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Amadey Info-Stealer: Exploiting N-Day Vulnerabilities to Launch Information Stealing Malware

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22
Mar 2023
22
Mar 2023
Amadey Info-stealer malware was detected across over 30 customers between August and December 2022, spanning various regions and industry verticals. This blog highlights the resurgence of Malware as a Service (MaaS) and the leveraging of existing N-Day vulnerabilities in SmokeLoader campaigns to launch Amadey on customers’ networks. This investigation was part of Darktrace’s continuous Threat Research work in efforts to identify and contextualize threats across the Darktrace fleet, building off of AI insights through collaborative human analysis.

The continued prevalence of Malware as a Service (MaaS) across the cyber threat landscape means that even the most inexperienced of would-be malicious actors are able to carry out damaging and wide-spread cyber-attacks with relative ease. Among these commonly employed MaaS are information stealers, or info-stealers, a type of malware that infects a device and attempts to gather sensitive information before exfiltrating it to the attacker. Info-stealers typically target confidential information, such as login credentials and bank details, and attempt to lie low on a compromised device, allowing access to sensitive data for longer periods of time. 

It is essential for organizations to have efficient security measures in place to defend their networks from attackers in an increasing versatile and accessible threat landscape, however incident response alone is not enough. Having an autonomous decision maker able to not only detect suspicious activity, but also take action against it in real time, is of the upmost importance to defend against significant network compromise. 

Between August and December 2022, Darktrace detected the Amadey info-stealer on more than 30 customer environments, spanning various regions and industry verticals across the customer base. This shows a continual presence and overlap of info-stealer indicators of compromise (IOCs) across the cyber threat landscape, such as RacoonStealer, which we discussed last November (Part 1 and Part 2).

Background on Amadey

Amadey Bot, a malware that was first discovered in 2018, is capable of stealing sensitive information and installing additional malware by receiving commands from the attacker. Like other malware strains, it is being sold in illegal forums as MaaS starting from $500 USD [1]. 

Researchers at AhnLab found that Amadey is typically distributed via existing SmokeLoader loader malware campaigns. Downloading cracked versions of legitimate software causes SmokeLoader to inject malicious payload into Windows Explorer processes and proceeds to download Amadey.  

The botnet has also been used for distributed denial of service (DDoS) attacks, and as a vector to install malware spam campaigns, such as LockBit 3.0 [2]. Regardless of the delivery techniques, similar patterns of activity were observed across multiple customer environments. 

Amadey’s primary function is to steal information and further distribute malware. It aims to extract a variety of information from infected devices and attempts to evade the detection of security measures by reducing the volume of data exfiltration compared to that seen in other malicious instances.

Darktrace DETECT/Network™ and its built-in features, such as Wireshark Packet Captures (PCAP), identified Amadey activity on customer networks, whilst Darktrace RESPOND/Network™ autonomously intervened to halt its progress.

Attack Details

Figure 1: Timeline of Amadey info-stealer kill chain.

Initial Access  

User engagement with malicious email attachments or cracked software results in direct execution of the SmokeLoader loader malware on a device. Once the loader has executed its payload, it is then able to download additional malware, including the Amadey info-stealer.

Unusual Outbound Connections 

After initial access by the loader and download of additional malware, the Amadey info-stealer captures screenshots of network information and sends them to Amadey command and control (C2) servers via HTTP POST requests with no GET to a .php URI. An example of this can be seen in Figure 2.  

Figure 2: PCAP from an affected customer showing screenshots being sent out to the Amadey C2 server via a .jpg file. 

C2 Communications  

The infected device continues to make repeated connections out to this Amadey endpoint. Amadey's C2 server will respond with instructions to download additional plugins in the form of dynamic-link libraries (DLLs), such as "/Mb1sDv3/Plugins/cred64.dll", or attempt to download secondary info-stealers such as RedLine or RaccoonStealer. 

Internal Reconnaissance 

The device downloads executable and DLL files, or stealer configuration files to steal additional network information from software including RealVNC and Outlook. Most compromised accounts were observed downloading additional malware following commands received from the attacker.

