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August 22, 2023

Darktrace’s Detection of Unattributed Ransomware

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22
Aug 2023
Leveraging anomaly-based detection, we successfully identified an ongoing ransomware attack on the network of a customer and the activity that preceded it.

In the current threat landscape, much of the conversation around ransomware focusses on high-profile strains and notorious threat groups. While organizations and their security teams are justified in these concerns, it is important not to underestimate the danger posed by smaller scale, unattributed ransomware attacks.

Unlike attributed ransomware strains, there are often no playbooks or lists of previously observed indicators of compromise (IoCs) that security teams can consult to help them shore up their cyber defenses. As such, anomaly detection is critical to ensure that emerging threats can be detected based on their abnormality on the network, rather than relying heavily on threat intelligence.

In mid-March 2023, a Darktrace customer requested analytical support from the Darktrace Security Operations Center (SOC) after they had been hit by a ransomware attack a few hours earlier. Darktrace was able to uncover a myriad of malicious activity that preceded the eventual ransomware deployment, ultimately assisting the customer to identify compromised devices and contain the ransomware attack.

Attack Overview

While there were a small number of endpoints that had been flagged as malicious by open-source intelligence (OSINT), Darktrace DETECT™ focused on the unusualness of the activity surrounding this emerging ransomware attack. This provided unparalleled visibility over this ransomware attack at every stage of the cyber kill chain, whilst also revealing the potential origins of the compromise which came months area.

Initial Compromise

Initial investigation revealed that several devices that Darktrace were observed performing suspicious activity had previously engaged in anomalous behavior several months before the ransomware event, indicating this could be a part of a repeated compromise or the result of initial access brokers.

Most notably, in late January 2023 there was a spike in unusual activity when some of the affected devices were observed performing activity indicative of network and device scanning.

Darktrace DETECT identified some of the devices establishing unusually high volumes of internal failed connections via TCP and UDP, and the SMB protocol. Various key ports, such as 135, 139, and 445, were also scanned.

Due to the number of affected devices, the exact initial attack vector is unclear; however, one likely scenario is associated with an internet-facing DNS server. Towards the end of January 2023, the server began to receive unusual TCP DNS requests from the rare external endpoint, 103.203.59[.]3, which had been flagged as potentially malicious by OSINT [4]. Based on a portion of the hostname of the device, dc01, we can assume that this server served as a gateway to the domain controller. If a domain controller is compromised, a malicious actor would gain access to usernames and passwords within a network allowing attackers to obtain administrative-level access to an organization’s digital estate.

Around the same time as the unusual TCP DNS requests, Darktrace DETECT observed the domain controller engaging in further suspicious activity. As demonstrated in Figure 1, Darktrace recognized that this server was not responding to common requests from multiple internal devices, as it would be expected to. Following this, the device was observed carrying out new or uncommon Windows Management Instrumentation (WMI) activity. WMI is typically used by network administrators to manage remote and local Windows systems [3].

Figure 1: Device event log depicting the possible Initial attack vector.


Had Darktrace RESPOND™ been enabled in autonomous response mode, it would have to blocked connections originating from the compromised internal devices as soon as they were detected, while also limiting affected devices to their pre-established patterns of file to prevent them from carrying out any further malicious activity.

Darktrace subsequently observed multiple devices establishing various chains of connections that are indicative of lateral movement activity, such as unusual internal RDP and WMI requests. While there may be devices within an organization that do regularly partake these types of connections, Darktrace recognized that this activity was extremely unusual for these devices.

Darktrace’s Self-Learning AI allows for a deep understanding of customer networks and the devices within them. It’s anomaly-based threat detection capability enables it to recognize subtle deviations in a device’s normal patterns of behavior, without depending on known IoCs or signatures and rules to guide it.

Figure 2: Observed chain of possible lateral movement.


Persistence

Darktrace DETECT observed several affected devices communicating with rare external endpoints that had also been flagged as potentially malicious by OSINT tools. Multiple devices were observed performing activity indicative of NTLM brute-forcing activity, as seen in the Figure 3 which highlights the event log of the aforementioned domain controller. Said domain controller continuously engaged in anomalous behavior throughout the course of the attack. The same device was seen using a potentially compromise credential, ‘cvd’, which was observed via an SMB login event.

