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May 19, 2023

Darktrace Stops Large-Scale Account Hijack

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19
May 2023
Learn how Darktrace detected and stopped a large-scale account hijack that led to a phishing attack. Protect your business with these insights.

Introduction 

As malicious actors across the threat landscape continue to take advantage of the widespread adoption of Software-as-a-Service (SaaS) platforms and multi-factor authentication (MFA) services to gain unauthorized access to organizations’ networks, it is crucial to have appropriate security tools in place to defend against account compromise at the earliest stage.

One method frequently employed by attackers is account takeover. Account takeovers occur when a threat actor exploits credentials to login to a SaaS account, often from an unusual location where the genuine actor does not usually login from. 

Access to these accounts can be caused by harvesting credentials through phishing emails and password spray attacks, or by exploiting insecure cloud safety practices such as not having MFA enabled on user accounts, requiring only user credentials for authentication. Once the integrity of the account is compromised, the threat actor can conduct further activity, such as delivering malware, reading and exfiltrating sensitive data, and sending out phishing emails to harvest further internal and external user credentials, repeating the attack cycle [1,2]. 

In early 2023, Darktrace detected a large-scale account takeover and phishing attack on the network of a customer in the education sector that affected hundreds of accounts and resulted in thousands of emails being forwarded outside of the network. The exceptional degree of visibility provided by Darktrace DETECT™ allowed for the detection of adversarial activity at every stage of the kill chain, and direct support from the Darktrace Analyst team via the Ask the Expert (ATE) service ensured the customer was fully informed and equipped to implement remedial action. 

Details of Attack Chain

Darktrace observed the same pattern of activity on all hijacked accounts on the customer’s network; login from unfamiliar locations, enablement of a mail forwarding rule that forwards all incoming emails to malicious email addresses, and the sending of phishing emails followed by their deletion. 

Figure 1: Timeline of attack on hijacked SaaS accounts.

Initial Access

Darktrace DETECT first detected anomalous SaaS activity on the customer environment on January 14, 2023, and then again on February 3, when multiple SaaS accounts were observed logging in from atypical locations with rare IP addresses and geographically impossible travel timings, or logging in whilst the account owner was active elsewhere. Subsequent investigation using open-source intelligence (OSINT) sources revealed one of the IP addressed had recently been associated with brute-force or password spray attempt.

This pattern of unusual login behavior persisted throughout the timeframe of the attack, with more unique accounts generating model breaches each day for similarly anomalous logins. As MFA authentication was not enforced for these user logins, the initial intrusion process was enabled by requiring only credentials for authentication.

Sending Emails 

The compromised accounts were also seen sending out emails with the subject ‘Email HELP DESK’ to external and internal recipients. This was likely represented a threat actor employing social engineering tactics to gain the trust of the recipient by posing as an internal help desk.

Mail Forwarding

Following the successful logins, compromised accounts began creating email rules to forward mail to external email addresses, some of which were associated with domains that had hits for malicious activity according to OSINT sources [3].

  • chotunai[.]com
  • bymercy[.]com
  • breazeim[.]com
  • brandoza[.]com

Forwarding mail is a commonly observed tactic during SaaS compromises to control lines of communication. Malicious actors often attempt to insert themselves into ongoing correspondence for illicit purposes, such as exfiltrating sensitive information, gaining persistent access to the compromised email or redirecting invoice payments. 

Email Deletions

Shortly after the mail forwarding activity, compromised accounts were detected performing anomalous email deletions en masse. Further investigation revealed that these accounts had previously sent a large volume of phishing emails and this mass deletion likely represented an attempt to conceal these activities by deleting them from their outboxes.

On February 10, the customer applied a mass password reset on all accounts that Darktrace had identified as compromised and provisioned, privileged accounts with MFA. They have indicated that those measures successfully halted the compromise, addressing the initial point of entry.  

Darktrace Coverage

Using its Self-Learning AI, Darktrace effectively demonstrated its ability to detect unusual SaaS activity that could indicate that an account has been hijacked by malicious actors. Rather than relying on a traditional rules and signature-based approach, Darktrace models develop an understanding of the network itself and can instantly recognize when a compromised deviates from its expected pattern of life.

Figure 2: Detection of unusual SaaS activity on hijacked SaaS account.

