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How Darktrace’s SOC Helped Thwart a BEC Attack in its Early Stages

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18
Jul 2023
18
Jul 2023
This blog details how Darktrace detected a case of Business Email Compromise (BEC) on a customer network. Darktrace’s SOC was able to alert the customer to the ongoing compromise within their SaaS environment, thwarting the attack in its tracks.

What is Business Email Compromise (BEC)?

Business Email Compromise (BEC) is the practice of tricking an organization into transferring funds or sensitive data to a malicious actor.

Although at face value this type of attack may not carry the same gravitas as the more blockbuster, cloak-and-dagger type of attack such as ransomware [1], the costs of BEC actually dwarf that of ransomware [2]. Moreover, among UK organizations that reported a cyber breach in 2023, attacks related to BEC – namely phishing attacks, email impersonation, attempted hacking of online back accounts, and account takeover – were reported as the most disruptive, ahead of ransomware and other types of cyber-attack [3].  

What makes a BEC attack successful?

BEC attacks are so successful and damaging due to the difficulty of detection for traditional security systems, along with their ease of execution.  BEC does not require much technical sophistication to accomplish; rather, it exploits humans’ natural trust in known correspondents, via a phishing email for example, to induce them to perform a certain action.

How does a BEC attack work?

BEC attacks typically begin with a phishing email to an employee of an organization. Traditional email gateways may be unable to block the initial phishing email, as the email often appear to have been sent by a known correspondent, or it may contain minimal payload content.

The recipient’s interaction with the initial phishing email will likely result in the attacker gaining access to the user’s identity. Once access is obtained, the attacker may abuse the identity of the compromised user to obtain details of the user’s financial relations to the rest of the organization or its customers, eventually using these details to conduct further malicious email activity, such as sending out emails containing fraudulent wire transfer requests.  Today, the continued growth in adoption of services to support remote working, such as cloud file storage and sharing, means that the compromise of a single user’s email account can also grant access to a wide range of corporate sensitive information.

How to protect against BEC attacks

The rapid uptake of cloud-based infrastructure and software-as-a-service (SaaS) outpaces the adoption of skills and expertise required to secure it, meaning that security teams are often less prepared to detect and respond to cloud-based attacks.  

Alongside the adoption of security measures that specialize in anomaly-based detection and autonomous response, like Darktrace DETECT™ and Darktrace RESPOND™, it is extremely beneficial for organizations to have an around the clock security operations center (SOC) in place to monitor and investigate ongoing suspicious activity as it emerges.

In June 2023, Darktrace’s SOC alerted a customer to an active BEC attack within their cloud environment, following the successful detection of suspicious activity by Darktrace’s AI, playing a fundamental role in thwarting the attack in its early stages.

Darktrace Mitigates BEC Attack

Figure 1: Screenshot of the SaaS Console showing location information for the compromised SaaS account.  The ability to visualize the distance between these two locations enables a SOC Analyst to deduce that the simultaneous activity from London and Derby may represent impossible travel’.

It was suspected the attack began with a phishing email, as on the previous day the user had received a highly anomalous email from an external sender with which the organization had not previously communicated. However, the customer had configured Darktrace/Email™ in passive mode, which meant that Darktrace was not able to carry out any RESPOND actions on this anomalous email to prevent it from landing in the user’s inbox. Despite this, Darktrace/Apps was able to instantly detect the subsequent unusual login to the customer’s SaaS environment; its anomaly-based approach to threat detection allowed it to recognize the anomalous behavior even though the malicious email had successfully reached the user.

Following the anomalous ExpressVPN login, Darktrace detected further account anomalies originating from another ExpressVPN IP (45.92.229[.]195), as the attacker accessed files over SharePoint.  Notably, Darktrace identified that the logins from ExpressVPN IPs were performed with the software Chrome 114, however, activity from the legitimate account owner prior to these unusual logins was performed using the software Chrome 102. It is unusual for a user to be using multiple browser versions simultaneously, therefore in addition to the observed impossible travel, this further implied the presence of different actors behind the simultaneous account activity.

Figure 2: Screenshot of the Event Log for the compromised SaaS account, showing simultaneous login and file access activity on the account from different browser versions, and thus likely from different devices.

Darktrace identified that the files observed during this anomalous activity referenced financial information and personnel schedules, suggesting that the attacker was performing internal reconnaissance to gather information about sensitive internal company procedures, in preparation for further fraudulent financial activity.

Although the actions taken by the attacker were mostly passive, Darktrace/Apps chained together the multiple anomalies to understand that this pattern of activity was indicative of movement along the cyber kill chain. The multiple model breaches generated by the ongoing unusual activity triggered an Enhanced Monitoring model breach that was escalated to Darktrace’s SOC as the customer had subscribed to Darktrace’s Proactive Threat Notification (PTN) service.  Enhanced Monitoring models detect activities that are more likely to be indicative of compromise.  