Figure 3: Continued unusual external connectivity.


Affected devices, including the domain controller, continued to engage in consistent communication with the endpoints prior to the actual ransomware attack. Darktrace identified that some of these malicious endpoints had likely been generated by Domain Generation Algorithms (DGA), a classic tactic utilized by threat actors. Subsequent OSINT investigation revealed that one such domain had been associated with malware such as TrojanDownloader:Win32/Upatre!rfn [5].

All external engagements were observed by Darktrace DETECT and would have been actioned on by Darktrace RESPOND, had it been configured in autonomous response mode. It would have blocked any suspicious outgoing connections originating from the compromised devices, thus preventing additional external engagement from taking place. Darktrace RESPOND works in tandem with DETECT to autonomously take action against suspicious activity based on its unusualness, rather than relying on static lists of ‘known-bads’ or malicious IoCs.

Reconnaissance

On March 14, 2023, a few days before the ransomware attack, Darktrace observed multiple internal devices failing to establish connections in a manner that suggests SMB, RDP and network scanning. Among these devices once more was the domain controller, which was seen performing potential SMB brute-forcing, representing yet another example of malicious activity carried out by this device.

Lateral Movement

Immediately prior to the attack, many compromised devices were observed mobilizing to conduct an array of high-severity lateral movement activity. Darktrace detected one device using two administrative credentials, namely ‘Administrator’ and ‘administrator’, while it also observed a notable spike in the volume of successful SMB connections from the device around the same time.

At this point, Darktrace DETECT was observing the progression of this attack along the cyber kill chain. What had started as internal recognisance, had escalated to exploitation and ensuing command-and-control activity. Following an SMB brute-force attempt, Darktrace DETECT identified a successful DCSync attack.

A DCSync attack occurs when a malicious actor impersonates a domain controller in an effort to gather sensitive information, such as user credentials and passwords hashes, by replicating directory services [1]. In this case, a device sent various successful DRSGetNCChanges operation requests to the DRSUAPI endpoint.

Data Exfiltration

Around the same time, Darktrace detected the compromised server transferring a high volume of data to rare external endpoints associated with Bublup, a third-party project management application used to save and share files. Although the actors attempted to avoid the detection of security tools by using a legitimate file storage service, Darktrace understood that this activity represented a deviation in this device’s expected pattern of life.

In one instance, around 8 GB of data was transferred, and in another, over 4 GB, indicating threat actors were employing a tactic known as ‘low and slow’ exfiltration whereby data is exfiltrated in small quantities via multiple connections, in an effort to mask their suspicious activity. While this tactic may have evaded the detection of traditional security measures, Darktrace’s anomaly-based detection allowed it to recognize that these two incidents represented a wider exfiltration event, rather than viewing the transfers in isolation.

Impact

Finally, Darktrace began to observe a large amount of suspicious SMB activity on the affected devices, most of which was SMB file encryption. DETECT observed the file extension ‘uw9nmvw’ being appended to many files across various internal shares and devices. In addition to this, a potential ransom note, ‘RECOVER-uw9nmvw-FILES.txt’, was detected on the network shortly after the start of the attack.

Figure 4: Depiction of the high-volume of suspicious SMB activity, including file encryption.


Conclusion

Ultimately, this incident show cases how Darktrace was able to successfully identify an emerging ransomware attack using its unrivalled anomaly-based detection capabilities, without having to rely on any previously established threat intelligence. Not only was Darktrace DETECT able to identify the ransomware at multiple stages of the kill chain, but it was also able to uncover the anomalous activity that took place in the buildup to the attack itself.

As the attack progressed along the cyber kill chain, escalating in severity at every juncture, DETECT was able to provide full visibility over the events. Through the successful identification of compromised devices, anomalous administrative credentials usage and encrypted files, Darktrace was able to greatly assist the customer, ensuring they were well-equipped to contain the incident and begin their incident management process.

Darktrace would have been able to aid the customer even further had they enabled its autonomous response technology on their network. Darktrace RESPOND would have taken targeted, mitigative action as soon as suspicious activity was detected, preventing the malicious actors from achieving their goals.