Initial Access

Initial access was detected by the following models:

  • Security Integration / High Severity Integration Detection  
  • SaaS / Unusual Activity / Activity from Multiple Unusual IPs 
  • SaaS / Access / Unusual External Source for SaaS Credential Use 
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active 

Initial access was also detected by the following Cyber AI Analyst Incidents:

  • Possible Hijack of Office365 Account 

The model breaches and AI Analyst incidents detected logins from 100% rare external IP addresses in conjunction with a lack of MFA usage, as depicted in Figure 3.

Figure 3: Breach log showing initial detection of a SaaS login from a 100% rare IP where MFA was not used.
Figure 4: Initial detection of unusual SaaS activity visualized in Darktrace's SaaS console.

Mail Forwarding

Mail forwarding was detected by the following models:

  • SaaS / Admin / Mail Forwarding Enabled 

Compromised accounts were largely detected configuring mail forwarding rules to external email addresses, ostensibly to establish persistence on the network and exfiltrate sensitive correspondence.

Figure 5: The enablement of mail forwarding was detected as 100% new or uncommon for the account in question.

Mass Email Deletion

Mass email deletion was detected by the following models:

  • SaaS / Compromise / Suspicious Login and Mass Email Deletes 
  • SaaS / Resource / Mass Email Deletes from Rare Location 
Figure 6: Compromised account deleting phishing emails it had previously sent from the outbox.

Darktrace detected accounts performing highly anomalous mass email deletions from rare locations. The actors deleted the email “Email HELP DESK” which was later confirmed as being the primary phishing email used in the attack. Deletions were observed on compromised accounts’ outboxes, presumably to conceal the malicious activity.

Darktrace also detected this linked pattern of activity in sequential models such as: 

  • SaaS / Compromise / Unusual Login, Sent Mail, Deleted Sent
  • SaaS / Compromise / Suspicious Login and Mass Email Deletes 

Ask the Expert

The customer used the ATE service to request more technical information and support concerning the attack. Darktrace’s 24/7 team of analysts were able to offer expert assistance and further details to assist in the subsequent investigations and remediation steps. 

Further Detection and Response  

Unfortunately, the customer did not have Darktrace/Email™ enabled at the time of the attack. Darktrace/Email has visibility over inbound and outbound mail-flow which provides an oversight on potential data loss incidents. In this case, Darktrace DETECT/Email would have been able to provide full visibility over the phishing emails sent by the compromised accounts, as well as the attackers attempts to spoof an internal helpdesk. Further to this, the new Analysis Outlook integration helps employees understand why an email is suspicious and enables them report emails directly to the security team, which helps to continuously build user awareness of phishing attacks. 

Darktrace/Email also enhances Darktrace/Network™ detections by triggering ‘Email Nexus’ models within Darktrace/Network, where malicious activity is detected across the digital estate, correlating moving from SaaS compromised logins to mass email spam being sent out by compromised users

Figure 7: Email Nexus models within the Darktrace/Network enhanced by Darktrace/Email

Darktrace RESPOND™ was not enabled on the customer environment at the time of the attack; if it were, Darktrace would have been able to autonomously take action against the SaaS model breaches detecting across multiple of the kill chain. RESPOND would have disabled the hijacked accounts or force them to log out for a period of time, whilst also disabling the inbox rules that had been established by malicious actors. This would have given the customer’s security team valuable time to analyze the incident and mitigate the situation, preventing the attack from escalating any further. 

Conclusion

Ultimately, Darktrace demonstrated its unparalleled visibility over customer networks which allowed for the detection of this large-scale targeted SaaS account takeover, and the subsequent phishing attack. It underscores the importance of defense in depth; critically, MFA was not enforced for this environment which likely made the targeted organization far more susceptible to compromise via credential theft. The phishing activity detected by Darktrace following this account compromise also highlights the need for email protection in any security stack. 

Darktrace’s visibility meant allowed it to detect the attack at a high degree of granularity, including the account logins, email forwarding rule creations, outbound mail, and the mass deletions of phishing emails. Darktrace’s anomaly-based detection means it does not have to rely on signatures, rules or known indicators of compromise (IoCs) when identifying an emerging threat, instead placing the emphasis on recognizing a user’s deviation from its normal behavior.

