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August 7, 2023

Detection of an Evasive Credential Harvester | IPFS Phishing

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07
Aug 2023
Discover the emerging trend of malicious actors abusing the Interplanetary File System (IPFS) file storage protocol in phishing campaigns. Learn more here!

IPFS Phishing Attacks

Phishing attacks continue to be one of the most common methods of infiltration utilized by threat actors and they represent a significant threat to an organization’s digital estate. As phishing campaigns typically leverage social engineering methods to evade security tools and manipulate users into following links, downloading files, or divulging confidential information. It is a relatively low effort but high-yield type of cyber-attack.

That said, in recent years security teams have become increasingly savvy to these efforts. Attackers are having to adapt and come up with novel ways to carry out their phishing campaigns. Recently, Darktrace has observed a rise in phishing attacks attempting to abuse the InterPlanetary File System (IPFS) in campaigns that are able to dynamically adapt depending on the target, making it extremely difficult for security vendors to detect and investigate.

What is a IPFS?

IPFS is a file storage protocol a peer-to-peer (P2P) network used for storing and sharing resources in a distributed file system [1]. It is also a file storage system similar in nature to other centralized file storage services like Dropbox and Google Drive.

File storage systems, like IPFS, are often abused by malicious actors, as they allow attackers to easily host their own content without maintaining infrastructure themselves. However, as these file storage systems often have legitimate usages, blocking everything related to file storages may cause unwanted problems and affect normal business operations. Thus, the challenge lies in differentiating between legitimate and malicious usage.

While centralized, web-based file storage services use a Client-Server model and typically deliver files over HTTP, IPFS uses a Peer-to-Peer model for storing and sharing files, as shown in Figure 1.

Figure 1: (a) shows the Client-Server model that centralized, web-based file storage services use. The resource is available on the server, and the clients access the resource from the server.(b) shows the Peer-to-Peer model that IPFS use. The resources are available on the peers.

To verify the authenticity and integrity of files, IPFS utilizes cryptographic hashes.

A cryptographic hash value is generated using a file’s content upon upload to IPFS. This is used to generate the Content Identifier (CID). IPFS uses Content Addressing as opposed to Location Addressing, and this CID is used to point to a resource in IPFS [4].

When a computer running IPFS requires a particular file, it asks the connected peers if they have the file with a specific hash. If a peer has the file with the matching hash, it will provide it to the requesting computer [1][6].

Taking down content on IPFS is much more difficult compared to centralized file storage hosts, as content is stored on several nodes without a centralized entity, as shown in Figure 2. To take down content from IPFS, it must be removed from all the nodes. Thus, IPFS is prone to being abused for malicious purposes.

Figure 2: When the resource is unavailable on the server for (a), all the clients are unable to access the resource. When the resource is unavailable on one of the peers for (b), the resources are still available on the other peers.

The domains used in these IPFS phishing links are gateways that enable an HTTPS URL to access resources within the distributed IPFS file system.

There are two types of IPFS links, the Path Gateway and Subdomain Gateway [1].

Path Gateways have a fixed domain/host and identifies the IPFS resource through a resource-identifying string in the path. The Path Gateway has the following structure:

•       https://<gateway-host>.tld/ipfs/<CID>/path/to/resource

•       https://<gateway-host>.tld/ipns/<dnslink/ipnsid>/path/to/resource

On the other hand, Subdomain Gateways have a resource-identifying string in the subdomain. Subdomain Gateways have the following structure:

•       https://<cidv1b32>.ipfs.<gateway-host>.tld/path/to/resource

One gateway domain serves the same role as any other, which means attackers can easily change the gateways that are used.

Thus, these link domains involved in these attacks can be much more variable than the ones in traditional file storage attacks, where a centralized service with a single domain is used (e.g., Dropbox, Google Docs), making detecting the malicious use of IPFS extremely challenging for traditional security vendors. Through its anomaly-based approach to threat detection, Darktrace/Email™ is consistently able to identify such tactics and respond to them, preventing malicious actors from abusing file storage systems life IPFS.

