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Analyzing Post-Exploitation on Papercut Servers| Darktrace

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29
Aug 2023
29
Aug 2023
Dive into our analysis covering post-exploitation activity on PaperCut servers. Learn the details and impact of this attack and how to keep yourself safe!

Introduction

Malicious cyber actors are known to exploit vulnerabilities in Internet-facing systems and services to gain entry to organizations’ digital environments. Keeping track of the vulnerabilities which malicious actors are exploiting is seemingly futile, with malicious actors continually finding new avenues of exploitation.  

In mid-April 2023, Darktrace, along with the wider security community, observed malicious cyber actors gaining entry to networks through exploitation of a critical vulnerability in the print management system, PaperCut. Darktrace observed two types of attack chain within its customer base, one involving the deployment of payloads to facilitate crypto-mining, and the other involving the deployment of a payload to facilitate Tor-based command-and-control (C2) communication.

Walking Through the Front Door

One of the most widely abused Initial Access methods attackers use to gain entry to an organization’s digital environment is the exploitation of vulnerabilities in Internet-facing systems and services [1]. The public disclosure of a critical vulnerability in a widely used, Internet-facing service, along with a proof of concept (POC) exploit for such vulnerability, provides malicious cyber actors with a key to the front door of countless organizations. Once malicious actors are in possession of such a key, security teams are in a race against time to patch all their vulnerable systems and services. But until organizations accomplish this, the doors are left open.

This year, the security community has seen malicious actors gaining entry to networks through the exploitation of vulnerabilities in a range of services. These services include familiar suspects, such as Microsoft Exchange and ManageEngine, along with less familiar suspects, such as PaperCut. PaperCut is a system for managing and tracking printing, copying, and scanning activity within organizations. In 2021, PaperCut was used in more than 50,000 sites across over 100 countries [2], making PaperCut a widely used print management system.

In January 2023, Trend Micro’s Zero Day Initiative (ZDI) notified PaperCut of a critical RCE vulnerability, namely CVE-2023–27350, in certain versions of PaperCut NG (PaperCut’s ‘print only’ variant) and PaperCut MF (PaperCut’s ‘extended feature’ variant) [3,4]. In March 2023, PaperCut released versions of PaperCut NG and PaperCut MF containing a fix for CVE-2023–27350 [4]. Despite this, security teams observed a surge in cases of malicious actors exploiting CVE-2023–27350 to compromise PaperCut servers in April 2023 [4-10]. This trend was mirrored in Darktrace’s customer base, where a surge in compromises of PaperCut servers was observed in April 2023.

Observed Attack Chains

In mid-April 2023, Darktrace identified two related clusters of attack chains. The attack chains within the first of these clusters involved Internet-facing PaperCut servers downloading payloads with crypto-mining capabilities from the external location, 50.19.48[.]59. While the attack chains within the second of the clusters involved Internet-facing PaperCut servers downloading payloads with Tor-based C2 capabilities from 192.184.35[.]216. The attack chains within the first cluster, which were observed on April 22, 2023, will be referred to as ‘50.19.48[.]59 chains’ and the attack chains in the second cluster, observed on April 24, 2023, will be called ‘192.184.35[.]216 chains’.

Both attack chains started with highly unusual external endpoints contacting the '/SetupCompleted' endpoint of an Internet-facing PaperCut server. These requests to the ‘/SetupCompleted’ endpoint likely represented attempts to exploit CVE-2023–27350 [10].  50.19.48[.]59 chains started with exploit connections from the external endpoint, 85.106.112[.]60, whereas 192.184.35[.]216 chains started with exploit connections from Tor nodes, such as 185.34.33[.]2.

Figure 1: Darktrace’s Advanced Search data showing likely CVE-2023-27350 exploitation activity from the suspicious, external endpoint, 85.106.112[.]60.

After the exploitation step, the two attack chains took different paths. In the 50.19.48[.]59 chains, the exploitation step was followed by the affected PaperCut server making HTTP GET requests over port 82 to the rare external endpoint, 50.19.48[.]59. In the 192.184.35[.]216 chains, the exploitation step was followed by the affected PaperCut server making an HTTP GET request over port 443 to 192.184.35[.]216.

The HTTP GET requests to 50.19.48[.]59 had Target URIs such as ‘/me1.bat’, ‘/me2.bat’, ‘/dom.zip’, ‘/mazar.bat’, and ‘/mazar.zip’, whilst the HTTP GET requests to 192.184.35[.]216 had the Target URI ‘/4591187629.exe’. The User-Agent header of the GET requests to 192.184.35[.]216 indicated that that the malicious file transfers were initiated through Microsoft’s pre-installed Background Intelligent Transfer Service (BITS).