However, without the presence of an autonomous response technology able to instantly intervene and stop ongoing attacks, organizations will always be reacting to attacks once the damage is done. Darktrace RESPOND is uniquely placed to take action against suspicious activity as soon as it is detected, preventing attacks from escalating and saving customers from significant disruption to their business.

Credit to: Zoe Tilsiter, Cyber Analyst, Gernice Lee, Cyber Analyst.

Appendices

Models Breached

SaaS / Access / Unusual External Source for SaaS Credential Use

SaaS / Admin / Mail Forwarding Enabled

SaaS / Compliance / Microsoft Cloud App Security Alert Detected

SaaS / Compromise / SaaS Anomaly Following Anomalous Login 

SaaS / Compromise / Unusual Login, Sent Mail, Deleted Sent

SaaS / Compromise / Suspicious Login and Mass Email Deletes 

SaaS / Resource / Mass Email Deletes from Rare Location

SaaS / Unusual Activity / Multiple Unusual External Sources For SaaS Credential

SaaS / Unusual Activity / Activity from Multiple Unusual IPs

SaaS / Unusual Activity / Multiple Unusual SaaS Activities 

Security Integration / Low Severity Integration Detection

Security Integration / High Severity Integration Detection

List of IoCs

brandoza[.]com - domain - probable domain of forwarded email address

breazeim[.]com - domain - probable domain of forwarded email address

bymercy[.]com - domain - probable domain of forwarded email address

chotunai[.]com - domain - probable domain of forwarded email address

MITRE ATT&CK Mapping

Tactic: INITIAL ACCESS, PERSISTENCE, PRIVILEGE ESCILATION, DEFENSE EVASION

Technique: T1078.004 – Cloud Accounts

Tactic: COLLECTION

Technique: T1114- Email Collection

Tactic:COLLECTION

Technique: T1114.003- Email Forwarding Rule

Tactic: IMPACT

Technique: T1485- Data Destruction

Tactic: DEFENSE EVASION

Technique: T1578.003 – Delete Cloud Instance

References

[1] Darktrace, 2022, Cloud Application Security_ Protect your SaaS with Self-Learning AI.pdf

[2] https://www.cloudflare.com/en-gb/learning/access-management/account-takeover/ 

[3] https://www.virustotal.com/gui/domain/chotunai.com 

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
Zoe Tilsiter
Cyber Analyst
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December 9, 2024

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Darktrace’s view on Operation Lunar Peek: Exploitation of Palo Alto firewall devices (CVE 2024-2012 and 2024-9474)

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As the first line of defense for many organizations, perimeter devices such as firewalls are frequently targeted by threat actors. If compromised, these devices can serve as the initial point of entry to the network, providing access to vulnerable internal resources. This pattern of malicious behavior has become readily apparent within the Darktrace customer base. In 2024, Darktrace Threat Research analysts identified and investigated at least two major campaigns targeting internet-exposed perimeter devices. These included the exploitation of PAN-OS firewall exploitation via CVE 2024-3400 and FortiManager appliances via CVE 2024-47575.

More recently, at the end of November, Darktrace analysts observed a spike in exploitation and post-exploitation activity affecting, once again, Palo Alto firewall devices in the days following the disclosure of the CVE 2024-0012 and CVE-2024-9474 vulnerabilities.

Threat Research analysts had already been investigating potential exploitation of the firewalls’ management interface after Palo Alto published a security advisory (PAN-SA-2024-0015) on November 8. Subsequent analysis of data from Darktrace’s Security Operations Center (SOC) and external research uncovered multiple cases of Palo Alto firewalls being targeted via the likely exploitation of these vulnerabilities since November 13, through the end of the month. Although this spike in anomalous behavior may not be attributable to a single malicious actor, Darktrace Threat Research identified a clear increase in PAN-OS exploitation across the customer base by threat actors likely utilizing the recently disclosed vulnerabilities, resulting in broad patterns of post-exploitation activity.

How did exploitation occur?

CVE 2024-0012 is an authentication bypass vulnerability affecting unpatched versions of Palo Alto Networks Next-Generation Firewalls. The vulnerability resides in the management interface application on the firewalls specifically, which is written in PHP. When attempting to access highly privileged scripts, users are typically redirected to a login page. However, this can be bypassed by simply supplying an HTTP request where a Palo Alto related authentication header can simply be set to “off”.  When accessing certain resource paths, users can cause the Nginx reverse server to send this authentication header without any prior processing[1].

