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

Jun 2024

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.

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.

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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/

‍

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

Adam Potter

Cyber Analyst

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Inside the SOC

Hashing out TA577: Darktrace’s Detection of NTLM Hash Theft

Jul 2024

What is credential theft and how does it work?

What began as a method to achieve unauthorized access to an account, often driven by the curiosity of individual attackers, credentials theft become a key tactic for malicious actors and groups, as stolen login credentials can be abused to gain unauthorized access to accounts and systems. This access can be leveraged to carry out malicious activities such as data exfiltration, fraud, espionage and malware deployment.

It is therefore no surprise that the number of dark web marketplaces selling privileged credentials has increased in recent years, making it easier for malicious actors to monetize stolen credentials [1]. This, in turn, has created new opportunities for threat actors to use increasingly sophisticated tactics such as phishing, social engineering and credential stuffing in their attacks, targeting individuals, organizations and government entities alike [1].

Credential theft example

TA577 Threat Actor

TA577 is a threat actor known to leverage stolen credentials, also known as Hive0118 [2], an initial access broker (IAB) group that was previously known for delivering malicious payloads [2]. On March 4, 2024, Proofpoint reported evidence of TA577 using a new attack chain with a different aim in mind: stealing NT LAN Manager (NTLM) hashes that can be used to authenticate to systems without needing to know plaintext passwords [3].

How does TA577 steal credentials?

Proofpoint reported that this new attack chain, which was first observed on February 26 and 27, was made up of two distinct campaigns. The first campaign consisted of a phishing attack featuring tens of thousands of emails targeting hundreds of organizations globally [3]. These phishing emails often appeared as replies to previous messages (thread hijacking) and contained zipped HTML attachments that each contained a unique file hash, customized for each recipient [3]. These attached files also contained a HTTP Meta refresh function, which triggered an automatic connection to a text file hosted on external IP addresses running as SMB servers [3].

When attempting to access the text file, the server requires an SMB session authentication via NTLM. This session is initiated when a client sends an ‘SMB_COM_NEGOTIATE’ request to the server, which answers with a ‘SMB_COM_NEGOTIATE’ response.

The client then proceeds to send a ‘SMB_COM_SESSION_SETUP_ANDX’ request to start the SMB session setup process, which includes initiating the NTLM authentication process. The server responds with an ‘SMB_COM_SESSION_SETUP_ANDX’ response, which includes an NTLM challenge message [6].

The client can then use the challenge message and its own credentials to generate a response by hashing its password using an NTLM hash algorithm. The response is sent to the server in an ‘SMB_COM_SESSION_SETUP_ANDX’ request. The server validates the response and, if the authentication is successful, the server answers with a final ‘SMB_COM_SESSION_SETUP_ANDX’ response, which completes the session setup process and allows the client to access the file listed on the server [6].

What is the goal of threat actor TA577?

As no malware delivery was detected during these sessions, researchers have suggested that the aim of TA577 was not to deliver malware, but rather to take advantage of the NTLMV2 challenge/response to steal NTLM authentication hashes [3] [4]. Hashes stolen by attackers can be exploited in pass-the-hash attacks to authenticate to a remote server or service [4]. They can also be used for offline password cracking which, if successful, could be utilized to escalate privileges or perform lateral movement through a target network [4]. Under certain circumstances, these hashes could also permit malicious actors to hijack accounts, access sensitive information and evade security products [4].

The open-source toolkit Impacket, which includes modules for password cracking [5] and which can be identified by the default NTLM server challenge “aaaaaaaaaaaaaaaa”[3], was observed during the SMB sessions. This indicates that TA577 actor aim to use stolen credentials for password cracking and pass-the-hash attacks.

TA577 has previously been associated with Black Basta ransomware infections and Qbot, and has been observed delivering various payloads including IcedID, SystemBC, SmokeLoader, Ursnif, and Cobalt Strike [2].This change in tactic to follow the current trend of credential theft may indicate that not only are TA577 actors aware of which methods are most effective in the current threat landscape, but they also have monetary and time resources needed to create new methods to bypass existing detection tools [3].