Credit to: Natalia Sánchez Rocafort, Cyber Security Analyst, Patrick Anjos, Senior Cyber Analyst.

MITRE Tactics/Techniques Mapping

RECONNAISSANCE

Scanning IP Blocks  (T1595.001)

RECONNAISSANCE

Vulnerability Scanning  (T1595.002)

IMPACT

Service Stop  (T1489)

LATERAL MOVEMENT

Taint Shared Content (T1080)

IMPACT

Data Encrypted for Impact (T1486)

INITIAL ACCESS

Replication Through Removable Media (T1200)

DEFENSE EVASION

Rogue Domain Controller (T1207)

COMMAND AND CONTROL

Domain Generation Algorithms (T1568.002)

EXECUTION

Windows Management Instrumentation (T1047)

INITIAL ACCESS

Phishing (T1190)

EXFILTRATION

Exfiltration Over C2 Channel (T1041)

IoC Table

IoC ----------- TYPE ------------- DESCRIPTION + PROBABILITY

CVD --------- credentials -------- Possible compromised credential

.UW9NMVW - File extension ----- Possible appended file extension

RECOVER-UW9NMVW-FILES.TXT - Ransom note - Possible ransom note observed

84.32.188[.]186 - IP address ------ C2 Endpoint

AS.EXECSVCT[.]COM - Hostname - C2 Endpoint

ZX.EXECSVCT[.]COM - Hostname - C2 Endpoint

QW.EXECSVCT[.]COM - Hostname - C2 Endpoint

EXECSVCT[.]COM - Hostname ------ C2 Endpoint

15.197.130[.]221 --- IP address ------ C2 Endpoint

AS59642 UAB CHERRY SERVERS - ASN - Possible ASN associated with C2 Endpoints

108.156.28[.]43

108.156.28[.]22

52.84.93[.]26

52.217.131[.]241

54.231.193[.]89 - IP addresses - Possible IP addresses associated with data exfiltration

103.203.59[.]3 -IP address ---- Possible IP address associated with initial attack vector

References:

[1] https://blog.netwrix.com/2021/11/30/what-is-dcsync-an-introduction/

[2] https://www.easeus.com/computer-instruction/delete-system32.html#:~:text=System32%20is%20a%20folder%20on,DLL%20files%2C%20and%20EXE%20files.

[3] https://www.techtarget.com/searchwindowsserver/definition/Windows-Management-Instrumentation#:~:text=WMI%20provides%20users%20with%20information,operational%20environments%2C%20including%20remote%20systems.

[4] https://www.virustotal.com/gui/ip-address/103.203.59[.]3

[5] https://otx.alienvault.com/indicator/ip/15.197.130[.]221

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
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Natalia Sánchez Rocafort
Cyber Security Analyst
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November 19, 2024

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Darktrace Leading the Future of Network Detection and Response with Recognition from KuppingerCole

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KuppingerCole has recognized Darktrace as an overall Leader, Product Leader, Market Leader and Innovation Leader in the KuppingerCole Leadership Compass: Network Detection and Response (2024).

With the perimeter all but dissolved, Network Detection and Response (NDR) tools are quickly becoming a critical component of the security stack, as the main tool to span the modern network. NDRs connect on-premises infrastructure to cloud, remote workers, identities, SaaS applications, and IoT/OT – something not available to EDR that requires agents and isolates visibility to individual devices.

KuppingerCole Analysts AG designated Darktrace an ‘Overall Leader’ position because of our continual innovation around user-led security. Self-Learning AI together with automated triage through Cyber AI Analyst and real-time autonomous response actions have been instrumental to security teams in stopping potential threats before they become a breach. With this time saved, Darktrace is leading beyond reactive security to truly harden a network, allowing the team to spend more time in preventive security measures.

Network Detection and Response protects where others fail to reach

NDR solutions operate at the network level, deploying inside or parallel to your network to ingest raw traffic via virtual or physical sensors. This gives them unprecedented potential to identify anomalies and possible breaches in any network - far beyond simple on-prem, into dynamic virtual environments, cloud or hybrid networks, cloud applications, and even remote devices accessing the corporate network via ZTNA or VPN.