Figure 2: Darktrace’s Advanced Search data showing a PaperCut server downloading Batch and ZIP files from 50.19.48[.]59 straight after receiving likely exploit connections from 85.106.112[.]60.
Figure 3: Darktrace’s Event Log data showing a PaperCut server downloading an executable file from 192.184.35[.]216 immediately after receiving a likely exploit connection from the Tor node, 185.34.33[.]2.

Downloads from 50.19.48[.]59 were followed by cURL GET requests to 138.68.61[.]82 and then connections to external endpoints associated with the cryptocurrency miner, Mimu (as seen in Fig 4). Downloads from 192.184.35[.]216 were followed by Python-urllib GET requests to api.ipify[.]org and long connections to Tor nodes (as seen in Fig 5).  

These facts suggest that the actor behind the 50.19.48[.]59 chains were seeking to drop cryptocurrency miners on PaperCut servers, with the intention of abusing the customer’s network to carry out resource intensive and costly cryptocurrency mining activity. Meanwhile, the actors behind the 192.184.35[.]216 chains were likely attempting to establish a Tor-based C2 channel with PaperCut servers to allow actors to further communicate with compromised devices.

Figure 4: Darktrace's Event Log data showing a PaperCut contacting 50.19.48[.]59 to download payloads, and then making a cURL request to 138.68.61[.]82 before contacting a Mimu crypto-mining endpoint.
Figure 5: Darktrace’s Event Log data showing a PaperCut server contacting 192.184.35[.]216 to download a payload, and then making connections to api.ipify[.]org and several Tor nodes.

The activities ensuing from both attack chains were varied, making it difficult to ascertain whether the activities were steps of separate attack chains, or steps of the existing 50.19.48[.]59 and 192.184.35[.]216 chains. A wide variety of activities ensued from observed 50.19.48[.]59 and 192.184.35[.]216 chains, including the abuse of pre-installed tools, such as cURL, CertUtil, and PowerShell to transfer further payloads to PaperCut servers, Cobalt Strike C2 communication, Ngrok usage, Mimikatz usage, AnyDesk usage, and in one case, detonation of the LockBit ransomware strain.

Figure 6: Diagram representing the steps of observed 50.19.48[.]59 chains.
Figure 7: Diagram representing the steps of observed 192.184.35[.]215 chains.

As the PaperCut servers that were targeted by malicious actors are Internet-facing, they regularly receive connections from unusual external endpoints. The exploit connections in the 50.19.48[.]59 and 192.184.35[.]216 chains, which originated from unusual external endpoints, were therefore not detected by Darktrace DETECT™, which relies on anomaly-based methods to detect network-based steps of an intrusion.

On the other hand, the post-exploitation steps of the 50.19.48[.]59 and 192.184.35[.]216 chains yielded ample anomaly-based detections, given that they consisted of PaperCut servers displaying highly unusual behaviors. As such Darktrace DETECT was able to successfully identify multiple chains of suspicious activity, including unusual file downloads from external endpoints and beaconing activity to rare external locations.

The file downloads from 50.19.48[.]59 observed in the 50.19.48[.]59 chains caused the following Darktrace DETECT models to breach:

- Anomalous Connection / Application Protocol on Uncommon Port

- Anomalous File / Internet Facing System File Download

- Anomalous File / Script from Rare External Location

- Anomalous File / Zip or Gzip from Rare External Location

- Device / Internet Facing Device with High Priority Alert

Figure 8: Darktrace’s Event Log data showing a PaperCut server breaching several models immediately after contacting 50.19.48[.]59.

The file downloads from 192.184.35[.]216 observed in the 192.184.35[.]216 chains caused the following Darktrace DETECT models to breach:

- Anomalous File / EXE from Rare External Location

- Anomalous File / Numeric File Download

- Device / Internet Facing Device with High Priority Alert

Figure 9: Darktrace’s Event Log data showing a PaperCut server breaching several models immediately after contacting 192.184.35[.]216.

Subsequent C2, beaconing, and crypto-mining connections in the 50.19.48[.]59 chains caused the following Darktrace DETECT models to breach:

- Anomalous Connection / New User Agent to IP Without Hostname

- Anomalous Server Activity / New User Agent from Internet Facing System

- Anomalous Server Activity / Rare External from Server

- Compromise / Crypto Currency Mining Activity

- Compromise / High Priority Crypto Currency Mining

- Compromise / High Volume of Connections with Beacon Score

- Compromise / Large Number of Suspicious Failed Connections

- Compromise / SSL Beaconing to Rare Destination

- Device / Initial Breach Chain Compromise

- Device / Large Number of Model Breaches

Figure 10: Darktrace’s Event Log data showing a PaperCut server breaching models as a result of its connections to a Mimu crypto-mining endpoint.

