Blog

Inside the SOC

Post-Exploitation Activities of Ivanti CS/PS Appliances

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

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”.

Darktrace DETECT™ identified 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, Darktrace RESPOND™ containted attackers’ operations by autonomously blocking suspicious patterns of network traffic as soon as they were identified by Darktrace DETECT.

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 DETECT 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 DETECT 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 RESPOND 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 DETECT 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 DETECT 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 RESPOND, 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 DETECT 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 DETECT 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 RESPOND 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.
AUTHOR
ABOUT ThE AUTHOR
Sam Lister
SOC Analyst
Book a 1-1 meeting with one of our experts
share this article
USE CASES
No items found.
PRODUCT SPOTLIGHT
No items found.
COre coverage
No items found.

More in this series

No items found.

Blog

Inside the SOC

Post-Exploitation Activities on PAN-OS Devices: A Network-Based Analysis

Default blog imageDefault blog image
20
Jun 2024

Introduction

Perimeter devices such as firewalls, virtual private networks (VPNs), and intrusion prevention systems (IPS), have long been the target of adversarial actors attempting to gain access to internal networks. However, recent publications and public service announcements by leading public institutions underscore the increased emphasis threat actors are putting on leveraging such products to initiate compromises.

A blog post by the UK National Cyber Security Center (NCSC) released in early 2024 notes that as improvements are made in the detection of phishing email payloads, threat actors have again begun re-focusing efforts to exploiting network edge devices, many of which are not secure by design, as a means of breach initiation.[i] As such, it comes as no surprise that new Common Vulnerabilities and Exposures (CVEs) are constantly discovered that exploit such internet-exposed systems.

Darktrace analysts frequently observe the impacts of such CVEs first through their investigations via Darktrace’s Security Operations Center (SOC), sometimes even before the public disclosure of proof of concepts for such exploits.  Beginning April 2024, Darktrace’s SOC began handling alerts and customer requests for potential incidents involving Palo Alto Networks firewall devices.  It was during this time that external researchers publicly disclosed what would later be classified as PAN-OS CVE-2024-3400, a form of remote command execution vulnerability that affects several versions of Palo Alto Networks’ firewall operating System (PAN-OS), namely PAN-OS 11.1, 11.0 and 10.2.

The increase in observed SOC activity for Palo Alto firewall devices, coupled with the public announcement of the new CVE, prompted Darktrace researchers to look for evidence of PAN-OS exploitation on customer networks. Researchers also focused on documenting post-exploitation activity from threat actors leveraging the recently disclosed vulnerability.

As such, this blog highlights the network-based behaviors involved in the CVE-2024-3400 attack chains investigated by Darktrace’s SOC and Threat Research teams. Moreover, this investigation also provides a deeper insight into the post-compromise activities of threat actors leveraging the novel CVE.  Such insights will not only prove relevant for cybersecurity teams looking to inhibit compromises in this specific instance, but also highlights general patterns of behavior by threat actors utilizing such CVEs to target internet-facing systems.

CVE-2024-3400

In April 2024, the Darktrace SOC observed an uptick in activity involving recurring patterns of malicious activity from Palo Alto firewall appliances. In response to this trend, Darktrace initiated a Threat Research investigation into such activity to try and identify common factors and indicators across seemingly parallel events. As the Threat Research team opened their investigation, external researchers concurrently provided public details of CVE-2024-3400, a form of remote command execution vulnerability in the GlobalProtect feature on Palo Alto Network firewall devices running PAN-OS versions: 10.2, 11.0, and 11.1.[ii]

In their proof of concept, security researchers at watchTowr demonstrated how an attacker can pass session ID (SESSID) values to these PAN-OS devices to request files that do not exist. In response, the system creates a zero-byte file with root privileges with the same name.[iii] Log data is passed on devices running telemetry services to external servers through command line functionality.[iv] Given this functionality, external actors could then request non-existent files in the SESSID containing command parameters which then be interpreted by the command line functionality.[v] Although researchers first believed the exploit could only be used against devices running telemetry services, this was later discovered to be untrue.[vi]

As details of CVE-2024-3400 began to surface, Darktrace’s Threat Research analysts quickly identified distinct overlaps in the observed activity on specific customer deployments and the post-exploitation behavior reported by external researchers. Given the parallels, Darktrace correlated the patterns of activity observed by the SOC team to exploitation of the newly discovered vulnerability in PAN-OS firewall appliances.

