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June 20, 2024

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

This blog investigates the network-based activity detected by Darktrace in compromises stemming from the exploitation of a vulnerability in Palo Alto Networks firewall devices, namely CVE-2024-3400.
Written by
Adam Potter
Senior Cyber Analyst
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
Adam Potter
Senior Cyber Analyst
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20
Jun 2024

Update:
Following the initial publication of this blog detailing exploitation campaigns utilizing the recently disclosed vulnerability, Darktrace analysts expanded the scope of the threat research investigation to identify potential earlier, pre-CVE disclosure, exploitation of CVE 2024-3400. While the majority of PAN-OS exploitation activity seen in the Darktrace customer base occurred after the public release of the CVE, Darktrace did also see tooling activity likely related to CVE-2024-3400 exploitation prior to the vulnerability's disclosure. Unlike the post-CVE-release exploitation activity, which largely reflected indiscriminate, opportunistic targeting of unpatched systems, these pre-CVE release activities likely represented selective targeting by more calculated actors.

Between March 26 and 28, Darktrace identified two Palo Alto firewall devices within the network of a public sector customer making HTTP GET requests utilizing both cURL and wget user agents, versions of which were seen in later compromise activity in April. The devices requested multiple shell script files (.sh) from rare external IP addresses. These IPs are likely associated with an operational relay box (ORB) network[1]. The connections also occurred without a specified hostname lookup, suggesting the IPs were hardcoded into process code or already cached through unexpected running processes. One of the destination IPs was later confirmed by Palo Alto Network’s Unit 42 as associated with exploitation of the PAN-OS vulnerability[2]. This observed activity closely resembles post-exploitation activity seen on affected firewall devices in mid-April. However, unlike the more disruptive and noisier follow-on exploitation activity seen in post-CVE-release incidents, the pre-CVE-release case observed by Darktrace appears to have been much more discreet, likely due to the relevant threat actor's desire to remain undetected.

--

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). Beginning in April 2024, Darktrace’s SOC began handling alerts and customer requests for potential incidents involving Palo Alto Networks firewall devices.  Just days prior, 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. At the time, multiple Darktrace customers were unaware of the recently announced vulnerability.

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 mid-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. Shortly before the Threat Research team opened their investigation, external researchers 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 ‍

Pre-CVE-Release IoCs

38.54[.]104[.]14/3.sh
154.223[.]16[.]34/1.sh
154.223[.]16[.]34/co.sh
38.54[.]104[.]14/

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 Connection / New User Agent to IP Without Hostname

·      Device / New User Agent (triggered by pre-CVE-release activity)

·      Anomalous File / Script from Rare External Location (triggered by pre-CVE-release activity)

·      Anomalous File / Masqueraded File Transfer

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Multiple EXE from Rare External Locations

·      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 / 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 / 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

[1] https://cloud.google.com/blog/topics/threat-intelligence/china-nexus-espionage-orb-networks

[2] https://unit42.paloaltonetworks.com/cve-2024-3400/

[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/

‍

Written by
Adam Potter
Senior Cyber Analyst
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
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Adam Potter
Senior Cyber Analyst

Catching a RAT: How Darktrace Neutralized AsyncRAT

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May 13, 2025
Isabel Evans
Cyber Analyst
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Network
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May 13, 2025

Catching a RAT: How Darktrace Neutralized AsyncRAT

Darktrace's AI-driven tools identified and disrupted AsyncRAT activity, detecting suspicious connections and blocking them autonomously. This proactive response prevented the compromise from escalating and safeguarded sensitive data from exfiltration.
Isabel Evans
Cyber Analyst
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Network
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May 8, 2025

Anomaly-Based Threat Hunting: Darktrace's Approach in Action

This blog outlines Darktrace's model-based anomaly detection and how security teams can leverage custom models for targeted threat hunts. Recently, Darktrace's Threat Research team applied this method in their report, "AI & Cybersecurity: The State of Cyber in UK and US Energy Sectors."
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
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Network
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May 1, 2025

SocGholish: From loader and C2 activity to RansomHub deployment

In early 2025, Darktrace uncovered SocGholish-to-RansomHub intrusion chains, including loader and C2 activity, alongside credential harvesting via WebDAV and SCF abuse. Learn more about SocGholish and its kill chain here!
Christina Kreza
Cyber Analyst
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Email

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May 21, 2025

Evaluating Email Security: How to Select the Best Solution for Your Organization

person holding ipadDefault blog imageDefault blog image

When evaluating email security solutions, it’s crucial to move beyond marketing claims and focus on real-world performance. One of the most effective ways to achieve this is through an A/B comparison approach – a side-by-side evaluation of vendors based on consistent, predefined criteria.