Data Exfiltration 

The stolen information is then sent out via high volumes of HTTP connection. It makes HTTP POSTs to malicious .php URIs again, this time exfiltrating more data such as the Amadey version, device names, and any anti-malware software installed on the system.

How did the attackers bypass the rest of the security stack?

Existing N-Day vulnerabilities are leveraged to launch new attacks on customer networks and potentially bypass other tools in the security stack. Additionally, exfiltrating data via low and slow HTTP connections, rather than large file transfers to cloud storage platforms, is an effective means of evading the detection of traditional security tools which often look for large data transfers, sometimes to a specific list of identified “bad” endpoints.

Darktrace Coverage 

Amadey activity was autonomously identified by DETECT and the Cyber AI Analyst. A list of DETECT models that were triggered on deployments during this kill chain can be found in the Appendices. 

Various Amadey activities were detected and highlighted in DETECT model breaches and their model breach event logs. Figure 3 shows a compromised device making suspicious HTTP POST requests, causing the ‘Anomalous Connection / Posting HTTP to IP Without Hostname’ model to breach. It also downloaded an executable file (.exe) from the same IP.

Figure 3: Amadey activity on a customer deployment captured by model breaches and event logs. 

DETECT’s built-in features also assisted with detecting the data exfiltration. Using the PCAP integration, the exfiltrated data was captured for analysis. Figure 4 shows a connection made to the Amadey endpoint, in which information about the infected device, such as system ID and computer name, were sent. 

Figure 4: PCAP downloaded from Darktrace event logs highlighting data egress to the Amadey endpoint. 

Further information about the infected system can be seen in the above PCAP. As outlined by researchers at Ahnlab and shown in Figure 5, additional system information sent includes the Amadey version (vs=), the device’s admin privilege status (ar=), and any installed anti-malware or anti-virus software installed on the infected environment (av=) [3]. 

Figure 5: AhnLab’s glossary table explaining the information sent to the Amadey C2 server. 

Darktrace’s AI Analyst was also able to connect commonalities between model breaches on a device and present them as a connected incident made up of separate events. Figure 6 shows the AI Analyst incident log for a device having breached multiple models indicative of the Amadey kill chain. It displays the timeline of these events, the specific IOCs, and the associated attack tactic, in this case ‘Command and Control’. 

Figure 6: A screenshot of multiple IOCs and activity correlated together by AI Analyst. 

When enabled on customer’s deployments, RESPOND was able to take immediate action against Amadey to mitigate its impact on customer networks. RESPOND models that breached include: 

  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
  • Antigena / Network / External Threat / Antigena Suspicious File Block 
  • Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach

On one customer’s environment, a device made a POST request with no GET to URI ‘/p84Nls2/index.php’ and unepeureyore[.]xyz. RESPOND autonomously enforced a previously established pattern of life on the device twice for 30 minutes each and blocked all outgoing traffic from the device for 10 minutes. Enforcing a device’s pattern of life restricts it to conduct activity within the device and/or user’s expected pattern of behavior and blocks anything anomalous or unexpected, enabling normal business operations to continue. This response is intended to reduce the potential scale of attacks by disrupting the kill chain, whilst ensuring business disruption is kept to a minimum. 

Figure 7: RESPOND actions taken on a customer deployment to disrupt the Amadey kill chain. 

The Darktrace Threat Research team conducted thorough investigations into Amadey activity observed across the customer base. They were able to identify and contextualize this threat across the fleet, enriching AI insights with collaborative human analysis. Pivoting from AI insights as their primary source of information, the Threat Research team were able to provide layered analysis to confirm this campaign-like activity and assess the threat across multiple unique environments, providing a holistic assessment to customers with contextualized insights.

Conclusion

The presence of the Amadey info-stealer in multiple customer environments highlights the continuing prevalence of MaaS and info-stealers across the threat landscape. The Amadey info-stealer in particular demonstrates that by evading N-day vulnerability patches, threat actors routinely launch new attacks. These malicious actors are then able to evade detection by traditional security tools by employing low and slow data exfiltration techniques, as opposed to large file transfers.