CVE-2024-9474 is a privilege escalation vulnerability that allows a PAN-OS administrator with access to the management web interface to execute root-level commands, granting full control over the affected device[2]. When combined, these vulnerabilities enable unauthenticated adversaries to execute arbitrary commands on the firewall with root privileges.

Post-Exploitation Patterns of Activity

Darktrace Threat Research analysts examined potential indicators of PAN-OS software exploitation via CVE 2024-0012 and CVE-2024-9474 during November 2024. The investigation identified three main groupings of post-exploitation activity:

1. Exploit validation and initial payload retrieval

2. Command and control (C2) connectivity, potentially featuring further binary downloads

3. Potential reconnaissance and crypto-mining activity

Exploit Validation

Across multiple investigated customers, Darktrace analysts identified likely vulnerable PAN-OS devices conducting external network connectivity to bin services. Specifically, several hosts performed DNS queries for, and HTTP requests to Out-of-Band Application Security Testing (OAST) domains, such as csv2im6eq58ujueonqs0iyq7dqpak311i.oast[.]pro. These endpoints are commonly used by network administrators to harden defenses, but they are increasingly used by threat actors to verify successful exploitation of targeted devices and assess their potential for further compromise. Although connectivity involving OAST domains were prevalent across investigated incidents, this activity was not necessarily the first indicator observed. In some cases, device behavior involving OAST domains also occurred shortly after an initial payload was downloaded.

Figure 1: Darktrace model alert logs detailing the HTTP request to an OAST domain immediately following PAN-OS device compromise.

Initial Payload Retrieval

Following successful exploitation, affected devices commonly performed behaviors indicative of initial payload download, likely in response to incoming remote command execution. Typically, the affected PAN-OS host would utilize the command line utilities curl and Wget, seen via use of user agents curl/7.61.1 and Wget/1.19.5 (linux-gnu), respectively.

In some cases, the use of these command line utilities by the infected devices was considered new behavior. Given the nature of the user agents, interaction with the host shell suggests remote command execution to achieve the outgoing payload requests.

While additional binaries and scripts were retrieved in later stages of the post-exploitation activity in some cases, this set of behaviors and payloads likely represent initial persistence and execution mechanisms that will enable additional functionality later in the kill chain. During the investigation, Darktrace analysts noted the prevalence of shell script payload requests. Devices analyzed would frequently make HTTP requests over the usual destination port 80 using the command line URL utility (curl), as seen in the user-agent field.

The observed URIs often featured requests for text files, such as “1.txt”, or shell scripts such as “y.sh”. Although packet capture (PCAP) samples were unavailable for review, external researchers have noted that the IP address hosting such “1.txt” files (46.8.226[.]75) serves malicious PHP payloads. When examining the contents of the “y.sh” shell script, Darktrace analysts noticed the execution of bash commands to upload a PHP-written web shell on the affected server. External sources suggest that the content of the PHP script is similar to that of the Neo-reGeorg tunnel[3][4].

Figure 2: PCAP showing the client request and server response associated with the download of the y.sh script from 45.76.141[.]166. The body content of the HTTP response highlights a shebang command to run subsequent code as bash script. The content is base64 encoded and details PHP script for what appears to be a webshell that will likely be written to the firewall device.

While not all investigated cases saw initial shell script retrieval, affected systems would commonly make an external HTTP connection, almost always via Wget, for the Executable and Linkable Format (ELF) file “/palofd” from the rare external IP  38.180.147[.]18.

Such requests were frequently made without prior hostname lookups, suggesting that the process or script initiating the requests already contained the external IP address. Analysts noticed a consistent SHA1 hash present for all identified instances of “/palofd” downloads (90f6890fa94b25fbf4d5c49f1ea354a023e06510). Multiple open-source intelligence (OSINT) vendors have associated this hash sample with Specter RAT, a remote access trojan with capabilities including remote command execution, payload delivery, process manipulation, file transfers, and data theft[5][6].

Figure 3: Advanced Search log metrics highlighting details of the “/palofd” file download over HTTP.

Several targeted customer devices were observed initiating TLS/SSL connections to rare external IPs with self-signed TLS certificates following exploitation. Model data from across the Darktrace fleet indicated some overlap in JA3 fingerprints utilized by affected PAN-OS devices engaging in the suspicious TLS activity. Although JA3 hashes alone cannot be used for process attribution, this evidence suggests some correlation of source process across instances of PAN-OS exploitation.

