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Darktrace’s Detection of a Hive Ransomware-as-Service

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23
May 2023
23
May 2023
This blog investigates a new strain of ransomware, Hive, a ransomware-as-a-service. Darktrace was able to provide full visibility over the attacks.

Update: On January 26, 2023, the Hive ransomware group was dismantled and servers associated with the sale of the ransomware were taken offline following an investigation by the FBI, German law enforcement and the National Crime Agency (NCA). The activity detailed in this blog took place in 2022, whilst the group was still active.

RaaS in Cyber Security

The threat of ransomware continues to be a constant concern for security teams across the cyber threat landscape. With the growing popularity of Ransomware-as-a-Service (RaaS), it is becoming more and more accessible for even inexperienced would-be attackers. As a result of this low barrier to entry, the volume of ransomware attacks is expected to increase significantly.

What’s more, RaaS is a highly tailorable market in which buyers can choose from varied kits and features to use in their ransomware deployments meaning attacks will rarely behave the same. To effectively detect and safeguard against these differentiations, it is crucial to implement security measures that put the emphasis on detecting anomalies and focusing on deviations in expected behavior, rather than relying on depreciated indicators of compromise (IoC) lists or playbooks that focus on attack chains unable to keep pace with the increasing speed of ransomware evolution.

In early 2022, Darktrace DETECT/Network™ identified several instances of Hive ransomware on the networks of multiple customers. Using its anomaly-based detection, Darktrace was able to successfully detect the attacks and multiple stages of the kill chain, including command and control (C2) activity, lateral movement, data exfiltration, and ultimately data encryption and the writing of ransom notes.

Hive Ransomware 

Hive ransomware is a relatively new strain that was first observed in the wild in June 2021. It is known to target a variety of industries including healthcare, energy providers, and retailers, and has reportedly attacked over 1,500 organizations, collecting more than USD 100m in ransom payments [1].

Hive is distributed via a RaaS model where its developers update and maintain the code, in return for a percentage of the eventual ransom payment, while users (or affiliates) are given the tools to carry out attacks using a highly sophisticated and complex malware they would otherwise be unable to use. Hive uses typical tactics, techniques and procedures (TTPs) associated with ransomware, though they do vary depending on the Hive affiliate carrying out the attack.

In most cases a double extortion attack is carried out, whereby data is first exfiltrated and then encrypted before a ransom demand is made. This gives attackers extra leverage as victims are at risk of having their sensitive data leaked to the public on websites such as the ‘HiveLeaks’ TOR website.

Attack Timeline

Owing to the highly customizable nature of RaaS, the tactics and methods employed by Hive actors are expected to differ on a case-by-case basis. Nonetheless in the majority of Hive ransomware incidents identified on Darktrace customer environments, Darktrace DETECT observed the following general attack stages and features. This is possibly indicative of the attacks originating from the same threat actor(s) or from a widely sold batch with a particular configuration to a variety of actors.

Figure 1: A typical timeline of a Hive attack observed by Darktrace.

Initial Access 

Although Hive actors are known to gain initial access to networks through multiple different vectors, the two primary methods reported by security researchers are the exploitation of Microsoft Exchange vulnerabilities, or the distribution of phishing emails with malicious attachments [2][3].

In the early stages of one Hive ransomware attack observed on the network of a Darktrace customer, for example, Darktrace detected a device connecting to the rare external location 23.81.246[.]84, with a PowerShell user agent via HTTP. During this connection, the device attempted to download an executable file named “file.exe”. It is possible that the file was initially accessed and delivered via a phishing email; however, as Darktrace/Email was not enabled at the time of the attack, this was outside of Darktrace’s purview. Fortunately, the connection failed the proxy authentication was thus blocked as seen in the packet capture (PCAP) in Figure 2. 

Shortly after this attempted download, the same device started to receive a high volume of incoming SSL connections from a rare external endpoint, namely 146.70.87[.]132. Darktrace logged that this endpoint was using an SSL certificate signed by Go Daddy CA, an easily obtainable and accessible SSL certificate, and that the increase in incoming SSL connections from this endpoint was unusual behavior for this device. 

It is likely that this highly anomalous activity detected by Darktrace indicates when the ransomware attack began, likely initial payload download.  

Darktrace DETECT models:

  • Anomalous Connection / Powershell to Rare External
  • Anomalous Server Activity / New Internet Facing System
Figure 2: PCAP of the HTTP connection to the rare endpoint 23.81.246[.]84 showing the failed proxy authentication.

