Blog
/
Network
/
January 26, 2024

Post-Exploitation Activities of Ivanti CS/PS Appliances

Darktrace’s teams have observed a surge in malicious activities targeting Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances. Learn more!
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.
Written by
Sam Lister
Specialist Security Researcher
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
26
Jan 2024

What are 'Unknown Unknowns'?

When critical vulnerabilities in Internet-facing assets are not yet publicly disclosed, they can provide unfettered access to organizations’ networks. Threat actors’ exploitation of these vulnerabilities are prime examples of “unknown unknowns” – behaviors which security teams are not even aware that they are not aware of.  

Therefore, it is not surprising that zero-day vulnerabilities in Internet-facing assets are so attractive to state-linked actors and cybercriminals. These criminals will abuse the access these vulnerabilities afford them to progress towards harmful or disruptive objectives. This trend in threat actor activity was particularly salient in January 2024, following the disclosure of two critical vulnerabilities in Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances. The widespread exploitation of these vulnerabilities was mirrored across Darktrace’s customer base in mid-January 2024, with Darktrace’s Security Operations Center (SOC) and Threat Research teams observing a surge in malicious activities targeting customers’ CS/PS appliances.

Vulnerabilities in Ivanti CS/PS

On January 10, 2024, Ivanti published a Security Advisory [1] and a Knowledge Base article [2] relating to the following two vulnerabilities in Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS):

  • CVE-2023-46805 (CVSS: 8.2; Type: Authentication bypass vulnerability)
  • CVE-2024-21887 (CVSS: 9.1; Type: Command injection vulnerability)

Conjoined exploitation of these vulnerabilities allows for unauthenticated, remote code execution (RCE) on vulnerable Ivanti systems. Volexity [3] and Mandiant [4] reported clusters of CS/PS compromises, tracked as UTA0178 and UNC5221 respectively. UTA0178 and UNC5221 compromises involve exploitation of CVE-2023-46805 and CVE-2024-21887 to deliver web shells and JavaScript credential harvesters to targeted CS/PS appliances. Both Volexity and Mandiant linked these compromises to a likely espionage-motivated, state-linked actor. GreyNoise [5] and Volexity [6] also reported likely cybercriminal activities targeting CS/PS appliances to deliver cryptominers.

The scale of this recent Ivanti CS/PS exploitation is illustrated by research findings recently shared by Censys [7]. According to these findings, as of January 22, around 1.5% of 26,000 Internet-exposed Ivanti CS appliances have been compromised, with the majority of compromised hosts falling within the United States. As cybercriminal interest in these Ivanti CS/PS vulnerabilities continues to grow, it is likely that so too will the number of attacks targeting them.

Observed Malicious Activities

Since January 15, 2024, Darktrace’s SOC and Threat Research team have observed a significant volume of malicious activities targeting customers’ Ivanti CS/PS appliances. Amongst the string of activities that were observed, the following threads were identified as salient:

  • Exploit validation activity
  • Exfiltration of system information
  • Delivery of C2 implant from AWS
  • Delivery of JavaScript credential stealer
  • SimpleHelp usage
  • Encrypted C2 on port 53
  • Delivery of cryptominer

Exploit Validation Activity

Malicious actors were observed using the out-of-band application security testing (OAST) services, Interactsh and Burp Collaborator, to validate exploits for CS/PS vulnerabilities. Malicious use of OAST services for exploit validation is common and has been seen in the early stages of previous campaigns targeting Ivanti systems [8]. In this case, the Interact[.]sh exploit tests were evidenced by CS/PS appliances making GET requests with a cURL User-Agent header to subdomains of 'oast[.]live', 'oast[.]site', 'oast[.]fun', 'oast[.]me', 'oast[.]online' and 'oast[.]pro'.  Burp Collaborator exploit tests were evidenced by CS/PS appliances making GET requests with a cURL User-Agent header to subdomains of ‘collab.urmcyber[.]xyz’ and ‘dnslog[.]store’.

Figure 1: Event Log showing a CS/PS appliance contacting an 'oast[.]pro' endpoint.
Figure 2: Event Log showing a CS/PS appliance contacting a 'collab.urmcyber[.]xyz' endpoint.
Figure 3: Packet capture (PCAP) of an Interactsh GET request.
Figure 4: PCAP of a Burp Collaborator GET request.

Exfiltration of System Information

The majority of compromised CS/PS appliances identified by Darktrace were seen using cURL to transfer hundreds of MBs of data to the external endpoint, 139.180.194[.]132. This activity appeared to be related to a threat actor attempting to exfiltrate system-related information from CS/PS appliances. These data transfers were carried out via HTTP on ports 443 and 80, with the Target URIs ‘/hello’ and ‘/helloq’ being seen in the relevant HTTP POST requests. The files sent over these data transfers were ‘.dat’ and ‘.sys’ files with what seems to be the public IP address of the targeted appliance appearing in each file’s name.

