. These are the technologies that allow operators to control processes and retrieve real time process data from a factory, rail system, pipeline, and other industrial processes.  

The role of AI in defending OT/ICS networks  

While largely adopted by industrial organizations, OT is utilized by Critical Infrastructures, these being the industries that directly affect the health, safety, and welfare of the public. As these organizations expand and adopt new networked industrial technologies, they are simultaneously expanding their attack surface.  

With a larger attack surface, more attacks targeting OT/ICS, and focused coordination around cyber security from regulatory authorities, security personnel have increasing workloads that make it difficult to keep pace with threats and vulnerabilities. Defenders are managing growing attack surfaces due to IT and OT convergence. Thus, the adoption of AI technology to protect, detect, respond, and recover from cyber incidents in industrial systems is paramount for keeping critical infrastructure safe.

This blog will explore three challenges facing industries managing OT/ICS, the perceived benefits of adopting AI technology to address these challenges, and Darktrace/OT’s unique role in this process.  

Darktrace also delivers complete AI-powered solutions to defend US federal government customers from cyber disruptions and ensure mission resilience. Learn more about high fidelity detection in Darktrace Federal’s TAC report.

Figure 1: AI statistics from Gartner and Deloitte

Three ways AI helps improves OT/ICS security  

1. Anomaly detection and response

In this heightened security landscape, OT/ICS environments face a spectrum of external cyber threats that demand vigilant defense. From the looming risk of industrial ransomware to the threat of insiders, yet another dimension is added to security challenge, meaning security professionals must be equipped to detect and respond to internal and external threats.  

While threats are eminent from both inside and outside the organization, many organizations rely on Indicator of Compromises (IOCs) for threat detection. By definition, these solutions can only detect network activity they recognize as an indicator of compromise; therefore, often miss insider threats and novel (zero-day) attacks because the tactics, techniques, and procedures (TTPs) and attack toolkits have never been seen in practice.  

Anomaly-based detection is best suited to combat never-before-seen threats and signatureless threats from the inside. However, not all detection methods are equal. Most anomaly-based detection solutions that leverage AI rely on a combination of supervised machine learning, deep learning, and transformers to train and inform their systems. This entails shipping your company’s data out to a large data lake housed somewhere in the cloud where it gets blended with attack data from thousands of other organizations. This data set gets used to train AI systems — yours and everyone else’s — to recognize patterns of attack based on previously encountered threats.  

While this method reduces the workload for security teams who would have to input attack data otherwise manually, it runs the same risk of only detecting known threats and has potential privacy concerns when shipping this data externally.  

To improve the quality and speed of anomaly detection, Darktrace/OT uses Self-Learning AI that leverages Bayesian Probabilistic Methodologies, Graph Theory, and Deep Neural Networks to learn your organization from the ground up in real time. By learning your unique organization, Darktrace/OT develops a sophisticated baseline knowledge of your network and assets, identifying abnormal activity that indicates a threat based on your unique network data at machine speed. Because the AI engine is local to the organization and/or assets, concerns of data residency and privacy are reduced, and the result is faster time to detect and triage incidents.  

Leveraging Self-Learning AI, Darktrace/OT uses autonomous response that severs only the anomalous or risky behaviors allowing the assets to continue to operate as normal. Organizations work with Darktrace to customize how they want Darktrace’s autonomous response to be applied. These options vary from on a device- by-device basis, device type by device type, or subnet by subnet basis and can be done completely autonomously or in human confirmation mode. This gives security teams more time to respond to an incident and reduces operational downtime when facing a threat.  

Darktrace leverages a combination of AI methods:

  • Self-Learning AI
  • Bayesian classification probabilistic models  
  • Deep neural networks
  • Transformers
  • Graph theory models
  • Clustering models  
  • Anomaly detection models
  • Generative and applied AI  
  • Natural language processing  
  • Supervised machine learning for investigation process of alerts

2. Vulnerability & Asset Management

At present, managing OT cyber risk is labor and resource intensive. Many organizations use third-party auditors to identify assets and vulnerabilities, grade compliance, and recommend improvements.  