These TLS/SSL sessions were typically established without the specification of a Server Name Indication (SNI) within the TLS extensions. The SNI extension prevents servers from supplying the incorrect SSL certificate to the client when multiple sites are hosted on the same IP. SSL connectivity without SNI specification suggests potentially malicious processes, as there is no expected ambiguity of the domain for which the client is requesting content. Although the encrypted nature of the connection prevented further analysis of the payload packets, external sources note that JavaScript content is transmitted during these sessions, serving as initial payloads for the Sliver C2 platform using Wget[7].

C2 Communication and Additional Payloads

Following validation and preliminary post-compromise actions, examined hosts would commonly initiate varying forms of C2 connectivity. During this time, devices were frequently detected making further payload downloads, likely in response to directives set within C2 communications.

Palo Alto firewalls likely exploited via the newly disclosed CVEs would commonly utilize the Sliver C2 platform for external communication. Sliver’s functionality allows for different styles and formatting for communication. An open-source alternative to Cobalt Strike, this framework has been increasingly popular among threat actors, enabling the generation of dynamic payloads (“slivers”) for multiple platforms, including Windows, MacOS, Linux.

These payloads allow operators to establish persistence, spawn new shells, and exfiltrate data. URI patterns and PCAPs analysis yielded evidence of both English word type encoding within Sliver and Gzip formatting.

For example, multiple devices contacted the Sliver-linked IP address 77.221.158[.]154 using HTTP to retrieve Gzip files. The URIs present for these requests follow known Sliver Gzip formatted communication patterns [8]. Investigations yielded evidence of both English word encoding within Sliver, identified through PCAP analysis, and Gzip formatting.

Figure 4: Sample of URIs observed in Advanced Search highlighting HTTP requests to 77.221.158[.]154 for Gzip content suggest of Sliver communication.
Figure 5: PCAP showing English word encoding for Sliver communication observed during post-exploitation C2 activity.

External connectivity during this phase also featured TCP connection attempts over uncommon ports for common application protocols. For both Sliver and non-Sliver related IP addresses, devices utilized destination ports such as 8089, 3939, 8880, 8084, and 9999 for the HTTP protocol, again using command line tools as user agents. The use of uncommon destination ports may represent attempts to avoid detection of connectivity to rare external endpoints. Moreover, some external beaconing within included URIs referencing the likely IP of the affected device. Such behavior can suggest the registration of compromised devices with command servers.

Targeted devices also proceeded to download additional payloads from rare external endpoints as beaconing/C2 activity was ongoing. For example, the newly registered domain repositorylinux[.]org (IP: 103.217.145[.]112) received numerous HTTP GET requests from investigated devices throughout the investigation period for script files including “linux.sh” and “cron.sh”. Young domains, especially those that present as similar to known code repositories, tend to host harmful content. Packet captures of the cron.sh file reveal commands within the HTTP body content involving crontab operations, likely to schedule future downloads. Some hosts that engaged in connectivity to the fake repository domain were later seen conducting crypto-mining connections, potentially highlighting the download of miner applications from the domain.

Additional payloads observed during this time largely featured variations of shell scripts, PHP content, and/or executables. Typically, shell scripts direct the device to retrieve additional content from external servers or repositories or contain potential configuration details for subsequent binaries to run on the device. For example, the “service.sh” retrieves a tar-compressed archive, a configuration JSON file as well as a file with the name “solr” from GitHub, potentially associated with the Apache Solr tool used for enterprise search. These could be used for further enumeration of the host and/or the network environment. PHP scripts observed may involve similar web shell functionality and were retrieved from both rare external IPs identified as well by external researchers [8]. Darktrace also detected the download of octet-stream data occurring mid-compromise from an Amazon Web Services (AWS) S3 bucket. Although no outside research confirmed the functionality, additional executable downloads for files such as “/initd”(IP: 178.215.224[.]246) and “/x6” (IP: 223.165.4[.]175) may relate to tool ingress, further Trojan/backdoor functionality, or cryptocurrency mining.