Figure 5: Event Log shows a CS/PS appliance making a POST request to 139.180.194[.]132 whilst simultaneously receiving connections from suspicious external endpoints.
Figure 6: PCAP of a POST request to 139.180.194[.]132.

Delivery of Command-and-Control (C2) implant from Amazon Web Services (AWS)

In many of the compromises observed by Darktrace, the malicious actor in question was observed delivering likely Rust-based ELF payloads to the CS/PS appliance from the AWS endpoints, archivevalley-media.s3.amazonaws[.]com, abode-dashboard-media.s3.ap-south-1.amazonaws[.]com, shapefiles.fews.net.s3.amazonaws[.]com, and blooming.s3.amazonaws[.]com. In one particular case, these downloads were immediately followed by the delivery of an 18 MB payload (likely a C2 implant) from the AWS endpoint, be-at-home.s3.ap-northeast-2.amazonaws[.]com, to the CS/PS appliance. Post-delivery, the implant seems to have initiated SSL beaconing connections to the external host, music.farstream[.]org. Around this time, Darktrace also observed the actor initiating port scanning and SMB enumeration activities from the CS/PS appliance, likely in preparation for moving laterally through the network.

Figure 7: Advanced Search logs showing a CS/PS appliance beaconing to music.farstream[.]org after downloading several payloads from AWS.

Delivery of JavaScript credential stealer

In a small number of observed cases, Darktrace observed malicious actors delivering what appeared to be a JavaScript credential harvester to targeted CS/PS appliances. The relevant JavaScript code contains instructions to send login credentials to likely compromised websites. In one case, the website, www.miltonhouse[.]nl, appeared in the code snippet, and in another, the website, cpanel.netbar[.]org, was observed. Following the delivery of this JavaScript code, HTTPS connections were observed to these websites.  This likely credential harvester appears to strongly resemble the credential stealer observed by Mandiant (dubbed ‘WARPWIRE’) in UNC5221 compromises and the credential stealer observed by Veloxity in UTA0178 compromises.

Figure 8: PCAP of ‘/3.js’ GET request for JavaScript credential harvester.
Figure 9: Snippet of response to '/3.js’ GET request.
Figure 10: PCAP of ‘/auth.js’ GET request for JavaScript credential harvester.
Figure 11: Snippet of response to '/auth.js’ GET request.
Figure 12: Advanced Search logs showing VPN-connected devices sending data to www.miltonhouse[.]nl after the Ivanti CS appliance received the JavaScript code.

The usage of this JavaScript credential harvester did not occur in isolation, but rather appears to have occurred as part of a chain of activity involving several further steps. The delivery of the ‘www.miltonhouse[.]nl’ JavaScript stealer seems to have occurred as a step in the following attack chain:  

1. Ivanti CS/PS appliance downloads a 8.38 MB ELF file over HTTP (with Target URI ‘/revsocks_linux_amd64’) from 188.116.20[.]38

2. Ivanti CS/PS appliance makes a long SSL connection (JA3 client fingerprint: 19e29534fd49dd27d09234e639c4057e) over port 8444 to 185.243.112[.]245, with several MBs of data being exchanged

3. Ivanti CS/PS appliance downloads a Perl script over HTTP (with Target URI ‘/login.txt’) from 188.116.20[.]38

4. Ivanti CS/PS appliance downloads a 1.53 ELF MB file over HTTP (with Target URI ‘/aparche2’) from 91.92.240[.]113

5. Ivanti CS/PS appliance downloads a 4.5 MB ELF file over HTTP (with Target URI ‘/agent’) from 91.92.240[.]113

6. Ivanti CS/PS appliance makes a long SSL connection (JA3 client fingerprint: 19e29534fd49dd27d09234e639c4057e) over port 11601 to 45.9.149[.]215, with several MBs of data being exchanged

7. Ivanti CS/PS appliance downloads Javascript credential harvester over HTTP (with Target URI ‘/auth.js’) from 91.92.240[.]113

8. Ivanti CS/PS appliance downloads a Perl script over HTTP (with Target URI ‘/login.cgi’) from 91.92.240[.]113

9. Ivanti CS/PS appliance makes a long SSL connection (JA3 client fingerprint: 19e29534fd49dd27d09234e639c4057e) over port 11601 to 91.92.240[.]71, with several MBs of data being exchanged

10. Ivanti CS/PS appliance makes a long SSL connection (JA3 client fingerprint: 19e29534fd49dd27d09234e639c4057e) over port 11601 to 45.9.149[.]215, with several MBs of data being exchanged

11. Ivanti CS/PS appliance makes a long SSL connection (JA3 client fingerprint: 19e29534fd49dd27d09234e639c4057e) over port 8080 to 91.92.240[.]113, with several MBs of data being exchanged

12. Ivanti CS/PS appliance makes a long SSL connection (JA3 client fingerprint: 19e29534fd49dd27d09234e639c4057e) over port 11601 to 45.9.149[.]112, with several MBs of data being exchanged  

These long SSL connections likely represent a malicious actor creating reverse shells from the targeted CS/PS appliance to their C2 infrastructure. Whilst it is not certain that these behaviors are part of the same attack chain, the similarities between them (such as the Target URIs, the JA3 client fingerprint and the use of port 11601) seem to suggest a link.  