C2 Beaconing 

Following the successful initial access, Hive actors begin to establish their C2 infrastructure on infected networks through numerous connections to C2 servers, and the download of additional stagers. 

On customer networks infected by Hive ransomware, Darktrace identified devices initiating a high volume of connections to multiple rare endpoints. This very likely represented C2 beaconing to the attacker’s infrastructure. In one particular example, further open-source intelligence (OSINT) investigation revealed that these endpoints were associated with Cobalt Strike.

Darktrace DETECT models:

  • Anomalous Connection / Multiple Connections to New External TCP
  • Anomalous Server Activity / Anomalous External Activity from Critical Network Device
  • Compromise / High Volume of Connections with Beacon Score
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Suspicious HTTP Beacons to Dotted Quad 
  • Compromise / SSL or HTTP Beacon
  • Device / Lateral Movement and C2 Activity

Internal Reconnaissance, Lateral Movement and Privilege Escalation

After C2 infrastructure has been established, Hive actors typically begin to uninstall antivirus products in an attempt to remain undetected on the network [3]. They also perform internal reconnaissance to look for vulnerabilities and open channels and attempt to move laterally throughout the network.

Amid the C2 connections, Darktrace was able to detect network scanning activity associated with the attack when a device on one customer network was observed initiating an unusually high volume of connections to other internal devices. A critical network device was also seen writing an executable file “mimikatz.exe” via SMB which appears to be the Mimikatz attack tool commonly used for credential harvesting. 

There were also several detections of lateral movement attempts via RDP and DCE-RPC where the attackers successfully authenticated using an “Administrator” credential. In one instance, a device was also observed performing ITaskScheduler activity. This service is used to remotely control tasks running on machines and is commonly observed as part of malicious lateral movement activity. Darktrace DETECT understood that the above activity represented a deviation from the devices’ normal pattern of behavior and the following models were breached:

Darktrace DETECT models:

  • Anomalous Connection / Anomalous DRSGetNCChanges Operation
  • Anomalous Connection / New or Uncommon Service Control
  • Anomalous Connection / Unusual Admin RDP Session
  • Anomalous Connection / Unusual SMB Version 1 Connectivity
  • Compliance / SMB Drive Write
  • Device / Anomalous ITaskScheduler Activity
  • Device / Attack and Recon Tools
  • Device / Attack and Recon Tools In SMB
  • Device / EXE Files Distributed to Multiple Devices
  • Device / Suspicious Network Scan Activity
  • Device / Increase in New RPC Services
  • User / New Admin Credentials on Server

Estrazione dei dati

At this stage of the attack, Hive actors have been known to carry out data exfiltration activity on infected networks using a variety of different methods. The Cybersecurity & Infrastructure Security Agency (CISA) reported that “Hive actors exfiltrate data likely using a combination of Rclone and the cloud storage service Mega[.]nz” [4]. Darktrace DETECT identified an example of this when a device on one customer network was observed making HTTP connections to endpoints related to Mega, including “w.apa.mega.co[.]nz”, with the user agent “rclone/v1.57.0” with at least 3 GiB of data being transferred externally (Figure 3). The same device was also observed transferring at least 3.6 GiB of data via SSL to the rare external IP, 158.51.85[.]157.

Figure 3: A summary of a device’s external connections to multiple endpoints and the respective amounts of data exfiltrated to Mega storage endpoints.

In another case, a device was observed uploading over 16 GiB of data to a rare external endpoint 93.115.27[.]71 over SSH. The endpoint in question was seen in earlier beaconing activity suggesting that this was likely an exfiltration event. 

However, Hive ransomware, like any other RaaS kit, can differ greatly in its techniques and features, and it is important to note that data exfiltration may not always be present in a Hive ransomware attack. In one incident detected by Darktrace, there were no signs of any data leaving the customer environment, indicating data exfiltration was not part of the Hive actor’s objectives.

Darktrace DETECT models:

  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous Connection / Lots of New Connections
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
  • Anomalous Connection / Suspicious Self-Signed SSL
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Device / New User Agent and New IP
  • Unusual Activity / Unusual External Data to New Endpoints
  • Unusual Activity / Unusual External Data Transfer
  • Unusual Activity / Enhanced Unusual External Data Transfer

Ransomware Deployment

In the final stage of a typical Hive ransomware attack, the ransomware payload is deployed and begins to encrypt files on infected devices. On one customer network, Darktrace detected several devices connecting to domain controllers (DC) to read a file named “xxx.exe”. Several sources have linked this file name with the Hive ransomware payload [5].