Subsequent C2, beaconing, and Tor connections in the 192.184.35[.]216 chains caused the following Darktrace DETECT models to breach:

- Anomalous Connection / Application Protocol on Uncommon Port

- Compromise / Anomalous File then Tor

- Compromise / Beaconing Activity To External Rare

- Compromise / Possible Tor Usage

- Compromise / Slow Beaconing Activity To External Rare

- Compromise / Uncommon Tor Usage

- Device / Initial Breach Chain Compromise

Figure 11: Darktrace’s Event Log data showing a PaperCut server breaching several models as a result of its connections to Tor nodes.

Darktrace RESPOND

Darktrace RESPOND™ was not active in any of the networks affected by 192.184.35[.]216 activity, however, RESPOND was active in some of the networks affected by 50.19.48[.]59 activity.  In those environments where RESPOND was enabled in autonomous mode, observed malicious activities resulted in intervention from RESPOND, including autonomous actions like blocking connections to specific external endpoints, blocking all outgoing traffic, and restricting affected devices to a pre-established pattern of behavior.

Figure 12: Darktrace’s Event Log data showing Darktrace RESPOND automatically performing inhibitive actions on a device in response to the device’s connection to 50.19.48[.]59.
Figure 13: Darktrace’s Event Log data showing Darktrace RESPOND automatically performing inhibitive actions on a device in response to the device’s connections to a Mimu crypto-mining endpoint.

Darktrace Cyber AI Analyst

Cyber AI Analyst autonomously investigated model breaches caused by events within these 50.19.48[.]59 and 192.184.35[.]216 chains. Cyber AI Analyst created user-friendly and detailed descriptions of these events, and then linked together these descriptions into threads representing the attack chains. Darktrace DETECT thus uncovered the individual steps of the attack chains, while Cyber AI Analyst was able to piece together the individual steps and uncover the attack chains themselves.  

Figure 14: An AI Analyst Incident entry showing the first event in a 50.19.48[.]59 chain uncovered by Cyber AI Analyst.
Figure 15: An AI Analyst Incident entry showing the second event in a 50.19.48[.]59 chain uncovered by Cyber AI Analyst.
Figure 16: An AI Analyst Incident entry showing the third event in a 50.19.48[.]59 chain uncovered by Cyber AI Analyst.
Figure 17: An AI Analyst Incident entry showing the first event in a 192.184.35[.]216 chain uncovered by Cyber AI Analyst.
Figure 18: An AI Analyst Incident entry showing the second event in a 192.184.35[.]216 chain uncovered by Cyber AI Analyst.

Conclusion

The existence of critical vulnerabilities in third-party software leaves organizations at constant risk of malicious actors breaching the perimeters of their networks. This risk can be mitigated through attack surface management and regular patching. However, this does not eliminate cyber risk entirely, meaning that organizations must be prepared for the eventuality of malicious actors getting inside their digital estate.

In April 2023, Darktrace observed malicious actors breaching the perimeters of several customer networks through exploitation of a critical vulnerability in PaperCut. Darktrace DETECT observed actors exploiting PaperCut servers to conduct a wide variety of post-exploitation activities, including downloading malicious payloads associated with cryptocurrency mining or payloads with Tor-based C2 capabilities. Darktrace DETECT created numerous model breaches based on this activity which alerted then customer’s security teams early in their development, providing them with ample time to take mitigative steps.

The successful detection of this payload delivery activity, along with the crypto-mining, beaconing, and Tor C2 activities which followed, elicited Darktrace RESPOND to take autonomous inhibitive action against the ongoing activity in those environments where it was operating in autonomous response mode.

If left to unfold, these intrusions developed in a variety of ways, in some cases leading to Cobalt Strike and ransomware activity. The detection of these intrusions in their early stages thus played a vital role in preventing malicious cyber actors from causing significant disruption.

Credit to: Sam Lister, Senior SOC Analyst, Zoe Tilsiter, Senior Cyber Analyst.