External connectivity during this phase also featured TCP connection attempts over uncommon ports for common application protocols. For both Sliver and non-Sliver related IP addresses, devices utilized destination ports such as 8089, 3939, 8880, 8084, and 9999 for the HTTP protocol, again using command line tools as user agents. The use of uncommon destination ports may represent attempts to avoid detection of connectivity to rare external endpoints. Moreover, some external beaconing within included URIs referencing the likely IP of the affected device. Such behavior can suggest the registration of compromised devices with command servers.

Targeted devices also proceeded to download additional payloads from rare external endpoints as beaconing/C2 activity was ongoing. For example, the newly registered domain repositorylinux[.]org (IP: 103.217.145[.]112) received numerous HTTP GET requests from investigated devices throughout the investigation period for script files including “linux.sh” and “cron.sh”. Young domains, especially those that present as similar to known code repositories, tend to host harmful content. Packet captures of the cron.sh file reveal commands within the HTTP body content involving crontab operations, likely to schedule future downloads. Some hosts that engaged in connectivity to the fake repository domain were later seen conducting crypto-mining connections, potentially highlighting the download of miner applications from the domain.

Additional payloads observed during this time largely featured variations of shell scripts, PHP content, and/or executables. Typically, shell scripts direct the device to retrieve additional content from external servers or repositories or contain potential configuration details for subsequent binaries to run on the device. For example, the “service.sh” retrieves a tar-compressed archive, a configuration JSON file as well as a file with the name “solr” from GitHub, potentially associated with the Apache Solr tool used for enterprise search. These could be used for further enumeration of the host and/or the network environment. PHP scripts observed may involve similar web shell functionality and were retrieved from both rare external IPs identified as well by external researchers [8]. Darktrace also detected the download of octet-stream data occurring mid-compromise from an Amazon Web Services (AWS) S3 bucket. Although no outside research confirmed the functionality, additional executable downloads for files such as “/initd”(IP: 178.215.224[.]246) and “/x6” (IP: 223.165.4[.]175) may relate to tool ingress, further Trojan/backdoor functionality, or cryptocurrency mining.

Figure 7: PCAP specifying the HTTP response headers and body content for the service.sh file request. The body content shown includes variable declarations for URLs that will eventually be called by the device shell via bash command.

Reconnaissance and Cryptomining

Darktrace analysts also noticed additional elements of kill chain operations from affected devices after periods of initial exploit activity. Several devices initiated TCP connections to endpoints affiliated with cryptomining pools such as us[.]zephyr[.]herominers[.]com and  xmrig[.]com. Connectivity to these domains indicates likely successful installation of mining software during earlier stages of post-compromise activity. In a small number of instances, Darktrace observed reconnaissance and lateral movement within the time range of PAN-OS exploitation. Firewalls conducted large numbers of internal connectivity attempts across several critical ports related to privileged protocols, including SMB and SSH. Darktrace detected anonymous NTLM login attempts and new usage of potential PAN-related credentials. These behaviors likely constitute attempts at lateral movement to adjacent devices to further extend network compromise impact.

Figure 8: Model alert connection logs detailing the uncommon failed NTLM logins using an anonymous user account following PAN-OS exploitation.

Conclusion

Darktrace Threat Research and SOC analysts increasingly detect spikes in malicious activity on internet-facing devices in the days following the publication of new vulnerabilities. The latest iteration of this trend highlighted how threat actors quickly exploited Palo Alto firewall using authentication bypass and remote command execution vulnerabilities to enable device compromise. A review of the post-exploitation activity during these events reveals consistent patterns of perimeter device exploitation, but also some distinct variations.

Prior campaigns targeting perimeter devices featured activity largely confined to the exfiltration of configuration data and some initial payload retrieval. Within the current campaign, analysts identified a broader scope post-compromise activity consisting not only of payloads downloads but also extensive C2 activity, reconnaissance, and coin mining operations. While the use of command line tools like curl featured prominently in prior investigations, devices were seen retrieving a generally wider array of payloads during the latest round of activity. The use of the Sliver C2 platform further differentiates the latest round of PAN-OS compromises, with evidence of Sliver activity in about half of the investigated cases.

Several of the endpoints contacted by the infected firewall devices did not have any OSINT associated with them at the time of the attack. However, these indicators were noted as unusual for the devices according to Darktrace based on normal network traffic patterns. This reality further highlights the need for anomaly-based detection that does not rely necessarily on known indicators of compromise (IoCs) associated with CVE exploitation for detection. Darktrace’s experience in 2024 of multiple rounds of perimeter device exploitation may foreshadow future increases in these types of comprise operations.  

