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July 9, 2024

Hashing out TA577: Darktrace’s Detection of NTLM Hash Theft

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09
Jul 2024
In early 2024, the TA577 threat group was observed utilizing a new attack chain to steal NTLM authentication data. Targets received a phishing email containing a ZIP file attachment which facilitated connection to malicious infrastructure, with NTLM hashes ultimately gathered by attackers. Here we detail Darktrace’s detection of this activity across its customer base.

What is credential theft and how does it work?

What began as a method to achieve unauthorized access to an account, often driven by the curiosity of individual attackers, credentials theft become a key tactic for malicious actors and groups, as stolen login credentials can be abused to gain unauthorized access to accounts and systems. This access can be leveraged to carry out malicious activities such as data exfiltration, fraud, espionage and malware deployment.

It is therefore no surprise that the number of dark web marketplaces selling privileged credentials has increased in recent years, making it easier for malicious actors to monetize stolen credentials [1]. This, in turn, has created new opportunities for threat actors to use increasingly sophisticated tactics such as phishing, social engineering and credential stuffing in their attacks, targeting individuals, organizations and government entities alike [1].

Credential theft example

TA577 Threat Actor

TA577 is a threat actor known to leverage stolen credentials, also known as Hive0118 [2], an initial access broker (IAB) group that was previously known for delivering malicious payloads [2]. On March 4, 2024, Proofpoint reported evidence of TA577 using a new attack chain with a different aim in mind: stealing NT LAN Manager (NTLM) hashes that can be used to authenticate to systems without needing to know plaintext passwords [3].

How does TA577 steal credentials?

Proofpoint reported that this new attack chain, which was first observed on February 26 and 27, was made up of two distinct campaigns. The first campaign consisted of a phishing attack featuring tens of thousands of emails targeting hundreds of organizations globally [3]. These phishing emails often appeared as replies to previous messages (thread hijacking) and contained zipped HTML attachments that each contained a unique file hash, customized for each recipient [3]. These attached files also contained a HTTP Meta refresh function, which triggered an automatic connection to a text file hosted on external IP addresses running as SMB servers [3].

When attempting to access the text file, the server requires an SMB session authentication via NTLM. This session is initiated when a client sends an ‘SMB_COM_NEGOTIATE’ request to the server, which answers with a ‘SMB_COM_NEGOTIATE’ response.

The client then proceeds to send a ‘SMB_COM_SESSION_SETUP_ANDX’ request to start the SMB session setup process, which includes initiating the NTLM authentication process. The server responds with an ‘SMB_COM_SESSION_SETUP_ANDX’ response, which includes an NTLM challenge message [6].

The client can then use the challenge message and its own credentials to generate a response by hashing its password using an NTLM hash algorithm. The response is sent to the server in an ‘SMB_COM_SESSION_SETUP_ANDX’ request. The server validates the response and, if the authentication is successful, the server answers with a final ‘SMB_COM_SESSION_SETUP_ANDX’ response, which completes the session setup process and allows the client to access the file listed on the server [6].

What is the goal of threat actor TA577?

As no malware delivery was detected during these sessions, researchers have suggested that the aim of TA577 was not to deliver malware, but rather to take advantage of the NTLMV2 challenge/response to steal NTLM authentication hashes [3] [4]. Hashes stolen by attackers can be exploited in pass-the-hash attacks to authenticate to a remote server or service [4]. They can also be used for offline password cracking which, if successful, could be utilized to escalate privileges or perform lateral movement through a target network [4]. Under certain circumstances, these hashes could also permit malicious actors to hijack accounts, access sensitive information and evade security products [4].

The open-source toolkit Impacket, which includes modules for password cracking [5] and which can be identified by the default NTLM server challenge “aaaaaaaaaaaaaaaa”[3], was observed during the SMB sessions. This indicates that TA577 actor aim to use stolen credentials for password cracking and pass-the-hash attacks.

TA577 has previously been associated with Black Basta ransomware infections and Qbot, and has been observed delivering various payloads including IcedID, SystemBC, SmokeLoader, Ursnif, and Cobalt Strike [2].This change in tactic to follow the current trend of credential theft may indicate that not only are TA577 actors aware of which methods are most effective in the current threat landscape, but they also have monetary and time resources needed to create new methods to bypass existing detection tools [3].  