IPFS Campaign Details

In several recent examples of IPFS abuse that Darktrace detected on a customer’s network, the apparent end goal was to harvest user credentials. Stolen credentials can be exploited by threat actors to further their attacks on organizations by escalating their privileges within the network, or even sold on the dark web.

Darktrace detected multiple IPFS links sent in malicious emails that contained the victim’s email address. Based on the domain in this email address, users would then be redirected to a fake login page that uses their organizations’ webpage visuals and branding to convince targets to enter their login details, unknowingly compromising their accounts in the process.

Figure 3: The credential harvester changes visuals depending on the victim’s email address specified in the URL.

These IPFS credential harvesting sites use various techniques to evade detection the detection of traditional security tools and prevent further analysis, such as obfuscation by Percent Encoding and Base64 Encoding the code.

There are also other mechanisms put into place to hinder investigation by security teams. For example, some IPFS credential harvester sites investigated by Darktrace did not allow right clicking and certain keystrokes, as a means to make post-attack analysis more difficult.

Figure 4: The code shows that it attempts to prevent certain keystrokes.

In the campaign highlighted in this blog, the following IPFS link was observed:

hxxps://ipfs[.]io/ipfs/QmfDDxLWoLiqFURX6dUZcsHxVBP1ZnM21H5jXGs1ffNxtP?filename=at ob.html#<EmailAddress>

This uses a Path Gateway, as it identifies the IPFS resource through a resource-identifying string in the path. The CID is QmfDDxLWoLiqFURX6dUZcsHxVBP1ZnM21H5jXGs1ffNxtP in this case.

It makes a GET request to image[.]thum[.]io and logo[.]clearbit[.]com as shown in Figure 5. The image[.]thum[.]io is a Free Website Screenshot Generator, that provides real-time screenshot of websites [2]. The logo[.]clearbit[.]com is used to lookup company logos using the domain [3]. These visuals are integrated into the credential harvester site. Figure 6 shows the domain name being extracted from the victim’s email address and used to obtain the visuals.

Figure 5: The GET requests to image[.]thum[.]io and logo[.]clearbit[.].
Figure 6: The code shows that it utilizes the domain name from the victim’s email address to obtain the visuals from logo.clearbit[.]com and image[.]thum.io.

The code reveals the credential POST endpoint as shown in Figure 16. When credentials are submitted, it makes a POST request to this endpoint as shown in Figure 7.

Figure 7: The credential POST endpoint can be seen inside the code.
Figure 8: The Outlook credential harvester will redirect to the real Outlook page when wrong credentials are submitted multiple times.

From the IPFS link alone, it is difficult to determine whether it leads to a malicious endpoint, however Darktrace has consistently identified emails containing these IPFS credential harvesting links as phishing attempts.

Darktrace Coverage

During one case of IPFS abuse detected by Darktrace in March 2023, a threat actor sent malicious emails with the subject “Renew Your E-mail Password” to 55 different recipients at. The sender appeared to be the organization’s administrator and used their internal domain.

Figure 9: Darktrace/Email’s detection of the “Renew Your E-mail Password” emails from “administrator”. These were all sent at 2023.03.21 02:39 UTC.

However, Darktrace recognized that the email did not pass Sender Policy Framework (SPF), and therefore it could not be validated as being sent from the organization’s domain. Darktrace also detected that the email contained a link to “ipfs.io, the official IPFS gateway. This was identified as a spoofing and phishing attempt by Darktrace/Email.

Figure 10: The Darktrace/Email overview tab shows the Anomaly Indicators, History, Association, and Validation information of this sender. It contained a link to “ipfs.io”, and did not pass SPF.

