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May 3, 2021

Understanding Modern-Day Cyber Attacks

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03
May 2021
Discover how Darktrace detects and mitigates threats in IoT ecosystems and globalized supply chains that are constantly evolving.

It’s ten to five on a Friday afternoon. A technician has come in to perform a routine check on an electronic door. She enters the office with no issues – she works for a trusted third-party vendor, employees see her every week. She opens her laptop and connects to the Door Access Control Unit, a small Internet of Things (IoT) device used to operate the smart lock. Minutes later, trojans have been downloaded onto the company network, a crypto-mining operation has begun, and there is evidence of confidential data being exfiltrated. Where did things go wrong?

Threats in a business: A new dawn surfaces

As organizations keep pace with the demands of digital transformation, the attack surface has become broader than ever before. There are numerous points of entry for a cyber-criminal – from vulnerabilities in IoT ecosystems, to blind spots in supply chains, to insiders misusing their access to the business. Darktrace sees these threats every day. Sometimes, like in the real-world example above, which will be examined in this blog, they can occur in the very same attack.

Insider threats can use their familiarity and level of access to a system as a critical advantage when evading detection and launching an attack. But insiders don’t necessarily have to be malicious. Every employee or contractor is a potential threat: clicking on a phishing link or accidentally releasing data often leads to wide-scale breaches.

At the same time, connectivity in the workspace – with each IoT device communicating with the corporate network and the Internet on its own IP address – is an urgent security issue. Access control systems, for example, add a layer of physical security by tracking who enters the office and when. However, these same control systems imperil digital security by introducing a cluster of sensors, locks, alarm systems, and keypads, which hold sensitive user information and connect to company infrastructure.

Furthermore, a significant proportion of IoT devices are built without security in mind. Vendors prioritize time-to-market and often don’t have the resources to invest in baked-in security measures. Consider the number of start-ups which manufacture IoT – over 60% of home automation companies have fewer than ten employees.

Insider threat detected by Cyber AI

In January 2021, a medium-sized North American company suffered a supply chain attack when a third-party vendor connected to the control unit for a smart door.

Figure 1: The attack lasted 3.5 hours in total, commencing 16:50 local time.

The technician from the vendor’s company had come in to perform scheduled maintenance. They had been authorized to connect directly to the Door Access Control Unit, yet were unaware that the laptop they were using, brought in from outside of the organization, had been infected with malware.

As soon as the laptop connected with the control unit, the malware detected an open port, identified the vulnerability, and began moving laterally. Within minutes, the IoT device was seen making highly unusual connections to rare external IP addresses. The connections were made using HTTP and contained suspicious user agents and URIs.

Darktrace then detected that the control unit was attempting to download trojans and other payloads, including upsupx2.exe and 36BB9658.moe. Other connections were used to send base64 encoded strings containing the device name and the organization’s external IP address.

Cryptocurrency mining activity with a Monero (XMR) CPU miner was detected shortly afterwards. The device also utilized an SMB exploit to make external connections on port 445 while searching for vulnerable internal devices using the outdated SMBv1 protocol.

One hour later, the device connected to an endpoint related to the third-party remote access tool TeamViewer. After a few minutes, the device was seen uploading over 15 MB to a 100% rare external IP.

Figure 2: Timeline of the connections made by an example device on the days around an incident (blue). The connections associated with the compromise are a significant deviation from the device’s normal pattern of life, and result in multiple unusual activity events and repeated model breaches (orange).

Security threats in the supply chain

Cyber AI flagged the insider threat to the customer as soon as the control unit had been compromised. The attack had managed to bypass the rest of the organization’s security stack, for the simple reason that it was introduced directly from a trusted external laptop, and the IoT device itself was managed by the third-party vendor, so the customer had little visibility over it.

Traditional security tools are ineffective against supply chain attacks such as this. From the SolarWinds hack to Vendor Email Compromise, 2021 has put the nail in the coffin for signature-based security – proving that we cannot rely on yesterday’s attacks to predict tomorrow’s threats.