In another example, Darktrace DETECT observed multiple devices downloading the executable files “nua64.exe” and “nua64.dll” from a rare external location, 194.156.90[.]25. OSINT investigation revealed that the files are associated with Hive ransomware.

Figure 4: Security vendor analysis of the malicious file hash [6] associated with Hive ransomware. 

Shortly after the download of this executable, multiple devices were observed performing an unusual amount of file encryption, appending randomly generated strings of characters to file extensions. 

Although it has been reported that earlier versions of Hive ransomware encrypted files with a “.hive” extension [7], Darktrace observed across multiple customers that encrypted files had extensions that were partially-randomized, but consistently 20 characters long, matching the regular expression “[a-zA-Z0-9\-\_]{8}[\-\_]{1}[A-Za-z0-9\-\_]{11}”.

Figure 5: Device Event Log showing SMB reads and writes of encrypted files with a randomly generated extension of 20 characters. 

Following the successful encryption of files, Hive proceeds to drop a ransom note, named “HOW_TO_DECRYPT.txt”, into each affected directory. Typically, the ransom note will contain a link to Hive’s “sales department” and, in the event that exfiltration took place, a link to the “HiveLeaks” site, where attackers threaten to publish exfiltrated data if their demands are not met (Figure 6).  In cases of Hive ransomware detected by Darktrace, multiple devices were observed attempting to contact “HiveLeaks” TOR domains, suggesting that endpoint users had followed links provided to them in ransom notes.

Figure 6: Sample of a Hive ransom note [4].

Examples of file extensions:

  • 36C-AT9-_wm82GvBoCPC
  • 36C-AT9--y6Z1G-RFHDT
  • 36C-AT9-_x2x7FctFJ_q
  • 36C-AT9-_zK16HRC3QiL
  • 8KAIgoDP-wkQ5gnYGhrd
  • kPemi_iF_11GRoa9vb29
  • kPemi_iF_0RERIS1m7x8
  • kPemi_iF_7u7e5zp6enp
  • kPemi_iF_y4u7pB3d3f3
  • U-9Xb0-k__T0U9NJPz-_
  • U-9Xb0-k_6SkA8Njo5pa
  • zm4RoSR1_5HMd_r4a5a9 

Darktrace DETECT models:

  • Anomalous Connection / SMB Enumeration
  • Anomalous Connection / Sustained MIME Type Conversion
  • Anomalous Connection / Unusual Admin SMB Session
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Compliance / SMB Drive Write
  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / Ransom or Offensive Words Written to SMB
  • Compromise / Ransomware / Possible Ransom Note Write
  • Compromise / High Priority Tor2Web
  • Compromise / Tor2Web
  • Device / EXE Files Distributed to Multiple Devices

Conclusion

As Hive ransomware attacks are carried out by different affiliates using varying deployment kits, the tactics employed tend to vary and new IoCs are regularly identified. Furthermore, in 2022 a new variant of Hive was written using the Rust programming language. This represented a major upgrade to Hive, improving its defense evasion techniques and making it even harder to detect [8]. 

Hive is just one of many RaaS offerings currently on the market, and this market is only expected to grow in usage and diversity of presentations.  As ransomware becomes more accessible and easier to deploy it is essential for organizations to adopt efficient security measures to identify ransomware at the earliest possible stage. 

Darktrace DETECT’s Self-Learning AI understands customer networks and learns the expected patterns of behavior across an organization’s digital estate. Using its anomaly-based detection Darktrace is able to identify emerging threats through the detection of unusual or unexpected behavior, without relying on rules and signatures, or known IoCs. 

Credit to: Emily Megan Lim, Cyber Analyst, Hyeongyung Yeom, Senior Cyber Analyst & Analyst Team Lead.