Figure 13: Advanced Search logs showing a chain of malicious behaviours from a CS/PS appliance.
Figure 14: Advanced Search data showing the JA3 client fingerprint ‘19e29534fd49dd27d09234e639c4057e’ exclusively appearing in the aforementioned, long SSL connections from the targeted CS/PS appliance.
Figure 15: PCAP of ‘/login.txt’ GET request for a Perl script.
Figure 16: PCAP of ‘/login.cgi’ GET request for a Pearl script.

SimpleHelp Usage

After gaining a foothold on vulnerable CS/PS appliances, certain actors attempted to deepen their foothold within targeted networks. In several cases, actors were seen using valid account credentials to pivot over RDP from the vulnerable CS/PS appliance to other internal systems. Over these RDP connections, the actors appear to have installed the remote support tool, SimpleHelp, onto targeted internal systems, as evidenced by these systems’ subsequent HTTP requests. In one of the observed cases, a lateral movement target downloaded a 7.33 MB executable file over HTTP (Target URI: /ta.dat; User-Agent header: Microsoft BITS/7.8) from 45.9.149[.]215 just before showing signs of SimpleHelp usage. The apparent involvement of 45.9.149[.]215 in these SimpleHelp threads may indicate a connection between them and the credential harvesting thread outlined above.

Figure 17: Advanced Search logs showing an internal system making SimpleHelp-indicating HTTP requests immediately after receiving large volumes of data over RDP from an CS/PS appliance.
Figure 18: PCAP of a SimpleHelp-related GET request.

Encrypted C2 over port 53

In a handful of the recently observed CS/PS compromises, Darktrace identified malicious actors dropping a 16 MB payload which appears to use SSL-based C2 communication on port 53. C2 communication on port 53 is a commonly used attack method, with various malicious payloads, including Cobalt Strike DNS, being known to tunnel C2 communications via DNS requests on port 53. Encrypted C2 communication on port 53, however, is less common. In the cases observed by Darktrace, payloads were downloaded from 103.13.28[.]40 and subsequently reached back out to 103.13.28[.]40 over SSL on port 53.

Figure 19: PCAP of a ‘/linb64.png’ GET request.
Figure 20: Advanced Search logs showing a CS/PS appliance making SSL conns over port 53 to 103.13.28[.]40 immediately after downloading a 16 MB payload from 103.13.28[.]40.

Delivery of cryptominer

As is often the case, financially motivated actors also appeared to have sought to exploit the Ivanti appliances, with actors observed exploiting CS/PS appliances to deliver cryptomining malware. In one case, Darktrace observed an actor installing a Monero cryptominer onto a vulnerable CS/PS appliance, with the miner being downloaded via HTTP on port 8089 from 192.252.183[.]116.

Figure 21: PCAP of GET request for a Bash script which appeared to kill existing cryptominers.
Figure 22: PCAP of a GET request for a JSON config file – returned config file contains mining details such as ‘auto.3pool[.]org:19999’.
Figure 23: PCAP of a GET request for an ELF payload

Potential Pre-Ransomware Post-Compromise Activity

In one observed case, a compromise of a customer’s CS appliance was followed by an attacker using valid account credentials to connect to the customer’s CS VPN subnet. The attacker used these credentials to pivot to other parts of the customer’s network, with tools and services such as PsExec, Windows Management Instrumentation (WMI) service, and Service Control being abused to facilitate the lateral movement. Other Remote Monitoring and Management (RMM) tools, such as AnyDesk and ConnectWise Control (previously known as ScreenConnect), along with certain reconnaissance tools such as Netscan, Nmap, and PDQ, also appear to have been used. The attacker subsequently exfiltrated data (likely via Rclone) to the file storage service, put[.]io, potentially in preparation for a double extortion ransomware attack. However, at the time of writing, it was not clear what the relation was between this activity and the CS compromise which preceded it.

Darktrace Coverage

Darktrace has observed malicious actors carrying out a variety of post-exploitation activities on Internet-exposed CS/PS appliances, ranging from data exfiltration to the delivery of C2 implants and crypto-miners. These activities inevitably resulted in CS/PS appliances displaying patterns of network traffic greatly deviating from their typical “patterns of life”.