At best, these exercises become tick-box exercises for companies to stay in compliance with little measurable reduction in cyber risk. At worst, asset owners can be left with a mountain of vulnerability information to work through, much of it irrelevant to the security risks Engineering and Operations teams deal with day to day, and increasingly out of date each passing day after the annual or biannual audit has been completed.  

In both cases, organizations are left using a patchwork of point products to address different aspects of preventative OT cyber security, most of which lack wider business context and lead to costly inefficiencies with no real impact to vulnerability or risk exposure.  

Darktrace’s technology helps in three unique ways:

  1. AI populates asset inventories: Self-Learning AI technology listens and learns from network traffic to populate or update asset inventories. It does this not just by identifying simple IPs, mac addresses, and hostnames, it learns from what it sees and automatically classifies or tags specific types of assets with the function that they perform. For example, if a specific device is performing functions like a PLC, sending commands to and from an HMI, it can appropriately tag and label these systems.
  2. AI prioritizes risk: Leveraging Bayesian Probabilistic Methodologies, Graph Theory, and Deep Neural Networks, Darktrace/OT assesses the strategic risks facing your organization in real time. Using knowledge of data points on all your networked assets, data flow topology, your assets vulnerabilities and OSINT, Darktrace identifies and prioritizes high-value assets, potential attack pathways based on an existing vulnerabilities targetability and impact.
  3. AI explains remediation tactics: Many OT devices run 24/7 operations and cannot be taken offline to apply a patch, assuming a patch is even available. Darktrace/OT uses natural language processing to provide and explain prioritized remediation and mitigation associated with a given cyber risk across all MITRE ATT&CK techniques. Thus, where a CVE exists but a patch cannot be applied, a different technical mitigation can be recommended to remove a potential attack path before it can be exploited, preemptively securing vital internal systems and assets.
Figure 2: A critical attack path which starts with the compromise of a PC in the internal IT network, and ends with a PLC in the OT network. Each step is mapped out to the real world TTPs including abuse of SSH sessions and the modifications of ICS programs

3. Simplify compliance and reporting

Organizations, regardless of size or resources, have compliance regulations they need to adhere to. What this creates is an increased workload for security professionals. For smaller organizations, security teams might lack the manpower or resources to report in the short time frame that is required. For large organizations, keeping track of a massive amount of assets proves to be a challenge. Both cases emanate the risk of reporting fatigue where organizations might be hesitant to report incidents due to the complexity and time requirements they demand.  

An AI engine within the Darktrace/OT platform, Cyber AI analyst autonomously investigates incidents, summarize findings in natural language, and provides comprehensive insights into the nature and scope of cyber threats to improve the time it takes to triage and report on incidents. The ability to stitch together and present related security events provides a holistic understanding of the incident, enabling security analysts to identify patterns, assess the scope of potential threats, and prioritize responses effectively.  

Darktrace's detection capabilities identify every stage of an intrusion, from a compromised domain controller to network reconnaissance and privilege escalation. The AI technology is capable of detecting infections across several devices and generating incident reports that piece together disparate events to give a clear security narrative containing details of the attack, bridging the communication gap between IT and OT specialists.  

Post-incident, the technology assists in outlining timelines, discerning compromised data, pinpointing unusual activities, and aiding security teams in proactive threat mitigation.  

With its capabilities, organizations can swiftly understand the attack timeline, affected assets, unauthorized accesses, compromised data points, and malicious interactions, facilitating appropriate communication and action. For example, when Cyber AI Analyst shows an attack path, the security team gains insight on the segmentation or lack thereof between two subnets allowing the security team to appropriately segment the subnets.  

Cyber AI improves critical infrastructure operators’ ability to report major cyber-attacks to regulatory authorities. Considering that 72 hours is the reporting period for most significant incidents — and 24 hours for ransomware payments — Cyber AI Analyst is no longer a nice-to-have but a must-have for critical infrastructure.

Figure 3: The tabs labeled 1-4 denote model breaches, each with a specific action and severity indicated by color dots. Darktrace integrates these breaches, offering the security team a unified view of interconnected security events.  