International supply chains and the sheer number of different partners and suppliers which modern organizations work with thus pose a serious security dilemma: how can we allow external vendors onto our network and keep an airtight system?

The first answer is zero-trust access. This involves treating every device as malicious, inside and outside the corporate network, and demanding verification at all stages. The second answer is visibility and response. Security products must shed a clear light into cloud and IoT infrastructure, and react autonomously as soon as subtle anomalies emerge across the enterprise.

IoT investigated

Darktrace’s Cyber AI Analyst reported on every stage of the attack, including the download of the first malicious executable file.

Figure 3: Example of Cyber AI Analyst detecting anomalous behavior on a device, including C2 connectivity and suspicious file downloads.

Cyber AI Analyst investigated the C2 connectivity, providing a high-level summary of the activity. The IoT device had accessed suspicious MOE files with randomly generated alphanumeric names.

Figure 4: A Cyber AI Analyst summary of C2 connectivity for a device.

Not only did the AI detect every stage of the activity, but the customer was also alerted via a Proactive Threat Notification following a high scoring model breach at 16:59, just minutes after the attack had commenced.

Stranger danger

Third parties coming in to tweak device settings and adjust the network can have unintended consequences. The hyper-connected world which we’re living in, with the advent of 5G and Industry 4.0, has become a digital playground for cyber-criminals.

In the real-world case study above, the IoT device was unsecured and misconfigured. With rushed creations of IoT ecosystems, intertwining supply chains, and a breadth of individuals and devices connecting to corporate infrastructure, modern-day organizations cannot expect simple security tools which rely on pre-defined rules to stop insider threats and other advanced cyber-attacks.

The organization did not have visibility over the management of the Door Access Control Unit. Despite this, and despite no prior knowledge of the attack type or the vulnerabilities present in the IoT device, Darktrace detected the behavioral anomalies immediately. Without Cyber AI, the infection could have remained on the customer’s environment for weeks or months, escalating privileges, silently crypto-mining, and exfiltrating sensitive company data.

Thanks to Darktrace analyst Grace Carballo for her insights on the above threat find.

Learn more about insider threats

Darktrace model detections:

  • Anomalous File/Anomalous Octet Stream
  • Anomalous Connection/New User Agent to IP Without Hostname
  • Unusual Activity/Unusual External Connectivity
  • Device/Increased External Connectivity
  • Anomalous Server Activity/Outgoing from Server
  • Device/New User Agent and New IP
  • Compliance/Cryptocurrency Mining Activity
  • Compliance/External Windows Connectivity
  • Anomalous File/Multiple EXE from Rare External Locations
  • Anomalous File/EXE from Rare External Location
  • Device/Large Number of Model Breaches
  • Anomalous File/Internet Facing System File Download
  • Device/Initial Breach Chain Compromise
  • Device/SMB Session Bruteforce
  • Device/Network Scan- Low Anomaly Score
  • Device/Large Number of Connections to New Endpoint
  • Anomalous Server Activity/Outgoing from Server
  • Compromise/Beacon to Young Endpoint
  • Anomalous Server Activity/Rare External from Server
  • Device/Multiple C2 Model Breaches
  • Compliance/Remote Management Tool on Server
  • Anomalous Connection/Data Sent to New External Device

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
Brianna Leddy
Director of Analyst Operations

Based in San Francisco, Brianna is Director of Analyst Operations at Darktrace. She joined the analyst team in 2016 and has since advised a wide range of enterprise customers on advanced threat hunting and leveraging Self-Learning AI for detection and response. Brianna works closely with the Darktrace SOC team to proactively alert customers to emerging threats and investigate unusual behavior in enterprise environments. Brianna holds a Bachelor’s degree in Chemical Engineering from Carnegie Mellon University.