Credit to Adam Potter (Senior Cyber Analyst), Alexandra Sentenac (Senior Cyber Analyst), Emma Foulger (Principal Cyber Analyst) and the Darktrace Threat Research team.

References

[1]: https://docs.paloaltonetworks.com/pan-os/10-1/pan-os-admin/firewall-administration/management-interfaces

[2]: https://security.paloaltonetworks.com/CVE-2024-9474

[3]: hxxps://cn-sec[.]com/archives/2514664.html

[4]: hxxps[:]//github[.]com/L-codes/Neo-reGeorg/blob/master/README-en.md

[5]: https://threatfox.abuse[.]ch/ioc/1346254/

[6]:https://www.virustotal.com/gui/file/4911396d80baff80826b96d6ea7e54758847c93fdbcd3b86b00946cfd7d1145b/detection

[7]: https://arcticwolf.com/resources/blog/arctic-wolf-observes-threat-campaign-targeting-palo-alto-networks-firewall-devices/

[8] https://www.immersivelabs.com/blog/detecting-and-decrypting-sliver-c2-a-threat-hunters-guide

[9]: https://arcticwolf.com/resources/blog/arctic-wolf-observes-threat-campaign-targeting-palo-alto-networks-firewall-devices/

Appendices

Darktrace Model Alerts

Anomalous Connection / Anomalous SSL without SNI to New External  

Anomalous Connection / Application Protocol on Uncommon Port  

Anomalous Connection / Multiple Failed Connections to Rare Endpoint  

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname  

Anomalous Connection / New User Agent to IP Without Hostname  

Anomalous Connection / Posting HTTP to IP Without Hostname  

Anomalous Connection / Rare External SSL Self-Signed  

Anomalous File / EXE from Rare External Location

Anomalous File / Incoming ELF File  

Anomalous File / Mismatched MIME Type From Rare Endpoint  

Anomalous File / Multiple EXE from Rare External Locations  

Anomalous File / New User Agent Followed By Numeric File Download  

Anomalous File / Script from Rare External Location  

Anomalous File / Zip or Gzip from Rare External Location  

Anomalous Server Activity / Rare External from Server  

Compromise / Agent Beacon (Long Period)  

Compromise / Agent Beacon (Medium Period)  

Compromise / Agent Beacon to New Endpoint  

Compromise / Beacon for 4 Days  

Compromise / Beacon to Young Endpoint  

Compromise / Beaconing Activity To External Rare  

Compromise / High Priority Tunnelling to Bin Services  

Compromise / High Volume of Connections with Beacon Score  

Compromise / HTTP Beaconing to New IP  

Compromise / HTTP Beaconing to Rare Destination  

Compromise / Large Number of Suspicious Failed Connections  

Compromise / Large Number of Suspicious Successful Connections  

Compromise / Slow Beaconing Activity To External Rare  

Compromise / SSL Beaconing to Rare Destination  

Compromise / Suspicious Beaconing Behavior  

Compromise / Suspicious File and C2  

Compromise / Suspicious HTTP and Anomalous Activity  

Compromise / Suspicious TLS Beaconing To Rare External  

Compromise / Sustained SSL or HTTP Increase  

Compromise / Sustained TCP Beaconing Activity To Rare Endpoint    

Device / Initial Attack Chain Activity  

Device / New User Agent  

MITRE ATT&CK Mapping

Tactic – Technique

INITIAL ACCESS – Exploit Public-Facing Application

RESOURCE DEVELOPMENT – Malware

EXECUTION – Scheduled Task/Job (Cron)

EXECUTION – Unix Shell

PERSISTENCE – Web Shell

DEFENSE EVASION – Masquerading (Masquerade File Type)

DEFENSE EVASION - Deobfuscate/Decode Files or Information

CREDENTIAL ACCESS – Brute Force

DISCOVERY – Remote System Discovery

COMMAND AND CONTROL – Ingress Tool Transfer

COMMAND AND CONTROL – Application Layer Protocol (Web Protocols)