Darktrace’s Coverage of TA577 Activity

On February 26 and 27, coinciding with the campaign activity reported by Proofpoint, Darktrace/Email™ observed a surge of inbound emails from numerous suspicious domains targeting multiple customer environments. These emails consistently included zip files with seemingly randomly generated names, containing HTLM content and links to an unusual external IP address [3].

A summary of anomaly indicators seen for a campaign email sent by TA577, as detected by Darktrace/Email.
Figure 1: A summary of anomaly indicators seen for a campaign email sent by TA577, as detected by Darktrace/Email.
Details of the name and size of the .zip file attached to a campaign email, along with the Darktrace/Email model alerts triggered by the email.
Figure 2: Details of the name and size of the .zip file attached to a campaign email, along with the Darktrace/Email model alerts triggered by the email.

The URL of these links contained an unusually named .txt file, which corresponds with Proofpoint reports of the automatic connection to a text file hosted on an external SMB server made when the attachment is opened [3].

A link to a rare external IP address seen within a campaign email, containing an unusually named .txt file.
Figure 3: A link to a rare external IP address seen within a campaign email, containing an unusually named .txt file.

Darktrace identified devices on multiple customer networks connecting to external SMB servers via the SMB protocol. It understood this activity was suspicious as the SMB protocol is typically reserved for internal connections and the endpoint in question had never previously been observed on the network.

The Event Log of a ‘Compliance / External Windows Communication’ model alert showing a connection to an external SMB server on destination port 445.
Figure 4: The Event Log of a ‘Compliance / External Windows Communication’ model alert showing a connection to an external SMB server on destination port 445.
External Sites Summary highlighting the rarity of the external SMB server.
Figure 5: External Sites Summary highlighting the rarity of the external SMB server.
External Sites Summary highlightin that the SMB server is geolocated in Moldova.
Figure 6: External Sites Summary highlightin that the SMB server is geolocated in Moldova.

During these connections, Darktrace observed multiple devices establishing an SMB session to this server via a NTLM challenge/response, representing the potential theft of the credentials used in this session. During this session, some devices also attempted to access an unusually named .txt file, further indicating that the affected devices were trying to access the .txt file hosted on external SMB servers [3].

Packet captures (PCAPs) of these sessions show the default NTLM server challenge, indicating the use of Impacket, suggesting that the captured NTLM hashes were to be used for password cracking or pass-the-hash-attacks [3]

PCAP analysis showing usage of the default NTLM server challenge associated with Impacket.
Figure 7: PCAP analysis showing usage of the default NTLM server challenge associated with Impacket.

Conclusions

Ultimately, Darktrace’s suite of products effectively detected and alerted for multiple aspects of the TA577 attack chain and NTLM hash data theft activity across its customer base. Darktrace/Email was able to uncover the inbound phishing emails that served as the initial access vector for TA577 actors, while Darktrace DETECT identified the subsequent external connections to unusual external locations and suspicious SMB sessions.

Furthermore, Darktrace’s anomaly-based approach enabled it to detect suspicious TA577 activity across the customer base on February 26 and 27, prior to Proofpoint’s report on their new attack chain. This showcases Darktrace’s ability to identify emerging threats based on the subtle deviations in a compromised device’s behavior, rather than relying on a static list of indicators of compromise (IoCs) or ‘known bads’.

This approach allows Darktrace to remain one step ahead of increasingly adaptive threat actors, providing organizations and their security teams with a robust AI-driven solution able to safeguard their networks in an ever-evolving threat landscape.

Credit to Charlotte Thompson, Cyber Analyst, Anna Gilbertson, Cyber Analyst.