Appendices

MITRE ATT&CK Mapping

Initial Access techniques:

- Exploit Public-Facing Application (T1190)

Execution techniques:

- Command and Scripting Interpreter: PowerShell (T1059.001)

Discovery techniques:

- System Network Configuration Discovery (T1016)

Command and Control techniques

- Application Layer Protocol: Web Protocols (T1071.001)

- Encrypted Channel: Asymmetric Cryptography (T1573.002)

- Ingress Tool Transfer (T1105)

- Non-Standard Port (T1571)

- Protocol Tunneling (T1572)

- Proxy: Multi-hop Proxy (T1090.003)

- Remote Access Software (T1219)

Defense Evasion techniques:

- BITS Jobs (T1197)

Impact techniques:

- Data Encrypted for Impact (T1486)

List of Indicators of Compromise (IoCs)

IoCs from 50.19.48[.]59 attack chains:

- 85.106.112[.]60

- http://50.19.48[.]59:82/me1.bat

- http://50.19.48[.]59:82/me2.bat

- http://50.19.48[.]59:82/dom.zip

- 138.68.61[.]82

- update.mimu-me[.]cyou • 102.130.112[.]157

- 34.195.77[.]216

- http://50.19.48[.]59:82/mazar.bat

- http://50.19.48[.]59:82/mazar.zip

- http://50.19.48[.]59:82/prx.bat

- http://50.19.48[.]59:82/lol.exe  

- http://77.91.85[.]117/122.exe

- windows.n1tro[.]cyou • 176.28.51[.]151

- 77.91.85[.]117

- 91.149.237[.]76

- kernel-mlclosoft[.]site • 104.21.29[.]206

- tunnel.us.ngrok[.]com • 3.134.73[.]173

- 212.113.116[.]105

- c34a54599a1fbaf1786aa6d633545a60 (JA3 client fingerprint of crypto-mining client)

IoCs from 192.184.35[.]216 attack chains:

- 185.56.83[.]83

- 185.34.33[.]2

- http://192.184.35[.]216:443/4591187629.exe

- api.ipify[.]org • 104.237.62[.]211

- www.67m4ipctvrus4cv4qp[.]com • 192.99.43[.]171

- www.ynbznxjq2sckwq3i[.]com • 51.89.106[.]29

- www.kuo2izmlm2silhc[.]com • 51.89.106[.]29

- 148.251.136[.]16

- 51.158.231[.]208

- 51.75.153[.]22

- 82.66.61[.]19

- backmainstream-ltd[.]com • 77.91.72[.]149

- 159.65.42[.]223

- 185.254.37[.]236

- http://137.184.56[.]77:443/for.ps1

- http://137.184.56[.]77:443/c.bat

- 45.88.66[.]59

- http://5.8.18[.]237/download/Load64.exe

- http://5.8.18[.]237/download/sdb64.dll

- 140e0f0cad708278ade0984528fe8493 (JA3 client fingerprint of Tor-based client)

References

[1] https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-137a

[2] https://www.papercut.com/kb/Main/PaperCutMFSolutionBrief/

[3] https://www.zerodayinitiative.com/advisories/ZDI-23-233/

[4] https://www.papercut.com/kb/Main/PO-1216-and-PO-1219

[5] https://www.trendmicro.com/en_us/research/23/d/update-now-papercut-vulnerability-cve-2023-27350-under-active-ex.html

[6] https://www.huntress.com/blog/critical-vulnerabilities-in-papercut-print-management-software

[7] https://news.sophos.com/en-us/2023/04/27/increased-exploitation-of-papercut-drawing-blood-around-the-internet/

[8] https://twitter.com/MsftSecIntel/status/1651346653901725696

[9] https://twitter.com/MsftSecIntel/status/1654610012457648129

[10] https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-131a

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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Sam Lister
SOC Analyst
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Jupyter Ascending: Darktrace’s Investigation of the Adaptive Jupyter Information Stealer

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18
Jul 2024

What is Malware as a Service (MaaS)?

Malware as a Service (MaaS) is a model where cybercriminals develop and sell or lease malware to other attackers.

This approach allows individuals or groups with limited technical skills to launch sophisticated cyberattacks by purchasing or renting malware tools and services. MaaS is often provided through online marketplaces on the dark web, where sellers offer various types of malware, including ransomware, spyware, and trojans, along with support services such as updates and customer support.

The Growing MaaS Marketplace

The Malware-as-a-Service (MaaS) marketplace is rapidly expanding, with new strains of malware being regularly introduced and attracting waves of new and previous attackers. The low barrier for entry, combined with the subscription-like accessibility and lucrative business model, has made MaaS a prevalent tool for cybercriminals. As a result, MaaS has become a significant concern for organizations and their security teams, necessitating heightened vigilance and advanced defense strategies.

Examples of Malware as a Service

  • Ransomware as a Service (RaaS): Providers offer ransomware kits that allow users to launch ransomware attacks and share the ransom payments with the service provider.
  • Phishing as a Service: Services that provide phishing kits, including templates and email lists, to facilitate phishing campaigns.
  • Botnet as a Service: Renting out botnets to perform distributed denial-of-service (DDoS) attacks or other malicious activities.
  • Information Stealer: Information stealers are a type of malware specifically designed to collect sensitive data from infected systems, such as login credentials, credit card numbers, personal identification information, and other valuable data.