Crucially, Darktrace’s AI insights were coupled with expert human analysis to detect, respond, and provide contextualized insights to notify customers of Amadey activity effectively. DETECT captured Amadey activity taking place on customer deployments, and where enabled, RESPOND’s autonomous technology was able to take immediate action to reduce the scale of such attacks. Finally, the Threat Research team were in place to provide enhanced analysis for affected customers to help security teams future-proof against similar attacks.

Appendices

Darktrace Model Detections 

Anomalous File / EXE from Rare External Location

Device / Initial Breach Chain Compromise

Anomalous Connection / Posting HTTP to IP Without Hostname 

Anomalous Connection / POST to PHP on New External Host

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname 

Compromise / Beaconing Activity To External Rare

Compromise / Slow Beaconing Activity To External Rare

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

List of IOCs

f0ce8614cc2c3ae1fcba93bc4a8b82196e7139f7 - SHA1 - Amadey DLL File Hash

e487edceeef3a41e2a8eea1e684bcbc3b39adb97 - SHA1 - Amadey DLL File Hash

0f9006d8f09e91bbd459b8254dd945e4fbae25d9 - SHA1 - Amadey DLL File Hash

4069fdad04f5e41b36945cc871eb87a309fd3442 - SHA1 - Amadey DLL File Hash

193.106.191[.]201 - IP - Amadey C2 Endpoint

77.73.134[.]66 - IP - Amadey C2 Endpoint

78.153.144[.]60 - IP - Amadey C2 Endpoint

62.204.41[.]252 - IP - Amadey C2 Endpoint

45.153.240[.]94 - IP - Amadey C2 Endpoint

185.215.113[.]204 - IP - Amadey C2 Endpoint

85.209.135[.]11 - IP - Amadey C2 Endpoint

185.215.113[.]205 - IP - Amadey C2 Endpoint

31.41.244[.]146 - IP - Amadey C2 Endpoint

5.154.181[.]119 - IP - Amadey C2 Endpoint

45.130.151[.]191 - IP - Amadey C2 Endpoint

193.106.191[.]184 - IP - Amadey C2 Endpoint

31.41.244[.]15 - IP - Amadey C2 Endpoint

77.73.133[.]72 - IP - Amadey C2 Endpoint

89.163.249[.]231 - IP - Amadey C2 Endpoint

193.56.146[.]243 - IP - Amadey C2 Endpoint

31.41.244[.]158 - IP - Amadey C2 Endpoint

85.209.135[.]109 - IP - Amadey C2 Endpoint

77.73.134[.]45 - IP - Amadey C2 Endpoint

moscow12[.]at - Hostname - Amadey C2 Endpoint

moscow13[.]at - Hostname - Amadey C2 Endpoint

unepeureyore[.]xyz - Hostname - Amadey C2 Endpoint

/fb73jc3/index.php - URI - Amadey C2 Endpoint

/panelis/index.php - URI - Amadey C2 Endpoint

/panelis/index.php?scr=1 - URI - Amadey C2 Endpoint

/panel/index.php - URI - Amadey C2 Endpoint

/panel/index.php?scr=1 - URI - Amadey C2 Endpoint

/panel/Plugins/cred.dll - URI - Amadey C2 Endpoint

/jg94cVd30f/index.php - URI - Amadey C2 Endpoint

/jg94cVd30f/index.php?scr=1 - URI - Amadey C2 Endpoint

/o7Vsjd3a2f/index.php - URI - Amadey C2 Endpoint

/o7Vsjd3a2f/index.php?scr=1 - URI - Amadey C2 Endpoint

/o7Vsjd3a2f/Plugins/cred64.dll - URI - Amadey C2 Endpoint

/gjend7w/index.php - URI - Amadey C2 Endpoint

/hfk3vK9/index.php - URI - Amadey C2 Endpoint

/v3S1dl2/index.php - URI - Amadey C2 Endpoint

/f9v33dkSXm/index.php - URI - Amadey C2 Endpoint

/p84Nls2/index.php - URI - Amadey C2 Endpoint

/p84Nls2/Plugins/cred.dll - URI - Amadey C2 Endpoint

/nB8cWack3/index.php - URI - Amadey C2 Endpoint

/rest/index.php - URI - Amadey C2 Endpoint

/Mb1sDv3/index.php - URI - Amadey C2 Endpoint

/Mb1sDv3/index.php?scr=1 - URI - Amadey C2 Endpoint

/Mb1sDv3/Plugins/cred64.dll  - URI - Amadey C2 Endpoint

/h8V2cQlbd3/index.php - URI - Amadey C2 Endpoint

/f5OknW/index.php - URI - Amadey C2 Endpoint

/rSbFldr23/index.php - URI - Amadey C2 Endpoint

/rSbFldr23/index.php?scr=1 - URI - Amadey C2 Endpoint

/jg94cVd30f/Plugins/cred64.dll - URI - Amadey C2 Endpoint

/mBsjv2swweP/Plugins/cred64.dll - URI - Amadey C2 Endpoint

