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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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June 9, 2025

Modernising UK Cyber Regulation: Implications of the Cyber Security and Resilience Bill

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The need for security and continued cyber resilience

The UK government has made national security a key priority, and the new Cyber Security and Resilience Bill (CSRB) is a direct reflection of that focus. In introducing the Bill, Secretary of State for Science, Innovation and Technology, Peter Kyle, recognised that the UK is “desperately exposed” to cyber threats—from criminal groups to hostile nation-states that are increasingly targeting the UK's digital systems and critical infrastructure[1].

Context and timeline for the new legislation

First announced during the King’s Speech of July 2024, and elaborated in a Department for Science, Innovation and Technology (DSIT) policy statement published in April 2025, the CSRB is expected to be introduced in Parliament during the 2025-26 legislative session.

For now, organisations in the UK remain subject to the 2018 Network and Information Systems (NIS) Regulations – an EU-derived law which was drafted before today’s increasing digitisation of critical services, rise in cloud adoption and emergence of AI-powered threats.

Why modernisation is critical

Without modernisation, the Government believes UK’s infrastructure and economy risks falling behind international peers. The EU, which revised its cybersecurity regulation under the NIS2 Directive, already imposes stricter requirements on a broader set of sectors.

The urgency of the Bill is also underscored by recent high-impact incidents, including the Synnovis attack which targeted the National Health Service (NHS) suppliers and disrupted thousands of patient appointments and procedures[2]. The Government has argued that such events highlight a systemic failure to keep pace with a rapidly evolving threat landscape[3].

What the Bill aims to achieve

This Bill represents a decisive shift. According to the Government, it will modernise and future‑proof the UK’s cyber laws, extending oversight to areas where risk has grown but regulation has not kept pace[4]. While the legislation builds on previous consultations and draws lessons from international frameworks like the EU’s NIS2 directive, it also aims to tailor solutions to the UK’s unique threat environment.

Importantly, the Government is framing cybersecurity not as a barrier to growth, but as a foundation for it. The policy statement emphasises that strong digital resilience will create the stability businesses need to thrive, innovate, and invest[5]. Therefore, the goals of the Bill will not only be to enhance security but also act as an enabler to innovation and economic growth.

Recognition that AI changes cyber threats

The CSRB policy statement recognises that AI is fundamentally reshaping the threat landscape, with adversaries now leveraging AI and commercial cyber tools to exploit vulnerabilities in critical infrastructure and supply chains. Indeed, the NCSC has recently assessed that AI will almost certainly lead to “an increase in the frequency and intensity of cyber threats”[6]. Accordingly, the policy statement insists that the UK’s regulatory framework “must keep pace and provide flexibility to respond to future threats as and when they emerge”[7].

To address the threat, the Bill signals new obligations for MSPs and data centres, timely incident reporting and dynamic guidance that can be refreshed without fresh primary legislation, making it essential for firms to follow best practices.

What might change in day-to-day practice?

New organisations in scope of regulation

Under the existing Network and Information Systems (NIS) Regulations[8], the UK already supervises operators in five critical sectors—energy, transport, drinking water, health (Operators of Essential Services, OES) and digital infrastructure (Relevant Digital Service Providers, RDSPs).

The Cyber Security and Resilience Bill retains this foundation and adds Managed Service Providers (MSPs) and data centres to the scope of regulation to “better recognise the increasing reliance on digital services and the vulnerabilities posed by supply chains”[9]. It also grants the Secretary of State for Science, Innovation and Technology the power to add new sectors or sub‑sectors via secondary legislation, following consultation with Parliament and industry.

Managed service providers (MSPs)

MSPs occupy a central position within the UK’s enterprise information‑technology infrastructure. Because they remotely run or monitor clients’ systems, networks and data, they hold privileged, often continuous access to multiple environments. This foothold makes them an attractive target for malicious actors.

The Bill aims to bring MSPs in scope of regulation by making them subject to the same duties as those placed on firms that provide digital services under the 2018 NIS Regulations. By doing so, the Bill seeks to raise baseline security across thousands of customer environments and to provide regulators with better visibility of supply‑chain risk.