Darktraceidentified these deviations and generated a variety of model breaches (i.e, alerts) highlighting the suspicious activity. Darktrace’s Cyber AI Analyst™ autonomously investigated the ongoing compromises and connected the individual model breaches, viewing them as related incidents rather than isolated events. When active and configured in autonomous response mode, Darktracntainted attackers’ operations by autonomously blocking suspicious patterns of network traffic as soon as they were identified by Darktrace

The exploit validation activities carried out by malicious actors resulted in CS/PS servers making HTTP connections with cURL User-Agent headers to endpoints associated with OAST services such as Interactsh and Burp Collaborator. Darktrace recognized that this HTTP activity was suspicious for affected devices, causing the following models to breach:

  • Compromise / Possible Tunnelling to Bin Services
  • Device / Suspicious Domain
  • Anomalous Server Activity / New User Agent from Internet Facing System
  • Device / New User Agent
Figure 24: Event Log showing a CS/PS appliance breaching models due to its Interactsh HTTP requests.
Figure 25: Cyber AI Analyst Incident Event highlighting a CS/PS appliance's Interactsh connections.

Malicious actors’ uploads of system information to 139.180.194[.]132 resulted in cURL POST requests being sent from the targeted CS/PS appliances. Darktrace DETECT judged these HTTP POST requests to be anomalous, resulting in combinations of the following model breaches:

  • Anomalous Connection / Posting HTTP to IP Without Hostname
  • Anomalous Server Activity / Outgoing from Server
  • Anomalous Server Activity / New User Agent from Internet Facing System
  • Unusual Activity / Unusual External Data Transfer
  • Unusual Activity / Unusual External Data to New Endpoint
  • Anomalous Connection / Data Sent to Rare Domain
Figure 26: Event Log showing the creation of a model breach due to a CS/PS appliance’s POST request to 139.180.194[.]132.
Figure 27: Cyber AI Analyst Incident Event highlighting POST requests from a CS/PS appliance to 139.180.194[.]132.

The installation of AWS-hosted C2 implants onto vulnerable CS/PS appliances resulted in beaconing connections which Darktrace recognized as anomalous, leading to the following model breaches:

  • Compromise / Beacon to Young Endpoint
  • Compromise / Beaconing Activity To External Rare
  • Compromise / High Volume of Connections with Beacon Score

When enabled in autonomous response mode, Darktrace's Autonomous Response was able to follow up these detections by blocking affected devices from connecting externally over port 80, 443, 445 or 8081, effectively shutting down the attacker’s beaconing activity.

Figure 28: Event Log showing the creation of a model breach and the triggering of an autonomous RESPOND action due to a CS/PS appliance's beaconing connections.

The use of encrypted C2 on port 53 by malicious actors resulted in CS/PS appliances making SSL connections over port 53. Darktrace judged this port to be uncommon for SSL traffic and consequently generated the following model breach:

  • Anomalous Connection / Application Protocol on Uncommon Port
Figure 29: Cyber AI Analyst Incident Event highlighting a ‘/linb64.png’ GET request from a CS/PS appliance to 103.13.28[.]40.
Figure 30: Event Log showing the creation of a model breach due to CS/PS appliance’s external SSL connection on port 53.
Figure 31: Cyber AI Analyst Incident Event highlighting a CS/PS appliance’s SSL connections over port 53 to 103.13.28[.]40.

Malicious actors’ attempts to run cryptominers on vulnerable CS/PS appliances resulted in downloads of Bash scripts and JSON files from external endpoints rarely visited by the CS/PS appliances themselves or by neighboring systems. Darktrace identified these deviations in device behavior and generated the following model breaches:

  • Anomalous File / Script from Rare External Location
  • Anomalous File / Internet Facing System File Download

Darktrace's Autonomous Response, when configured to respond autonomously, was subsequently able to carry out a number of actions to contain the attacker’s activity. This included blocking all outgoing traffic on offending devices and enforcing a “pattern of life” on devices ensuring they had to adhere to expected network behavior.

Figure 32: Event Log showing the creation of model breaches and the triggering of autonomous RESPOND actions in response to a CS/PS appliance’s cryptominer download.
Figure 33: Cyber AI Analyst Incident Event highlighting a CS/PS appliance’s cryptominer download.

The use of RDP to move laterally and spread SimpleHelp to other systems resulted in CS/PS appliances using privileged credentials to initiate RDP sessions. These RDP sessions, and the subsequent traffic resulting from usage of SimpleHelp, were recognized by Darktrace as being highly out of character, prompting the following model breaches:

  • Anomalous Connection / Unusual Admin RDP Session
  • Device / New User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Compromise / Suspicious HTTP Beacons to Dotted Quad
  • Anomalous File / Anomalous Octet Stream (No User Agent)
  • Anomalous Server Activity / Rare External from Server
Figure 34: Event Log showing the creation of a model breach due to a CS/PS appliance’s usage of an admin credential to RDP to another internal system.
Figure 35: Event Log showing the creation of model breaches due to SimpleHelp-HTTP requests from a device targeted for lateral movement.
Figure 36: Cyber AI Analyst Incident Event highlighting the SimpleHelp-indicating HTTP requests made by an internal system.