The right AI for the right challenge

Incident Phase:

Protect

Role of AI:

Cyber risk prioritization

Attack path modelling

Compliance reporting

Darktrace Product:

PREVENT/OT

Incident Phase:

Detect

Role of AI:

Anomaly detection

Triaging and investigating

Darktrace Product:

Cyber AI analyst

DETECT/OT

Incident Phase:

Respond

Role of AI: 

Autonomous response  

Incident reporting

Darktrace Product:

RESPOND/OT

Incident Phase:

Recover

Role of AI:

Incident preparedness

Incident simulations

Darktrace Product:

HEAL

Credit to: Nicole Carignan, VP of Strategic Cyber AI - Kendra Gonzalez Duran, Director of Technology Innovation - & Daniel Simonds, Director of Operational Technology for their contribution to this blog.

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
Oakley Cox
Director of Product

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April 29, 2025

MFA Under Attack: AiTM Phishing Kits Abusing Legitimate Services

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In late 2024 and early 2025, the Darktrace Security Operations Center (SOC) investigated alerts regarding separate cases of Software-as-a-Service (SaaS) account compromises on two customer environments that presented several similarities, suggesting they were part of a wider phishing campaign.

This campaign was found to leverage the project collaboration and note-taking application, Milanote, and the Tycoon 2FA phishing kit.

Legitimate services abused

As highlighted in Darktrace's 2024 Annual Threat Report [1], threat actors are abusing legitimate services, like Milanote, in their phishing campaigns. By leveraging these trusted platforms and domains, malicious actors can bypass traditional security measures, making their phishing emails appear benign and increasing the likelihood of successful attacks.

Darktrace categorizes these senders and platforms as free content senders. These services allow users to send emails containing custom content (e.g., files) from fully validated, fixed service address belonging to legitimate corporations. Although some of these services permit full body and subject customization by attackers, the structure of these emails is generally consistent, making it challenging to differentiate between legitimate and malicious emails.

What is Tycoon 2FA?

Tycoon 2FA is an Adversary-in-the-Middle (AitM) phishing kit, first seen in August 2023 and distributed via the Phishing-as-a-Service (PhaaS) model [2]. It targets multi-factor authentication (MFA) by intercepting credentials and MFA tokens during authentication on fake Microsoft or Google login pages. The attacker captures session cookies after MFA is completed, allowing them to replay the session and access the user account, even if credentials are reset. The rise in MFA use has increased the popularity of AitM phishing kits like Tycoon 2FA and Mamba 2FA, another AiTM phishing kit investigated by Darktrace.

Initial access via phishing email

At the beginning of 2025, Darktrace observed phishing emails leveraging Milanote being sent to multiple internal recipients in an organization. In this attack, the same email was sent to 19 different users, all of which were held by Darktrace.

The subject line of the emails mentioned both a legitimate internal user of the company, the company name, as well as a Milanote board regarding a “new agreement” in German. It is a common social engineering technique to mention urgent matters, such as unpaid invoices, expired passwords, or awaiting voicemails, in the subject line to prompt immediate action from the user. However, this tactic is now widely covered in phishing awareness training, making users more suspicious of such emails. In this case, while the subject mentioned a “new agreement,” likely raising the recipient’s curiosity, the tone remained professional and not overly alarming. Additionally, the mention of a colleague and the standardized language typical of free content sender emails further helped dispel concerns regarding the email.

These emails were sent by the legitimate address support@milanote[.]com and referenced "Milanote" in the personal field of the header but originated from the freemail address “ahnermatternk.ef.od.13@gmail[.]com”. Darktrace / EMAIL recognized that none of the recipients had previously received a file share email from Milanote, making this sender unfamiliar in the customer's email environment

The emails contained several benign links to legitimate Milanote endpoints (including an unsubscribe link) which were not flagged by Darktrace. However, they also included a malicious link designed to direct recipients to a pre-filled credential harvesting page hosted on Milanote, prompting them to register for an account. Despite not blocking the legitimate Milanote links in the same email, Darktrace locked the malicious link, preventing users from visiting the credential harvester.

Credential harvesting page sent to recipients, as seen in. sandbox environment.
Figure 1: Credential harvesting page sent to recipients, as seen in. sandbox environment.