The proposed definition for MSPs is a service which:

  1. Is provided to another organisation
  2. Relies on the use of network and information systems to deliver the service
  3. Relates to ongoing management support, active administration and/or monitoring of AI systems, IT infrastructure, applications, and/or IT networks, including for the purpose of activities relating to cyber security.
  4. Involves a network connection and/or access to the customer’s network and information systems.

Data centres

Building on the September 2024 designation of data centres as critical national infrastructure, the CSRB will fold data infrastructure into the NIS-style regime by naming it an “relevant sector" and data centres as “essential service”[10].

About 182 colocation facilities run by 64 operators will therefore come under statutory duties to notify the regulator, maintain proportionate CAF-aligned controls and report significant incidents, regardless of who owns them or what workloads they host.

New requirements for regulated organisations

Incident reporting processes

There could be stricter timelines or broader definitions of what counts as a reportable incident. This might nudge organisations to formalise detection, triage, and escalation procedures.

The Government is proposing to introduce a new two-stage incident reporting process. This would include an initial notification which would be submitted within 24 hours of becoming aware of a significant incident, followed by a full incident report which should be submitted within 72 hours of the same.

Supply chain assurance requirements

Supply chains for the UK's most critical services are becoming increasingly complex and present new and serious vulnerabilities for cyber-attacks. The recent Synnovis ransomware attacks on the NHS[11] exemplify the danger posed by attacks against the supply chains of important services and organisations. This is concerning when reflecting on the latest Cyber Security Breaches survey conducted by DSIT, which highlights that fewer than 25% of large businesses review their supply chain risks[12].

Despite these risks, the UK’s legacy cybersecurity regulatory regime does not explicitly cover supply chain risk management. The UK instead relies on supporting and non-statutory guidance to close this gap, such as the NCSC’s Cyber Assessment Framework (CAF)[13].

The CSRB policy statement acts on this regulatory shortcoming and recognises that “a single supplier’s disruption can have far-reaching impacts on the delivery of essential or digital services”[14].

To address this, the Bill would make in-scope organisations (OES and RDPS) directly accountable for the cybersecurity of their supply chains. Secondary legislation would spell out these duties in detail, ensuring that OES and RDSPs systematically assess and mitigate third-party cyber risks.

Updated and strengthened security requirements

By placing the CAF into a firmer footing and backing it with a statutory Code of Practice, the Government is setting clearer expectations about government expectations on technical standards and methods organisations will need to follow to prove their resilience.

How Darktrace can help support affected organizations

Demonstrate resilience

Darktrace’s Self-Learning AITM continuously monitors your digital estate across cloud, network, OT, email, and endpoint to detect, investigate, and autonomously respond to emerging threats in real time. This persistent visibility and defense posture helps organizations demonstrate cyber resilience to regulators with confidence.

Streamline incident reporting and compliance

Darktrace surfaces clear alerts and automated investigation reports, complete with timeline views and root cause analysis. These insights reduce the time and complexity of regulatory incident reporting and support internal compliance workflows with auditable, AI-generated evidence.

Improve supply chain visibility

With full visibility across connected systems and third-party activity, Darktrace detects early indicators of lateral movement, account compromise, and unusual behavior stemming from vendor or partner access, reducing the risk of supply chain-originated cyber-attacks.

Ensure MSPs can meet new standards

For managed service providers, Darktrace offers native multi-tenant support and autonomous threat response that can be embedded directly into customer environments. This ensures consistent, scalable security standards across clients—helping MSPs address increasing regulatory obligations.

[related-resource]

References

[1] https://www.theguardian.com/uk-news/article/2024/jul/29/uk-desperately-exposed-to-cyber-threats-and-pandemics-says-minister

[2] https://www.england.nhs.uk/2024/06/synnovis-cyber-attack-statement-from-nhs-england/

[3] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[4] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[5] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[6] https://www.ncsc.gov.uk/report/impact-ai-cyber-threat-now-2027

[7] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[8] https://www.gov.uk/government/collections/nis-directive-and-nis-regulations-2018

[9] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[10] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[11] https://www.england.nhs.uk/2024/06/synnovis-cyber-attack-statement-from-nhs-england/

[12] https://www.gov.uk/government/statistics/cyber-security-breaches-survey-2025/cyber-security-breaches-survey-2025

[13] https://www.ncsc.gov.uk/collection/cyber-assessment-framework

[14] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

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June 5, 2025

Unpacking ClickFix: Darktrace’s detection of a prolific social engineering tactic

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What is ClickFix and how does it work?