Following the successful identification of the malicious emails, Darktrace RESPOND™ took immediate autonomous action to prevent them from leading to potentially damaging network compromise. For email-based threats, Darktrace RESPOND is able to carry out numerous actions to stop malicious emails and reduce the risk of compromise. In response to this specific incident, RESPOND took multiple preventative actions (as seen in Figure 11), including include lock link, an action that prevents access to URLs deemed as suspicious, send to junk, an action that automatically places emails in the recipient’s junk folder, and hold message, the most severe RESPOND action that prevents malicious emails from reaching the recipients inbox at all.

Figure 11: The Darktrace/Email model tab shows all the models that triggered on the email and the associated RESPOND actions.
Figure 12: The ipfs.io link used in this email contains the recipient’s email address, and has a CID of QmfDDxLWoLiqFURX6dUZcsHxVBP1ZnM21H5jXGs1ffNxtP. It has a Darktrace Domain Rarity Score of 100
Figure 13: The IPFS credential harvester that uses the organization’s website’s visuals.

Further investigation revealed that the IPFS link contained the recipients’ email address, and when clicked led to a credential harvester that utilized the same visuals and branding as the customer’s website.

Concluding Thoughts

Ultimately, despite the various tactics employed threat actors to evade the detection of traditional security tools, Darktrace was able to successfully detect and mitigate these often very fruitful phishing attacks that attempted to abuse the IPFS file storage system.

As file storage platforms like IPFS do have legitimate business uses, blocking traffic related to file storage is likely to negatively impact the day-to-day operations of an organization. The challenge security teams face is to differentiate between malicious and legitimate uses of such services, and only act on malicious cases. As such, it is more important than ever for organizations to have an effective anomaly detection tool in place that is able to identify emerging threats without relying on rules, signatures or previously observed indicators of compromise (IoC).

By leveraging its Self-Learning AI, Darktrace understands what represents expected activity on customer networks and can recognize subtle deviations from expected behavior, that may be indicative of compromise. Then, using its autonomous response capabilities, Darktrace RESPOND is able to instantly and autonomously take action against emerging threats to stop them at the earliest possible stage.

Credit to Ben Atkins, Senior Model Developer for their contribution to this blog.

Appendices

Example IOCs

Type: URL

IOC: hxxps://ipfs[.]io/ipfs/QmfDDxLWoLi qFURX6dUZcsHxVBP1ZnM21H5jXGs

1ffNxtP?filename=atob.html#<Email Address>

Description: Path Gateway link

Type: URL

IOC: hxxps://bafybeibisyerwlu46re6rxrfw doo2ubvucw7yu6zjcfjmn7rqbwcix2 mku.ipfs[.]dweb.link/webn cpmk.htm?bafybeigh77sqswniy74nzyklybstfpkxhsqhpf3qt26nwnh4wf2vv gbdaybafybeigh77sqswniy74nzyklybstfpkxhsqhpf3qt26nwnh4wf2vvgbda y#<EmailAddress>

Description: Subdomain Gateway link

Relevant Darktrace DETECT Models

•       Spoof / Internal Domain from Unexpected Source + New Unknown Link

•       Link / High Risk Link + Low Sender Association

•       Link / New Correspondent Classified Link

•       Link / Watched Link Type

•       Proximity / Phishing + New activity

•       Proximity / Phishing + New Address Known Domain

•       Spoof / Internal Domain from Unexpected Source + High Risk Link

References

[1]    https://docs.ipfs.tech/

[2]    https://www.thum.io/

[3]    https://clearbit.com/logo

[4]    https://filebase.com/blog/ipfs-content-addressing-explained/

[5]    https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/the-attack-of-the-chameleon-phishing-page/

[6]    https://wiki.ipfsblox.com/

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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Lena Yu
Cyber Security Analyst
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November 19, 2024

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

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

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

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

Network Detection and Response protects where others fail to reach

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

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

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

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

Celebrating success in leadership and innovation

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

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

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

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

Darktrace’s pioneering AI approach sets it apart

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

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

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

Within the KuppingerCole report, several standout strengths were listed:

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

Going beyond reactive security

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

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

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

Putting customers first

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

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

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

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

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

References

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

[2] Darktrace's AI Analyst customer fleet data

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

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Gabriel Few-Wiegratz
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November 18, 2024

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Inside the SOC

From Royal to BlackSuit: Understanding the Tactics and Impact of a Sophisticated Ransomware Strain

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What is BlackSuit Ransomware?