Campaign Analysis

Between the April and May 2024, Darktrace identified four main themes of post-exploitation activity involving Palo Alto Network firewall devices likely targeted via CVE-2024-3400: exploitation validation, shell command and tool retrieval, configuration data exfiltration, and ongoing command and control through encrypted channels and application protocols.

1. Exploit Validation and Further Vulnerability Enumeration

Many of the investigated attack chains began with malicious actors using out-of-band application security testing (OAST) services such as Interactsh to validate exploits against Palo Alto firewall appliances. This exploit validation activity typically resulted in devices attempting to contact unusual external endpoints (namely, subdomains of ‘oast[.]pro’, ‘oast[.]live’, ‘oast[.]site’, ‘oast[.]online’, ‘oast[.]fun’, ‘oast[.]me’, and ‘g3n[.]in’) associated with OAST services such as Interactsh. These services can be used by developers to inspect and debug internet traffic, but also have been easily abused by threat actors.

While attempted connections to OAST services do not alone indicate CVE-2024-3400 exploitation, the prevalence of such activities in observed Palo Alto firewall attack chains suggests widespread usage of these OAST services to validate initial access methods and possibly further enumerate systems for additional vulnerabilities.

Figure 1: Model alert log details showcasing a PAN-OS device making DNS queries for Interactsh domain names in what could be exploit validation, and/or further host enumeration.

2. Command and Payload Transmission

The most common feature across analyzed incidents was HTTP GET requests for shell scripts and Linux executable files (ELF) from external IPs associated with exploitation of the CVE. These HTTP requests were frequently initiated using the utilities, cURL and wget. On nearly every device likely targeted by threat actors leveraging the CVE, Darktrace analysts highlighted the retrieval of shell scripts that either featured enumeration commands, the removal of evidence of compromise activity, or commands to retrieve and start binaries on the destination device.

a) Shell Script Retrieval

Investigated devices commonly performed HTTP GET requests to retrieve shell command scripts. Despite this commonality, there was some degree of variety amongst the retrieved payloads and their affiliation with certain command tools. Several distinct types of shell commands and files were identified during the analyzed breaches. For example, some firewall devices were seen requesting .txt files associated with both Sliver C2, whose malicious use has previously been investigated by Darktrace, and Cobalt Strike. The target URIs of devices’ HTTP requests for these files included, “36shr.txt”, “2.txt”, “bin.txt”, and “data.txt”.

More interestingly, though, was the frequency with which analyzed systems requested bash scripts from rare external IP addresses, sometimes over non-standard ports for the HTTP protocol. These bash scripts would feature commands usually for the recipient system to check for certain existing files and or running processes. If the file did not exist, the system would then use cURL or wget to obtain content from external sites, change the permissions of the file, and then execute, sending output to dev/null as a means of likely defense evasion. In some scripts, the system would first make a new folder, and change directories prior to acquiring external content. Additionally, some samples highlighted multiple attempts at enumeration of the host system.

Figure 2: Packet capture (PCAP) data highlighting the incoming shell scripts providing instructions to use cURL to obtain external content, change the permissions of the file to execute, and then run the binary using the credentials and details provided.
Figure 3: PCAP data highlighting a variation of a shell script seen in an HTTP response processed by compromised devices. The script provides instructions to make a directory, retrieve and execute external content, and to hide the output.

Not every retrieved file that was not explicitly a binary featured bash scripts. Model alerts on some deployments also included file masquerading attempts by threat actors, whereby the Palo Alto firewall device would request content with a misleading extension in the URI. In one such instance, the requested URI, and HTTP response header suggests the returned content is an image/png, but the actual body response featured configuration parameters for a new daemon service to be run on the system.

Figure 4: PCAP data indicating configuration details likely for a new daemon on an investigated host. Such HTTP body content differs from the image/png extension within the request URI and declared content type in the HTTP response header.

Bash scripts analyzed across customer deployments also mirrored those identified by external security teams. External researchers previously reported on a series of identifiable shell commands in some cases of CVE-2024-3400 exploitation analyzed by their teams. Commands frequently involved a persistence mechanism they later labeled as the “UPSTYLE” backdoor.[vii]  This python-based program operates by reading commands hidden in error logs generated by 404 requests to the compromised server. The backdoor interprets the requests and writes the output to CSS files on the device. In many cases, Darktrace’s Threat Research team noted clear parallels between shell commands retrieved via HTTP GET request with those directly involving UPSTYLE. There were also matches with some URI patterns identified with the backdoor and requests observed on Darktrace deployments.