Amid heightened security awareness, threat actors continue to seek stealthy methods to infiltrate target networks, often finding the human end user to be the most vulnerable and easily exploited entry point.

ClickFix baiting is an exploitation of the end user, making use of social engineering techniques masquerading as error messages or routine verification processes, that can result in malicious code execution.

Since March 2024, the simplicity of this technique has drawn attention from a range of threat actors, from individual cybercriminals to Advanced Persistent Threat (APT) groups such as APT28 and MuddyWater, linked to Russia and Iran respectively, introducing security threats on a broader scale [1]. ClickFix campaigns have been observed affecting organizations in across multiple industries, including healthcare, hospitality, automotive and government [2][3].

Actors carrying out these targeted attacks typically utilize similar techniques, tools and procedures (TTPs) to gain initial access. These include spear phishing attacks, drive-by compromises, or exploiting trust in familiar online platforms, such as GitHub, to deliver malicious payloads [2][3]. Often, a hidden link within an email or malvertisements on compromised legitimate websites redirect the end user to a malicious URL [4]. These take the form of ‘Fix It’ or fake CAPTCHA prompts [4].

From there, users are misled into believing they are completing a human verification step, registering a device, or fixing a non-existent issue such as a webpage display error. As a result, they are guided through a three-step process that ultimately enables the execution of malicious PowerShell commands:

  1. Open a Windows Run dialog box [press Windows Key + R]
  2. Automatically or manually copy and paste a malicious PowerShell command into the terminal [press CTRL+V]
  3. And run the prompt [press ‘Enter’] [2]

Once the malicious PowerShell command is executed, threat actors then establish command and control (C2) communication within the targeted environment before moving laterally through the network with the intent of obtaining and stealing sensitive data [4]. Malicious payloads associated with various malware families, such as XWorm, Lumma, and AsyncRAT, are often deployed [2][3].

Attack timeline of ClickFix cyber attack

Based on investigations conducted by Darktrace’s Threat Research team in early 2025, this blog highlights Darktrace’s capability to detect ClickFix baiting activity following initial access.

Darktrace’s coverage of a ClickFix attack chain

Darktrace identified multiple ClickFix attacks across customer environments in both Europe, the Middle East, and Africa (EMEA) and the United States. The following incident details a specific attack on a customer network that occurred on April 9, 2025.

Although the initial access phase of this specific attack occurred outside Darktrace’s visibility, other affected networks showed compromise beginning with phishing emails or fake CAPTCHA prompts that led users to execute malicious PowerShell commands.

Darktrace’s visibility into the compromise began when the threat actor initiated external communication with their C2 infrastructure, with Darktrace / NETWORK detecting the use of a new PowerShell user agent, indicating an attempt at remote code execution.

Darktrace / NETWORK's detection of a device making an HTTP connection with new PowerShell user agent, indicating PowerShell abuse for C2 communications.
Figure 1: Darktrace / NETWORK's detection of a device making an HTTP connection with new PowerShell user agent, indicating PowerShell abuse for C2 communications.

Download of Malicious Files for Lateral Movement

A few minutes later, the compromised device was observed downloading a numerically named file. Numeric files like this are often intentionally nondescript and associated with malware. In this case, the file name adhered to a specific pattern, matching the regular expression: /174(\d){7}/. Further investigation into the file revealed that it contained additional malicious code designed to further exploit remote services and gather device information.

Darktrace / NETWORK's detection of a numeric file, one minute after the new PowerShell User Agent alert.
Figure 2: Darktrace / NETWORK's detection of a numeric file, one minute after the new PowerShell User Agent alert.

The file contained a script that sent system information to a specified IP address using an HTTP POST request, which also processed the response. This process was verified through packet capture (PCAP) analysis conducted by the Darktrace Threat Research team.

By analyzing the body content of the HTTP GET request, it was observed that the command converts the current time to Unix epoch time format (i.e., 9 April 2025 13:26:40 GMT), resulting in an additional numeric file observed in the URI: /1744205200.

PCAP highlighting the HTTP GET request that sends information to the specific IP, 193.36.38[.]237, which then generates another numeric file titled per the current time.
Figure 3: PCAP highlighting the HTTP GET request that sends information to the specific IP, 193.36.38[.]237, which then generates another numeric file titled per the current time.