References

1)    https://www.sentinelone.com/cybersecurity-101/what-is-credential-theft/

2)    https://malpedia.caad.fkie.fraunhofer.de/actor/ta577

3)    https://www.proofpoint.com/us/blog/threat-insight/ta577s-unusual-attack-chain-leads-ntlm-data-theft

4)    https://www.bleepingcomputer.com/news/security/hackers-steal-windows-ntlm-authentication-hashes-in-phishing-attacks/

5)    https://pawanjswal.medium.com/the-power-of-impacket-a-comprehensive-guide-with-examples-1288f3a4c674

6)    https://learn.microsoft.com/en-us/openspecs/windows_protocols/ms-nlmp/c083583f-1a8f-4afe-a742-6ee08ffeb8cf

7)    https://www.hivepro.com/threat-advisory/ta577-targeting-windows-ntlm-hashes-in-global-campaigns/

Darktrace Model Detections

Darktrace/Email

·       Attachment / Unsolicited Archive File

·       Attachment / Unsolicited Attachment

·       Link / New Correspondent Classified Link

·       Link / New Correspondent Rare Link

·       Spoof / Internal User Similarities

Darktrace DETECT

·       Compliance / External Windows Communications

Darktrace RESPOND

·       Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

IoCs

IoC - Type - Description

176.123.2[.]146 - IP address -Likely malicious SMB Server

89.117.2[.]33 - IP address - Likely malicious SMB Server

89.117.1[.]161 - IP address - Likely malicious SMB Server

104.129.20[.]167 - IP address - Likely malicious SMB Server

89.117.1[.]160 - IP address - Likely malicious SMB Server

85.239.33[.]149 - IP address - Likely malicious SMB Server

89.117.2[.]34 - IP address - Likely malicious SMB Server

146.19.213[.]36 - IP address - Likely malicious SMB Server

66.63.188[.]19 - IP address - Likely malicious SMB Server

103.124.104[.]76 - IP address - Likely malicious SMB Server

103.124.106[.]224 - IP address - Likely malicious SMB Server

\5aohv\9mn.txt - SMB Path and File - SMB Path and File

\hvwsuw\udrh.txt - SMB Path and File - SMB Path and File

\zkf2rj4\VmD.txt = SMB Path and File - SMB Path and File

\naams\p3aV.txt - SMB Path and File - SMB Path and File

\epxq\A.txt - SMB Path and File - SMB Path and File

\dbna\H.txt - SMB Path and File - SMB Path and File

MAGNAMSB.zip – Filename - Phishing Attachment

e751f9dddd24f7656459e1e3a13307bd03ae4e67 - SHA1 Hash - Phishing Attachment

OMNIS2C.zip  - Filename - Phishing Attachment

db982783b97555232e28d5a333525118f10942e1 - SHA1 Hash - Phishing Attachment

aaaaaaaaaaaaaaaa - NTLM Server Challenge -Impacket Default NTLM Challenge

MITRE ATT&CK Tactics, Techniques and Procedures (TTPs)

Tactic - Technique

TA0001            Initial Access

TA0002            Execution

TA0008            Lateral Movement

TA0003            Persistence

TA0005            Defense Evasion

TA0006            Credential Access

T1021.002       SMB/Windows Admin Shares

T1021  Remote Services

T1566.001       Spearfishing Attachment

T1566  Phishing

T1204.002       Malicious File

T1204  User Execution

T1021.002       SMB/Windows Admin Shares

T1574  Hijack Execution Flow

T1021  Remote Services

T1555.004       Windows Credential Manager

T1555  Credentials from Password Stores

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.
Author
Charlotte Thompson
Cyber Analyst
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February 19, 2025

Darktrace Releases Annual 2024 Threat Insights

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Introduction: Darktrace’s threat research

Defenders must understand the threat landscape in order to protect against it. They can do that with threat intelligence.

Darktrace approaches threat intelligence with a unique perspective. Unlike traditional security vendors that rely on established patterns from past incidents, it uses a strategy that is rooted in the belief that identifying behavioral anomalies is crucial for identifying both known and novel threats.

For Darktrace analysts and researchers, the incidents detected by the AI solution mark the beginning of a deeper investigation, aiming to connect mitigated threats to wider trends from across the threat landscape. Through hindsight analysis, the Darktrace Threat Research team has highlighted numerous threats, including zero-day, n-day, and other novel attacks, showcasing their evolving nature and Darktrace’s ability to identify them.

In 2024, the Threat Research team observed major trends around vulnerabilities in internet-facing systems, new and re-emerging ransomware strains, and sophisticated email attacks. Read on to discover some of our key insights into the current cybersecurity threat landscape.

Multiple campaigns target vulnerabilities in internet-facing systems

It is increasingly common for threat actors to identify and exploit newly discovered vulnerabilities in widely used services and applications, and in some cases, these vulnerability exploitations occur within hours of disclosure.