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March 7, 2025

Darktrace's Early Detection of the Latest Ivanti Exploits

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As reported in Darktrace’s 2024 Annual Threat Report, the exploitation of Common Vulnerabilities and Exposures (CVEs) in edge infrastructure has consistently been a significant concern across the threat landscape, with internet-facing assets remaining highly attractive to various threat actors.

Back in January 2024, the Darktrace Threat Research team investigated a surge of malicious activity from zero-day vulnerabilities such as those at the time on Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances. These vulnerabilities were disclosed by Ivanti in January 2024 as CVE-2023-46805 (Authentication bypass vulnerability) and CVE-2024-21887 (Command injection vulnerability), where these two together allowed for unauthenticated, remote code execution (RCE) on vulnerable Ivanti systems.

What are the latest vulnerabilities in Ivanti products?

In early January 2025, two new vulnerabilities were disclosed in Ivanti CS and PS, as well as their Zero Trust Access (ZTA) gateway products.

  • CVE-2025-0282: A stack-based buffer overflow vulnerability. Successful exploitation could lead to unauthenticated remote code execution, allowing attackers to execute arbitrary code on the affected system [1]
  • CVE-2025-0283: When combined with CVE-2025-0282, this vulnerability could allow a local authenticated attacker to escalate privileges, gaining higher-level access on the affected system [1]

Ivanti also released a statement noting they are currently not aware of any exploitation of CVE-2025-0283 at the time of disclosure [1].

Darktrace coverage of Ivanti

The Darktrace Threat Research team investigated the new Ivanti vulnerabilities across their customer base and discovered suspicious activity on two customer networks. Indicators of Compromise (IoCs) potentially indicative of successful exploitation of CVE-2025-0282 were identified as early as December 2024, 11 days before they had been publicly disclosed by Ivanti.

Case 1: December 2024

Authentication with a Privileged Credential

Darktrace initially detected suspicious activity connected with the exploitation of CVE-2025-0282 on December 29, 2024, when a customer device was observed logging into the network via SMB using the credential “svc_negbackups”, before authenticating with the credential “svc_negba” via RDP.

This likely represented a threat actor attempting to identify vulnerabilities within the system or application and escalate their privileges from a basic user account to a more privileged one. Darktrace / NETWORK recognized that the credential “svc_negbackups” was new for this device and therefore deemed it suspicious.

Darktrace / NETWORK’s detection of the unusual use of a new credential.
Figure 1: Darktrace / NETWORK’s detection of the unusual use of a new credential.

Likely Malicious File Download

Shortly after authentication with the privileged credential, Darktrace observed the device performing an SMB write to the C$ share, where a likely malicious executable file, ‘DeElevate64.exe’ was detected. While this is a legitimate Windows file, it can be abused by malicious actors for Dynamic-Link Library (DLL) sideloading, where malicious files are transferred onto other devices before executing malware. There have been external reports indicating that threat actors have utilized this technique when exploiting the Ivanti vulnerabilities [2].

Darktrace’s detection the SMB write of the likely malicious file ‘DeElevate64.exe’ on December 29, 2024.
Figure 2: Darktrace’s detection the SMB write of the likely malicious file ‘DeElevate64.exe’ on December 29, 2024.

Shortly after, a high volume of SMB login failures using the credential “svc_counteract-ext” was observed, suggesting potential brute forcing activity. The suspicious nature of this activity triggered an Enhanced Monitoring model alert that was escalated to Darktrace’s Security Operations Center (SOC) for further investigation and prompt notification, as the customer was subscribed to the Security Operations Support service.  Enhanced Monitoring are high-fidelity models detect activities that are more likely to be indicative of compromise

Suspicious Scanning and Internal Reconnaissance

Darktrace then went on to observe the device carrying out network scanning activity as well as anomalous ITaskScheduler activity. Threat actors can exploit the task scheduler to facilitate the initial or recurring execution of malicious code by a trusted system process, often with elevated permissions. The same device was also seen carrying out uncommon WMI activity.