Conclusion

The recent widespread exploitation of Ivanti CS/PS is a stark reminder of the threat posed by malicious actors armed with exploits for Internet-facing assets.

Based on the telemetry available to Darktrace, a wide range of malicious activities were carried out against CS/PS appliances, likely via exploitation of the recently disclosed CVE-2023-46805 and CVE-2024-21887 vulnerabilities.

These activities include the usage of OAST services for exploit validation, the exfiltration of system information to 139.180.194[.]132, the delivery of AWS-hosted C2 implants, the delivery of JavaScript credential stealers, the usage of SimpleHelp, the usage of SSL-based C2 on port 53, and the delivery of crypto-miners. These activities are far from exhaustive, and many more activities will undoubtedly be uncovered as the situation develops and our understanding grows.

While there were no patches available at the time of writing, Ivanti stated that they were expected to be released shortly, with the “first version targeted to be available to customers the week of 22 January 2023 and the final version targeted to be available the week of 19 February” [9].

Fortunately for vulnerable customers, in their absence of patches Darktrace was able to identify and alert for anomalous network activity that was carried out by malicious actors who had been able to successfully exploit the Ivanti CS and PS vulnerabilities. While the activity that followed these zero-day vulnerabilities may been able to have bypass traditional security tools reliant upon existing threat intelligence and indicators of compromise (IoCs), Darktrace’s anomaly-based approach allows it to identify such activity based on the subtle deviations in a devices behavior that typically emerge as threat actors begin to work towards their goals post-compromise.

In addition to Darktrace’s ability to identify this type of suspicious behavior, its autonomous response technology, Darktrace's Autonomous Response is able to provide immediate follow-up with targeted mitigative actions to shut down malicious activity on affected customer environments as soon as it is detected.

Credit to: Nahisha Nobregas, SOC Analyst, Emma Foulger, Principle Cyber Analyst, and the Darktrace Threat Research Team

Appendices

List of IoCs Possible IoCs:

-       curl/7.19.7 (i686-redhat-linux-gnu) libcurl/7.63.0 OpenSSL/1.0.2n zlib/1.2.3

-       curl/7.19.7 (i686-redhat-linux-gnu) libcurl/7.63.0 OpenSSL/1.0.2n zlib/1.2.7

Mid-high confidence IoCs:

-       http://139.180.194[.]132:443/hello

-       http://139.180.194[.]132:443/helloq

-       http://blooming.s3.amazonaws[.]com/Ea7fbW98CyM5O (SHA256 hash: 816754f6eaf72d2e9c69fe09dcbe50576f7a052a1a450c2a19f01f57a6e13c17)

-       http://abode-dashboard-media.s3.ap-south-1.amazonaws[.]com/kaffMm40RNtkg (SHA256 hash: 47ff0ae9220a09bfad2a2fb1e2fa2c8ffe5e9cb0466646e2a940ac2e0cf55d04)

-       http://archivevalley-media.s3.amazonaws[.]com/bbU5Yn3yayTtV (SHA256 hash: c7ddd58dcb7d9e752157302d516de5492a70be30099c2f806cb15db49d466026)

-       http://shapefiles.fews.net.s3.amazonaws[.]com/g6cYGAxHt4JC1 (SHA256 hash: c26da19e17423ce4cb4c8c47ebc61d009e77fc1ac4e87ce548cf25b8e4f4dc28)

-       http://be-at-home.s3.ap-northeast-2.amazonaws[.]com/2ekjMjslSG9uI

-       music.farstream[.]org  • 104.21.86[.]153 / 172.67.221[.]78

-       http://197.243.22[.]27/3.js

-       http://91.92.240[.]113/auth.js

-       www.miltonhouse[.]nl • 88.240.53[.]22

-       cpanel.netbar[.]org • 146.19.212[.]12

-       http://188.116.20[.]38/revsocks_linux_amd64

-       185.243.112[.]245:8444

-        http://188.116.20[.]38/login.txt

-       http://91.92.240[.]113/aparche2 (SHA256 hash: 9d11c3cf10b20ff5b3e541147f9a965a4e66ed863803c54d93ba8a07c4aa7e50)

-       http://91.92.240[.]113/agent (SHA256 hash: 7967def86776f36ab6a663850120c5c70f397dd3834f11ba7a077205d37b117f)

-       45.9.149[.]215:11601

-       45.9.149[.]112:11601

-       http://91.92.240[.]113/login.cgi

-       91.92.240[.]71:11601

-       91.92.240[.]113:8080

-       http://45.9.149[.]215/ta.dat (SHA256 hash: 4bcf1333b3ad1252d067014c606fb3a5b6f675f85c59b69ca45669d45468e923)

-       91.92.241[.]18

-       94.156.64[.]252

-       http://144.172.76[.]76/lin86

-       144.172.122[.]14:443

-       http://185.243.115[.]58:37586/

-       http://103.13.28[.]40/linb64.png

-       103.13.28[.]40:53

-       159.89.82[.]235:8081

-       http://192.252.183[.]116:8089/u/123/100123/202401/d9a10f4568b649acae7bc2fe51fb5a98.sh

-       http://192.252.183[.]116:8089/u/123/100123/202401/sshd

-       http://192.252.183[.]116:8089/u/123/100123/202401/31a5f4ceae1e45e1a3cd30f5d7604d89.json

-       http://103.27.110[.]83/module/client_amd64

-       http://103.27.110[.]83/js/bootstrap.min.js?UUID=...