In 2024, the most significant campaigns observed involved the ongoing exploitation of zero-day and n-day vulnerabilities in edge and perimeter network technologies. In fact, in the first half of the year, 40% of all identified campaign activity came from the exploitation of internet-facing devices. Some of the most common exploitations involved Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances, Palo Alto Network (PAN-OS) firewall devices, and Fortinet appliances.

Darktrace helps security teams identify suspicious behavior quickly, as demonstrated with the critical vulnerability in PAN-OS firewall devices. The vulnerability was publicly disclosed on April 11, 2024, yet with anomaly-based detection, Darktrace’s Threat Research team was able to identify a range of suspicious behavior related to exploitation of this vulnerability, including command-and-control (C2) connectivity, data exfiltration, and brute-forcing activity, as early as March 26.

That means that Darktrace and our Threat Research team detected this Common Vulnerabilities and Exposure (CVE) exploitation 16 days before the vulnerability was disclosed. Addressing critical vulnerabilities quickly massively benefits security, as teams can reduce their effectiveness by slowing malicious operations and forcing attackers to pursue more costly and time-consuming methods.

Persistent ransomware threats continue to evolve

The continued adoption of the Ransomware-as-a-Service (RaaS) model provides even less experienced threat actors with the tools needed to carry out disruptive attacks, significantly lowering the barrier to entry.

The Threat Research team tracked both novel and re-emerging strains of ransomware across the customer fleet, including Akira, LockBit, and Lynx. Within these ransomware attempts and incidents, there were notable trends in attackers’ techniques: using phishing emails as an attack vector, exploiting legitimate tools to mask C2 communication, and exfiltrating data to cloud storage services.

Read the Annual 2024 Threat Report for the complete list of prominent ransomware actors and their commonly used techniques.

Onslaught of email threats continues

With a majority of attacks originating from email, it is crucial that organizations secure the inboxes and beyond.

Between December 21, 2023, and December 18, 2024, Darktrace / EMAIL detected over 30.4 million phishing emails across the fleet. Of these, 70% successfully bypassed Domain-based Message Authentication, Reporting, and Conformance (DMARC) verification checks and 55% passed through all other existing layers of customer email security.

The abuse of legitimate services and senders continued to be a significant method for threat actors throughout 2024. By leveraging trusted platforms and domains, malicious actors can bypass traditional security measures and increase the likelihood of their phishing attempts being successful.

This past year, there was a substantial use of legitimately authenticated senders and previously established domains, with 96% of phishing emails detected by Darktrace / EMAIL utilizing existing domains rather than registering new ones.

These are not the only types of email attacks we observed. Darktrace detected over 2.7 million emails with multistage payloads.

While most traditional cybersecurity solutions struggle to cover multiple vectors and recognize each stage of complex attacks as part of wider malicious activity, Darktrace can detect and respond across email, identities, network, and cloud.

Conclusion

The Darktrace Threat Research team continues to monitor the ever-evolving threat landscape. Major patterns over the last year have revealed the importance of fast-acting, anomaly-based detection like Darktrace provides.

For example, response speed is essential when campaigns target vulnerabilities in internet-facing systems, and these vulnerabilities can be exploited by attackers within hours of their disclosure if not even before that.

Similarly, anomaly-based detection can identify hard to find threats like ransomware attacks that increasingly use living-off-the-land techniques and legitimate tools to hide malicious activity. A similar pattern can be found in the realm of email security, where attacks are also getting harder to spot, especially as they frequently exploit trusted senders, use redirects via legitimate services, and craft attacks that bypass DMARC and other layers of email security.

As attacks appear with greater complexity, speed, and camouflage, defenders must have timely detection and containment capabilities to handle all emerging threats. These hard-to-spot attacks can be identified and stopped by Darktrace.

Download the full report

Discover the latest threat landscape trends and recommendations from the Darktrace Threat Research team.

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February 18, 2025

Unifying IT & OT With AI-Led Investigations for Industrial Security

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As industrial environments modernize, IT and OT networks are converging to improve efficiency, but this connectivity also creates new attack paths. Previously isolated OT systems are now linked to IT and cloud assets, making them more accessible to attackers.