Appendices

MITRE AT&CK Mapping

Reconnaissance

T1595.001 – Scanning IP Blocks

T1595.002 – Vulnerability Scanning

Resource Development

T1583.006 – Web Services

Initial Access

T1078 – Valid Accounts

T1190 – Exploit Public-Facing Application

T1200 – Hardware Additions

Execution

T1053.005 – Scheduled Task

T1059.001 – PowerShell

Persistence/Privilege Escalation

T1053.005 – Scheduled Task

T1078 – Valid Accounts

Defense Evasion

T1078 – Valid Accounts

T1207 – Rogue Domain Controller

T1550.002 – Pass the Hash

Discovery

T1018 – Remote System Discovery

T1046 – Network Service Discovery

T1083 – File and Directory Discovery

T1135 – Network Share Discovery

Movimento laterale

T1021.001 – Remote Desktop Protocol

T1021.002 – SMB/Windows Admin Shares

T1021.003 – Distributed Component Object Model

T1080 – Taint Shared Content

T1210 – Exploitation of Remote Services

T1550.002 – Pass the Hash

T1570 – Lateral Tool Transfer

Collection

T1185 – Man in the Browser

Command and Control

T1001 – Data Obfuscation

T1071 – Application Layer Protocol

T1071.001 – Web Protocols

T1090.003 – Multi-hop proxy

T1095 – Non-Application Layer Protocol

T1102.003 – One-Way Communication

T1571 – Non-Standard Port

Exfiltration

T1041 – Exfiltration Over C2 Channel

T1567.002 – Exfiltration to Cloud Storage

Impact

T1486 – Data Encrypted for Impact

T1489 – Service Stop

List of IoCs 

23.81.246[.]84 - IP Address - Likely Malicious File Download Endpoint

146.70.87[.]132 - IP Address - Possible Ransomware Endpoint

5.199.162[.]220 - IP Address - C2 Endpoint

23.227.178[.]65 - IP Address - C2 Endpoint

46.166.161[.]68 - IP Address - C2 Endpoint

46.166.161[.]93 - IP Address - C2 Endpoint

93.115.25[.]139 - IP Address - C2 Endpoint

185.150.1117[.]189 - IP Address - C2 Endpoint

192.53.123[.]202 - IP Address - C2 Endpoint

209.133.223[.]164 - IP Address - Likely C2 Endpoint

cltrixworkspace1[.]com - Domain - C2 Endpoint

vpnupdaters[.]com - Domain - C2 Endpoint

93.115.27[.]71 - IP Address - Possible Exfiltration Endpoint

158.51.85[.]157 - IP Address - Possible Exfiltration Endpoint

w.api.mega.co[.]nz - Domain - Possible Exfiltration Endpoint

*.userstorage.mega.co[.]nz - Domain - Possible Exfiltration Endpoint

741cc67d2e75b6048e96db9d9e2e78bb9a327e87 - SHA1 Hash - Hive Ransomware File

2f9da37641b204ef2645661df9f075005e2295a5 - SHA1 Hash - Likely Hive Ransomware File

hiveleakdbtnp76ulyhi52eag6c6tyc3xw7ez7iqy6wc34gd2nekazyd[.]onion - TOR Domain - Likely Hive Endpoint

References

[1] https://www.justice.gov/opa/pr/us-department-justice-disrupts-hive-ransomware-variant

[2] https://www.varonis.com/blog/hive-ransomware-analysis

[3] https://www.trendmicro.com/vinfo/us/security/news/ransomware-spotlight/ransomware-spotlight-hive 

[4]https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-321a

[5] https://www.trendmicro.com/en_us/research/22/c/nokoyawa-ransomware-possibly-related-to-hive-.html

[6] https://www.virustotal.com/gui/file/60f6a63e366e6729e97949622abd9de6d7988bba66f85a4ac8a52f99d3cb4764/detection

[7] https://heimdalsecurity.com/blog/what-is-hive-ransomware/

[8] https://www.microsoft.com/en-us/security/blog/2022/07/05/hive-ransomware-gets-upgrades-in-rust/ 

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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Emily Megan Lim
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The State of AI in Cybersecurity: The Impact of AI on Cybersecurity Solutions

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13
May 2024

About the AI Cybersecurity Report

Darktrace surveyed 1,800 CISOs, security leaders, administrators, and practitioners from industries around the globe. Our research was conducted to understand how the adoption of new AI-powered offensive and defensive cybersecurity technologies are being managed by organizations.

This blog continues the conversation from “The State of AI in Cybersecurity: Unveiling Global Insights from 1,800 Security Practitioners” which was an overview of the entire report. This blog will focus on one aspect of the overarching report, the impact of AI on cybersecurity solutions.

To access the full report, click here.

The effects of AI on cybersecurity solutions

Overwhelming alert volumes, high false positive rates, and endlessly innovative threat actors keep security teams scrambling. Defenders have been forced to take a reactive approach, struggling to keep pace with an ever-evolving threat landscape. It is hard to find time to address long-term objectives or revamp operational processes when you are always engaged in hand-to-hand combat.                  