How does information stealer malware work?

Information stealers are an often-discussed type MaaS tool used to harvest personal and proprietary information such as administrative credentials, banking information, and cryptocurrency wallet details. This information is then exfiltrated from target networks via command-and-control (C2) communication, allowing threat actors to monetize the data. Information stealers have also increasingly been used as an initial access vector for high impact breaches including ransomware attacks, employing both double and triple extortion tactics.

After investigating several prominent information stealers in recent years, the Darktrace Threat Research team launched an investigation into indicators of compromise (IoCs) associated with another variant in late 2023, namely the Jupyter information stealer.

What is Jupyter information stealer and how does it work?

The Jupyter information stealer (also known as Yellow Cockatoo, SolarMarker, and Polazert) was first observed in the wild in late 2020. Multiple variants have since become part of the wider threat landscape, however, towards the end of 2023 a new variant was observed. This latest variant achieved greater stealth and updated its delivery method, targeting browser extensions such as Edge, Firefox, and Chrome via search engine optimization (SEO) poisoning and malvertising. This then redirects users to download malicious files that typically impersonate legitimate software, and finally initiates the infection and the attack chain for Jupyter [3][4]. In recently noted cases, users download malicious executables for Jupyter via installer packages created using InnoSetup – an open-source compiler used to create installation packages in the Windows OS.

The latest release of Jupyter reportedly takes advantage of signed digital certificates to add credibility to downloaded executables, further supplementing its already existing tactics, techniques and procedures (TTPs) for detection evasion and sophistication [4]. Jupyter does this while still maintaining features observed in other iterations, such as dropping files into the %TEMP% folder of a system and using PowerShell to decrypt and load content into memory [4]. Another reported feature includes backdoor functionality such as:

  • C2 infrastructure
  • Ability to download and execute malware
  • Execution of PowerShell scripts and commands
  • Injecting shellcode into legitimate windows applications

Darktrace Coverage of Jupyter information stealer

In September 2023, Darktrace’s Threat Research team first investigated Jupyter and discovered multiple IoCs and TTPs associated with the info-stealer across the customer base. Across most investigated networks during this time, Darktrace observed the following activity:

  • HTTP POST requests over destination port 80 to rare external IP addresses (some of these connections were also made via port 8089 and 8090 with no prior hostname lookup).
  • HTTP POST requests specifically to the root directory of a rare external endpoint.
  • Data streams being sent to unusual external endpoints
  • Anomalous PowerShell execution was observed on numerous affected networks.

Taking a further look at the activity patterns detected, Darktrace identified a series of HTTP POST requests within one customer’s environment on December 7, 2023. The HTTP POST requests were made to the root directory of an external IP address, namely 146.70.71[.]135, which had never previously been observed on the network. This IP address was later reported to be malicious and associated with Jupyter (SolarMarker) by open-source intelligence (OSINT) [5].

Device Event Log indicating several connections from the source device to the rare external IP address 146.70.71[.]135 over port 80.
Figure 1: Device Event Log indicating several connections from the source device to the rare external IP address 146.70.71[.]135 over port 80.

This activity triggered the Darktrace / NETWORK model, ‘Anomalous Connection / Posting HTTP to IP Without Hostname’. This model alerts for devices that have been seen posting data out of the network to rare external endpoints without a hostname. Further investigation into the offending device revealed a significant increase in external data transfers around the time Darktrace alerted the activity.

This External Data Transfer graph demonstrates a spike in external data transfer from the internal device indicated at the top of the graph on December 7, 2023, with a time lapse shown of one week prior.
Figure 2: This External Data Transfer graph demonstrates a spike in external data transfer from the internal device indicated at the top of the graph on December 7, 2023, with a time lapse shown of one week prior.

Packet capture (PCAP) analysis of this activity also demonstrates possible external data transfer, with the device observed making a POST request to the root directory of the malicious endpoint, 146.70.71[.]135.

PCAP of a HTTP POST request showing streams of data being sent to the endpoint, 146.70.71[.]135.
Figure 3: PCAP of a HTTP POST request showing streams of data being sent to the endpoint, 146.70.71[.]135.

In other cases investigated by the Darktrace Threat Research team, connections to the rare external endpoint 67.43.235[.]218 were detected on port 8089 and 8090. This endpoint was also linked to Jupyter information stealer by OSINT sources [6].