/rSbFldr23/Plugins/cred64.dll - URI - Amadey C2 Endpoint

/Plugins/cred64.dll - URI - Amadey C2 Endpoint

Mitre Attack and Mapping 

Collection:

T1185 - Man the Browser

Initial Access and Resource Development:

T1189 - Drive-by Compromise

T1588.001 - Malware

Persistence:

T1176 - Browser Extensions

Command and Control:

T1071 - Application Layer Protocol

T1071.001 - Web Protocols

T1090.002 - External Proxy

T1095 - Non-Application Layer Protocol

T1571 - Non-Standard Port

T1105 - Ingress Tool Transfer

References 

[1] https://malpedia.caad.fkie.fraunhofer.de/details/win.amadey

[2] https://asec.ahnlab.com/en/41450/

[3] https://asec.ahnlab.com/en/36634/

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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Zoe Tilsiter
Cyber Analyst
The Darktrace Threat Research Team
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Appleby law firm uses Darktrace and Microsoft for proactive cyber resilience and compliance

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02
May 2024

Security Challenges for Appleby law firm

Appleby is an international law firm that provides offshore legal advice to clients. As such, assuring confidentiality is one of our priorities. I regularly discuss cybersecurity with our clients and prospects who want to know that their data will be protected.

Like all security teams, we are working to keep ahead of the evolving cyber threat landscape while also managing our internal tools and infrastructure.

Although we already applied security philosophies like defense-in-depth and multi-tiered protection, we wanted to expand our coverage especially given the increase in working from home. These improvements would be especially impactful given our lean security team, which must provide 24/7 coverage for our 10 offices around the globe that span several jurisdictions and time zones.

Given these challenges and goals, we turned to Darktrace.

Going beyond an XDR with Darktrace and Microsoft

We wanted to move away from point solutions, and after doing extensive research, we chose to consolidate around Darktrace and Microsoft. This helped us achieve increased coverage, seamless security operations, and even reduced costs.

While considering our upgrade from E3 to E5, we went through an extensive TCO exercise. After reviewing our stack, we were able to sunset legacy tools and consolidate our vendors into an integrated and cost-efficient modern platform built around Darktrace and Microsoft. We now have a single portal to manage security for all our coverage areas, improving upon what we had with our legacy eXtended Detection and Response (XDR) tool.

Darktrace’s AI-led understanding of our business operations, people, processes, and technology has helped us automate so our small team can easily achieve continuous detection, investigation, and response across our systems. This has helped us save time and overcome resource limitations, giving us comprehensive cyber resilience and new opportunities to move past firefighting to take proactive measures that harden our environment.

Darktrace and Microsoft have allowed us to simplify workflows and reduce costs without compromising security. In fact, it’s now stronger than ever.

Proactive protection with Darktrace PREVENT/Attack Surface Management™

I come from a physical security background, so I’ve always been keen on the prevention side. You would always rather prevent somebody from entering in the first place than deal with them once they are inside. With that mindset, we’re pushing our strongest controls to the boundary to stop threat actors before they gain access to our systems.