The impact of AI on the threat landscape will soon make yesterday’s approaches untenable. Cybersecurity vendors are racing to capitalize on buyer interest in AI by supplying solutions that promise to meet the need. But not all AI is created equal, and not all these solutions live up to the widespread hype.  

Do security professionals believe AI will impact their security operations?

Yes! 95% of cybersecurity professionals agree that AI-powered solutions will level up their organization’s defenses.                                                                

Not only is there strong agreement about the ability of AI-powered cybersecurity solutions to improve the speed and efficiency of prevention, detection, response, and recovery, but that agreement is nearly universal, with more than 95% alignment.

This AI-powered future is about much more than generative AI. While generative AI can help accelerate the data retrieval process within threat detection, create quick incident summaries, automate low-level tasks in security operations, and simulate phishing emails and other attack tactics, most of these use cases were ranked lower in their impact to security operations by survey participants.

There are many other types of AI, which can be applied to many other use cases:

Supervised machine learning: Applied more often than any other type of AI in cybersecurity. Trained on attack patterns and historical threat intelligence to recognize known attacks.

Natural language processing (NLP): Applies computational techniques to process and understand human language. It can be used in threat intelligence, incident investigation, and summarization.

Large language models (LLMs): Used in generative AI tools, this type of AI applies deep learning models trained on massively large data sets to understand, summarize, and generate new content. The integrity of the output depends upon the quality of the data on which the AI was trained.

Unsupervised machine learning: Continuously learns from raw, unstructured data to identify deviations that represent true anomalies. With the correct models, this AI can use anomaly-based detections to identify all kinds of cyber-attacks, including entirely unknown and novel ones.

What are the areas of cybersecurity AI will impact the most?

Improving threat detection is the #1 area within cybersecurity where AI is expected to have an impact.                                                                                  

The most frequent response to this question, improving threat detection capabilities in general, was top ranked by slightly more than half (57%) of respondents. This suggests security professionals hope that AI will rapidly analyze enormous numbers of validated threats within huge volumes of fast-flowing events and signals. And that it will ultimately prove a boon to front-line security analysts. They are not wrong.

Identifying exploitable vulnerabilities (mentioned by 50% of respondents) is also important. Strengthening vulnerability management by applying AI to continuously monitor the exposed attack surface for risks and high-impact vulnerabilities can give defenders an edge. If it prevents threats from ever reaching the network, AI will have a major downstream impact on incident prevalence and breach risk.

Where will defensive AI have the greatest impact on cybersecurity?

Cloud security (61%), data security (50%), and network security (46%) are the domains where defensive AI is expected to have the greatest impact.        

Respondents selected broader domains over specific technologies. In particular, they chose the areas experiencing a renaissance. Cloud is the future for most organizations,
and the effects of cloud adoption on data and networks are intertwined. All three domains are increasingly central to business operations, impacting everything everywhere.

Responses were remarkably consistent across demographics, geographies, and organization sizes, suggesting that nearly all survey participants are thinking about this similarly—that AI will likely have far-reaching applications across the broadest fields, as well as fewer, more specific applications within narrower categories.

Going forward, it will be paramount for organizations to augment their cloud and SaaS security with AI-powered anomaly detection, as threat actors sharpen their focus on these targets.

How will security teams stop AI-powered threats?            

Most security stakeholders (71%) are confident that AI-powered security solutions are better able to block AI-powered threats than traditional tools.

There is strong agreement that AI-powered solutions will be better at stopping AI-powered threats (71% of respondents are confident in this), and there’s also agreement (66%) that AI-powered solutions will be able to do so automatically. This implies significant faith in the ability of AI to detect threats both precisely and accurately, and also orchestrate the correct response actions.

There is also a high degree of confidence in the ability of security teams to implement and operate AI-powered solutions, with only 30% of respondents expressing doubt. This bodes well for the acceptance of AI-powered solutions, with stakeholders saying they’re prepared for the shift.

On the one hand, it is positive that cybersecurity stakeholders are beginning to understand the terms of this contest—that is, that only AI can be used to fight AI. On the other hand, there are persistent misunderstandings about what AI is, what it can do, and why choosing the right type of AI is so important. Only when those popular misconceptions have become far less widespread can our industry advance its effectiveness.  

To access the full report, click here.

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Connecting the Dots: Darktrace’s Detection of the Exploitation of the ConnectWise ScreenConnect Vulnerabilities

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10
May 2024

Introduction

Across an ever changing cyber landscape, it is common place for threat actors to actively identify and exploit newly discovered vulnerabilities within commonly utilized services and applications. While attackers are likely to prioritize developing exploits for the more severe and global Common Vulnerabilities and Exposures (CVEs), they typically have the most success exploiting known vulnerabilities within the first couple years of disclosure to the public.