Since late 2023, Darktrace has detected BlackSuit ransomware infiltrating multiple customer networks in the US. This ransomware has targeted a wide range of industries, including arts, entertainment, real estate, public administration, defense, and social security.

Emerging in May 2023, BlackSuit is believed to be a spinoff of Royal ransomware due to similarities in code and Conti, and most likely consists of Russian and Eastern European hackers [1]. Recorded Future reported that the ransomware had affected 95 organizations worldwide, though the actual number is likely much higher [2]. While BlackSuit does not appear to focus on any particular sector, it has targeted multiple organizations in the healthcare, education, IT, government, retail and manufacturing industries [3]. Employing double extortion tactics, BlackSuit not only encrypts files but also steals sensitive data to leverage ransom payments.

BlackSuit has demanded over USD 500 million in ransoms, with the highest individual demand reaching USD 60 million [4]. Notable targets include CDK Global, Japanese media conglomerate Kadokawa, multiple educational institutions, Octapharma Plasma, and the government of Brazil [5][6][7][8].

Darktrace’s Coverage of BlackSuit Ransomware Attack

Case 1, November 2023

The earliest attack on a Darktrace customer by BlackSuit was detected at the start of November 2023. The unusual network activity began on a weekend—a time commonly chosen by ransomware groups to increase their chances of success, as many security teams operate with reduced staff. Darktrace identified indicators of the attackers’ presence on the network for almost two weeks, during which a total of 15 devices exhibited suspicious behavior.

The attack commenced with unusual internal SMB (Server Message Block) connections using a compromised service account. An internal device uploaded an executable (zzza.exe) to a domain controller (DC) and shortly after, wrote a script (socks5.ps1) to another device. According to a Cybersecurity Advisory from the CISA (Cybersecurity and Infrastructure Security Agency, US), the script file was a PowerShell reverse proxy [9].

Approximately an hour and a half later, the device to which the script was written exhibited uncommon WMI (Windows Management Instrumentation) activity. Two hours after receiving the executable file, the DC was observed making an outgoing NTLM request, using PowerShell to remotely execute commands, distributing differently named executable files (<PART OF THE CUSTOMER’S NAME>.exe), and controlling services on other devices.

Eighteen hours after the start of the unusual activity, Darktrace detected another device making repeated connections to “mystuff.bublup[.]com”, which the aforementioned CISA Advisory identifies as a domain used by BlackSuit for data exfiltration [9].

About ten minutes after the suspicious executables were distributed across the network, and less than 24 hours after the start of the unusual activity, file encryption began. A total of ten devices were seen appending the “.blacksuit” extension to files saved on other devices using SMB, as well as writing ransom notes (readme.blacksuit.txt). The file encryption lasted less than 20 minutes.

 An example of the contents of a BlackSuit ransom note being written over SMB.
Figure 1: An example of the contents of a BlackSuit ransom note being written over SMB.

During this compromise, external connections to endpoints related to ConnectWise’s ScreenConnect remote management tool were also seen from multiple servers, suggesting that the tool was likely being abused for command-and-control (C2) activity. Darktrace identified anomalous connectivity associated with ScreenConnect was seen up to 11 days after the start of the attack.

10 days after the start of the compromise, an account belonging to a manager was detected adding “.blacksuit” extensions to the customer’s Software-a-Service (SaaS) resources while connecting from 173.251.109[.]106. Six minutes after file encryption began, Darktrace flagged the unusual activity and recommended a block. However, since Autonomous Response mode was not enabled, the customer’s security team needed to manually confirm the action. Consequently, suspicious activity continued for about a week after the initial encryption. This included disabling authentication on the account and an unusual Teams session initiated from the suspicious external endpoint 216.151.180[.]147.