Across Darktrace’s investigations into other customers' affected by ClickFix campaigns, both internal information discovery events and further execution of malicious code were observed.

Data Exfiltration

By following the HTTP stream in the same PCAP, the Darktrace Threat Research Team assessed the activity as indicative of data exfiltration involving system and device information to the same command-and-control (C2) endpoint, , 193.36.38[.]237. This endpoint was flagged as malicious by multiple open-source intelligence (OSINT) vendors [5].

PCAP highlighting HTTP POST connection with the numeric file per the URI /1744205200 that indicates data exfiltration to 193.36.38[.]237.
Figure 4: PCAP highlighting HTTP POST connection with the numeric file per the URI /1744205200 that indicates data exfiltration to 193.36.38[.]237.

Further analysis of Darktrace’s Advanced Search logs showed that the attacker’s malicious code scanned for internal system information, which was then sent to a C2 server via an HTTP POST request, indicating data exfiltration

Advanced Search further highlights Darktrace's observation of the HTTP POST request, with the second numeric file representing data exfiltration.
Figure 5: Advanced Search further highlights Darktrace's observation of the HTTP POST request, with the second numeric file representing data exfiltration.

Actions on objectives

Around ten minutes after the initial C2 communications, the compromised device was observed connecting to an additional rare endpoint, 188.34.195[.]44. Further analysis of this endpoint confirmed its association with ClickFix campaigns, with several OSINT vendors linking it to previously reported attacks [6].

In the final HTTP POST request made by the device, Darktrace detected a file at the URI /init1234 in the connection logs to the malicious endpoint 188.34.195[.]44, likely depicting the successful completion of the attack’s objective, automated data egress to a ClickFix C2 server.

Darktrace / NETWORK grouped together the observed indicators of compromise (IoCs) on the compromised device and triggered an Enhanced Monitoring model alert, a high-priority detection model designed to identify activity indicative of the early stages of an attack. These models are monitored and triaged 24/7 by Darktrace’s Security Operations Center (SOC) as part of the Managed Threat Detection service, ensuring customers are promptly notified of malicious activity as soon as it emerges.

Darktrace correlated the separate malicious connections that pertained to a single campaign.
Figure 6: Darktrace correlated the separate malicious connections that pertained to a single campaign.

Darktrace Autonomous Response

In the incident outlined above, Darktrace was not configured in Autonomous Response mode. As a result, while actions to block specific connections were suggested, they had to be manually implemented by the customer’s security team. Due to the speed of the attack, this need for manual intervention allowed the threat to escalate without interruption.

However, in a different example, Autonomous Response was fully enabled, allowing Darktrace to immediately block connections to the malicious endpoint (138.199.156[.]22) just one second after the initial connection in which a numerically named file was downloaded [7].

Darktrace Autonomous Response blocked connections to a suspicious endpoint following the observation of the numeric file download.
Figure 7: Darktrace Autonomous Response blocked connections to a suspicious endpoint following the observation of the numeric file download.

This customer was also subscribed to our Managed Detection and Response service, Darktrace’s SOC extended a ‘Quarantine Device’ action that had already been autonomously applied in order to buy their security team additional time for remediation.

Autonomous Response blocked connections to malicious endpoints, including 138.199.156[.]22, 185.250.151[.]155, and rkuagqnmnypetvf[.]top, and also quarantined the affected device. These actions were later manually reinforced by the Darktrace SOC.
Figure 8: Autonomous Response blocked connections to malicious endpoints, including 138.199.156[.]22, 185.250.151[.]155, and rkuagqnmnypetvf[.]top, and also quarantined the affected device. These actions were later manually reinforced by the Darktrace SOC.

Conclusion

ClickFix baiting is a widely used tactic in which threat actors exploit human error to bypass security defenses. By tricking end point users into performing seemingly harmless, everyday actions, attackers gain initial access to systems where they can access and exfiltrate sensitive data.

Darktrace’s anomaly-based approach to threat detection identifies early indicators of targeted attacks without relying on prior knowledge or IoCs. By continuously learning each device’s unique pattern of life, Darktrace detects subtle deviations that may signal a compromise. In this case, Darktrace's Autonomous Response, when operating in a fully autonomous mode, was able to swiftly contain the threat before it could progress further along the attack lifecycle.