Around one minute later, one recipient received a legitimate email from Milanote confirming their successful account registration, indicating they had accessed the phishing page. This email had a lower anomaly score and was not flagged by Darktrace / EMAIL because, unlike the first email, it did not contain any suspicious links and was a genuine account registration notification. Similarly, in the malicious Milanote email, only the link leading to the phishing page was blocked, while the benign and legitimate Milanote links remained accessible, demonstrating Darktrace’s precise and targeted actioning.

A legitimate and a malicious Milanote email received by one recipient.
Figure 2: A legitimate and a malicious Milanote email received by one recipient.

Around the same time, Darktrace / NETWORK observed the same user’s device making DNS query for the domain name “lrn.ialeahed[.]com” , which has been flagged as a Tycoon 2FA domain [2], suggesting the use of this phishing platform.

Once the user had entered their details in the credential harvester, it is likely that they were presented a document hosted on Milanote that contained the final payload link – likely hidden behind text instructing users to access a “new agreement” document.

External research indicates that the user was likely directed to a Cloudflare Turnstile challenge meant to reroute unwanted traffic, such as automated security scripts and penetration testing tools [2] [3]. After these checks and other background processes are completed, the user is directed to the final landing page. In this case, it was likely a fake login prompt hosted on the attacker’s server, where the user is asked to authenticate to their account using MFA. By burrowing malicious links and files in this manner, threat actors can evade analysis by traditional security email gateways, effectively bypassing their protection.

Darktrace’s analysis of the structure and word content of the phishing emails resulted in an 82% probability score that the email was malicious, and the email further received a 67% phishing inducement score, representing how closely the structure and word content of the emails compared to typical phishing emails.

All these unusual elements triggered multiple alerts in Darktrace / EMAIL, focusing on two main suspicious aspects: a new, unknown sender with no prior correspondence with the recipients or the environment, and the inclusion of a link to a previously unseen file storage solution.

Milanote phishing email as seen within Darktrace / EMAIL.
Figure 3: Milanote phishing email as seen within Darktrace / EMAIL.

After detecting the fifth email, the “Sender Surge” model alert was triggered in Darktrace / EMAIL due to a significant number of recipients being emailed by this new suspicious sender in a short period. These recipients were from various departments across the customer’s organization, including sales, marketing, purchasing, and production. Darktrace / EMAIL determined that the emails were sent to a highly unusual group of internal recipients, further raising doubts about the business legitimacy.

Darktrace / EMAIL suggested actions to contain the attack by holding all Milanote phishing emails back from recipient’s inboxes, except for the detailed email with locked links. However, autonomous actions were not enabled at the time, allowing the initial email to reach recipients' inboxes, providing a brief window for interaction. Unfortunately, during this window, one recipient clicked on the Milanote payload link, leading to the compromise of their account.

SaaS account takeover

About three minutes after the malicious Milanote email was received, Darktrace / IDENTITY detected an unusual login to the email recipient’s SaaS account. The SaaS actor was observed accessing files from their usual location in Germany, while simultaneously, a 100% rare login occurred from a location in the US that had never been seen in the customer’s environment before. This login was also flagged as suspicious by Microsoft 365, triggering a 'Conditional Access Policy' that required MFA authentication, which was successfully completed.

Tycoon 2FA adnimistration panel login page dated from October 2023 [3].
Figure 4: Tycoon 2FA adnimistration panel login page dated from October 2023 [3].

Despite the successful authentication, Darktrace / IDENTITY recognized that the login from this unusual location, coupled with simultaneous activity in another geographically distant location, were highly suspicious. Darktrace went on to observe MFA-validated logins from three separate US-based IP addresses: 89.185.80[.]19, 5.181.3[.]68, and 38.242.7[.]252. Most of the malicious activity was performed from the latter, which is associated with the Hide My Ass (HMA) VPN network [5].

Darktrace’s detection of the suspicious login from the US while the legitimate user was logged in from Germany.
Figure 5: Darktrace’s detection of the suspicious login from the US while the legitimate user was logged in from Germany.
Darktrace’s detection of the suspicious login following successful MFA authentication.
Figure 6: Darktrace’s detection of the suspicious login following successful MFA authentication.