Figure 5: HTTP response data containing shell commands potentially relating to the UPSTYLE backdoor.

The presence of these UPSTYLE-related shell commands in response to Palo Alto firewall devices’ HTTP requests provides further evidence for initial exploitation of the CVE. Many bash scripts in examined cases interacted with folders and files likely related to CVE-2024-3400 exploitation. These scripts frequently sought to delete contents of certain folders, such as “/opt/panlogs/tmp/device_telemetry/minute/*” where evidence of exploitation would likely reside. Moreover, recursive removal and copy commands were frequently seen targeting CSS files within the GlobalProtect folder, already noted as the vulnerable element within PAN-OS versions. This evidence is further corroborated by host-based forensic analysis conducted by external researchers.[viii]

Figure 6: PCAP data from investigated system indicating likely defense evasion by removing content on folders where CVE exploitation occurred.

b) Executable File Retrieval

Typically, following command processing, compromised Palo Alto firewall devices proceeded to make web requests for several unusual and potentially malicious files. Many such executables would be retrieved via processed scripts. While there a fair amount of variety in specific executables and binaries obtained, overall, these executables involved either further command tooling such as Sliver C2 or Cobalt Strike payloads, or unknown executables. Affected systems would also employ uncommon ports for HTTP connections, in a likely attempt to evade detection. Extensions featured within the URI, when visible, frequently noted ‘.elf’ (Linux executable) or ‘.exe’ payloads. While most derived hashes did not feature identifiable open-source intelligence (OSINT) details, some samples did have external information tying the sample to specific malware. For example, one such investigation featured a compromised system requesting a file with a hash identified as the Spark malware (backdoor) while another investigated case included a host requesting a known crypto-miner.

Figure 7: PCAP data highlighting compromised system retrieving ELF content from a rare external server running a simple Python HTTP server.
Figure 8: Darktrace model alert logs highlighting a device labeled “Palo Alto” making a HTTP request on an uncommon port for an executable file following likely CVE exploitation.

3. Configuration Data Exfiltration and Unusual HTTP POST Activity

During Darktrace’s investigations, there were also several instances of sensitive data exfiltration from PAN-OS firewall devices. Specifically, targeted systems were observed making HTTP POST requests via destination port 80 to rare external endpoints that OSINT sources associate with CVE-2024-3400 exploitation and activity. PCAP analysis of such HTTP requests revealed that they often contained sensitive configuration details of the targeted Palo Alto firewall devices, including the IP address, default gateway, domain, users, superusers, and password hashes, to name only a few. Threat actors frequently utilized Target URIs such as “/upload” in their HTTP POST requests of this multi-part boundary form data. Again, the User-Agent headers of these HTTP requests largely involved versions of cURL, typically 7.6.1, and wget.

Figure 9: PCAP datahighlighting Palo Alto Firewall device running vulnerable version of PAN-OSposting configuration details to rare external services via HTTP.
Figure 10: Model alert logs highlighting a Palo Alto firewall device performing HTTP POSTs to a rare external IP, without a prior hostname lookup, on an uncommon port using a URI associated with configuration data exfiltration across analyzed incidents
Figure 11: Examples of TargetURIs of HTTP POST requests involving base64 encoded IPs and potential dataegress.

4. Ongoing C2 and Miscellaneous Activity

Lastly, a smaller number of affected Palo Alto firewall devices were seen engaging in repeated beaconing and/or C2 communication via both encrypted and unencrypted protocols during and following the initial series of kill chain events. Such encrypted channels typically involved protocols such as TLS/SSL and SSH. This activity likely represented ongoing communication of targeted systems with attacker infrastructure. Model alerts typically highlighted unusual levels of repeated external connectivity to rare external IP addresses over varying lengths of time. In some investigated incidents, beaconing activity consisted of hundreds of thousands of connections over several days.

Figure 12:  Advanced search details highlighting high levels of ongoing external communication to endpoints associated with C2 infrastructure exploiting CVE-2024-3400.

Some beaconing activity appears to have involved the use of the WebSocket protocol, as indicated by the appearance of “/ws” URIs and validated within packet captures. Such connections were then upgraded to an encrypted connection.

Figure 13:  PCAP highlighting use of WebSocket protocol to engage in ongoing external connectivity to likely C2 infrastructure following CVE-2024-3400 compromise.