Darktrace’s detection of a suspicious network scan from the compromised device.
Figure 3: Darktrace’s detection of a suspicious network scan from the compromised device.

Further information on the suspicious scanning activity retrieved by Cyber AI Analyst, including total number of connections and ports scanned.
Figure 4: Further information on the suspicious scanning activity retrieved by Cyber AI Analyst, including total number of connections and ports scanned.
Darktrace’s detection of a significant spike in WMI activity represented by DCE_RPC protocol request increases at the time, with little to no activity observed one week either side.
Figure 5: Darktrace’s detection of a significant spike in WMI activity represented by DCE_RPC protocol request increases at the time, with little to no activity observed one week either side.

Case 2: January 2025

Suspicious File Downloads

On January 13, 2025, Darktrace began to observe activity related to the exploitation of CVE-2025-0282  on the network of another customer, with one in particular device attempting to download likely malicious files.

Firstly, Darktrace observed the device making a GET request for the file “DeElevator64.dll” hosted on the IP 104.238.130[.]185. The device proceeded to download another file, this time “‘DeElevate64.exe”. from the same IP. This was followed by the download of “DeElevator64.dll”, similar to the case observed in December 2024. External reporting indicates that this DLL has been used by actors exploiting CVE-2025-0282 to sideload backdoor into infected systems [2]

Darktrace’s detection of the download of the suspicious file “DeElevator64.dll” on January 13, 2025.
Figure 6: Darktrace’s detection of the download of the suspicious file “DeElevator64.dll” on January 13, 2025.

Suspicious Internal Activity

Just like the previous case, on January 15, the same device was observed making numerous internal connections consistent with network scanning activity, as well as DCE-RPC requests.

Just a few minutes later, Darktrace again detected the use of a new administrative credential, observing the following details:

  • domain=REDACTED hostname=DESKTOP-1JIMIV3 auth_successful=T result=success ntlm_version=2 .

The hostname observed by Darktrace, “DESKTOP-1JIMIV3,” has also been identified by other external vendors and was associated with a remote computer name seen accessing compromised accounts [2].

Darktrace also observed the device performing an SMB write of an additional file, “to.bat,” which may have represented another malicious file loaded from the DLL files that the device had downloaded earlier. It is possible this represented the threat actor attempting to deploy a remote scheduled task.

Darktrace’s detection of SMB Write of the suspicious file “to.bat”.
Figure 7: Darktrace’s detection of SMB Write of the suspicious file “to.bat”.

Further investigation revealed that the device was likely a Veeam server, with its MAC address indicating it was a VMware device. It also appeared that the Veeam server was capturing activities referenced from the hostname DESKTOP-1JIMIV3. This may be analogous to the remote computer name reported by external researchers as accessing accounts [2]. However, this activity might also suggest that while the same threat actor and tools could be involved, they may be targeting a different vulnerability in this instance.

Autonomous Response

In this case, the customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device. This action allows a device to make its usual connections while blocking any that deviate from expected behavior. These mitigative actions by Darktrace ensured that the compromise was promptly halted, preventing any further damage to the customer’s environment.

Darktrace's Autonomous Response capability actively mitigating the suspicious internal connectivity.
Figure 8: Darktrace's Autonomous Response capability actively mitigating the suspicious internal connectivity.

Conclusion

If the previous blog in January 2024 was a stark reminder of the threat posed by malicious actors exploiting Internet-facing assets, the recent activities surrounding CVE-2025-0282 and CVE-2025-0283 emphasize this even further.

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

These activities included the download of suspicious files such as “DeElevate64.exe” and “DeElevator64.dll” potentially used by attackers to sideload backdoors into infected systems. The suspicious hostname DESKTOP-1JIMIV3 was also observed and appears to be associated with a remote computer name seen accessing compromised accounts. These activities are far from exhaustive, and many more will undoubtedly be uncovered as threat actors evolve.

Fortunately, Darktrace was able to swiftly detect and respond to suspicious network activity linked to the latest Ivanti vulnerabilities, sometimes even before these vulnerabilities were publicly disclosed.