Darktrace’s Coverage of TA577 Activity

On February 26 and 26, coinciding with the campaign activity reported by Proofpoint, Darktrace/Email™ observed a surge of inbound emails from numerous suspicious domains targeting multiple customer environments. These emails consistently included zip files with seemingly randomly generated names, containing HTLM content and links to an unusual external IP address [3].

Figure 1: A summary of anomaly indicators seen for a campaign email sent by TA577, as detected by Darktrace/Email.

Figure 2: Details of the name and size of the .zip file attached to a campaign email, along with the Darktrace/Email model alerts triggered by the email.

The URL of these links contained an unusually named .txt file, which corresponds with Proofpoint reports of the automatic connection to a text file hosted on an external SMB server made when the attachment is opened [3].

Figure 3: A link to a rare external IP address seen within a campaign email, containing an unusually named .txt file.

Darktrace identified devices on multiple customer networks connecting to external SMB servers via the SMB protocol. It understood this activity was suspicious as the SMB protocol is typically reserved for internal connections and the endpoint in question had never previously been observed on the network.

Figure 4: The Event Log of a ‘Compliance / External Windows Communication’ model alert showing a connection to an external SMB server on destination port 445.

Figure 5: External Sites Summary highlighting the rarity of the external SMB server.

Figure 6: External Sites Summary highlightin that the SMB server is geolocated in Moldova.

During these connections, Darktrace observed multiple devices establishing an SMB session to this server via a NTLM challenge/response, representing the potential theft of the credentials used in this session. During this session, some devices also attempted to access an unusually named .txt file, further indicating that the affected devices were trying to access the .txt file hosted on external SMB servers [3].

Packet captures (PCAPs) of these sessions show the default NTLM server challenge, indicating the use of Impacket, suggesting that the captured NTLM hashes were to be used for password cracking or pass-the-hash-attacks [3]

Figure 7: PCAP analysis showing usage of the default NTLM server challenge associated with Impacket.

Conclusions

Ultimately, Darktrace’s suite of products effectively detected and alerted for multiple aspects of the TA577 attack chain and NTLM hash data theft activity across its customer base. Darktrace/Email was able to uncover the inbound phishing emails that served as the initial access vector for TA577 actors, while Darktrace DETECT identified the subsequent external connections to unusual external locations and suspicious SMB sessions.

Furthermore, Darktrace’s anomaly-based approach enabled it to detect suspicious TA577 activity across the customer base on February 26 and 27, prior to Proofpoint’s report on their new attack chain. This showcases Darktrace’s ability to identify emerging threats based on the subtle deviations in a compromised device’s behavior, rather than relying on a static list of indicators of compromise (IoCs) or ‘known bads’.

This approach allows Darktrace to remain one step ahead of increasingly adaptive threat actors, providing organizations and their security teams with a robust AI-driven solution able to safeguard their networks in an ever-evolving threat landscape.

Credit to Charlotte Thompson, Cyber Analyst, Anna Gilbertson, Cyber Analyst.

References

1) https://www.sentinelone.com/cybersecurity-101/what-is-credential-theft/

2) https://malpedia.caad.fkie.fraunhofer.de/actor/ta577

3) https://www.proofpoint.com/us/blog/threat-insight/ta577s-unusual-attack-chain-leads-ntlm-data-theft

4) https://www.bleepingcomputer.com/news/security/hackers-steal-windows-ntlm-authentication-hashes-in-phishing-attacks/

5) https://pawanjswal.medium.com/the-power-of-impacket-a-comprehensive-guide-with-examples-1288f3a4c674

6) https://learn.microsoft.com/en-us/openspecs/windows_protocols/ms-nlmp/c083583f-1a8f-4afe-a742-6ee08ffeb8cf

7) https://www.hivepro.com/threat-advisory/ta577-targeting-windows-ntlm-hashes-in-global-campaigns/