While not directly visible in all the deployments, some investigations also yielded evidence of attempts at further post-exploitation activity. For example, a handful of the analyzed binaries that were downloaded by examined devices had OSINT information suggesting a relation to crypto-mining malware strains. However, crypto-mining activity was not directly observed at this time. Furthermore, several devices also triggered model alerts relating to brute-forcing activity via several authentication protocols (namely, Keberos and RADIUS) during the time of compromise. This brute-force activity likely represented attempts to move laterally from the affected firewall system to deeper parts of the network.

Figure 14: Model alert logs noting repeated SSL connectivity to a Sliver C2-affiliated endpoint in what likely constitutes C2 connectivity.
Figure 15: Model alert logs featuring repeated RADIUS login failures from a compromised PAN-OS device using generic usernames, suggesting brute-force activity.

Conclusion

Between April and late May 2024, Darktrace’s SOC and Threat Research teams identified several instances of likely PAN-OS CVE-2024-3400 exploitation across the Darktrace customer base. The subsequent investigation yielded four major themes that categorize the observed network-based post-exploitation activity. These major themes were exploit validation activity, retrieval of binaries and shell scripts, data exfiltration via HTTP POST activity, and ongoing C2 communication with rare external endpoints. The insights shared in this article will hopefully contribute to the ongoing discussion within the cybersecurity community about how to handle the likely continued exploitation of this vulnerability. Moreover, this article may also help cybersecurity professionals better respond to future exploitation of not only Palo Alto PAN-OS firewall devices, but also of edge devices more broadly.

Threat actors will continue to discover and leverage new CVEs impacting edge infrastructure. Since it is not yet known which CVEs threat actors will exploit next, relying on rules and signatures for the detection of exploitation of such CVEs is not a viable approach. Darktrace’s anomaly-based approach to threat detection, however, is well positioned to robustly adapt to threat actors’ changing methods, since although threat actors can change the CVEs they exploit, they cannot change the fact that their exploitation of CVEs results in highly unusual patterns of activity.

Credit to Adam Potter, Cyber Analyst, Sam Lister, Senior Cyber Analyst

Appendices

Indicators of Compromise

Indicator – Type – Description

94.131.120[.]80              IP             C2 Endpoint

94.131.120[.]80:53/?src=[REDACTED]=hour=root                  URL        C2/Exfiltration Endpoint

134.213.29[.]14/?src=[REDACTED]min=root             URL        C2/Exfiltration Endpoint

134.213.29[.]14/grep[.]mips64            URL        Payload

134.213.29[.]14/grep[.]x86_64             URL        Payload

134.213.29[.]14/?deer               URL        Payload

134.213.29[.]14/?host=IDS   URL        Payload

134.213.29[.]14/ldr[.]sh           URL        Payload

91ebcea4e6d34fd6e22f99713eaf67571b51ab01  SHA1 File Hash               Payload

185.243.115[.]250/snmpd2[.]elf        URL        Payload

23.163.0[.]111/com   URL        Payload

80.92.205[.]239/upload            URL        C2/Exfiltration Endpoint

194.36.171[.]43/upload            URL        C2/Exfiltration Endpoint

update.gl-protect[.]com          Hostname         C2 Endpoint

update.gl-protect[.]com:63869/snmpgp      URL        Payload

146.70.87[.]237              IP address         C2 Endpoint

146.70.87[.]237:63867/snmpdd         URL        Payload

393c41b3ceab4beecf365285e8bdf0546f41efad   SHA1 File Hash               Payload

138.68.44[.]59/app/r URL        Payload

138.68.44[.]59/app/clientr     URL        Payload

138.68.44[.]59/manage            URL        Payload

72.5.43[.]90/patch      URL        Payload

217.69.3[.]218                 IP             C2 Endpoint

5e8387c24b75c778c920f8aa38e4d3882cc6d306                  SHA1 File Hash               Payload

217.69.3[.]218/snmpd[.]elf   URL        Payload

958f13da6ccf98fcaa270a6e24f83b1a4832938a    SHA1 File Hash               Payload

6708dc41b15b892279af2947f143af95fb9efe6e     SHA1 File Hash               Payload

dc50c0de7f24baf03d4f4c6fdf6c366d2fcfbe6c       SHA1 File Hash               Payload