To help us with that, we use Darktrace PREVENT/Attack Surface Management™ (ASM). With just our brand name, it was able to reveal our entire attack surface, including shadow IT we didn’t know was there. PREVENT/ASM continuously monitors our exposures with AI and reports its findings to my team with actionable insights that contain key metrics and prioritizations based on critical risk. This enables us to maximize our impact with limited time and resources.

PREVENT/ASM has already identified typo squatting domains that threat actors set up to impersonate our brand in phishing attacks. Finding this type of brand abuse not only defends our company from attackers who could damage our reputation, but also protects our clients and vendors who could be targeted with these imitations. PREVENT/ASM even collects the necessary data needed for my team to file a Notice and Takedown order.

In addition to finding vulnerabilities such as brand abuse, PREVENT/ASM integrates with our other Darktrace products to give us platform-wide coverage. This is key because an attacker will never hit only one point, they’re going to hit a sequence of targets to try to get in.

Now, we can easily understand vulnerabilities and attacks because of the AI outputs flowing across the Darktrace platform as part of the comprehensive, interconnected system. I have already made a practice of seeing an alert in Darktrace DETECT/Network and clicking through to the PREVENT/ASM interface to get more context.

Achieving compliance standards for our clients

We work hard to ensure confidentiality for our clients and prospects and we also frequently work with regulated entities, so we must demonstrate that we have controls in place.

With Darktrace in our security stack, we have 24/7 coverage and can provide evidence of how autonomous responses have successfully blocked malicious activity in the past. When I have demonstrated how Darktrace works to regulators, it ticks several of their boxes. Our Darktrace coverage has been critical in helping us achieve ISO27001 compliance, the world’s best-known standard for information security management systems.

Darktrace continues to prove its value. Last year, we brought a red team into our office for penetration testing. As soon as the first tester plugged into our network, Darktrace shut him out. We spent hours clearing the alerts and blocks to let the red team continue working, which validated that Darktrace stopped them at every step.

The red team reported that our controls are effective and even in the top 10% of all companies they had ever tested. That feedback, when presented to ISO auditors, regulators, and clients, immediately answers a lot of their more arduous questions and concerns.

Darktrace helps us meet compliance frameworks while reassuring both my team and our clients that our digital infrastructure is safe.

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About the author
Michael Hughes
CISO, Appleby (guest contributor)

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Inside the SOC

Detecting Attacks Across Email, SaaS, and Network Environments with Darktrace’s AI Platform Approach

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30
Apr 2024

The State of AI in Cybersecurity

In a recent survey outlined in Darktrace’s State of AI Cyber Security whitepaper, 95% of cyber security professionals agree that AI-powered security solutions will improve their organization’s detection of cyber-threats [1]. Crucially, a combination of multiple AI methods is the most effective to improve cybersecurity; improving threat detection, accelerating threat investigation and response, and providing visibility across an organization’s digital environment.

In March 2024, Darktrace’s AI-led security platform was able to detect suspicious activity affecting a customer’s email, Software-as-a-Service (SaaS), and network environments, whilst its applied supervised learning capability, Cyber AI Analyst, autonomously correlated and connected all of these events together in one single incident, explained concisely using natural language processing.

Attack Overview

Following an initial email attack vector, an attacker logged into a compromised SaaS user account from the Netherlands, changed inbox rules, and leveraged the account to send thousands of phishing emails to internal and external users. Internal users fell victim to the emails by clicking on contained suspicious links that redirected them to newly registered suspicious domains hosted on same IP address as the hijacked SaaS account login. This activity triggered multiple alerts in Darktrace DETECT™ on both the network and SaaS side, all of which were correlated into one Cyber AI Analyst incident.

In this instance, Darktrace RESPOND™ was not active on any of the customer’s environments, meaning the compromise was able to escalate until their security team acted on the alerts raised by DETECT. Had RESPOND been enabled at the time of the attack, it would have been able to apply swift actions to contain the attack by blocking connections to suspicious endpoints on the network side and disabling users deviating from their normal behavior on the customer’s SaaS environment.