Rather than looking at processes level data, NDR can detect the lateral movement of an adversary across multiple assets by analyzing network traffic patterns which endpoint solutions may not be able to identify [1]. In the face of a growing, complex environment, organizations large and small, will benefit from using NDRs either in conjunction, or as the foundation for, their Extended Detection and Response (XDR) for a unified view that improves their overall threat detection, ease of investigation and faster response times.

Today's NDR solutions are expected to include advanced ML and artificial intelligence (AI) algorithms [1]

Traditional IDS & IPS systems are labor intensive, requiring continuous rule creation, outdated signature maintenance, and manual monitoring for false positives or incorrect actions. This is no longer viable against a higher volume and changing landscape, making NDR the natural network tool to level against these evolutions. The role of AI in NDRs is designed to meet this challenge, “to reduce both the labor need for analysis and false positives, as well as add value by improving anomaly detection and overall security posture” .

Celebrating success in leadership and innovation

Darktrace is proud to have been recognized as an NDR “Overall Leader” in KuppingerCole Analyst AG’s Leadership Compass. The report gave further recognition to Darktrace as a ‘Product Leader”, “Innovation Leader” and “Market Leader”.

Maximum scores were received for core product categories, in addition to market presence and financial strength. Particular attention was directed to our innovation. This year has seen several NDR updates via Darktrace’s ActiveAI Security Platform version 6.2 which has enhanced investigation workflows and provided new AI transparency within the toolset.

Positive scores were also received for Darktrace’s deployment ecosystem and surrounding support, minimizing the need for extraneous integrations through a unique platform architecture that connects with over 90 other vendors.

High Scores received in Darktrace’s KuppingerCole Spider Chart across Core NDR capability areas
Figure 1: High Scores received in Darktrace’s KuppingerCole Spider Chart across Core NDR capability areas

Darktrace’s pioneering AI approach sets it apart

Darktrace / NETWORK’s approach is fundamentally different to other NDRs. Continual anomaly-based detection (our Self-Learning AI), understands what is normal across each of your network entities, and then examines deviations from these behaviors rather than needing to apply static rules or ML to adversary techniques. As a result, Darktrace / NETWORK can focus on surfacing the novel threats that cannot be anticipated, whilst our proactive solutions expose gaps that can be exploited and reduce the risk of known threats.    

Across the millions of possible network events that may occur, Darktrace’s Cyber AI Analyst reduces that manual workload for SOC teams by presenting only what is most important in complete collated incidents. This accelerates SOC Level 2 analyses of incidents by 10x2, giving time back, first for any necessary response and then for preventive workflows.

Finally, when incidents begin to escalate, Darktrace can natively (or via third-party) autonomously respond and take precise actions based on a contextual understanding of both the affected assets and incident in question so that threats can be disarmed without impacting wider operations.

Within the KuppingerCole report, several standout strengths were listed:

  • Cyber AI Analyst was celebrated as a core differentiator, enhancing both visibility and investigation into critical network issues and allowing a faster response.
  • Darktrace / NETWORK was singled for its user benefits. Both a clear interface for analysts with advanced filtering and analytical tools, and efficient role-based access control (RBAC) and configuration options for administrators.
  • At the product level, Darktrace was recognized for complete network traffic analysis (NTA) capabilities allowing extensive analysis into components like application use/type, fingerprinting, source/destination communication, in addition to comprehensive protocol support across a range of network device types from IT, OT, IoT and mobiles and detailed MITRE ATT&CK mapping.
  • Finally, at the heart of it, Darktrace’s innovation was highlighted in relation to its intrinsic Self Learning AI, utilizing multiple layers of deep learning, neural networks, LLMs, NLP, Generative AI and more to understand network activity and filter it for what’s critical on an individual customer level.

Going beyond reactive security

Darktrace’s visibility and AI-enabled detection, investigation and response enable security teams to focus on hardening gaps in their network through contextual relevance & priority. Darktrace / NETWORK explicitly gives time back to security teams allowing them to focus on the bigger strategic and governance workflows that sometimes get overlooked. This is enabled through proactive solutions intrinsically connected to our NDR:

  • Darktrace / Proactive Exposure Management, which looks beyond just CVE risks to instead discover, prioritize and validate risks by business impact and how to mobilize against them early, to reduce the number of real threats security teams face.
  • Darktrace / Incident Readiness & Recovery, a solution rather than service-based approach to incident response (IR) that lets teams respond in the best way to each incident and proactively test their familiarity and effectiveness of IR workflows with sophisticated incident simulations involving their own analysts and assets.