This method cuts through biases, reveals true capability differences, and ensures that all solutions are assessed on a level playing field. It’s not just about finding an objectively good solution – it’s about finding the best solution for your organization’s specific needs.

An A/B comparison approach is particularly effective for three main reasons:

  1. Eliminates bias: By comparing solutions under identical conditions, it’s easier to spot differences in performance without the fog of marketing jargon.
  2. Highlights real capabilities: Direct side-by-side testing exposes genuine strengths and weaknesses, making it easier to judge which features are impactful versus merely decorative.
  3. Encourages objective decision-making: This structured method reduces emotional or brand-driven decisions, focusing purely on metrics and performance.

Let’s look at the key factors to consider when setting up your evaluation to ensure a fair, accurate, and actionable comparison.

Deployment: Setting the stage for fair evaluation

To achieve a genuine comparison, deployment must be consistent across all evaluated solutions:

  • Establish the same scope: All solutions should be granted identical visibility across relevant tenants and domains to ensure parity.
  • Set a concrete timeline: Deploy and test each solution with the same dataset, at the same points in time. This allows you to observe differences in learning periods and adaptive capabilities.

Equal visibility and synchronized timelines prevent discrepancies that could skew your understanding of each vendor’s true capabilities. But remember – quicker results might not equal better learning or understanding!

Tuning and configurations: Optimizing for real-world conditions

Properly tuning and configuring each solution is critical for fair evaluation:

  • Compare on optimal performance: Consult with each vendor to understand what optimal deployment looks like for their solution, particularly if machine learning is involved.
  • Consider the long term: Configuration adjustments should be made with long-term usage in mind. Short-term fixes can mask long-term challenges.
  • Data visibility: Ensure each solution can retain and provide search capabilities on all data collected throughout the evaluation period.

These steps guarantee that you are comparing fully optimized versions of each platform, not underperforming or misconfigured ones.

Evaluation: Applying consistent metrics

Once deployment and configurations are aligned, the evaluation itself must be consistent, to prevent unfair scoring and help to identify true differences in threat detection and response capabilities.

  • Coordinate your decision criteria: Ensure all vendors are measured against the same set of criteria, established before testing begins.
  • Understand vendor threat classification: Each vendor may have different ways of classifying threats, so be sure to understand these nuances.
  • Maintain communication: If results seem inaccurate, engage with the vendors. Their response and remediation capabilities are part of the evaluation.

Making a decision: Look beyond the metrics

When it comes to reviewing the performance of each solution, it’s important to both consider and look beyond the raw data. This is about choosing the solution that best aligns with your specific business needs, which may include factors and features not captured in the results.

  • Evaluate based on results: Consider accuracy, threats detected, precision, and response effectiveness.
  • Evaluate beyond results: Assess the overall experience, including support, integrations, training, and long-term alignment with your security strategy.
  • Review and communicate: Internally review the findings and communicate them back to the vendors.

Choosing the right email security solution isn’t just about ticking boxes, it’s about strategic alignment with your organization’s goals and the evolving threat landscape. A structured, A/B comparison approach will help ensure that the solution you select is truly the best fit.

For a full checklist of the features and capabilities to compare, as well as how to perform a commercial and technical evaluation, check out the full Buyer’s Checklist for Evaluating Email Security.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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OT

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May 21, 2025

Adapting to new USCG cybersecurity mandates: Darktrace for ports and maritime systems

Cargo ships at a portDefault blog imageDefault blog image

What is the Marine Transportation System (MTS)?

Marine Transportation Systems (MTS) play a substantial roll in U.S. commerce, military readiness, and economic security. Defined as a critical national infrastructure, the MTS encompasses all aspects of maritime transportation from ships and ports to the inland waterways and the rail and roadways that connect them.