Case 2, February 2024

Another BlackSuit compromise occurred at the start of February 2024, when Darktrace identified approximately 50 devices exhibiting ransomware-related activity in another US customer’s environment. Further investigation revealed that a significant number of additional devices had also been compromised. These devices were outside Darktrace’s purview to the customer’s specific deployment configuration. The threat actors managed to exfiltrate around 4 TB of data.

Initial access to the network was gained via a virtual private network (VPN) compromise in January 2024, when suspicious connections from a Romanian IP address were detected. According to CISA, the BlackSuit group often utilizes the services of initial access brokers (IAB)—actors who specialize in infiltrating networks, such as through VPNs, and then selling that unauthorized access to other threat actors [9]. Other initial access vectors include phishing emails, RDP (Remote Desktop Protocol) compromise, and exploitation of vulnerable public-facing applications.

Similar to the first case, the file encryption began at the end of the working week. During this phase of the attack, affected devices were observed encrypting files on other internal devices using two compromised administrator accounts. The encryption activity lasted for approximately six and a half hours. Multiple alerts were sent to the customer from Darktrace’s Security Operations Centre (SOC) team, who began reviewing the activity within four minutes of the start of the file encryption.

Darktrace’s Cyber AI Analyst clustering together multiple events related to unusual activity on the network, including file encryption over SMB by BlackSuit.
Figure 2: Darktrace’s Cyber AI Analyst clustering together multiple events related to unusual activity on the network, including file encryption over SMB by BlackSuit.
Figure 3: A spike in model alerts on the day when file encryption by BlackSuit was observed in the network.

In this case, the threat actor utilized SystemBC proxy malware for command and control (C2). A domain controller (DC) was seen connecting to 137.220.61[.]94 on the same day the file encryption took place. The DC was also observed connecting to a ProxyScrape domain around the same time, which is related to the SOCKS5 protocol used by SystemBC. During this compromise, RDP, SSH, and SMB were used for lateral movement within the network.

Figure 4: A Cyber AI Analyst investigation alerting to a device on the VPN subnet making suspicious internal SSH connections due to malicious actors moving laterally within the network.

Signs of threat actors potentially being on the network were observed as early as two days prior to the file encryption. This included unusual internal network scanning via multiple protocols (ICMP, SMB, RDP, etc.), credential brute-forcing, SMB access failures, and anonymous SMBv1 sessions. These activities were traced to IP addresses belonging to two desktop devices in the VPN subnet associated with two regular employee user accounts. Threat actors were seemingly able to exploit at least one of these accounts due to LDAP legacy policies being in place on the customer’s environment.

A Cyber AI Analyst incident summary alerting to a device on the VPN subnet conducting internal reconnaissance.
Figure 5: A Cyber AI Analyst incident summary alerting to a device on the VPN subnet conducting internal reconnaissance.
Examples of the proposed Darktrace Autonomous Response actions on the day BlackSuit initiated file encryption.
Figure 6: Examples of the proposed Darktrace Autonomous Response actions on the day BlackSuit initiated file encryption.

Case 3, August 2024

The most recently observed BlackSuit compromise occurred in August 2024, when a device was observed attempting to brute-force the credentials of an IT administrator. This activity continued for 11 days.

Once the admin’s account was successfully compromised, network scanning, unusual WMI, and SAMR (Security Account Manager Remote protocol) activity followed. A spike in the use of this account was detected on a Sunday—once again, the attackers seemingly targeting the weekend—when the account was used by nearly 50 different devices.

The compromised admin’s account was exploited for data gathering via SMB, resulting in the movement of 200 GB of data between internal devices in preparation for exfiltration. The files were then archived using the naming convention “*.part<number>.rar”.