Darktrace recognized that such suspicious connections represented unusual activity and raised several model alerts on multiple customer environments, including ‘Compromise / Large Number of Suspicious Successful Connections’ and ‘Anomalous Connection / Multiple Connections to New External TCP Port’.

In one instance, a device that was observed performing many suspicious connections to 67.43.235[.]218 was later observed making suspicious HTTP POST connections to other malicious IP addresses. This included 2.58.14[.]246, 91.206.178[.]109, and 78.135.73[.]176, all of which had been linked to Jupyter information stealer by OSINT sources [7] [8] [9].

Darktrace further observed activity likely indicative of data streams being exfiltrated to Jupyter information stealer C2 endpoints.

Graph displaying the significant increase in the number of HTTP POST requests with No Get made by an affected device, likely indicative of Jupyter information stealer C2 activity.
Figure 4: Graph displaying the significant increase in the number of HTTP POST requests with No Get made by an affected device, likely indicative of Jupyter information stealer C2 activity.

In several cases, Darktrace was able to leverage customer integrations with other security vendors to add additional context to its own model alerts. For example, numerous customers who had integrated Darktrace with Microsoft Defender received security integration alerts that enriched Darktrace’s model alerts with additional intelligence, linking suspicious activity to Jupyter information stealer actors.

The security integration model alerts ‘Security Integration / Low Severity Integration Detection’ and (right image) ‘Security Integration / High Severity Integration Detection’, linking suspicious activity observed by Darktrace with Jupyter information stealer (SolarMarker).
Figure 5: The security integration model alerts ‘Security Integration / Low Severity Integration Detection’ and (right image) ‘Security Integration / High Severity Integration Detection’, linking suspicious activity observed by Darktrace with Jupyter information stealer (SolarMarker).

Conclusion

The MaaS ecosystems continue to dominate the current threat landscape and the increasing sophistication of MaaS variants, featuring advanced defense evasion techniques, poses significant risks once deployed on target networks.

Leveraging anomaly-based detections is crucial for staying ahead of evolving MaaS threats like Jupyter information stealer. By adopting AI-driven security tools like Darktrace / NETWORK, organizations can more quickly identify and effectively detect and respond to potential threats as soon as they emerge. This is especially crucial given the rise of stealthy information stealing malware strains like Jupyter which cannot only harvest and steal sensitive data, but also serve as a gateway to potentially disruptive ransomware attacks.

Credit to Nahisha Nobregas (Senior Cyber Analyst), Vivek Rajan (Cyber Analyst)

References

1.     https://www.paloaltonetworks.com/cyberpedia/what-is-multi-extortion-ransomware

2.     https://flashpoint.io/blog/evolution-stealer-malware/

3.     https://blogs.vmware.com/security/2023/11/jupyter-rising-an-update-on-jupyter-infostealer.html

4.     https://www.morphisec.com/hubfs/eBooks_and_Whitepapers/Jupyter%20Infostealer%20WEB.pdf

5.     https://www.virustotal.com/gui/ip-address/146.70.71.135

6.     https://www.virustotal.com/gui/ip-address/67.43.235.218/community

7.     https://www.virustotal.com/gui/ip-address/2.58.14.246/community

8.     https://www.virustotal.com/gui/ip-address/91.206.178.109/community

9.     https://www.virustotal.com/gui/ip-address/78.135.73.176/community

Appendices

Darktrace Model Detections

  • Anomalous Connection / Posting HTTP to IP Without Hostname
  • Compromise / HTTP Beaconing to Rare Destination
  • Unusual Activity / Unusual External Data to New Endpoints
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / Large Number of Suspicious Successful Connections
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Compromise / Excessive Posts to Root
  • Compromise / Sustained SSL or HTTP Increase
  • Security Integration / High Severity Integration Detection
  • Security Integration / Low Severity Integration Detection
  • Anomalous Connection / Multiple Connections to New External TCP Port
  • Unusual Activity / Unusual External Data Transfer

AI Analyst Incidents:

  • Unusual Repeated Connections
  • Possible HTTP Command and Control to Multiple Endpoints
  • Possible HTTP Command and Control