Darktrace Model Detections

Darktrace/Email

· Attachment / Unsolicited Archive File

· Attachment / Unsolicited Attachment

· Link / New Correspondent Classified Link

· Link / New Correspondent Rare Link

· Spoof / Internal User Similarities

Darktrace DETECT

· Compliance / External Windows Communications

Darktrace RESPOND

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

IoCs

IoC - Type - Description

176.123.2[.]146 - IP address -Likely malicious SMB Server

89.117.2[.]33 - IP address - Likely malicious SMB Server

89.117.1[.]161 - IP address - Likely malicious SMB Server

104.129.20[.]167 - IP address - Likely malicious SMB Server

89.117.1[.]160 - IP address - Likely malicious SMB Server

85.239.33[.]149 - IP address - Likely malicious SMB Server

89.117.2[.]34 - IP address - Likely malicious SMB Server

146.19.213[.]36 - IP address - Likely malicious SMB Server

66.63.188[.]19 - IP address - Likely malicious SMB Server

103.124.104[.]76 - IP address - Likely malicious SMB Server

103.124.106[.]224 - IP address - Likely malicious SMB Server

\5aohv\9mn.txt - SMB Path and File - SMB Path and File

\hvwsuw\udrh.txt - SMB Path and File - SMB Path and File

\zkf2rj4\VmD.txt = SMB Path and File - SMB Path and File

\naams\p3aV.txt - SMB Path and File - SMB Path and File

\epxq\A.txt - SMB Path and File - SMB Path and File

\dbna\H.txt - SMB Path and File - SMB Path and File

MAGNAMSB.zip – Filename - Phishing Attachment

e751f9dddd24f7656459e1e3a13307bd03ae4e67 - SHA1 Hash - Phishing Attachment

OMNIS2C.zip - Filename - Phishing Attachment

db982783b97555232e28d5a333525118f10942e1 - SHA1 Hash - Phishing Attachment

aaaaaaaaaaaaaaaa - NTLM Server Challenge -Impacket Default NTLM Challenge

MITRE ATT&CK Tactics, Techniques and Procedures (TTPs)

Tactic - Technique

TA0001 Initial Access

TA0002 Execution

TA0008 Lateral Movement

TA0003 Persistence

TA0005 Defense Evasion

TA0006 Credential Access

T1021.002 SMB/Windows Admin Shares

T1021 Remote Services

T1566.001 Spearfishing Attachment

T1566 Phishing

T1204.002 Malicious File

T1204 User Execution

T1021.002 SMB/Windows Admin Shares

T1574 Hijack Execution Flow

T1021 Remote Services

T1555.004 Windows Credential Manager

T1555 Credentials from Password Stores

About the author

Charlotte Thompson

Cyber Analyst

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Credential Phishing: Common attack methods and defense strategies 

Jul 2024

Credential theft remains a top cybersecurity threat

Adversaries have many options in their arsenal to gain access into an organization.

Exploitable vulnerabilities: This can provide access into a system’s processes and allow activity within the context of the service account.  

Weak or misconfigured systems: These can provide direct avenues of access into exposed systems.  

However, the more desirable option is to obtain user or API credentials permitting the adversary to authenticate and operate as one of the organization’s authorized entities.

While 2023 noted a marked increase in vulnerability exploits as the chosen vector of attack, the use of credentials by adversaries still ranked #1 at 24% in the latest Verizon Data Breach Investigations Report. Mandiant’s M-Trends report noted 14% of their investigations involved stolen credentials as the attack vector, and Darktrace’s 2023 End of Year Threat Report revealed that Credential Access was one of the most observed MITRE ATT&CK tactics.

Credential phishing methods 

There are many ways an adversary can obtain a user’s credentials. Some require gaining access to the target system or exploiting an application while others target the end-user directly. 

Joshua (WarGames) | Villains Wiki | Fandom

Social Engineering: Many users have a habit of incorporating things in their life into their passwords. Family members, important dates, hobbies, movies, and music favorites have all been used. Adversaries know this and will scour social media to gain knowledge about their intended target. This method was beautifully demonstrated in the 1983 movie, Wargames, where Matthew Broderick’s character scours articles, papers, and video about Dr. Stephen Falken, finally guessing that the password into the WOPR (War Operations Plan Response) computer is that of his deceased child, Joshua.