Around the same time, Darktrace observed data transfers from 19 internal devices to “bublup-media-production.s3.amazonaws[.]com,” totaling just over 200 GB—the same volume of data gathered internally. Connections to other Bublup domains were also detected. The internal data download and external data transfer activity took approximately 8-9 hours.

Unfortunately, Darktrace was not configured in Autonomous Response mode at the time of the attack, meaning any mitigative actions to stop the data gathering or exfiltration required human confirmation.  

One of the compromised devices was seen sending 80 GB of data to bublup-media-production.s3.amazonaws[.]com within a span of 4 hours.
Figure 7: One of the compromised devices was seen sending 80 GB of data to bublup-media-production.s3.amazonaws[.]com within a span of 4 hours.

Once the information was stolen, the threat actor moved on to the final stage of the attack—file encryption. Five internal devices, using either the compromised admin account or connecting via anonymous SMBv1 sessions, were seen encrypting files and writing ransom notes to five other devices on the network. The attempts at file encryption continued for around two hours, but Darktrace’s Autonomous Response capability was able to block the activity and prevent the attack from escalating.

Conclusion

The persistent and evolving threat posed by ransomware like BlackSuit underscores the critical importance of robust cybersecurity measures across all sectors. Since its emergence in 2023, BlackSuit has demonstrated a sophisticated approach to infiltrating networks, leveraging double extortion tactics, and demanding substantial ransoms. The cases highlighted above illustrate the varied methods and persistence of BlackSuit attackers, from exploiting VPN vulnerabilities to abusing remote management tools and targeting off-hours to maximize impact.

Although many similar connection patterns, such as the abuse of Bublup services for data exfiltration or the use of SOCKS5 proxies for C2, were observed during cases investigated by Darktrace, BlackSuit actors are highly sophisticated and tailors their attacks to each target organization. The consequences of a successful attack can be highly disruptive, and remediation efforts can be time-consuming and costly. This includes taking the entire network offline while responding to the incident, restoring encrypted files from backups (if available), dealing with damage to the organization’s reputation, and potential lawsuits.

These BlackSuit ransomware incidents emphasize the need for continuous vigilance, timely updates to security protocols, and the adoption of autonomous response technologies to swiftly counteract such attacks. As ransomware tactics continue to evolve, organizations must remain agile and informed to protect their critical assets and data. By learning from these incidents and enhancing their cybersecurity frameworks, organizations can better defend against the relentless threat of ransomware and ensure the resilience of their operations in an increasingly digital world.

Credit to Signe Zaharka (Principal Cyber Analyst) and Adam Potter (Senior Cyber Analyst)

Insights from Darktrace’s First 6: Half-year threat report for 2024

First 6: half year threat report darktrace screenshot

Darktrace’s First 6: Half-Year Threat Report 2024 highlights the latest attack trends and key threats observed by the Darktrace Threat Research team in the first six months of 2024.

  • Focuses on anomaly detection and behavioral analysis to identify threats
  • Maps mitigated cases to known, publicly attributed threats for deeper context
  • Offers guidance on improving security posture to defend against persistent threats

Appendices

Darktrace Model Detections

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / High Volume of New or Uncommon Service Control

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / Rare WinRM Outgoing

Anomalous Connection / SMB Enumeration

Anomalous Connection / Suspicious Activity On High Risk Device

Anomalous Connection / Suspicious Read Write Ratio

Anomalous Connection / Suspicious Read Write Ratio and Unusual SMB

Anomalous Connection / Sustained MIME Type Conversion

Anomalous Connection / Uncommon 1 GiB Outbound

Anomalous Connection / Unusual Admin SMB Session

Anomalous File / Internal / Additional Extension Appended to SMB File

Anomalous File / Internal / Executable Uploaded to DC

Anomalous File / Internal / Unusual SMB Script Write

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Server Activity / Outgoing from Server