Together, these solutions allow Darktrace / NETWORK to go beyond the traditional NDR and shift teams to a more hardened and proactive state.

Putting customers first

Customers continue to sit at the forefront of Darktrace R&D, with their emerging needs and pain points being the direct inspiration for our continued innovation.

This year Darktrace / NETWORK has protected thousands of customers against the latest attacks, from data exfil and destruction, to unapproved privilege escalation and ransomware including strains like Medusa, Qilin and AlphV BlackCat.

In each instance, Darktrace / NETWORK was able to provide a holistic lens of the anomalies present in their traffic, collated those that were important, and either responded or gave teams the ability to take targeted actions against their threats – even when adversaries pivoted. In one example of a Gootloader compromise, Darktrace ensured a SOC went from detection to recovery within 5 days, 92.8% faster than the average containment time of 69 days.

Results like these, focused on user-led security, have secured Darktrace’s position within the latest NDR Leadership Compass.

To find out more about what makes Darktrace / NETWORK special, read the full KuppingerCole report.

References

[1] Osman Celik, KuppingerCole Leadership Compass:Network Detection and Response (2024)

[2] Darktrace's AI Analyst customer fleet data

[3] https://www.ibm.com/reports/data-breach

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Gabriel Few-Wiegratz
Product Marketing Manager

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November 1, 2024

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Inside the SOC

Phishing and Persistence: Darktrace’s Role in Defending Against a Sophisticated Account Takeover

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The exploitation of SaaS platforms

As businesses continue to grow and evolve, the need for sharing ideas through productivity and cloud Software-as-a-Service (SaaS) platforms is becoming increasingly crucial. However, these platforms have also become prime targets for cyber attackers.

Threat actors often exploit these widely-used services to gain unauthorized access, steal sensitive information, and disrupt business operations. The growing reliance on SaaS platforms makes them attractive entry points for cybercriminals, who use sophisticated techniques such as phishing, social engineering, and malware to compromise these systems.

Services like Microsoft 365 are regularly targeted by threat actors looking for an entry point into an organization’s environment to carry out malicious activities. Securing these platforms is crucial to protect business data and ensure operational continuity.

Darktrace / EMAIL detection of the phishing attack

In a recent case, Darktrace observed a customer in the manufacturing sector receiving a phishing email that led to a threat actor logging in and creating an email rule. Threat actors often create email rules to move emails to their inbox, avoiding detection. Additionally, Darktrace detected a spoofed domain registered by the threat actor. Despite already having access to the customer’s SaaS account, the actor seemingly registered this domain to maintain persistence on the network, allowing them to communicate with the spoofed domain and conduct further malicious activity.

Darktrace / EMAIL can help prevent compromises like this one by blocking suspicious emails as soon as they are identified. Darktrace’s AI-driven email detection and response recognizes anomalies that might indicate phishing attempts and applies mitigative actions autonomously to prevent the escalation of an attack.

Unfortunately, in this case, Darktrace was not configured in Autonomous Response mode at the time of the attack, meaning actions had to be manually applied by the customer’s security team. Had it been fully enabled, it would have held the emails, preventing them from reaching the intended recipient and stopping the attack at its inception.

However, Darktrace’s Managed Threat Detection alerted the Security Operations Center (SOC) team to the compromise, enabling them to thoroughly investigate the incident and notify the customer before further damage could occur.

The Managed Threat Detection service continuously monitors customer networks for suspicious activities that may indicate an emerging threat. When such activities are detected, alerts are sent to Darktrace’s expert Cyber Analysts for triage, significantly speeding up the remediation process.

Attack Overview

On May 2, 2024, Darktrace detected a threat actor targeting a customer in the manufacturing sector then an unusual login to their SaaS environment was observed prior to the creation of a new email rule.

Darktrace immediately identified the login as suspicious due to the rarity of the source IP (31.222.254[.]27) and ASN, coupled with the absence of multi-factor authentication (MFA), which was typically required for this account.