MTS interconnected systems include:

  • Waterways: Coastal and inland rivers, shipping channels, and harbors
  • Ports: Terminals, piers, and facilities where cargo and passengers are transferred
  • Vessels: Commercial ships, barges, ferries, and support craft
  • Intermodal Connections: Railroads, highways, and logistics hubs that tie maritime transport into national and global supply chains

The Coast Guard plays a central role in ensuring the safety, security, and efficiency of the MTS, handling over $5.4 trillion in annual economic activity. As digital systems increasingly support operations across the MTS, from crane control to cargo tracking, cybersecurity has become essential to protecting this lifeline of U.S. trade and infrastructure.

Maritime Transportation Systems also enable international trade, making them prime targets for cyber threats from ransomware gangs to nation-state actors.

To defend against growing threats, the United States Coast Guard (USCG) has moved from encouraging cybersecurity best practices to enforcing them, culminating in a new mandate that goes into effect on July 16, 2025. These regulations aim to secure the digital backbone of the maritime industry.

Why maritime ports are at risk

Modern ports are a blend of legacy and modern OT, IoT, and IT digitally connected technologies that enable crane operations, container tracking, terminal storage, logistics, and remote maintenance.

Many of these systems were never designed with cybersecurity in mind, making them vulnerable to lateral movement and disruptive ransomware attack spillover.

The convergence of business IT networks and operational infrastructure further expands the attack surface, especially with the rise of cloud adoption and unmanaged IoT and IIoT devices.

Cyber incidents in recent years have demonstrated how ransomware or malicious activity can halt crane operations, disrupt logistics, and compromise safety at scale threatening not only port operations, but national security and economic stability.

Relevant cyber-attacks on maritime ports

Maersk & Port of Los Angeles (2017 – NotPetya):
A ransomware attack crippled A.P. Moller-Maersk, the world’s largest shipping company. Operations at 17 ports, including the Port of Los Angeles, were halted due to system outages, causing weeks of logistical chaos.

Port of San Diego (2018 – Ransomware Attack):
A ransomware attack targeted the Port of San Diego, disrupting internal IT systems including public records, business services, and dockside cargo operations. While marine traffic was unaffected, commercial activity slowed significantly during recovery.

Port of Houston (2021 – Nation-State Intrusion):
A suspected nation-state actor exploited a known vulnerability in a Port of Houston web application to gain access to its network. While the attack was reportedly thwarted, it triggered a federal investigation and highlighted the vulnerability of maritime systems.

Jawaharlal Nehru Port Trust, India (2022 – Ransomware Incident):
India’s largest container port experienced disruptions due to a ransomware attack affecting operations and logistics systems. Container handling and cargo movement slowed as IT systems were taken offline during recovery efforts.

A regulatory shift: From guidance to enforcement

Since the Maritime Transportation Security Act (MTSA) of 2002, ports have been required to develop and maintain security plans. Cybersecurity formally entered the regulatory fold in 2020 with revisions to 33 CFR Part 105 and 106, requiring port authorities to assess and address computer system vulnerabilities.

In January 2025, the USCG finalized new rules to enforce cybersecurity practices across the MTS. Key elements include (but are not limited to):

  • A dedicated cyber incident response plan (PR.IP-9)
  • Routine cybersecurity risk assessments and exercises (ID.RA)
  • Designation of a cybersecurity officer and regular workforce training (section 3.1)
  • Controls for access management, segmentation, logging, and encryption (PR.AC-1:7)
  • Supply chain risk management (ID.SC)
  • Incident reporting to the National Response Center

Port operators are encouraged to align their programs with the NIST Cybersecurity Framework (CSF 2.0) and NIST SP 800-82r3, which provide comprehensive guidance for IT and OT security in industrial environments.

How Darktrace can support maritime & ports

Unified IT + OT + Cloud coverage

Maritime ports operate in hybrid environments spanning business IT systems (finance, HR, ERP), industrial OT (cranes, gates, pumps, sensors), and an increasing array of cloud and SaaS platforms.

Darktrace is the only vendor that provides native visibility and threat detection across OT/IoT, IT, cloud, and SaaS environments — all in a single platform. This means:

  • Cranes and other physical process control networks are monitored in the same dashboard as Active Directory and Office 365.
  • Threats that start in the cloud (e.g., phishing, SaaS token theft) and pivot or attempt to pivot into OT are caught early — eliminating blind spots that siloed tools miss.