Addressing these vulnerabilities in a timely manner reduces the effectiveness of known vulnerabilities, decreasing the pace of malicious actor operations and forcing pursuit of more costly and time-consuming methods, such as zero-day related exploits or attacking software supply chain operations. While actors also develop tools to exploit other vulnerabilities, developing exploits for critical and publicly known vulnerabilities gives actors impactful tools at a low cost they are able to use for quite some time.

Between January and March 2024, the Darktrace Threat Research team investigated one such example that involved indicators of compromise (IoCs) suggesting the exploitation of vulnerabilities in ConnectWise’s remote monitoring and management (RMM) software ScreenConnect.

What are the ConnectWise ScreenConnect vulnerabilities?

CVE-2024-1708 is an authentication bypass vulnerability in ScreenConnect 23.9.7 (and all earlier versions) that, if exploited, would enable an attacker to execute remote code or directly impact confidential information or critical systems. This exploit would pave the way for a second ScreenConnect vunerability, CVE-2024-1709, which allows attackers to directly access confidential information or critical systems [1].

ConnectWise released a patch and automatically updated cloud versions of ScreenConnect 23.9.9, while urging security temas to update on-premise versions immediately [3].

If exploited in conjunction, these vulnerabilities could allow a malicious actor to create new administrative accounts on publicly exposed instances by evading existing security measures. This, in turn, could enable attackers to assume an administrative role and disable security tools, create backdoors, and disrupt RMM processes. Access to an organization’s environment in this manner poses serious risk, potentially leading to significant consequences such as deploying ransomware, as seen in various incidents involving the exploitation of ScreenConnect [2]

Darktrace Coverage of ConnectWise Exploitation

Darktrace’s anomaly-based detection was able to identify evidence of exploitation related to CVE-2024-1708 and CVE-2024-1709 across two distinct timelines; these detections included connectivity with endpoints that were later confirmed to be malicious by multiple open-source intelligence (OSINT) vendors. The activity observed by Darktrace suggests that threat actors were actively exploiting these vulnerabilities across multiple customer environments.

In the cases observed across the Darktrace fleet, Darktrace DETECT™ and Darktrace RESPOND™ were able to work in tandem to pre-emptively identify and contain network compromises from the onset. While Darktrace RESPOND was enabled in most customer environments affected by the ScreenConnect vulnerabilities, in the majority of cases it was configured in Human Confirmation mode. Whilst in Human Confirmation mode, RESPOND will provide recommended actions to mitigate ongoing attacks, but these actions require manual approval from human security teams.

When enabled in autonomous response mode, Darktrace RESPOND will take action automatically, shutting down suspicious activity as soon as it is detected without the need for human intervention. This is the ideal end state for RESPOND as actions can be taken at machine speed, without any delays waiting for user approval.

Looking within the patterns of activity observed by Darktrace , the typical  attack timeline included:

Darktrace observed devices on affected customer networks performing activity indicative of ConnectWise ScreenConnect usage, for example connections over 80 and 8041, connections to screenconnect[.]com, and the use of the user agent “LabTech Agent”. OSINT research suggests that this user agent is an older name for ConnectWise Automate [5] which also includes ScreenConnect as standard [6].

Darktrace DETECT model alert highlighting the use of a remote management tool, namely “screenconnect[.]com”.
Figure 1: Darktrace DETECT model alert highlighting the use of a remote management tool, namely “screenconnect[.]com”.

This activity was typically followed by anomalous connections to the external IP address 108.61.210[.]72 using URIs of the form “/MyUserName_DEVICEHOSTNAME”, as well as additional connections to another external, IP 185.62.58[.]132. Both of these external locations have since been reported as potentially malicious [14], with 185.62.58[.]132 in particular linked to ScreenConnect post-exploitation activity [2].

Figure 2: Darktrace DETECT model alert highlighting the unusual connection to 185.62.58[.]132 via port 8041.
Figure 2: Darktrace DETECT model alert highlighting the unusual connection to 185.62.58[.]132 via port 8041.
Figure 3: Darktrace DETECT model alert highlighting connections to 108.61.210[.]72 using a new user agent and the “/MyUserName_DEVICEHOSTNAME” URI.
Figure 3: Darktrace DETECT model alert highlighting connections to 108.61.210[.]72 using a new user agent and the “/MyUserName_DEVICEHOSTNAME” URI.