109.120.178[.]253:10000/data[.]txt                  URL        Payload

109.120.178[.]253:10000/bin[.]txt   URL        Payload

bc9dc2e42654e2179210d98f77822723740a5ba6                 SHA1 File Hash               Payload

109.120.178[.]253:10000/123              URL        Payload

65283921da4e8b5eabb926e60ca9ad3d087e67fa                 SHA1 File Hash               Payload

img.dxyjg[.]com/6hiryXjZN0Mx[.]sh                  URL        Payload

149.56.18[.]189/IC4nzNvf7w/2[.]txt                 URL        Payload

228d05fd92ec4d19659d71693198564ae6f6b117 SHA1 File Hash               Payload

54b892b8fdab7c07e1e123340d800e7ed0386600                 SHA1 File Hash               Payload

165.232.121[.]217/rules          URL        Payload

165.232.121[.]217/app/request          URL        Payload

938faec77ebdac758587bba999e470785253edaf SHA1 File Hash               Payload

165.232.121[.]217/app/request63   URL        Payload

165.232.121[.]217:4443/termite/165.232.121[.]217             URL        Payload

92.118.112[.]60/snmpd2[.]elf               URL        Payload

2a90d481a7134d66e8b7886cdfe98d9c1264a386                 SHA1 File Hash               Payload

92.118.112[.]60/36shr[.]txt   URL        Payload

d6a33673cedb12811dde03a705e1302464d8227f                 SHA1 File Hash               Payload

c712712a563fe09fa525dfc01ce13564e3d98d67  SHA1 File Hash               Payload

091b3b33e0d1b55852167c3069afcdb0af5e5e79 SHA1 File Hash               Payload

5eebf7518325e6d3a0fd7da2c53e7d229d7b74b6                  SHA1 File Hash               Payload

183be7a0c958f5ed4816c781a2d7d5aa8a0bca9f SHA1 File Hash               Payload

e7d2f1224546b17d805617d02ade91a9a20e783e                 SHA1 File Hash               Payload

e6137a15df66054e4c97e1f4b8181798985b480d SHA1 File Hash               Payload

95.164.7[.]33:53/sea[.]png    URL        Payload

95.164.7[.]33/rules     URL        Payload

95.164.7[.]33:53/lb64                URL        Payload

c2bc9a7657bea17792048902ccf2d77a2f50d2d7 SHA1 File Hash               Payload

923369bbb86b9a9ccf42ba6f0d022b1cd4f33e9d SHA1 File Hash               Payload

52972a971a05b842c6b90c581b5c697f740cb5b9                 SHA1 File Hash               Payload

95d45b455cf62186c272c03d6253fef65227f63a    SHA1 File Hash               Payload

322ec0942cef33b4c55e5e939407cd02e295973e                  SHA1 File Hash               Payload

6335e08873b4ca3d0eac1ea265f89a9ef29023f2  SHA1 File Hash               Payload

134.213.29[.]14              IP             C2 Endpoint

185.243.115[.]250       IP             C2 Endpoint

80.92.205[.]239              IP             C2 Endpoint

194.36.171[.]43              IP             C2 Endpoint

92.118.112[.]60              IP             C2 Endpoint

109.120.178[.]253       IP             C2 Endpoint

23.163.0[.]111                 IP             C2 Endpoint

72.5.43[.]90     IP             C2 Endpoint

165.232.121[.]217       IP             C2 Endpoint

8.210.242[.]112              IP             C2 Endpoint

149.56.18[.]189              IP             C2 Endpoint

95.164.7[.]33  IP             C2 Endpoint

138.68.44[.]59                 IP             C2 Endpoint

Img[.]dxyjg[.]com         Hostname         C2 Endpoint

Darktrace Model Alert Coverage

·      Anomalous File / Masqueraded File Transfer

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Multiple EXE from Rare External Locations