Subsequently, Darktrace’s SOC triaged the activity detected on the SaaS account and sent a PTN alert to the customer, advising urgent follow up action.  The encrypted alert contained relevant technical details of the incident that were summarized by an expert Darktrace Analyst, along with recommendations to the customer’s internal SOC team to take immediate action.  Upon receipt and validation of the alert, the customer used Darktrace RESPOND to perform a manual force logout and block access from the external ExpressVPN IP.

Had Darktrace RESPOND been enabled in autonomous response mode, it would have immediately taken action to disable the account after ongoing anomalies were detected from it. However, as the customer only had RESPOND configured in the manual human confirmation model, the expertise of Darktrace’s SOC team was critical in enabling the customer to react and prevent further escalation of post-compromise activity.  Evidence of further attempts to access the compromised account were observed hours after RESPOND actions were taken, including failed login attempts from another rare external IP, this time associated with the VPN service NordVPN.

Figure 3: Timeline of attack and response actions from Darktrace SOC and Darktrace RESPOND.

Because the customer had subscribed to Darktrace’s PTN service, they were able to further leverage the expertise of Darktrace’s global team of cyber analysts and request further analysis of which files were accessed by the legitimate account owner versus the attacker.  This information was shared securely within the same Customer Portal ticket that was automatically opened on behalf of the customer when the PTN was alerted, allowing the customer’s security team to submit further queries and feedback, and request assistance to further investigate this alert within Darktrace. A similar service called Ask the Expert (ATE) exists for customers to draw from the expertise of Darktrace’s analysts at any time, not just when PTNs are alerted.

Conclusion

The growing prevalence and impact of BEC attacks amid the shift to cloud-based infrastructure means that already stretched internal security teams may not have the sufficient human capacity to detect and respond to these threats.

Darktrace’s round-the-clock SOC thwarted a BEC attack that had the potential to result in significant financial and reputational damage to the legal services company, by alerting the customer to high priority activity during the early stages of the attack and sharing actionable insights that the customer could use to prevent further escalation.  Following the confirmed compromise, the support and in-depth analysis provided by Darktrace’s SOC on the files accessed by the attacker enabled the customer to effectively report this breach to the Information Commissioner’s Office, to maintain compliance with UK data protection regulations. [4].  

Although the attacker used IP addresses that were local to the customer’s country of operations and did not perform overtly noisy actions during reconnaissance, Darktrace was able to identify that this activity deviated from the legitimate user’s typical pattern of life, triggering model breaches at each stage of the attack as it progressed from initial access to internal reconnaissance. While Darktrace RESPOND triggered an action that would have prevented the attack autonomously, the customer’s configuration meant that Darktrace’s SOC had an even more significant role in alerting the customer directly to take manual action.

Credit to: Sam Lister, Senior Analyst, for his contributions to this blog.

Appendices

Darktrace DETECT/Apps Models Breached:

  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active
  • SaaS / Unusual Activity / Activity from Multiple Unusual IPs
  • SaaS / Unusual Activity / Multiple Unusual SaaS Activities
  • SaaS / Access / Suspicious Login Attempt
  • SaaS / Compromise / SaaS Anomaly Following Anomalous Login (Enhanced Monitoring Model)

Darktrace RESPOND/Apps Models Breached:

  • Antigena / SaaS / Antigena Unusual Activity Block
  • Antigena / SaaS / Antigena Suspicious SaaS Activity Block

MITRE ATT&CK Mapping

Tactic Techniques
Reconnaissance • T1598 – Phishing for Information
Initial Access • T1078.004 – Valid Accounts: Cloud Accounts
Collection • T1213.002 – Data from Information Repositories: Sharepoint

References

[1] Rand, D. (2022, November 10). Why Business Email Compromise Costs Companies More Than Ransomware Attacks. Retrieved from Tanium: https://www.tanium.com/blog/whybusiness-email-compromise-costs-companies-more-than-ransomware-attacks/

[2] Federal Bureau of Investigation. (2022). 2022 IC3 Report. Retrieved from IC3.gov: https://www.ic3.gov/Media/PDF/AnnualReport/2022_IC3Report.pdf

[3] Department for Science, Innovation & Technology. (2023, April 19). Cyber security breaches survey 2023. Retrieved from gov.uk: https://www.gov.uk/government/statistics/cyber-security-breaches-survey-2023/cybersecurity-breaches-survey-2023

[4] ICO. (2023). Personal data breaches: a guide. Retrieved from Information Commissioner's Office: https://ico.org.uk/for-organisations/report-a-breach/personal-data-breach/personal-data-breaches-a-guide/#whatbreachesdo

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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Nicole Wong
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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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Justin Torres
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