This unification is critical to meeting USCG requirements for network-wide monitoring, risk identification, and incident response.

AI that understands your environment. Not just known threats

Darktrace’s AI doesn’t rely on rules or signatures. Instead, it uses Self-Learning AI TM that builds a unique “pattern of life” for every device, protocol, user, and network segment, whether it’s a crane router or PLC, SCADA server, Workstation, or Linux file server.

  • No predefined baselines or manual training
  • Real-time anomaly detection for zero-days, ransomware, and supply chain compromise
  • Continuous adaptation to new devices, configurations, and operations

This approach is critical in diverse distributed OT environments where change and anomalous activity on the network are more frequent. It also dramatically reduces the time and expertise needed to classify and inventory assets, even for unknown or custom-built systems.

Supporting incident response requirements

A key USCG requirement is that cybersecurity plans must support effective incident response.

Key expectations include:

  • ‍Defined response roles and procedures: Personnel must know what to do and when (RS.CO-1).
  • ‍Timely reporting: Incidents must be reported and categorized according to established criteria (RS.CO-2, RS.AN-4).‍
  • Effective communication: Information must be shared internally and externally, including voluntary collaboration with law enforcement and industry peers (RS.CO-3 through RS.CO-5).‍
  • Thorough analysis: Alerts must be investigated, impacts understood, and forensic evidence gathered to support decision-making and recovery (RS.AN-1 through RS.AN-5).‍
  • Swift mitigation: Incidents must be contained and resolved efficiently, with newly discovered vulnerabilities addressed or documented (RS.MI-1 through RS.MI-3).‍
  • Ongoing improvement: Organizations must refine their response plans using lessons learned from past incidents (RS.IM-1 and RS.IM-2).

That means detections need to be clear, accurate, and actionable.

Darktrace cuts through the noise using AI that prioritizes only high-confidence incidents and provides natural-language narratives and investigative reports that explain:

  • What’s happening, where it’s happening, when it’s happening
  • Why it’s unusual
  • How to respond

Result: Port security teams often lean and multi-tasked can meet USCG response-time expectations and reporting needs without needing to scale headcount or triage hundreds of alerts.

Built-for-edge deployment

Maritime environments are constrained. Many traditional SaaS deployment types often are unsuitable for tugboats, cranes, or air-gapped terminal systems.

Darktrace builds and maintains its own ruggedized, purpose-built appliances and unique virtual deployment options that:

  • Deploy directly into crane networks or terminal enclosures
  • Require no configuration or tuning, drop-in ready
  • Support secure over-the-air updates and fleet management
  • Operate without cloud dependency, supporting isolated and air-gapped systems

Use case: Multiple ports have been able to deploy Darktrace directly into the crane’s switch enclosure, securing lateral movement paths without interfering with the crane control software itself.

Segmentation enforcement & real-time threat containment

Darktrace visualizes real-time connectivity and attack pathways across IT, OT, and IoT it and integrates with firewalls (e.g., Fortinet, Cisco, Palo Alto) to enforce segmentation using AI insights alongside Darktrace’s own native autonomous and human confirmed response capabilities.

Benefits of autonomous and human confirmed response:

  • Auto-isolate rogue devices before the threat can escalate
  • Quarantine a suspicious connectivity with confidence operations won’t be halted
  • Autonomously buy time for human responders during off-hours or holidays
  • This ensures segmentation isn't just documented but that in the case of its failure or exploitation responses are performed as a compensating control

No reliance on 3rd parties or external connectivity

Darktrace’s supply chain integrity is a core part of its value to critical infrastructure customers. Unlike solutions that rely on indirect data collection or third-party appliances, Darktrace:

  • Uses in-house engineered sensors and appliances
  • Does not require transmission of data to or from the cloud

This ensures confidence in both your cyber visibility and the security of the tools you deploy.

See examples here of how Darktrace stopped supply chain attacks:

Readiness for USCG and Beyond

With a self-learning system that adapts to each unique port environment, Darktrace helps maritime operators not just comply but build lasting cyber resilience in a high-threat landscape.

Cybersecurity is no longer optional for U.S. ports its operationally and nationally critical. Darktrace delivers the intelligence, automation, and precision needed to meet USCG requirements and protect the digital lifeblood of the modern port.

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About the author
Daniel Simonds
Director of Operational Technology
Your data. Our AI.
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