While organizations have traditionally relied on air gaps, firewalls, data diodes, and access controls to separate IT and OT, these measures alone aren’t enough. Threat actors often infiltrate IT/Enterprise networks first then exploit segmentation, compromising credentials, or shared IT/OT systems to move laterally, escalate privileges, and ultimately enter the OT network.

To defend against these threats, organizations must first ensure they have complete visibility across IT and OT environments.

Visibility: The first piece of the puzzle

Visibility is the foundation of effective industrial cybersecurity, but it’s only the first step. Without visibility across both IT and OT, security teams risk missing key alerts that indicate a threat targeting OT at their earliest stages.

For Attacks targeting OT, early stage exploits often originate in IT environments, adversaries perform internal reconnaissance among other tactics and procedures but then laterally move into OT first affecting IT devices, servers and workstations within the OT network. If visibility is limited, these threats go undetected. To stay ahead of attackers, organizations need full-spectrum visibility that connects IT and OT security, ensuring no early warning signs are missed.

However, visibility alone isn’t enough. More visibility also means more alerts, this doesn’t just make it harder to separate real threats from routine activity, but bogs down analysts who have to investigate all these alerts to determine their criticality.

Investigations: The real bottleneck

While visibility is essential, it also introduces a new challenge: Alert fatigue. Without the right tools, analysts are often occupied investigating alerts with little to no context, forcing them to manually piece together information and determine if an attack is unfolding. This slows response times and increases the risk of missing critical threats.

Figure 1: Example ICS attack scenario

With siloed visibility across IT and OT each of these events shown above would be individually alerted by a detection engine with little to no context nor correlation. Thus, an analyst would have to try to piece together these events manually. Traditional security tools struggle to keep pace with the sophistication of these threats, resulting in an alarming statistic: less than 10% of alerts are thoroughly vetted, leaving organizations vulnerable to undetected breaches. As a result, incidents inevitably follow.

Darktrace’s Cyber AI Analyst uses AI-led investigations to improve workflows for analysts by automatically correlating alerts wherever they occur across both IT and OT. The multi-layered AI engine identifies high-priority incidents, and provides analysts with clear, actionable insights, reducing noise and highlighting meaningful threats. The AI significantly alleviates workloads, enabling teams to respond faster and more effectively before an attack escalates.

Overcoming organizational challenges across IT and OT

Beyond technical challenges like visibility and alert management, organizational dynamics further complicate IT-OT security efforts. Fundamental differences in priorities, workflows, and risk perspectives create challenges that can lead to misalignment between teams:

Non-transferable practices: IT professionals might assume that cybersecurity practices from IT environments can be directly applied to OT environments. This can lead to issues, as OT systems and workflows may not handle IT security processes as expected. It's crucial to recognize and respect the unique requirements and constraints of OT environments.

Segmented responsibilities: IT and OT teams often operate under separate organizational structures, each with distinct priorities, goals, and workflows. While IT focuses on data security, network integrity, and enterprise applications, OT prioritizes uptime, reliability, and physical processes.

Different risk perspectives: While IT teams focus on preventing cyber threats and regulatory violations, OT teams prioritize uptime and operational reliability making them drawn towards asset inventory tools that provide no threat detection capability.

Result: A combination of disparate and ineffective tools and misaligned teams can make any progress toward risk reduction at an organization seem impossible. The right tools should be able to both free up time for collaboration and prompt better communication between IT and OT teams where it is needed. However, different size operations structure their IT and OT teams differently which impacts the priorities for each team.

In real-world scenarios, small IT teams struggle to manage security across both IT and OT, while larger organizations with OT security teams face alert fatigue and numerous false positives slowing down investigations and hindering effective communication with the IT security teams.

By unifying visibility and investigations, Darktrace / OT helps organizations of all sizes detect threats earlier, streamline workflows, and enhance security across both IT and OT environments. The following examples illustrate how AI-driven investigations can transform security operations, improving detection, investigation, and response.

Before and after AI-led investigation

Before: Small manufacturing company

At a small manufacturing company, a 1-3 person IT team juggles everything from email security to network troubleshooting. An analyst might see unusual traffic through the firewall:

  • Unusual repeated outbound traffic from an IP within their OT network destined to an unidentifiable external IP.