Credit to: Nahisha Nobregas, Senior Cyber Analyst, Emma Foulger, Principle Cyber Analyst, Ryan Trail, Analyst Content Lead and the Darktrace Threat Research Team

Appendices

Darktrace Model Detections

Case 1

·      Anomalous Connection / Unusual Admin SMB Session

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Internal / Unusual SMB Script Write

·      Anomalous File / Multiple EXE from Rare External Locations

·      Anomalous File / Script from Rare External Location

·      Compliance / SMB Drive Write

·      Device / Multiple Lateral Movement Model Alerts

·      Device / Network Range Scan

·      Device / Network Scan

·      Device / New or Uncommon WMI Activity

·      Device / RDP Scan

·      Device / Suspicious Network Scan Activity

·      Device / Suspicious SMB Scanning Activity

·      User / New Admin Credentials on Client

·      User / New Admin Credentials on Server 

Case 2

·      Anomalous Connection / Unusual Admin SMB Session

·      Anomalous Connection / Unusual Admin RDP Session

·      Compliance / SMB Drive Write

·      Device / Multiple Lateral Movement Model Alerts

·      Device / SMB Lateral Movement

·      Device / Possible SMB/NTLM Brute Force

·      Device / Suspicious SMB Scanning Activity

·      Device / Network Scan

·      Device / RDP Scan

·      Device / Large Number of Model Alerts

·      Device / Anomalous ITaskScheduler Activity

·      Device / Suspicious Network Scan Activity

·      Device / New or Uncommon WMI Activity

List of IoCs Possible IoCs:

·      DeElevator64.dll

·      deelevator64.dll

·      DeElevate64.exe

·      deelevator64.dll

·      deelevate64.exe

·      to.bat

Mid-high confidence IoCs:

-       104.238.130[.]185

-       http://104.238.130[.]185/DeElevate64.exe

-       http://104.238.130[.]185/DeElevator64.dll

-       DESKTOP-1JIMIV3

References:

1.     https://www.ivanti.com/blog/security-update-ivanti-connect-secure-policy-secure-and-neurons-for-zta-gateways

2.     https://unit42.paloaltonetworks.com/threat-brief-ivanti-cve-2025-0282-cve-2025-0283/

3.     https://www.proofpoint.com/uk/blog/identity-threat-defense/privilege-escalation-attack#:~:text=In%20this%20approach%2C%20attackers%20exploit,handing%20over%20their%20login%20credentials

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About the author
Hugh Turnbull
Cyber Analyst

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March 6, 2025

From Containment to Remediation: Darktrace / CLOUD & Cado Reducing MTTR

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Cloud environments operate at speed, with workloads spinning up and down in seconds. This agility is great for business and is one of the main reasons for cloud adoption. But this same agility and speed presents new challenges for security teams. When a threat emerges, every second counts—yet many organizations struggle with slow Mean Time to Respond (MTTR) due to operational bottlenecks, outdated tooling, and the complexity of modern cloud infrastructure.

To minimize disruption and potential damage, containment is a critical step in incident response. By effectively responding to contain a threat, organizations can help prevent lateral movement limiting an attack’s impact.

However, containment is not the end goal. Full remediation requires a deep understanding of exactly what happened, how far the threat spread, and what assets were involved and what changes may be needed to prevent it from happening again.

This is why Darktrace’s recent acquisition of Cado is so exciting. Darktrace / CLOUD provides real-time threat detection and automated cloud native response for containment. With Cado, Darktrace / CLOUD ensures security teams have the forensic insights that are required to fully remediate and strengthen their defenses.

Why do organizations struggle with MTTR in the cloud?

Many security teams experience delays in fully responding to cloud threats due to several key challenges:

1. Limited access to cloud resources

Security teams often don’t have direct access to cloud environments because often infrastructure is managed by a separate operations team—or even an outsourced provider. When a threat is detected, analysts must submit access requests or escalate to another team, slowing down investigations.