-       http://103.27.110[.]83/js/jquery.min.js

-       http://95.179.238[.]3/bak

-       http://91.92.244[.]59:8080/mbPHenSdr6Cf79XDAcKEVA

-       31.220.30[.]244

-       http://172.245.60[.]61:8443/SMUkbpX-0qNtLGsuCIuffAOLk9ZEBCG7bIcB2JT6GA/

-       http://172.245.60[.]61/ivanti

-       http://89.23.107[.]155:8080/l-5CzlHWjkp23gZiVLzvUg

-       http://185.156.72[.]51:8080/h7JpYIZZ1-rrk98v3YEy6w

-       http://185.156.72[.]51:8080/8uSQsOTwFyEAsXVwbAJ2mA

-       http://185.156.72[.]51:8080/vuln

-       185.156.72[.]51:4440

-       185.156.72[.]51:8080

-       185.156.72[.]51:4433

-       185.156.72[.]51:4446

-       185.156.72[.]51:4445

-       http://185.156.72[.]51/set.py

-       185.156.72[.]51:7777

-       45.9.151[.]107:7070

-       185.195.59[.]74:7070

-       185.195.59[.]74:20958

-       185.195.59[.]74:34436

-       185.195.59[.]74:37464

-       185.195.59[.]74:41468    

References

[1] https://forums.ivanti.com/s/article/CVE-2023-46805-Authentication-Bypass-CVE-2024-21887-Command-Injection-for-Ivanti-Connect-Secure-and-Ivanti-Policy-Secure-Gateways?language=en_US

[2] https://forums.ivanti.com/s/article/KB-CVE-2023-46805-Authentication-Bypass-CVE-2024-21887-Command-Injection-for-Ivanti-Connect-Secure-and-Ivanti-Policy-Secure-Gateways?language=en_US

[3] https://www.volexity.com/blog/2024/01/10/active-exploitation-of-two-zero-day-vulnerabilities-in-ivanti-connect-secure-vpn/

[4] https://www.mandiant.com/resources/blog/suspected-apt-targets-ivanti-zero-day

[5] https://www.greynoise.io/blog/ivanti-connect-secure-exploited-to-install-cryptominers

[6] https://www.volexity.com/blog/2024/01/18/ivanti-connect-secure-vpn-exploitation-new-observations/

[7] https://censys.com/the-mass-exploitation-of-ivanti-connect-secure/

[8] https://darktrace.com/blog/entry-via-sentry-analyzing-the-exploitation-of-a-critical-vulnerability-in-ivanti-sentry

[9] https://forums.ivanti.com/s/article/CVE-2023-46805-Authentication-Bypass-CVE-2024-21887-Command-Injection-for-Ivanti-Connect-Secure-and-Ivanti-Policy-Secure-Gateways?language=en_US  

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.
Written by
Sam Lister
Specialist Security Researcher

More in this series

No items found.

Blog

/

Network

/

April 2, 2026

How Chinese-Nexus Cyber Operations Have Evolved – And What It Means For Cyber Risk and Resilience 

Chinese-Nexus Cyber OperationsDefault blog imageDefault blog image

Cybersecurity has traditionally organized risk around incidents, breaches, campaigns, and threat groups. Those elements still matter—but if we fixate on individual incidents, we risk missing the shaping of the entire ecosystem. Nation‑state–aligned operators are increasingly using cyber operations to establish long-term strategic leverage, not just to execute isolated attacks or short‑term objectives.  

Our latest research, Crimson Echo, shifts the lens accordingly. Instead of dissecting campaigns, malware families, or actor labels as discrete events, the threat research team analyzed Chinese‑nexus activity as a continuum of behaviors over time. That broader view reveals how these operators position themselves within environments: quietly, patiently, and persistently—often preparing the ground long before any recognizable “incident” occurs.  

How Chinese-nexus cyber threats have changed over time

Chinese-nexus cyber activity has evolved in four phases over the past two decades. This ranges from early, high-volume operations in the 1990s and early 2000s to more structured, strategically-aligned activity in the 2010s, and now toward highly adaptive, identity-centric intrusions.  

Today’s phase is defined by scale, operational restraint, and persistence. Attackers are establishing access, evaluating its strategic value, and maintaining it over time. This reflects a broader shift: cyber operations are increasingly integrated into long-term economic and geopolitical strategies. Access to digital environments, specifically those tied to critical national infrastructure, supply chains, and advanced technology, has become a form of strategic leverage for the long-term.  