Anomalous Server Activity / Rare External from Server

Anomalous Server Activity / Write to Network Accessible WebRoot

Compliance / Outgoing NTLM Request from DC

Compliance / Remote Management Tool On Server

Compliance / SMB Drive Write

Compromise / Beacon to Young Endpoint

Compromise / Beaconing Activity To External Rare

Compromise / Ransomware / Possible Ransom Note Read

Compromise / Ransomware / Possible Ransom Note Write

Compromise / Ransomware / SMB Reads then Writes with Additional Extensions

Compromise / Ransomware / Suspicious SMB Activity

Device / Anomalous RDP Followed By Multiple Model Breaches

Device / EXE Files Distributed to Multiple Devices

Device / Internet Facing Device with High Priority Alert

Device / Large Number of Model Breaches

Device / Large Number of Model Breaches from Critical Network Device

Device / Multiple Lateral Movement Model Breaches

Device / Network Scan

Device / New or Uncommon WMI Activity

Device / New or Unusual Remote Command Execution

Device / New User Agent To Internal Server

Device / SMB Lateral Movement

Device / SMB Session Brute Force (Admin)

Device / Suspicious SMB Scanning Activity

Device / Unusual LDAP Query For Domain Admins

SaaS / Access / Teams Activity from Rare Endpoint

SaaS / Resource / SaaS Resources With Additional Extensions

SaaS / Unusual Activity / Disabled Strong Authentication

SaaS / Unusual Activity / Multiple Unusual SaaS Activity Scores

SaaS / Unusual Activity / Unusual SaaS Activity Score

SaaS / Unusual Activity / Unusual Volume of SaaS Modifications

Unusual Activity / Anomalous SMB Delete Volume

Unusual Activity / Anomalous SMB Move & Write

Unusual Activity / High Volume Client Data Transfer

Unusual Activity / High Volume Server Data Transfer

Unusual Activity / Internal Data Transfer

Unusual Activity / SMB Access Failures

Unusual Activity / Sustained Anomalous SMB Activity

Unusual Activity / Unusual External Data to New Endpoint

User / New Admin Credentials on Client

User / New Admin Credentials on Server

User/ Kerberos Password Bruteforce

Autonomous Response Models

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

Antigena / Network / External Threat / Antigena Ransomware Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / External Threat / SMB Ratio Antigena Block

Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity

Antigena / Network / Insider Threat / Antigena Internal Data Transfer Block

Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

Antigena / Network / Insider Threat / Antigena Network Scan Block

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

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

Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

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

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

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

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

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Antigena / Network / Significant Anomaly / Repeated Antigena Breaches

Antigena / SaaS / Antigena Unusual Activity Block

List of Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

.blacksuit - File extension – When encrypting the files, this extension is appended to the filename – High

readme.blacksuit.txt – ransom note - A file demanding cryptocurrency payment in exchange for decrypting the victim's files and not leaking the stolen data – High

mystuff.bublup[.]com, bublup-media-production.s3.amazonaws[.]com – data exfiltration domains related to an organization and project management app that has document sharing functionality – High

137.220.61[.]94:4001 – SystemBC C2 related IP address (this tool is often used by other ransomware groups as well) - Medium

173.251.109[.]106 – IP address seen during a SaaS BlackSuit compromise (during file encryption) – Medium

216.151.180[.]147 – IP address seen during a SaaS BlackSuit compromise (during an unusual Teams session) - Medium