Nevertheless, thanks to DETECT and Cyber AI Analyst, Darktrace was able to provide comprehensive visibility across the customer’s three digital estate environments, decreasing both investigation and response time which enabled them to quickly enact remediation during the attack. This highlights the crucial role that Darktrace’s combined AI approach can play in anomaly detection cyber defense

Attack Details & Darktrace Coverage

Attack timeline

1. Email: the initial attack vector  

The initial attack vector was likely email, as on March 18, 2024, Darktrace observed a user device making several connections to the email provider “zixmail[.]net”, shortly before it connected to the first suspicious domain. Darktrace/Email identified multiple unusual inbound emails from an unknown sender that contained a suspicious link. Darktrace recognized these emails as potentially malicious and locked the link, ensuring that recipients could not directly click it.

Suspected initial compromise email from an unknown sender, containing a suspicious link, which was locked by Darktrace/Email.
Figure 1: Suspected initial compromise email from an unknown sender, containing a suspicious link, which was locked by Darktrace/Email.

2. Escalation to Network

Later that day, despite Darktrace/Email having locked the link in the suspicious email, the user proceeded to click on it and was directed to a suspicious external location, namely “rz8js7sjbef[.]latovafineart[.]life”, which triggered the Darktrace/Network DETECT model “Suspicious Domain”. Darktrace/Email was able to identify that this domain had only been registered 4 days before this activity and was hosted on an IP address based in the Netherlands, 193.222.96[.]9.

3. SaaS Account Hijack

Just one minute later, Darktrace/Apps observed the user’s Microsoft 365 account logging into the network from the same IP address. Darktrace understood that this represented unusual SaaS activity for this user, who had only previously logged into the customer’s SaaS environment from the US, triggering the “Unusual External Source for SaaS Credential Use” model.

4. SaaS Account Updates

A day later, Darktrace identified an unusual administrative change on the user’s Microsoft 365 account. After logging into the account, the threat actor was observed setting up a new multi-factor authentication (MFA) method on Microsoft Authenticator, namely requiring a 6-digit code to authenticate. Darktrace understood that this authentication method was different to the methods previously used on this account; this, coupled with the unusual login location, triggered the “Unusual Login and Account Update” DETECT model.

5. Obfuscation Email Rule

On March 20, Darktrace detected the threat actor creating a new email rule, named “…”, on the affected account. Attackers are typically known to use ambiguous or obscure names when creating new email rules in order to evade the detection of security teams and endpoints users.

The parameters for the email rule were:

“AlwaysDeleteOutlookRulesBlob: False, Force: False, MoveToFolder: RSS Feeds, Name: ..., MarkAsRead: True, StopProcessingRules: True.”

This rule was seemingly created with the intention of obfuscating the sending of malicious emails, as the rule would move sent emails to the "RSS Feeds” folder, a commonly used tactic by attackers as the folder is often left unchecked by endpoint users. Interestingly, Darktrace identified that, despite the initial unusual login coming from the Netherlands, the email rule was created from a different destination IP, indicating that the attacker was using a Virtual Private Network (VPN) after gaining a foothold in the network.

Hijacked SaaS account making an anomalous login from the unusual Netherlands-based IP, before creating a new email rule.
Figure 2: Hijacked SaaS account making an anomalous login from the unusual Netherlands-based IP, before creating a new email rule.

6. Outbound Phishing Emails Sent

Later that day, the attacker was observed using the compromised customer account to send out numerous phishing emails to both internal and external recipients. Darktrace/Email detected a significant spike in inbound emails on the compromised account, with the account receiving bounce back emails or replies in response to the phishing emails. Darktrace further identified that the phishing emails contained a malicious DocSend link hidden behind the text “Click Here”, falsely claiming to be a link to the presentation platform Prezi.

Figure 3: Darktrace/Email detected that the DocSend link displayed via text “Click Here”, was embedded in a Prezi link.
Figure 3: Darktrace/Email detected that the DocSend link displayed via text “Click Here”, was embedded in a Prezi link.

7. Suspicious Domains and Redirects

After the phishing emails were sent, multiple other internal users accessed the DocSend link, which directed them to another suspicious domain, “thecalebgroup[.]top”, which had been registered on the same day and was hosted on the aforementioned Netherlands-based IP, 193.222.96[.]91. At the time of the attack, this domain had not been reported by any open-source intelligence (OSINT), but it has since been flagged as malicious by multiple vendors [2].