Credential Cracking / Dumping: If the adversary has gained access to a targeted system, they may employ a password cracking, or credential dumping, program. For Unix-based solutions, obtaining the /etc/passwd and /etc/shadow files provides the users, groups, and encrypted passwords. Adversaries can exfiltrate these files and then utilize password crackers such as John the Ripper, Crack, or codebreaker003. Mimikatz(see more below) can also pass cache information for Mac / Unix and Linux systems.

Windows-based solutions: Adversaries have successfully utilized programs such as Mimikatz to dump credentials and hashes. Mimikatz can pass the hash string to the Local Security Authority Subsystem Service (LSASS) to authorize user actions, as well as perform “kerberoasting”. Kerberos is how Windows systems authorize users utilizing a 3-entity authentication method and symmetric key cryptography to create “tickets” that authorize requested actions. Mimikatz can use Kerberos tickets to gain non-expiring domain administration credentials (Golden Tickets) or tickets to login as a service on the network (Silver Tickets).

Post-It Notes: As organizations and applications started requiring stronger passwords that met complexity requirements, users did what you would expect to ensure they didn’t forget them. They wrote them down (this was also demonstrated in Wargames). The modern-day equivalent is to create a text file with all your passwords (or API credentials) in it – something adversaries are delighted to find.

One of the funniest, yet totally on-point, comic routines I’ve seen on this topic is Michael McIntyre’s You Should Probably Change Your Password skit at the London Palladium.

Phishing Alert: Pay attention to NC State login pages and Duo prompts – Office of Information Technology

Phishing / Smishing: Forged messages requesting users to reset their passwords or directing them to enter their credentials used to be easier to spot. However, the emergence of Artificial Intelligence (AI) is allowing adversaries to create very realistic messages and web pages that mimic an organization’s authentication pages. These attempts are not just limited to email, adversaries are utilizing SMS messages and other collaborative communication solutions like Microsoft Teams to transmit fake messages to unsuspecting users. Also, security teams are seeing increased use of Quick Response (QR) codes in scam messages. QR codes are appearing in all aspects of everyday life (I’m finding it hard to go into a restaurant without having to scan a QR code to read the menu) and there is a false sense of security people have in thinking that QR codes are safe to scan.

Vulnerability Exploits: Gaining access to the credential cache or password file is not the only way adversaries can obtain user credentials. Some applications will store the user credentials in process memory (decrypted). If the application is vulnerable to a remote exploit, it can be possible for the adversary to dump the memory of the application process and locate these stored credentials. This was clearly illustrated in the Heartbleed exploit disclosed to the public in 2014.

Air Cracking: Air Cracking is specific to Wi-Fi networks and involves cracking programs that analyze wireless encrypted packets and extracting WEP or WPA/WPA2 PSK passwords (giving the adversary access to the Wi-Fi network).

Dark Web Purchase: Threat groups know how to monetize compromised credentials. Selling compromised credentials on the Dark Web occurs on a regular basis. Sites such as HaveIBeenPwned.com can assist users in determining if a particular password has been found to be compromised. Note: Users should ensure that the sites they are checking to see if their password has been compromised are actual legitimate sites and not a credential harvesting site!

You need a strong, unique password for EVERY account : r/memes

What is credential stuffing and why is it so effective?

Credential Stuffing is so successful because users tend to utilize the same, or very similar, passwords across all the systems and applications they access. This includes both personal and business accounts. Once an adversary harvests credentials from one site, they will try that password on other sites, and if that fails, they can utilize generative AI to predict potential variations of the password.

How to reduce the risk of credential stuffing?

Users can help reduce exposure of their credentials by creating passwords that meet complexity requirements but are also easy to remember. A good approach is to take a phrase and apply a substitution rule. For example, let’s take the start of Charles Dicken’s book A Tale of Two Cities and create a substitution rule for it:

It was the best of times, it was the worst of times

Let’s shorten that to: Best of times Worst of times

Apply the following substitution rule: o = 0, i = 1, e = 3, spaces = @

Now my phrase becomes: B3st@0f@t1m3s@W0rst@0f@t1m3s

You now have a 28-character password that contains letters, a capital letter, number, and special character. Nobody is cracking that, and the phrase and substitution rule makes it much easier to remember (PS: 12-character passwords are also fine, taking ~34,000 years to crack using current technology).