Following this, the malicious actor accessed the user’s inbox and created a new mailbox rule named “GTH” that deleted any incoming email containing the string “milanote” in the subject line or body. Rules like this are a common technique used by attackers to leverage compromised accounts for launching phishing campaigns and concealing replies to phishing emails that might raise suspicions among legitimate account holders. Using legitimate, albeit compromised, accounts to send additional phishing emails enhances the apparent legitimacy of the malicious emails. This tactic has been reported as being used by Tycoon 2FA attackers [4].

The attacker accessed over 140 emails within the legitimate user’s inbox, including both the inbox and the “Sent Items” folder. Notably, the attacker accessed five emails in the “Sent Items” folder and modified their attachments. These emails were mainly related to invoices, suggesting the threat actor may have been looking to hijack those email threads to send fake invoices or replicate previous invoice emails.

Darktrace’s Cyber AI AnalystTM launched autonomous investigations into the individual events surrounding this suspicious activity. It connected these separate events into a single, broad account takeover incident, providing the customer with a clearer view of the ongoing compromise.

Cyber AI Analyst’s detection of unusual SaaS account activities in a single incident.
Figure 7: Cyber AI Analyst’s detection of unusual SaaS account activities in a single incident.
Cyber AI Analyst investigation of suspicious activities performed by the attacker.
Figure 8: Cyber AI Analyst investigation of suspicious activities performed by the attacker.

Darktrace's response

Within three minutes of the first unusual login alert, Darktrace’s Autonomous Response intervened, disabling the compromised user account for two hours.

As the impacted customer was subscribed to the Managed Threat Detection Service, Darktrace’s SOC team investigated the activity further and promptly alerted the customer’s security team. With the user’s account still disabled by Autonomous Response, the attack was contained, allowing the customer’s security team valuable time to investigate and remediate. Within ten minutes of receiving the alert from Darktrace’s SOC, they reset the user’s password, closed all active SaaS sessions, and deleted the malicious email rule. Darktrace’s SOC further supported the customer through the Security Operations Service Support service by providing information about the data accessed and identifying any other affected users.

Autonomous Response actions carried out by Darktrace / IDENTITY to contain the malicious activity
Figure 9: Autonomous Response actions carried out by Darktrace / IDENTITY to contain the malicious activity.

A wider Milanote phishing campaign?

Around a month before this compromise activity, Darktrace alerted another customer to similar activities involving two compromised user accounts. These accounts created new inbox rules named “GFH” and “GVB” to delete all incoming emails containing the string “milanote” in their subject line and/or body.

The phishing emails that led to the compromise of these user accounts were similar to the ones discussed above. Specifically, these emails were sent via the Milanote platform and referenced a “new agreement” (in Spanish) being shared by a colleague. Additionally, the payload link included in the phishing emails showed the same UserPrincipalName (UPN) attribute (i.e., click?upn=u001.qLX9yCzR), which has been seen in other Milanote phishing emails leveraging Tycoon 2FA reported by OSINT sources [6]. Interestingly, in some cases, the email also referenced a “new agreement” in Portuguese, indicating a global campaign.

Based on the similarities in the rule’s naming convention and action, as well as the similarities in the phishing email subjects, it is likely that these were part of the same campaign leveraging Milanote and Tycoon 2FA to compromise user accounts. Since its introduction, the Tycoon 2FA phishing kit has undergone several enhancements to increase its stealth and obfuscation methods, making it harder for security tools to detect. For example, the latest versions contain special source code to obstruct web page analysis by defenders, prevent users from copying meaningful text from the phishing webpages, and disable the right-click menu to prevent offline analysis [4].

Conclusion

Threat actors are continually employing new methods to bypass security detection tools and measures. As highlighted in this blog, even robust security mechanisms like MFA can be compromised using AitM phishing kits. The misuse of legitimate services such as Milanote for malicious purposes can help attackers evade traditional email security solutions by blurring the distinction between legitimate and malicious content.

This is why security tools based on anomaly detection are crucial for defending against such attacks. However, user awareness is equally important. Delays in processing can impact the speed of response, making it essential for users to be informed about these threats.