Same Exploit, Different Tactics?  

While the majority of instances of ConnectWise ScreenConnect exploitation observed by Darktrace followed the above pattern of activity, Darktrace was able to identify some deviations from this.

In one customer environment, Darktrace’s detection of post-exploitation activity began with the same indicators of ScreenConnect usage, including connections to screenconnect[.]com via port 8041, followed by connections to unusual domains flagged as malicious by OSINT, in this case 116.0.56[.]101 [16] [17]. However, on this deployment Darktrace also observed threat actors downloading a suspicious AnyDesk installer from the endpoint with the URI “hxxp[:]//116.0.56[.]101[:]9191/images/Distribution.exe”.

Figure 4: Darktrace DETECT model alert highlighting the download of an unusual executable file from 116.0.56[.]101.
Figure 4: Darktrace DETECT model alert highlighting the download of an unusual executable file from 116.0.56[.]101.

Further investigation by Darktrace’s Threat Research team revealed that this endpoint was associated with threat actors exploiting CVE-2024-1708 and CVE-2024-1709 [1]. Darktrace was additionally able to identify that, despite the customer being based in the United Kingdom, the file downloaded came from Pakistan. Darktrace recognized that this represented a deviation from the device’s expected pattern of activity and promptly alerted for it, bringing it to the attention of the customer.

Figure 5: External Sites Summary within the Darktrace UI pinpointing the geographic locations of external endpoints, in this case highlighting a file download from Pakistan.
Figure 5: External Sites Summary within the Darktrace UI pinpointing the geographic locations of external endpoints, in this case highlighting a file download from Pakistan.

Darktrace’s Autonomous Response

In this instance, the customer had Darktrace enabled in autonomous response mode and the post-exploitation activity was swiftly contained, preventing the attack from escalating.

As soon as the suspicious AnyDesk download was detected, Darktrace RESPOND applied targeted measures to prevent additional malicious activity. This included blocking connections to 116.0.56[.]101 and “*.56.101”, along with blocking all outgoing traffic from the device. Furthermore, RESPOND enforced a “pattern of life” on the device, restricting its activity to its learned behavior, allowing connections that are considered normal, but blocking any unusual deviations.

Figure 6: Darktrace RESPOND enforcing a “pattern of life” on the offending device after detecting the suspicious AnyDesk download.
Figure 6: Darktrace RESPOND enforcing a “pattern of life” on the offending device after detecting the suspicious AnyDesk download.
Figure 7: Darktrace RESPOND blocking connections to the suspicious endpoint 116.0.56[.]101 and “*.56.101” following the download of the suspicious AnyDesk installer.
Figure 7: Darktrace RESPOND blocking connections to the suspicious endpoint 116.0.56[.]101 and “*.56.101” following the download of the suspicious AnyDesk installer.

The customer was later able to use RESPOND to manually quarantine the offending device, ensuring that all incoming and outgoing traffic to or from the device was prohibited, thus preventing ay further malicious communication or lateral movement attempts.

Figure 8: The actions applied by Darktrace RESPOND in response to the post-exploitation activity related to the ScreenConnect vulnerabilities, including the manually applied “Quarantine device” action.

Conclusion

In the observed cases of the ConnectWise ScreenConnect vulnerabilities being exploited across the Darktrace fleet, Darktrace was able to pre-emptively identify and contain network compromises from the onset, offering vital protection against disruptive cyber-attacks.

While much of the post-exploitation activity observed by Darktrace remained the same across different customer environments, important deviations were also identified suggesting that threat actors may be adapting their tactics, techniques and procedures (TTPs) from campaign to campaign.

While new vulnerabilities will inevitably surface and threat actors will continually look for novel ways to evolve their methods, Darktrace’s Self-Learning AI and behavioral analysis offers organizations full visibility over new or unknown threats. Rather than relying on existing threat intelligence or static lists of “known bads”, Darktrace is able to detect emerging activity based on anomaly and respond to it without latency, safeguarding customer environments whilst causing minimal disruption to business operations.

Credit: Emma Foulger, Principal Cyber Analyst for their contribution to this blog.