External Sites Summary showing the suspicious domain that had never previously been seen on the network. A total of 11 “Suspicious Domain” models were triggered in response to this activity.
Figure 4: External Sites Summary showing the suspicious domain that had never previously been seen on the network. A total of 11 “Suspicious Domain” models were triggered in response to this activity.  

8. Cyber AI Analyst’s Investigation

As this attack was unfolding, Darktrace’s Cyber AI Analyst was able to autonomously investigate the events, correlating them into one wider incident and continually adding a total of 14 new events to the incident as more users fell victim to the phishing links.

Cyber AI Analyst successfully weaved together the initial suspicious domain accessed in the initial email attack vector (Figure 5), the hijack of the SaaS account from the Netherlands IP (Figure 6), and the connection to the suspicious redirect link (Figure 7). Cyber AI Analyst was also able to uncover other related activity that took place at the time, including a potential attempt to exfiltrate data out of the customer’s network.

By autonomously analyzing the thousands of connections taking place on a network at any given time, Darktrace’s Cyber AI Analyst is able to detect seemingly separate anomalous events and link them together in one incident. This not only provides organizations with full visibility over potential compromises on their networks, but also saves their security teams precious time ensuring they can quickly scope out the ongoing incident and begin remediation.

Figure 5: Cyber AI Analyst correlated the attack’s sequence, starting with the initial suspicious domain accessed in the initial email attack vector.
Figure 5: Cyber AI Analyst correlated the attack’s sequence, starting with the initial suspicious domain accessed in the initial email attack vector.
Figure 6: As the attack progressed, Cyber AI Analyst correlated and appended additional events to the same incident, including the SaaS account hijack from the Netherlands-based IP.
Figure 6: As the attack progressed, Cyber AI Analyst correlated and appended additional events to the same incident, including the SaaS account hijack from the Netherlands-based IP.
Cyber AI Analyst correlated and appended additional events to the same incident, including additional users connecting to the suspicious redirect link following the outbound phishing emails being sent.
Figure 7: Cyber AI Analyst correlated and appended additional events to the same incident, including additional users connecting to the suspicious redirect link following the outbound phishing emails being sent.

Conclusion

In this scenario, Darktrace demonstrated its ability to detect and correlate suspicious activities across three critical areas of a customer’s digital environment: email, SaaS, and network.

It is essential that cyber defenders not only adopt AI but use a combination of AI technology capable of learning and understanding the context of an organization’s entire digital infrastructure. Darktrace’s anomaly-based approach to threat detection allows it to identify subtle deviations from the expected behavior in network devices and SaaS users, indicating potential compromise. Meanwhile, Cyber AI Analyst dynamically correlates related events during an ongoing attack, providing organizations and their security teams with the information needed to respond and remediate effectively.

Credit to Zoe Tilsiter, Analyst Consulting Lead (EMEA), Brianna Leddy, Director of Analysis

Appendices

References

[1] https://darktrace.com/state-of-ai-cyber-security

[2] https://www.virustotal.com/gui/domain/thecalebgroup.top

Darktrace DETECT Model Coverage

SaaS Models

- SaaS / Access / Unusual External Source for SaaS Credential Use

- SaaS / Compromise / Unusual Login and Account Update

- SaaS / Compliance / Anomalous New Email Rule

- SaaS / Compromise / Unusual Login and New Email Rule

Network Models

- Device / Suspicious Domain

- Multiple Device Correlations / Multiple Devices Breaching Same Model

Cyber AI Analyst Incidents

- Possible Hijack of Office365 Account

- Possible SSL Command and Control

Indicators of Compromise (IoCs)

IoC – Type – Description

193.222.96[.]91 – IP – Unusual Login Source

thecalebgroup[.]top – Domain – Possible C2 Endpoint

rz8js7sjbef[.]latovafineart[.]life – Domain – Possible C2 Endpoint

https://docsend[.]com/view/vcdmsmjcskw69jh9 - Domain - Phishing Link

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About the author
Zoe Tilsiter
Cyber Analyst
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