·      Anomalous File / Script from Rare External Location

·      Anomalous File / Script and EXE from Rare External

·      Anomalous File / Suspicious Octet Stream Download

·      Anomalous File / Numeric File Download

·      Anomalous Connection / Application Protocol on Uncommon Port

·      Anomalous Connection / New User Agent to IP Without Hostname

·      Anomalous Connection / Posting HTTP to IP Without Hostname

·      Anomalous Connection / Multiple Failed Connections to Rare Endpoint

·      Anomalous Connection / Suspicious Self-Signed SSL

·      Anomalous Connection / Anomalous SSL without SNI to New External

·      Anomalous Connection / Multiple Connections to New External TCP Port

·      Anomalous Connection / Rare External SSL Self-Signed

·      Anomalous Server Activity / Outgoing from Server

·      Anomalous Server Activity / Rare External from Server

·      Compromise / SSH Beacon

·      Compromise / Beacon for 4 Days

·      Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

·      Compromise / High Priority Tunnelling to Bin Services

·      Compromise / Sustained SSL or HTTP Increase

·      Compromise / Connection to Suspicious SSL Server

·      Compromise / Suspicious File and C2

·      Compromise / Large Number of Suspicious Successful Connections

·      Compromise / Slow Beaconing Activity To External Rare

·      Compromise / HTTP Beaconing to New Endpoint

·      Compromise / SSL or HTTP Beacon

·      Compromise / Suspicious HTTP and Anomalous Activity

·      Compromise / Beacon to Young Endpoint

·      Compromise / High Volume of Connections with Beacon Score

·      Compromise / Suspicious Beaconing Behaviour

·      Compliance / SSH to Rare External Destination

·      Compromise / HTTP Beaconing to Rare Destination

·      Compromise / Beaconing Activity To External Rare

·      Device::New User Agent

·      Device / Initial Breach Chain Compromise

·      Device / Multiple C2 Model Breaches

MITRE ATTACK Mapping

Tactic – Technique

Initial Access  T1190 – Exploiting Public-Facing Application

Execution           T1059.004 – Command and Scripting Interpreter: Unix Shell

Persistence      T1543.002 – Create or Modify System Processes: Systemd Service

Defense Evasion           T1070.004 – Indicator Removal: File Deletion

Credential Access       T1110.001 – Brute Force: Password Guessing

Discovery           T1083 – File and System Discovery

T1057 – Process Discovery

Collection         T1005 – Data From Local System

Command and Control             T1071.001 – Application Layer Protocol:  Web Protocols

T1573.002 – Encrypted Channel: Asymmetric Cryptography

T1571 – Non-Standard Port

T1105 – Ingress Tool Transfer

Exfiltration         T1041 – Exfiltration over C2 Protocol

T1048.002 - Exfiltration Over Alternative Protocol: Exfiltration Over Asymmetric Encrypted Non-C2 Protocol

References

[i]  https://www.ncsc.gov.uk/blog-post/products-on-your-perimeter

[ii] https://security.paloaltonetworks.com/CVE-2024-3400

[iii] https://labs.watchtowr.com/palo-alto-putting-the-protecc-in-globalprotect-cve-2024-3400/

[iv] https://labs.watchtowr.com/palo-alto-putting-the-protecc-in-globalprotect-cve-2024-3400/

[v] https://labs.watchtowr.com/palo-alto-putting-the-protecc-in-globalprotect-cve-2024-3400/

[vi] https://security.paloaltonetworks.com/CVE-2024-3400

[vii] https://www.volexity.com/blog/2024/04/12/zero-day-exploitation-of-unauthenticated-remote-code-execution-vulnerability-in-globalprotect-cve-2024-3400/

[viii] https://www.volexity.com/blog/2024/05/15/detecting-compromise-of-cve-2024-3400-on-palo-alto-networks-globalprotect-devices/

Continue reading
About the author
Adam Potter
Cyber Analyst

Safeguarding Distribution Centers in the Digital Age

Default blog imageDefault blog image
12
Jun 2024

Challenges securing distribution centers

For large retail providers, e-commerce organizations, logistics & supply chain organizations, and other companies who rely on the distribution of goods to consumers cybersecurity efforts are often focused on an immense IT infrastructure. However, there's a critical, often overlooked segment of infrastructure that demands vigilant monitoring and robust protection: distribution centers.

Distribution centers play a critical role in the business operations of supply chains, logistics, and the retail industry. They serve as comprehensive logistics hubs, with many organizations operating multiple centers worldwide to meet consumer needs. Depending on their size and hours of operation, even just one hour of downtime at these centers can result in significant financial losses, ranging from tens to hundreds of thousands of dollars per hour.

Due to the time-sensitive nature and business criticality of distribution centers, there has been a rise in applying modern technologies now including AI applications to enhance efficiency within these facilities. Today’s distribution centers are increasingly connected to Enterprise IT networks, the cloud and the internet to manage every stage of the supply chain. Additionally, it is common for organizations to allow 3rd party access to the distribution center networks and data for reasons including allowing them to scale their operations effectively.