List of IoCs

Indicators – Type – Description

146.70.71[.]135

IP Address

Jupyter info-stealer C2 Endpoint

91.206.178[.]109

IP Address

Jupyter info-stealer C2 Endpoint

146.70.92[.]153

IP Address

Jupyter info-stealer C2 Endpoint

2.58.14[.]246

IP Address

Jupyter info-stealer C2 Endpoint

78.135.73[.]176

IP Address

Jupyter info-stealer C2 Endpoint

217.138.215[.]105

IP Address

Jupyter info-stealer C2 Endpoint

185.243.115[.]88

IP Address

Jupyter info-stealer C2 Endpoint

146.70.80[.]66

IP Address

Jupyter info-stealer C2 Endpoint

23.29.115[.]186

IP Address

Jupyter info-stealer C2 Endpoint

67.43.235[.]218

IP Address

Jupyter info-stealer C2 Endpoint

217.138.215[.]85

IP Address

Jupyter info-stealer C2 Endpoint

193.29.104[.]25

IP Address

Jupyter info-stealer C2 Endpoint

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About the author
Nahisha Nobregas
SOC Analyst

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What you need to know about the new SEC Cybersecurity rules

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17
Jul 2024

What is new in 2023 to SEC cybersecurity rules?

Form 8-K Item 1.05: Requiring the timely disclosure of material cybersecurity incidents.

Regulation S-K item 106: requiring registrants’ annual reports on Form 10-K to address cybersecurity risk management, strategy, and governance processes.

Comparable disclosures are required for reporting foreign private issuers on Forms 6-K and 20-F respectively.

What is Form 8-K Item 1.05 SEC cybersecurity rules?

Form 8-K Item 1.05 requires the following to be reported within four business days from when an incident is determined to be “material” (1), unless extensions are granted by the SEC under certain qualifying conditions:

“If the registrant experiences a cybersecurity incident that is determined by the registrant to be material, describe the material aspects of the nature, scope, and timing of the incident, and the material impact or reasonably likely material impact on the registrant, including its financial condition and results of operations.” (2, 3)

How does the SEC define cybersecurity incident?

Cybersecurity incident defined by the SEC means an unauthorized occurrence, or a series of related unauthorized occurrences, on or conducted through a registrant’s information systems that jeopardizes the confidentiality, integrity, or availability of a registrant’s information systems or any information residing therein. (4)

How can Darktrace assist in the process of disclosing incidents to the SEC?

Accelerate reporting

Darktrace’s Cyber AI Analyst generates automated reports that synthesize discrete data points potentially indicative of cybersecurity threats, forming reports that provide an overview of the evolution and impact of a threat.

Thus, when a potential threat is identified by Darktrace, AI Analyst can quickly compile information that organizations might include in their disclosure of an occurrence they determined to be material, including the following: incident timelines, incident events, incident summary, related model breaches, investigation process (i.e., how Darktrace’s AI conducted the investigation), linked incident events, and incident details. The figure below illustrates how Darktrace compiles and presents incident information and insights in the UI.

Overview of information provided in an ‘AI Analyst Report’ that could be relevant to registrants reporting a material cybersecurity incident to the SEC
Figure 1: Overview of information provided in an ‘AI Analyst Report’ that could be relevant to registrants reporting a material cybersecurity incident to the SEC

It should be noted that Instruction 4 to the new Form 8-K Item 1.05 specifies the “registrant need not disclose specific or technical information about its planned response to the incident or its cybersecurity systems, related networks and devices, or potential system vulnerabilities in such detail as would impede the registrant’s response or remediation of the incident” (5).

As such, the incident report generated by Darktrace may provide more information, including technical details, than is needed for the 8-K disclosure. In general, users should take appropriate measures to ensure that the information they provide in SEC reports meets the requirements outlined by the relevant regulations. Darktrace cannot recommend that an incident should be reported, nor report an incident itself.

Determine if a cybersecurity incident is material

Item 1.05 requires registrants to determine for themselves whether cybersecurity incidents qualify as ‘material’. This involves considerations such as ‘the nature scope and timing of the incident, and the material impact or reasonably likely material impact on the registrant, including its financial condition and results of operations.’

While it is up to the registrant to determine, consistent with existing legal standards, the materiality of an incident, Darktrace’s solution can provide relevant information which might aid in this evaluation. Darktrace’s Threat Visualizer user interface provides a 3-D visualization of an organization’s digital environment, allowing users to assess the likely degree to which an attack may have spread throughout their digital environment. Darktrace Cyber AI Analyst identifies connections among discrete occurrences of threatening activity, which can help registrants quickly assess the ‘scope and timing of an incident'.

Furthermore, in order to establish materiality it would be useful to understand how an attack might extend across recipients and environments. In the image below, Darktrace/Email identifies how a user was impacted across different platforms. In this example, Darktrace/Email identified an attacker that deployed a dual channel social engineering attack via both email and a SaaS platform in an effort to acquire login credentials. In this case, the attacker useding a legitimate SharePoint link that only reveals itself to be malicious upon click. Once the attacker gained the credentials, it proceeded to change email rules to obfuscate its activity.

Darktrace/Email presents this information in one location, making such investigations easier for the end user.