This delay can be particularly costly in cloud environments where attacks unfold rapidly. Without immediate access to affected resources, the time to contain, investigate, and remediate an incident can increase significantly.

2. The cloud’s ephemeral nature

Cloud workloads are often dynamic and short-lived. Serverless functions, containers, and auto-scaling resources can exist for minutes or even seconds. If a security event occurs in one of these ephemeral resources and it disappears before forensic data is captured, understanding the full scope of the attack becomes nearly impossible.

Traditional forensic methods, which rely on static endpoints, fail in these environments—leaving security teams blind to what happened.

3. Containment is critical, but businesses require more

Automated cloud native response for containment is essential for stopping an attack in progress. However, regulatory frameworks underline the need for a full understanding to prove the extent of an incident and determine the root cause, this goes beyond just containing a threat.

Digital Operational Resilience Act (DORA): [1] Enacted by the European Union, DORA requires financial entities to establish robust incident reporting mechanisms. Organizations must detect, manage, and notify authorities of significant ICT-related incidents, ensuring a comprehensive understanding of each event's impact. This includes detailed analysis and documentation to enhance operational resilience and compliance.

Network and Information Security Directive 2 (NIS2): [2]This EU directive imposes advanced reporting obligations on essential and important entities, requiring them to report significant cybersecurity incidents to relevant authorities. Organizations must conduct thorough post-incident analysis to understand the incident's scope and prevent future occurrences.

Forensic analysis plays a critical role in full remediation, particularly when organizations need to:

  • Conduct post-incident investigations for compliance and reporting.
  • Identify affected data and impacted users.
  • Understand attacker behavior to prevent repeat incidents.

Without a clear forensic understanding, security teams are at risk of incomplete remediation, potentially leaving gaps that adversaries can exploit in a future attack.

How Darktrace / CLOUD & Cado reduce MTTR and enable full remediation

By combining Darktrace / CLOUD’s AI-driven platform with Cado’s automated forensics capture, organizations can achieve rapid containment and deep investigative capabilities, accelerating MTTR metrics while ensuring full remediation in complex cloud environments.

Darktrace / CLOUD: Context-aware anomaly detection & cloud native response

Darktrace / CLOUD provides deep visibility into hybrid cloud environments, by understanding the relationships between assets, identity behaviours, combined with misconfiguration data and runtime anomaly activity. Enabling customers to:

  • Detect and contain anomalous activity before threats escalate.
  • Understand how cloud identities, permissions, and configurations contribute to organizational risk.
  • Provide visibility into deployed cloud assets and services logically grouped into architectures.

Even in containerized services like AWS Fargate, where traditional endpoint security tools often struggle due to the lack of persistent accessible infrastructure, Darktrace / CLOUD monitors for anomalous behavior. If a threat is detected, security teams can launch a Cado forensic investigation from the Darktrace platform, ensuring rapid evidence collection and deeper analysis.

Ensuring:

  • Complete timeline reconstruction to understand the full impact.
  • Identification of persistence mechanisms that attackers may have left behind.
  • Forensic data preservation to meet compliance mandates like DORA, NIS2, and ISO 27001.

The outcome: Faster, smarter incident response

Darktrace / CLOUD with Cado enables organizations to detect, contain and forensically analyse activity across hybrid cloud environments

  • Reduce MTTR by automating containment and enabling forensic analysis.
  • Seamlessly pivot to a forensic investigation when needed—right from the Darktrace platform.
  • Ensure full remediation with deep forensic insights—even in ephemeral environments.

Stopping an attack is only the first step—understanding its impact is what prevents it from happening again. Together, Darktrace / CLOUD and Cado empower security teams to investigate, respond, and remediate cloud threats with speed and confidence.

References

[1] eiopa.europa.eu

[2] https://zcybersecurity.com/eu-nis2-requirements

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About the author
Adam Stevens
Director of Product, Cloud Security
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