However, this influx of new technologies and interconnected systems across IT, OT and cloud introduces new risks on the cybersecurity front. Distribution center networks include industrial operational technologies ICS/OT, IoT technologies, enterprise network technology, and cloud systems working in coordination. The convergence of these technologies creates a greater chance that blind spots exist for security practitioners and this increasing presence of networked technology increases the attack surface and potential for vulnerability. Thus, having cybersecurity measures that cover IT, OT or Cloud alone is not enough to secure a complex and dynamic distribution center network infrastructure.  

The OT network encompasses various systems, devices, hardware, and software, such as:

  • Enterprise Resource Planning (ERP)
  • Warehouse Execution System (WES)
  • Warehouse Control System (WCS)
  • Warehouse Management System (WMS)
  • Energy Management Systems (EMS)
  • Building Management Systems (BMS)
  • Distribution Control Systems (DCS)
  • Enterprise IT devices
  • OT and IoT: Engineering workstations, ICS application and management servers, PLCs, HMI, access control, cameras, and printers
  • Cloud applications

Distribution centers: An expanding attack surface

As these distribution centers have become increasingly automated, connected, and technologically advanced, their attack surfaces have inherently increased. Distribution centers now have a vastly different potential for cyber risk which includes:  

  • More networked devices present
  • Increased routable connectivity within industrial systems
  • Externally exposed industrial control systems
  • Increased remote access
  • IT/OT enterprise to industrial convergence
  • Cloud connectivity
  • Contractors, vendors, and consultants on site or remoting in  

Given the variety of connected systems, distribution centers are more exposed to external threats than ever before. Simultaneously, distribution center’s business criticality has positioned them as interesting targets to cyber adversaries seeking to cause disruption with significant financial impact.

Increased connectivity requires a unified security approach

When assessing the unique distribution center attack surface, the variety of interconnected systems and devices requires a cybersecurity approach that can cover the diverse technology environment.  

From a monitoring and visibility perspective, siloed IT, OT or cloud security solutions cannot provide the comprehensive asset management, threat detection, risk management, and response and remediation capabilities across interconnected digital infrastructure that a solution natively covering IT, cloud, OT, and IoT can provide.  

The problem with using siloed cybersecurity solutions to cover a distribution center is the visibility gaps that are inherently created when using multiple solutions to try and cover the totality of the diverse infrastructure. What this means is that for cross domain and multi-stage attacks, depending on the initial access point and where the adversary plans on actioning their objectives, multiple stages of the attack may not be detected or correlated if they security solutions lack visibility into OT, IT, IoT and cloud.

Comprehensive security under one solution

Darktrace leverages Self-Learning AI, which takes a new approach to cybersecurity. Instead of relying on rules and signatures, this AI trains on the specific business to learn a ‘pattern of life’ that models normal activity for every device, user, and connection. It can be applied anywhere an organization has data, and so can natively cover IT, OT, IoT, and cloud.  

With these models, Darktrace /OT provides improved visibility, threat detection and response, and risk management for proactive hardening recommendations.  

Visibility: Darktrace is the only OT security solution that natively covers IT, IoT and OT in unison. AI augmented workflows ensure OT cybersecurity analysts and operation engineers can manage IT and OT environments, leveraging a live asset inventory and tailored dashboards to optimize security workflows and minimize operator workload.

Threat detection, investigation, and response: The AI facilitates anomaly detection capable of detecting known, unknown, and insider threats and precise response for OT environments that contains threats at their earliest stages before they can jeopardize control systems. Darktrace immediately understands, identifies, and investigates all anomalous activity in OT networks, whether human or machine driven and uses Explainable AI to generate investigation reports via Darktrace’s Cyber AI Analyst.

Proactive risk identification: Risk management capabilities like attack path modeling can prioritize remediation and mitigation that will most effectively reduce derived risk scores. Rather than relying on knowledge of past attacks and CVE lists and scores, Darktrace AI learns what is ‘normal’ for its environment, discovering previously unknown threats and risks by detecting subtle shifts in behavior and connectivity. Through the application of Darktrace AI for OT environments, security teams can investigate novel attacks, discover blind spots, get live-time visibility across all their physical and digital assets, and reduce the time to detect, respond to, and triage security events.

Continue reading
About the author
Daniel Simonds
Director of Operational Technology
Our ai. Your data.

Elevate your cyber defenses with Darktrace AI

Start your free trial
Darktrace AI protecting a business from cyber threats.