Darktrace/Email indicating a threat across SaaS and email
Figure 2: Darktrace/Email indicating a threat across SaaS and email

What is regulation S-K item 106 of the SEC cybersecurity rules?

The new rules add Item 106 to Regulation S-K requiring registrants to disclose certain information regarding their risk management, strategy, and governance relating to cybersecurity in their annual reports on Form 10-K. The new rules add Item 16K to Form 20-F to require comparable disclosure by [foreign private issuers] in their annual reports on Form 20-F. (6)

SEC cybersecurity rules: Risk management

Specifically, with respect to risk management, Item 106(b) and Item 16K(b) require registrants to describe their processes, if any, for assessing, identifying, and managing material risks from cybersecurity threats, as well as whether any risks from cybersecurity threats, including as a result of any previous cybersecurity incidents, have materially affected or are reasonably likely to materially affect them. The new rules include a non-exclusive list of disclosure items registrants should provide based on their facts and circumstances. (6)

SEC cybersecurity rules: Governance

With respect to governance, Item 106 and Item 16K require registrants to describe the board of directors’ oversight of risks from cybersecurity threats (including identifying any board committee or subcommittee responsible for such oversight) and management’s role in assessing and managing material risks from cybersecurity threats. (6)

How can Darktrace solutions aid in disclosing their risk management, strategy, and governance related to cybersecurity?

Impact scores

Darktrace End-to-End (E2E) leverages AI to understand the complex relationships across users and devices to model possible attack paths, giving security teams a contextual understanding of risk across their digital environments beyond isolated CVEs or CVSS scores. Additionally, teams can prioritize risk management actions to increase their cyber resilience through the E2E Advisory dashboard.

Attack paths consider:

  • Potential damages: Both the potential consequences if a given device was compromised and its immediate implications on other devices.
  • Exposure: Devices' level of interactivity and accessibility. For example, how many emails does a user get via mailing lists and from what kind of sources?
  • Impact: Where a user or asset sits in terms of the IT or business hierarchy and how they communicate with each other. Darktrace can simulate a range of possible outcomes for an uncertain event.
  • Weakness: A device’s patch latency and difficulty, a composite metric that looks at attacker MITRE methods and our own scores to determine how hard each stage of compromise is to achieve.

Because the SEC cybersecurity rules require “oversight of risks from cybersecurity threats” and “management’s role in assessing and managing material risks from cybersecurity threats” (6), the scores generated by Darktrace E2E can aid end-user’s ability to identify risks facing their organization and assign responsibilities to address those risks.

E2E attack paths leverage a deep understanding of a customer’ digital environment and highlight potential attack routes that an attacker could leverage to reach critical assets or entities. Difficulty scores (see Figure 5) allow security teams to measure potential damage, exposure, and impact of an attack on a specific asset or entity.

An example of an attack path in a digital environment
Figure 3: An example of an attack path in a digital environment

Automatic executive threat reports

Darktrace’s solution automatically produces Executive Threat Reports that present a simple visual overview of model breaches (i.e., indicators of unusual and threatening behaviors) and activity in the network environment. Reports can be customized to include extra details or restricted to high level information.

These reports can be generated on a weekly, quarterly, and yearly basis, and can be documented by registrants in relation to Item 106(b) to document parts of their efforts toward assessing, identifying, and managing material risks from cybersecurity threats.

Moreover, Cyber AI Analyst incident reports (described above) can be leveraged to document key details concerning significant previous incidents identified by the Darktrace solution that the registrant determined to be ‘material’.

While the disclosures required by Item 106(c) relate to the governance processes by which the board of directors, the management, and other responsible bodies within an organization oversee risks resulting from cybersecurity threats, the information provided by Darktrace’s Executive Threat Reports and Cyber AI Analyst incident reports can also help relevant stakeholders communicate more effectively regarding the threat landscape and previous incidents.

DISCLAIMER

The material above is provided for informational purposes only. This summary does not constitute legal or compliance advice, recommendations, or guidance. Darktrace encourages you to verify the contents of this summary with your own advisors.

References

  1. Note that the rule does not set forth any specific timeline between the incident and the materiality determination, but the materiality determination should be made without unreasonable delay.
  2. https://www.sec.gov/files/form8-k.pdf
  3. https://www.sec.gov/news/press-release/2023-139
  4. https://www.ecfr.gov/current/title-17/chapter-II/part-229
  5. https://www.sec.gov/files/form8-k.pdf
  6. https://www.sec.gov/corpfin/secg-cybersecurity
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About the author
Kendra Gonzalez Duran
Director of Technology Innovation
Our ai. Your data.

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