Credit to Keanna Grelicha (Cyber Analyst) and Jennifer Beckett (Cyber Analyst)

Appendices

NETWORK Models

  • Device / New PowerShell User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous Connection / Posting HTTP to IP Without Hostname
  • Anomalous Connection / Powershell to Rare External
  • Device / Suspicious Domain
  • Device / New User Agent and New IP
  • Anomalous File / New User Agent Followed By Numeric File Download (Enhanced Monitoring Model)
  • Device / Initial Attack Chain Activity (Enhanced Monitoring Model)

Autonomous Response Models

  • Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block
  • Antigena / Network::Significant Anomaly::Antigena Enhanced Monitoring from Client Block
  • Antigena / Network::External Threat::Antigena File then New Outbound Block
  • Antigena / Network::External Threat::Antigena Suspicious File Block
  • Antigena / Network::Significant Anomaly::Antigena Alerts Over Time Block
  • Antigena / Network::External Threat::Antigena Suspicious File Block

IoC - Type - Description + Confidence

·       141.193.213[.]11 – IP address – Possible C2 Infrastructure

·       141.193.213[.]10 – IP address – Possible C2 Infrastructure

·       64.94.84[.]217 – IP address – Possible C2 Infrastructure

·       138.199.156[.]22 – IP address – C2 server

·       94.181.229[.]250 – IP address – Possible C2 Infrastructure

·       216.245.184[.]181 – IP address – Possible C2 Infrastructure

·       212.237.217[.]182 – IP address – Possible C2 Infrastructure

·       168.119.96[.]41 – IP address – Possible C2 Infrastructure

·       193.36.38[.]237 – IP address – C2 server

·       188.34.195[.]44 – IP address – C2 server

·       205.196.186[.]70 – IP address – Possible C2 Infrastructure

·       rkuagqnmnypetvf[.]top – Hostname – C2 server

·       shorturl[.]at/UB6E6 – Hostname – Possible C2 Infrastructure

·       tlgrm-redirect[.]icu – Hostname – Possible C2 Infrastructure

·       diagnostics.medgenome[.]com – Hostname – Compromised Website

·       /1741714208 – URI – Possible malicious file

·       /1741718928 – URI – Possible malicious file

·       /1743871488 – URI – Possible malicious file

·       /1741200416 – URI – Possible malicious file

·       /1741356624 – URI – Possible malicious file

·       /ttt – URI – Possible malicious file

·       /1741965536 – URI – Possible malicious file

·       /1.txt – URI – Possible malicious file

·       /1744205184 – URI – Possible malicious file

·       /1744139920 – URI – Possible malicious file

·       /1744134352 – URI – Possible malicious file

·       /1744125600 – URI – Possible malicious file

·       /1[.]php?s=527 – URI – Possible malicious file

·       34ff2f72c191434ce5f20ebc1a7e823794ac69bba9df70721829d66e7196b044 – SHA-256 Hash – Possible malicious file

·       10a5eab3eef36e75bd3139fe3a3c760f54be33e3 – SHA-1 Hash – Possible malicious file

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique  

Spearphishing Link - INITIAL ACCESS - T1566.002 - T1566

Drive-by Compromise - INITIAL ACCESS - T1189

PowerShell - EXECUTION - T1059.001 - T1059

Exploitation of Remote Services - LATERAL MOVEMENT - T1210

Web Protocols - COMMAND AND CONTROL - T1071.001 - T1071

Automated Exfiltration - EXFILTRATION - T1020 - T1020.001

References

[1] https://www.logpoint.com/en/blog/emerging-threats/clickfix-another-deceptive-social-engineering-technique/

[2] https://www.proofpoint.com/us/blog/threat-insight/security-brief-clickfix-social-engineering-technique-floods-threat-landscape

[3] https://cyberresilience.com/threatonomics/understanding-the-clickfix-attack/

[4] https://www.group-ib.com/blog/clickfix-the-social-engineering-technique-hackers-use-to-manipulate-victims/

[5] https://www.virustotal.com/gui/ip-address/193.36.38.237/detection

[6] https://www.virustotal.com/gui/ip-address/188.34.195.44/community

[7] https://www.virustotal.com/gui/ip-address/138.199.156.22/detection

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About the author
Keanna Grelicha
Cyber Analyst
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