How Darktrace analysts took a behavioral approach to a complex problem

One of the challenges in analyzing nation-state cyber activity is attribution. Traditional approaches often rely on tracking specific threat groups, malware families, or infrastructure. But these change constantly, and in the case of Chinese-nexus operations, they often overlap.

Crimson Echo is the result of a retrospective analysis of three years of anomalous activity observed across the Darktrace fleet between July 2022 and September 2025. Using behavioral detection, threat hunting, open-source intelligence, and a structured attribution framework (the Darktrace Cybersecurity Attribution Framework), the team identified dozens of medium- to high-confidence cases and analyzed them for recurring operational patterns.  

This long-horizon, behavior-centric approach allows Darktrace to identify consistent patterns in how intrusions unfold, reinforcing that behavioral patterns that matter.  

What the data shows

Several clear trends emerged from the analysis:

  • Targeting is concentrated in strategically important sectors. Across the dataset, 88% of intrusions occurred in organizations classified as critical infrastructure, including transportation, critical manufacturing, telecommunications, government, healthcare, and Information Technology (IT) services.  
  • Strategically important Western economies are a primary focus. The US alone accounted for 22.5% of observed cases, and when combined with major European economies including Germany, Italy, Spain and the UK, over half of all intrusions (55%) were concentrated in these regions.  
  • Nearly 63% of intrusions of intrusions began with the exploitation of internet-facing systems, reinforcing the continued risk posed by externally exposed infrastructure.  

Two models of cyber operations

Across the dataset, Chinese-nexus activity followed two operational models.  

The first is best described as “smash and grab.” These are short-horizon intrusions optimized for speed. Attackers move quickly – often exfiltrating data within 48 hours – and prioritize scale over stealth. The median duration of these compromises is around 10 days. It’s clear they are willing to risk detection for short-term gain.  

The second is “low and slow.” These operations were less prevalent in the dataset, but potentially more consequential. Here, attackers prioritize persistence, establishing durable access through identity systems and legitimate administrative tools, so they can maintain access undetected for months or even years. In one notable case, the actor had fully compromised the environment and established persistence, only to resurface in the environment more than 600 days after. The operational pause underscores both the depth of the intrusion and the actor’s long‑term strategic intent. This suggests that cyber access is a strategic asset to preserve and leverage over time, and we observed these attacks most often inin sectors of the high strategic importance.  

It’s important to note that the same operational ecosystem can employ both models concurrently, selecting the appropriate model based on target value, urgency, intended access. The observation of a “smash and grab” model should not be solely interpreted as a failure of tradecraft, but instead an operational choice likely aligned with objectives. Where “low and slow” operations are optimized for patience, smash and grab is optimized for speed; both seemingly are deliberate operational choices, not necessarily indicators of capability.  

Rethinking cyber risk

For many organizations, cyber risk is still framed as a series of discrete events. Something happens, it is detected and contained, and the organization moves on. But persistent access, particularly in deeply interconnected environments that span cloud, identity-based SaaS and agentic systems, and complex supply chain networks, creates a major ongoing exposure risk. Even in the absence of disruption or data theft, that access can provide insight into operations, dependencies, and strategic decision-making. Cyber risk increasingly resembles long-term competitive intelligence.  

This has impact beyond the Security Operations Center. Organizations need to shift how they think about governance, visibility, and resilience, and treat cyber exposure as a structural business risk instead of an incident response challenge.  

What comes next

The goal of this research is to provide a clearer understanding of how these operations work, so defenders can recognize them earlier and respond more effectively. That includes shifting from tracking indicators to understanding behaviors, treating identity providers as critical infrastructure risks, expanding supplier oversight, investing in rapid containment capabilities, and more.  

Learn more about the findings of Darktrace’s latest research, Crimson Echo: Understanding Chinese-nexus Cyber Operations Through Behavioral Analysis, by downloading the full report and summaries for business leaders, CISOs, and SOC analysts here.  

Continue reading
About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO

Blog

/

Proactive Security

/

April 1, 2026

AI-powered security for a rapidly growing grocery enterprise

Default blog imageDefault blog image

Protecting a complex, fast-growing retail organization

For this multi-banner grocery holding organization, cybersecurity is considered an essential business enabler, protecting operations, growth, and customer trust. The organization’s lean IT team manages a highly distributed environment spanning corporate offices, 100+ stores, distribution centers and  thousands of endpoints, users, and third-party connections.

Mergers and acquisitions fueled rapid growth, but they also introduced escalating complexity that constrained visibility into users, endpoints, and security risks inherited across acquired environments.

Closing critical visibility gaps with limited resources

Enterprise-wide visibility is a top priority for the organization, says the  Vice President of Information Technology. “We needed insights beyond the perimeter into how users and devices were behaving across the organization.”