The new email rule was intended to mark emails as read and moved to the ‘Conversation History’ folder for inbound emails from a specific domain. The rule was named “….,,,”, likely the attacker attempting to setup their new rule with an unnoteworthy name to ensure it would not be noticed by the account’s legitimate owner. Likewise, by moving emails from a specific domain to ‘Conversation History’, a folder that is rarely used by most users, any phishing emails sent by that domain would remain undetected by the user.

Darktrace’s detection of the unusual SaaS login and subsequent creation of the new email rule “….,,,”.
Figure 1: Darktrace’s detection of the unusual SaaS login and subsequent creation of the new email rule “….,,,”.

The domain in question was identified as being newly registered and an example of a typosquat domain. Typosquatting involves registering new domains with intentional misspelling designed to convince users to visit fake, and often malicious, websites. This technique is often used in phishing campaigns to create a sense of legitimacy and trust and deceive users into providing sensitive information. In this case, the suspicious domain closely resembled several of the customer’s internal domains, indicating an attempt to impersonate the organization’s legitimate internal sites to gain the target’s trust. Furthermore, the creation of this lookalike domain suggests that the attack was highly targeted at this specific customer.

Interestingly, the threat actor registered this spoofed domain despite already having account access. This was likely intended to ensure persistence on the network without having to launch additional phishing attacks. Such use of spoofed domain could allow an attacker to maintain a foothold in their target network and escalate their malicious activities without having to regain access to the account. This persistence can be used for various purposes, including data exfiltration, spreading malware, or launching further attacks.

Following this, Darktrace detected a highly anomalous email being sent to the customer’s account from the same location as the initial unsual SaaS login. Darktrace’s anomaly-based detection is able to identify threats that human security teams and traditional signature-based methods might miss. By analyzing the expected behavior of network users, Darktrace can recognize the subtle deviations from the norm that may indicate malicious activity. Unfortunately, in this instance, without Darktrace’s Autonomous Response capability enabled, the phishing email was able to successfully reach the recipient. While Darktrace / EMAIL did suggest that the email should be held from the recipients inbox, the customer was required to manually approve it.

Despite this, the Darktrace SOC team were still able to support the customer as they were subscribed to the Managed Threat Detection service. Following the detection of the highlight anomalous activity surrounding this compromise, namely the unusual SaaS login followed by a new email rule, an alert was sent to the Darktrace SOC for immediate triage, who then contacted the customer directly urging immediate action.

Conclusion

This case underscores the need to secure SaaS platforms like Microsoft 365 against sophisticated cyber threats. As businesses increasingly rely on these platforms, they become prime targets for attackers seeking unauthorized access and disruption.

Darktrace’s anomaly-based detection and response capabilities are crucial in identifying and mitigating such threats. In this instance, Darktrace detected a phishing email that led to a threat actor logging in and creating a suspicious email rule. The actor also registered a spoofed domain to maintain persistence on the network.

Darktrace / EMAIL, with its AI-driven detection and analysis, can block suspicious emails before they reach the intended recipient, preventing attacks at their inception. Meanwhile, Darktrace’s SOC team promptly investigated the activity and alerted the customer to the compromise, enabling them to take immediate action to remediate the issue and prevent any further damage.

Credit to Vivek Rajan (Cyber Security Analyst) and Ryan Traill (Threat Content Lead).

Appendices

Darktrace Model Detections

  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active
  • SaaS / Resource / Unusual Access to Delegated Resource by Non Owner
  • SaaS / Email Nexus / Unusual Login Location Following Sender Spoof
  • Compliance / Anomalous New Email Rule
  • SaaS / Compromise / Unusual Login and New Email Rule

Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

31.222.254[.]27 – IP -  Suspicious Login Endpoint

MITRE ATT&CK Mapping

Tactic – Technqiue – Sub-technique of (if applicable)

Cloud Accounts - DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - T1078.004 - T1078

Cloud Service Dashboard – DISCOVERY - T1538

Compromise Accounts - RESOURCE DEVELOPMENT - T1586

Steal Web Session Cookie - CREDENTIAL ACCESS - T1539

Outlook Rules – PERSISTENCE - T1137.005 - T1137

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About the author
Vivek Rajan
Cyber Analyst
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