Appendices

Darktrace Model Coverage

DETECT Models

Compromise / Agent Beacon (Medium Period)

Compromise / Agent Beacon (Long Period)

Anomalous File / EXE from Rare External Location

Device / New PowerShell User Agent

Anomalous Connection / Powershell to Rare External

Anomalous Connection / New User Agent to IP Without Hostname

User / New Admin Credentials on Client

Device / New User Agent

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Compromise / Suspicious Request Data

Compliance / Remote Management Tool On Server

Anomalous File / Anomalous Octet Stream (No User Agent)

RESPOND Models

Antigena / Network::External Threat::Antigena Suspicious File Block

Antigena / Network::External Threat::Antigena File then New Outbound Block

Antigena / Network::Significant Anomaly::Antigena Enhanced Monitoring from Client Block

Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block

Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach

Antigena / Network::Insider Threat::Antigena Unusual Privileged User Activities Block

Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Pattern of Life Block

List of IoCs

IoC - Type - Description + Confidence

185.62.58[.]132 – IP- IP linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

108.61.210[.]72- IP - IP linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

116.0.56[.]101    - IP - IP linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

/MyUserName_ DEVICEHOSTNAME – URI - URI linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

/images/Distribution.exe – URI - URI linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

24780657328783ef50ae0964b23288e68841a421 - SHA1 Filehash - Filehash linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

a21768190f3b9feae33aaef660cb7a83 - MD5 Filehash - Filehash linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

MITRE ATT&CK Mapping

Technique – Tactic – ID - Sub-technique of

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

Web Services      - RESOURCE DEVELOPMENT - T1583.006 - T1583

Drive-by Compromise - INITIAL ACCESS - T1189 – NA

Ingress Tool Transfer   - COMMAND AND CONTROL - T1105 - NA

Malware - RESOURCE DEVELOPMENT - T1588.001- T1588

Exploitation of Remote Services - LATERAL MOVEMENT - T1210 – NA

PowerShell – EXECUTION - T1059.001 - T1059

Pass the Hash      - DEFENSE EVASION, LATERAL MOVEMENT     - T1550.002 - T1550

Valid Accounts - DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - T1078 – NA

Man in the Browser – COLLECTION - T1185     - NA

Exploit Public-Facing Application - INITIAL ACCESS - T1190         - NA

Exfiltration Over C2 Channel – EXFILTRATION - T1041 – NA

IP Addresses – RECONNAISSANCE - T1590.005 - T1590

Remote Access Software - COMMAND AND CONTROL - T1219 – NA

Lateral Tool Transfer - LATERAL MOVEMENT - T1570 – NA

Application Layer Protocol - COMMAND AND CONTROL - T1071 – NA

References:

[1] https://unit42.paloaltonetworks.com/connectwise-threat-brief-cve-2024-1708-cve-2024-1709/  

[2] https://www.huntress.com/blog/slashandgrab-screen-connect-post-exploitation-in-the-wild-cve-2024-1709-cve-2024-1708    

[3] https://www.huntress.com/blog/a-catastrophe-for-control-understanding-the-screenconnect-authentication-bypass

[4] https://www.speedguide.net/port.php?port=8041  

[5] https://www.connectwise.com/company/announcements/labtech-now-connectwise-automate

[6] https://www.connectwise.com/solutions/software-for-internal-it/automate

[7] https://www.securityweek.com/slashandgrab-screenconnect-vulnerability-widely-exploited-for-malware-delivery/

[8] https://arcticwolf.com/resources/blog/cve-2024-1709-cve-2024-1708-follow-up-active-exploitation-and-pocs-observed-for-critical-screenconnect-vulnerabilities/https://success.trendmicro.com/dcx/s/solution/000296805?language=en_US&sfdcIFrameOrigin=null

[9] https://www.connectwise.com/company/trust/security-bulletins/connectwise-screenconnect-23.9.8

[10] https://socradar.io/critical-vulnerabilities-in-connectwise-screenconnect-postgresql-jdbc-and-vmware-eap-cve-2024-1597-cve-2024-22245/

[11] https://www.trendmicro.com/en_us/research/24/b/threat-actor-groups-including-black-basta-are-exploiting-recent-.html

[12] https://otx.alienvault.com/indicator/ip/185.62.58.132

[13] https://www.virustotal.com/gui/ip-address/185.62.58.132/community

[14] https://www.virustotal.com/gui/ip-address/108.61.210.72/community

[15] https://otx.alienvault.com/indicator/ip/108.61.210.72

[16] https://www.virustotal.com/gui/ip-address/116.0.56[.]101/community

[17] https://otx.alienvault.com/indicator/ip/116.0.56[.]101

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About the author
Justin Torres
Cyber Analyst
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