A security breach that occurred before the current IT leadership joined the company reinforced the urgency and elevated cybersecurity to an executive-level priority with a focus on protecting customer trust. The goal was to build a multi-layered security model that could deliver autonomous, enterprise-wide protection without adding headcount.

Managing cyber risk in M&A

Mergers and acquisitions are central to the grocery holding company’s growth strategy. But each transaction introduces new cyber risk, including inherited network architectures, inconsistent tooling, excessive privileges, and remnants of prior security incidents that were never fully remediated.

“Our M&A targets range from small chains with a single IT person and limited cyber tools to large chains with more developed IT teams, toolsets and instrumentation,” explains the VP of IT. “We needed a fast, repeatable, and reliable way to assess cyber risk before transactions closed.”

AI-driven security built for scale, speed, and resilience

Rather than layering additional point tools onto an already complex environment, the retailer adopted the Darktrace ActiveAI Security Platform™ in 2020 as part of a broader modernization effort to improve resilience, close visibility gaps, and establish a security foundation that could scale with growth.

“Darktrace’s AI-driven approach provided the ideal solution to these challenges,” shares the VP of IT. “It has empowered our organization to maintain a robust security strategy, ensuring the protection of our network and the smooth operation of our business.”

Enterprise-wide visibility into traffic  

By monitoring both north-south and east-west traffic and applying Self-Learning AI, Darktrace develops a dynamic understanding of how users and devices normally behave across locations, roles, and systems.

“Modeling normal behavior across the environment enables us to quickly spot behavior that doesn’t fit. Even subtle changes that could signal a threat but appear legitimate at first glance,” explains the VP of IT.

Real-time threat containment, 24/7

Adopting autonomous response has created operational breathing room for the security team, says the company’s Cybersecurity  Engineer.

“Early on, we enabled full Darktrace autonomous mode and we continue to do so today,” shares the IT Security Architect. “Allowing the technology to act first gives us the time we need to investigate incidents during business hours without putting the business at risk.”

Unified, actionable view of security ecosystem

The grocery retailer integrated Darktrace with its existing security ecosystem of firewalls, vulnerability management tools, and endpoint detection and response, and the VP of IT described the adoption process as “exceptionally smooth.”

The team can correlate enterprise-wide security data for a unified and actionable picture of all activity and risk. Using this “single pane of glass” approach, the retailer trains Level 1 and Level 2 operations staff to assist with investigations and user follow-ups, effectively extending the reach of the security function without expanding headcount.

From reactive defense to security at scale

With Darktrace delivering continuous visibility, autonomous containment, and integrated security workflows, the organization has strengthened its cybersecurity posture while improving operational efficiency. The result is a security model that not only reduces risk, but also supports growth, resilience, and informed decision-making at the business level.

Faster detection, faster resolution

With autonomous detection and response, the retailer can immediately contain risk while analysts investigate and validate activity. With this approach, the company can maintain continuous protection even outside business hours and reduce the chance of lateral spread across systems or locations.

Enterprise-grade protection with a lean team

From cloud environments to clients to SaaS collaboration tools, Darktrace provides holistic autonomous AI defense, processing petabytes of the organization’s network traffic and investigating millions of individual events that could be indicative of a wider incident.

Today, Darktrace autonomously conducts the majority of all investigations on behalf of the IT team, escalating only a tiny fraction for analyst review. The impact has been profound, freeing analysts from endless alerts and hours of triage so they can focus on more valuable, proactive, and gratifying work.

“From an operational perspective, Darktrace gives us time back,” says the Cybersecurity Engineer. More importantly, says the VP of IT, “it gives us peace of mind that we’re protected even if we’re not actively monitoring every alert.”

A strategic input for M&A decision-making

One of the most strategic outcomes has been the role of cybersecurity on M&A. 90 days prior to closing a transaction, the security team uses Darktrace alongside other tools to perform a cyber risk assessment of the potential acquisition. “Our approach with Darktrace has consistently identified gaps and exposed risks,” says the VP of IT, including:

  • Remnants of previous incidents that were never fully remediated
  • Network configurations with direct internet exposure
  • Excessive administrative privileges in Active Directory or on critical hosts

While security findings may not alter deal timelines, the VP of IT says they can have enormous business implications. “With early visibility into these risks, we can reduce exposure to inherited cyber threats, strengthen our position during negotiations, and establish clear remediation requirements.”

A security strategy built to evolve with the business

As the holding group expands its cloud footprint, it will extend Darktrace protections into Azure, applying the same AI-driven visibility and autonomous response to cloud workloads. The VP of IT says Darktrace's evolving capabilities will be instrumental in addressing the organization’s future cybersecurity needs and ability to adapt to the dynamic nature of cloud security.

“With Darktrace’s AI-driven approach, we have moved beyond reactive defense, establishing a resilient security foundation for confident expansion and modernization.”

Continue reading
About the author
Your data. Our AI.
Elevate your network security with Darktrace AI