Appendices

References

[1] https://www.darktrace.com/resources/annual-threat-report-2024

[2] https://www.validin.com/blog/tycoon_2fa_analyzing_and_hunting_phishing-as-a-service_domains

[3] https://blog.sekoia.io/tycoon-2fa-an-in-depth-analysis-of-the-latest-version-of-the-aitm-phishing-kit/#h-iocs-amp-technical-details

[4] https://blog.barracuda.com/2025/01/22/threat-spotlight-tycoon-2fa-phishing-kit

[5] https://spur.us/context/38.242.7.252    

[6] https://any.run/report/5ef1ac94e4c6c1dc35579321c206453aea80d414108f9f77abd2e2b03ffbd658/be5351d9-53c0-470b-8708-ee2e29300e70

Indicators of Compromise (IoCs)

IoC         Type      Description + Probability

89.185.80[.]19 - IP Address - Malicious login

5.181.3[.]68 - IP Address -Malicious login

38.242.7[.]252 - IP Address - Malicious login and new email inbox rule creation -  Hide My Ass VPN

lrn.ialeahed[.]com – Hostname - Likely Tycoon 2FA domain

Darktrace Model Detections

Email alerts

Platforms / Free Content Sender + High Sender Surge

Platforms / Free Content Sender + Sender Surge

Platforms / Free Content Sender + Unknown Initiator

Platforms / Free Content Sender

Platforms / Free Content Sender + First Time Recipient

Unusual / New Sender Surge

Unusual / Sender Surge

Antigena Anomaly / High Antigena Anomaly

Association / Unknown Sender

History / New Sender

Link / High Rarity Link to File Storage

Link/ Link To File Storage

Link / Link to File Storage + Unknown Sender

Link / Low Link Association

Platforms / Free Content Sender + First Time Initiator

Platforms / Free Content Sender + Unknown Initiator + Freemail

Platforms / Free Content Sender Link

Unusual / Anomalous Association

Unusual / Unlikely Recipient Association

IDENTITY

SaaS / Access / Unusual External Source for SaaS Credential Use

SaaS / Compromise / Login from Rare High Risk Endpoint

SaaS / Access / M365 High Risk Level Login

SaaS / Compromise / Login From Rare Endpoint While User Is Active

SaaS / Access / MailItemsAccessed from Rare Endpoint

SaaS / Unusual Activity / Multiple Unusual SaaS Activities

SaaS / Unusual Activity / Multiple Unusual External Sources For SaaS Credential

SaaS / Compliance / Anomalous New Email Rule

SaaS / Compromise / Unusual Login and New Email Rule

SaaS / Compromise / SaaS Anomaly Following Anomalous Login

Antigena / SaaS / Antigena Suspicious SaaS Activity Block

Antigena / SaaS / Antigena Enhanced Monitoring from SaaS User Block

Antigena / SaaS / Antigena Unusual Activity Block

Antigena / SaaS / Antigena Suspicious SaaS and Email Activity Block

Cyber AI Analyst Incident

Possible Hijack of Office365 Account

MITRE ATT&CK Mapping

Tactic – Technique

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - Cloud Accounts

INITIAL ACCESS - Phishing

CREDENTIAL ACCESS - Steal Web Session Cookie

PERSISTENCE - Account Manipulation

PERSISTENCE - Outlook Rules

RESOURCE DEVELOPMENT - Email Accounts

RESOURCE DEVELOPMENT - Compromise Accounts

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About the author
Alexandra Sentenac
Cyber Analyst

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April 29, 2025

The Importance of NDR in Resilient XDR

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As threat actors become more adept at targeting and disabling EDR agents, relying solely on endpoint detection leaves critical blind spots.

Network detection and response (NDR) offers the visibility and resilience needed to catch what EDR can’t especially in environments with unmanaged devices or advanced threats that evade local controls.

This blog explores how threat actors can disable or bypass EDR-based XDR solutions and demonstrates how Darktrace’s approach to NDR closes the resulting security gaps with Self-Learning AI that enables autonomous, real-time detection and response.

Threat actors see local security agents as targets

Recent research by security firms has highlighted ‘EDR killers’: tools that deliberately target EDR agents to disable or damage them. These include the known malicious tool EDRKillShifter, the open source EDRSilencer, EDRSandblast and variants of Terminator, and even the legitimate business application HRSword.