With no dedicated OT security tools and limited visibility into the industrial network, they don’t know what the internal device in question is, if it is beaconing to a malicious external IP, and what it may be doing to other devices within the OT network. Without a centralized dashboard, they must manually check logs, ask operators about changes, and hunt for anomalies across different systems.

After a day of investigation, they concluded the traffic was not to be expected activity. They stop production within their smaller OT network, update their firewall rules and factory reset all OT devices and systems within the blast radius of the IP device in question.

After: Faster, automated response with Cyber AI Analyst

With Darktrace / OT and Cyber AI Analyst, the IT team moves from reactive, manual investigations to proactive, automated threat detection:

  • Cyber AI Analyst connects alerts across their IT and OT infrastructure temporally mapping them to attack frameworks and provides contextual analysis of how alerts are linked, revealing in real time attackers attempting lateral movement from IT to OT.
  • A human-readable incident report explains the full scope of the incident, eliminating hours of manual investigation.
  • The team is faster to triage as they are led directly to prioritized high criticality alerts, now capable of responding immediately instead of wasting valuable time hunting for answers.

By reducing noise, providing context, and automating investigations, Cyber AI Analyst transforms OT security, enabling small IT teams to detect, understand, and respond to threats—without deep OT cybersecurity expertise.

Before: Large critical infrastructure organization

In large critical infrastructure operations, OT and IT teams work in separate silos. The OT security team needs to quickly assess and prioritize alerts, but their system floods them with notifications:

  • Multiple new device connected to the ICS network alerts
  • Multiple failed logins to HMI detected
  • Multiple Unusual Modbus/TCP commands detected
  • Repeated outbound OT traffic to IT destinations

At first glance, these alerts seem important, but without context, it’s unclear whether they indicate a routine error, a misconfiguration, or an active cyber-attack. They might ask:

  • Are the failed logins just a mistake, or a brute-force attempt?
  • Is the outbound traffic part of a scheduled update, or data exfiltration?

Without correlation across events, the engineer must manually investigate each one—checking logs, cross-referencing network activity, and contacting operators—wasting valuable time. Meanwhile, if it’s a coordinated attack, the adversary may already be disrupting operations.

After: A new workflow with Cyber AI Analyst

With Cyber AI Analyst, the OT security team gets clear, automated correlation of security events, making investigations faster and more efficient:

  • Automated correlation of OT threats: Instead of isolated alerts, Cyber AI Analyst stitches together related events, providing a single, high-confidence incident report that highlights key details.
  • Faster time to meaning: The system connects anomalous behaviors (e.g., failed logins, unusual traffic from an HMI, and unauthorized PLC modifications) into a cohesive narrative, eliminating hours of manual log analysis.
  • Prioritized and actionable alerts: OT security receives clear, ranked incidents, immediately highlighting what matters most.
  • Rapid threat understanding: Security teams know within minutes whether an event is a misconfiguration or a cyber-attack, allowing for faster containment.

With Cyber AI Analyst, large organizations cut through alert noise, accelerate investigations, and detect threats faster—without disrupting OT operations.

An AI-led approach to industrial cybersecurity

Security vendors with a primary focus on IT may lack insight into OT threats. Even OT-focused vendors have limited visibility into IT device exploitation within OT networks, leading to failed ability to detect early indicators of compromise. A comprehensive solution must account for the unique characteristics of various OT environments.

In a world where industrial security is no longer just about protecting OT but securing the entire digital-physical ecosystem as it interacts with the OT network, Darktrace / OT is an AI-driven solution that unifies visibility across IT, IoT and OT, Cloud into one cohesive defense strategy.

Whether an attack originates from an external breach, an insider threat, a supply chain compromise, in the Cloud, OT, or IT domains Cyber AI Analyst ensures that security teams see the full picture - before disruption occurs.

Learn more about Darktrace / OT 

  • Unify IT and OT security under a single platform, ensuring seamless communication and protection for all interconnected devices.
  • Maintain uptime with AI-driven threat containment, stopping attacks without disrupting production.
  • Mitigate risks with or without patches, leveraging MITRE mitigations to reduce attack opportunities.

Download the solution brief to see how Darktrace secures critical infrastructure.

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About the author
Daniel Simonds
Director of Operational Technology
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