MITRE ATT&CK Mapping

Tactic - Technqiue

Account Manipulation - PERSISTENCE - T1098

Alarm Suppression - INHIBIT RESPONSE FUNCTION - T0878

Application Layer Protocol - COMMAND AND CONTROL - T1071

Automated Collection - COLLECTION - T1119

Block Command Message - INHIBIT RESPONSE FUNCTION - T0803

Block Reporting Message - INHIBIT RESPONSE FUNCTION - T0804

Browser Extensions - PERSISTENCE - T1176

Brute Force I/O - IMPAIR PROCESS CONTROL - T0806

Brute Force - CREDENTIAL ACCESS - T1110

Client Configurations - RECONNAISSANCE - T1592.004 - T1592

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

Data Destruction - IMPACT - T1485

Data Destruction - INHIBIT RESPONSE FUNCTION - T0809

Data Encrypted for Impact - IMPACT - T1486

Data from Cloud Storage Object - COLLECTION - T1530

Data Staged - COLLECTION - T1074

Domain Groups - DISCOVERY - T1069.002 - T1069

Email Collection - COLLECTION - T1114

Exfiltration Over C2 Channel - EXFILTRATION - T1041

Exfiltration to Cloud Storage - EXFILTRATION - T1567.002 - T1567

Exploit Public - Facing Application - INITIAL ACCESS - T1190

Exploitation for Privilege Escalation - PRIVILEGE ESCALATION - T0890

Exploitation of Remote Services - LATERAL MOVEMENT - T1210

File and Directory Discovery - DISCOVERY - T1083

File Deletion - DEFENSE EVASION - T1070.004 - T1070

IP Addresses - RECONNAISSANCE - T1590.005 - T1590

Lateral Tool Transfer - LATERAL MOVEMENT - T1570

LLMNR/NBT - NS Poisoning and SMB Relay - CREDENTIAL ACCESS, COLLECTION - T1557.001 - T1557

Modify Alarm Settings - INHIBIT RESPONSE FUNCTION - T0838

Modify Control Logic - IMPAIR PROCESS CONTROL, INHIBIT RESPONSE FUNCTION - T0833

Modify Parameter - IMPAIR PROCESS CONTROL - T0836

Network Service Scanning - DISCOVERY - T1046

Network Share Discovery - DISCOVERY - T1135

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

RDP Hijacking - LATERAL MOVEMENT - T1563.002 - T1563

Remote Access Software - COMMAND AND CONTROL - T1219

Remote Desktop Protocol - LATERAL MOVEMENT - T1021.001 - T1021

Remote System Discovery - DISCOVERY - T1018

Rename System Utilities - DEFENSE EVASION - T1036.003 - T1036

Scanning IP Blocks - RECONNAISSANCE - T1595.001 - T1595

Scheduled Transfer - EXFILTRATION - T1029

Service Execution - EXECUTION - T1569.002 - T1569

Service Stop - IMPACT - T1489

SMB/Windows Admin Shares - LATERAL MOVEMENT - T1021.002 - T1021

Stored Data Manipulation - IMPACT - T1565.001 - T1565

Taint Shared Content - LATERAL MOVEMENT - T1080

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

Vulnerability Scanning - RECONNAISSANCE - T1595.002 - T1595

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

Web Services - RESOURCE DEVELOPMENT - T1583.006 - T1583

Web Shell - PERSISTENCE - T1505.003 - T1505

Windows Management Instrumentation - EXECUTION - T1047

Windows Remote Management - LATERAL MOVEMENT - T1021.006 - T1021

References

1.     https://www.trendmicro.com/en_us/research/23/e/investigating-blacksuit-ransomwares-similarities-to-royal.html

2.     https://www.reuters.com/technology/cybersecurity/blacksuit-hacker-behind-cdk-global-attack-hitting-us-car-dealers-2024-06-27/

3.     https://www.sentinelone.com/anthology/blacksuit/

4.     https://thehackernews.com/2024/08/fbi-and-cisa-warn-of-blacksuit.html

5.     https://www.techtarget.com/whatis/feature/The-CDK-Global-outage-Explaining-how-it-happened

6.     https://therecord.media/japanese-media-kadokawa-investigating-cyber

7.     https://therecord.media/plasma-donation-company-cyberattack-blacksuit

8.     https://thecyberexpress.com/government-of-brazil-cyberattack-by-blacksuit/

9.     https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-061a

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About the author
Signe Zaharka
Senior Cyber Security Analyst
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