The attack surface of any endpoint agent is inevitably large, whether the software is challenged directly, by contesting its local visibility and access mechanisms, or by targeting the Operating System it relies upon. Additionally, threat actors can readily access and analyze EDR tools, and due to their uniformity across environments an exploit proven in a lab setting will likely succeed elsewhere.

Sophos have performed deep research into the EDRShiftKiller tool, which ESET have separately shown became accessible to multiple threat actor groups. Cisco Talos have reported via TheRegister observing significant success rates when an EDR kill was attempted by ransomware actors.

With the local EDR agent silently disabled or evaded, how will the threat be discovered?

What are the limitations of relying solely on EDR?

Cyber attackers will inevitably break through boundary defences, through innovation or trickery or exploiting zero-days. Preventive measures can reduce but not completely stop this. The attackers will always then want to expand beyond their initial access point to achieve persistence and discover and reach high value targets within the business. This is the primary domain of network activity monitoring and NDR, which includes responsibility for securing the many devices that cannot run endpoint agents.

In the insights from a CISA Red Team assessment of a US CNI organization, the Red Team was able to maintain access over the course of months and achieve their target outcomes. The top lesson learned in the report was:

“The assessed organization had insufficient technical controls to prevent and detect malicious activity. The organization relied too heavily on host-based endpoint detection and response (EDR) solutions and did not implement sufficient network layer protections.”

This proves that partial, isolated viewpoints are not sufficient to track and analyze what is fundamentally a connected problem – and without the added visibility and detection capabilities of NDR, any downstream SIEM or MDR services also still have nothing to work with.

Why is network detection & response (NDR) critical?

An effective NDR finds threats that disable or can’t be seen by local security agents and generally operates out-of-band, acquiring data from infrastructure such as traffic mirroring from physical or virtual switches. This means that the security system is extremely inaccessible to a threat actor at any stage.

An advanced NDR such as Darktrace / NETWORK is fully capable of detecting even high-end novel and unknown threats.

Detecting exploitation of Ivanti CS/PS with Darktrace / NETWORK

On January 9th 2025, two new vulnerabilities were disclosed in Ivanti Connect Secure and Policy Secure appliances that were under malicious exploitation. Perimeter devices, like Ivanti VPNs, are designed to keep threat actors out of a network, so it's quite serious when these devices are vulnerable.

An NDR solution is critical because it provides network-wide visibility for detecting lateral movement and threats that an EDR might miss, such as identifying command and control sessions (C2) and data exfiltration, even when hidden within encrypted traffic and which an EDR alone may not detect.

Darktrace initially detected suspicious activity connected with the exploitation of CVE-2025-0282 on December 29, 2024 – 11 days before the public disclosure of the vulnerability, this early detection highlights the benefits of an anomaly-based network detection method.

Throughout the campaign and based on the network telemetry available to Darktrace, a wide range of malicious activities were identified, including the malicious use of administrative credentials, the download of suspicious files, and network scanning in the cases investigated.

Darktrace / NETWORK’s autonomous response capabilities played a critical role in containment by autonomously blocking suspicious connections and enforcing normal behavior patterns. At the same time, Darktrace Cyber AI Analyst™ automatically investigated and correlated the anomalous activity into cohesive incidents, revealing the full scope of the compromise.

This case highlights the importance of real-time, AI-driven network monitoring to detect and disrupt stealthy post-exploitation techniques targeting unmanaged or unprotected systems.

Unlocking adaptive protection for evolving cyber risks

Darktrace / NETWORK uses unique AI engines that learn what is normal behavior for an organization’s entire network, continuously analyzing, mapping and modeling every connection to create a full picture of your devices, identities, connections, and potential attack paths.

With its ability to uncover previously unknown threats as well as detect known threats Darktrace is an essential layer of the security stack. Darktrace has helped secure customers against attacks including 2024 threat actor campaigns against Fortinet’s FortiManager , Palo Alto firewall devices, and more.  

Stay tuned for part II of this series which dives deeper into the differences between NDR types.

Credit to Nathaniel Jones VP, Security & AI Strategy, FCISO & Ashanka Iddya, Senior Director of Product Marketing for their contribution to this blog.

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
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