Organizations can reduce exposure through implementation of two-factor authentication (2FA), so even if the passwords are compromised through the methods described above, another authentication layer stands in the way of the adversary.

Additionally, preventing phishing messages from landing in user’s inboxes (Email or collaborative solutions such as Microsoft Teams) is critical not only for reducing the potential exposure of user credentials, but also user’s opening malicious attachments or links. Generative AI tools such as ChatGPT have resulted in over an 135% increase in novel social engineering attacks.

How Darktrace protects against sophisticated credential phishing attempts 

Malicious actors can exploit these leaked credentials to drastically lower the barrier to entry associated with brute-forcing access to their target networks. While implementing well-configured MFA and enforcing regular password changes can help protect organizations, these measures alone may not be enough to fully negate the advantage attackers gain with stolen credentials. 

In early 2024, one Darktrace customer was compromised by a malicious actor after their internal credentials had been leaked on the dark web. Subsequent attack phases were detected by Darktrace/Network and the customer was alerted to the suspicious activity via the Proactive Threat Notification (PTN) service, following an investigation by Darktrace’s Security Operation Center (SOC). 

Darktrace detected a device on the network of a customer in the US carrying out a string of anomalous activity indicative of network compromise. The device was observed using a new service account to authenticate to a Virtual Private Network (VPN) server, before proceeding to perform a range of suspicious activity including internal reconnaissance and lateral movement. 

Unfortunately for the customer in this case, Darktrace’s autonomous response was not enabled on the network at the time of the attack. Had it been active, it would have been able to autonomously act against the malicious activity by disabling users, strategically blocking suspicious connections and limiting devices to their expected patterns of activity. 

For the full in depth story with a step-by-step walk through of the attack visit our Inside the SOC blog post.

Conclusion

Head of security, and your password is "password"? | Scattered Quotes | Funny marvel memes, Marvel funny, Marvel jokes

Adversaries have various methods available to compromise user and API credentials. There is no single silver bullet that will protect users and organizations, but rather, a layered approach that incorporates education, security controls such as 2FA, unsupervised AI to detect novel and sophisticated spear-phishing messages, as well as protection against exploits that give adversaries access to systems.

‍

About the author

John Bradshaw

Sr. Director, Technical Marketing

Our ai. Your data.

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Check out this article by Darktrace: Post-Exploitation Activities on PAN-OS Devices: A Network-Based Analysis

Blog‍

Inside the SOC

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

Introduction

CVE-2024-3400

Campaign Analysis

1. Exploit Validation and Further Vulnerability Enumeration

2. Command and Payload Transmission

a) Shell Script Retrieval

b) Executable File Retrieval

3. Configuration Data Exfiltration and Unusual HTTP POST Activity

4. Ongoing C2 and Miscellaneous Activity

Conclusion

Appendices ‍

Pre-CVE-Release IoCs

Indicators of Compromise

Darktrace Model Alert Coverage

MITRE ATTACK Mapping

References

Like this and want more?

Like this and want more?

More in this series

Blog‍

Inside the SOC

Hashing out TA577: Darktrace’s Detection of NTLM Hash Theft

What is credential theft and how does it work?

Credential theft example

TA577 Threat Actor

How does TA577 steal credentials?

What is the goal of threat actor TA577?

Darktrace’s Coverage of TA577 Activity

Conclusions

References

Darktrace Model Detections

IoCs

MITRE ATT&CK Tactics, Techniques and Procedures (TTPs)

Blog‍

Credential Phishing: Common attack methods and defense strategies

Credential theft remains a top cybersecurity threat

Credential phishing methods

What is credential stuffing and why is it so effective?

How to reduce the risk of credential stuffing?

How Darktrace protects against sophisticated credential phishing attempts

Conclusion

Elevate your cyber defenses with Darktrace AI

Blog
‍

Blog
‍

Blog
‍

Credential Phishing: Common attack methods and defense strategies 

Credential phishing methods 

How Darktrace protects against sophisticated credential phishing attempts 