COMMAND AND CONTROL – Encrypted Channel

COMMAND AND CONTROL – Non-Standard Port

COMMAND AND CONTROL – Data Obfuscation

IMPACT – Resource Hijacking (Compute)

List of IoCs

IoC         –          Type         –        Description

  • sys.traceroute[.]vip     – Hostname - C2 Endpoint
  • 77.221.158[.]154     – IP - C2 Endpoint
  • 185.174.137[.]26     – IP - C2 Endpoint
  • 93.113.25[.]46     – IP - C2 Endpoint
  • 104.131.69[.]106     – IP - C2 Endpoint
  • 95.164.5[.]41     – IP - C2 Endpoint
  • bristol-beacon-assets.s3.amazonaws[.]com     – Hostname - Payload Server
  • img.dxyjg[.]com     – Hostname - Payload Server
  • 38.180.147[.]18     – IP - Payload Server
  • 143.198.1[.]178     – IP - Payload Server
  • 185.208.156[.]46     – IP - Payload Server
  • 185.196.9[.]154     – IP - Payload Server
  • 46.8.226[.]75     – IP - Payload Server
  • 223.165.4[.]175     – IP - Payload Server
  • 188.166.244[.]81     – IP - Payload Server
  • bristol-beaconassets.s3[.]amazonaws[.]com/Y5bHaYxvd84sw     – URL - Payload
  • img[.]dxyjg[.]com/KjQfcPNzMrgV     – URL - Payload
  • 38.180.147[.]18/palofd     – URL - Payload
  • 90f6890fa94b25fbf4d5c49f1ea354a023e06510     – SHA1 - Associated to file /palofd
  • 143.198.1[.]178/7Z0THCJ     – URL - Payload
  • 8d82ccdb21425cf27b5feb47d9b7fb0c0454a9ca     – SHA1 - Associated to file /7Z0THCJ
  • fefd0f93dcd6215d9b8c80606327f5d3a8c89712     – SHA1 - Associated to file /7Z0THCJ
  • e5464f14556f6e1dd88b11d6b212999dd9aee1b1     – SHA1 - Associated to file /7Z0THCJ
  • 143.198.1[.]178/o4VWvQ5pxICPm     – URL - Payload
  • 185.208.156[.]46/lUuL095knXd62DdR6umDig     – URL - Payload
  • 185.196.9[.]154/ykKDzZ5o0AUSfkrzU5BY4w     – URL - Payload
  • 46.8.226[.]75/1.txt     – URL - Payload
  • 223.165.4[.]175/x6     – URL - Payload
  • 45.76.141[.]166/y.sh     – URL - Payload
  • repositorylinux[.]org/linux.sh     – URL - Payload
  • repositorylinux[.]org/cron.sh     – URL - Payload

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About the author
Adam Potter
Senior Cyber Analyst

Blog

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November 28, 2024

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Cloud

Cloud security: addressing common CISO challenges with advanced solutions

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Cloud adoption is a cornerstone of modern business with its unmatched potential for scalability, cost efficiency, flexibility, and net-zero targets around sustainability. However, as organizations migrate more workloads, applications, and sensitive data to the cloud it introduces more complex challenges for CISO’s. Let’s dive into the most pressing issues keeping them up at night—and how Darktrace / CLOUD provides a solution for each.

1. Misconfigurations: The Silent Saboteur

Misconfigurations remain the leading cause of cloud-based data breaches. In 2023 alone over 80%  of data breaches involved data stored in the cloud.1  Think open storage buckets or overly permissive permissions; seemingly minor errors that are easily missed and can snowball into major disasters. The fallout of breaches can be costly—both financially and reputationally.

How Darktrace / CLOUD Helps:

Darktrace / CLOUD continuously monitors your cloud asset configurations, learning your environment and using these insights to flag potential misconfigurations. New scans are triggered when changes take place, then grouped and prioritised intelligently, giving you an evolving and prioritised view of vulnerabilities, best practice and mitigation strategies.

2. Hybrid Environments: The Migration Maze

Many organizations are migrating to the cloud, but hybrid setups (where workloads span both on-premises and cloud environments) create unique challenges and visibility gaps which significantly increase complexity. More traditional and most cloud native security tooling struggles to provide adequate monitoring for these setups.

How Darktrace / CLOUD Helps:

Provides the ability to monitor runtime activity for both on-premises and cloud workloads within the same user interface. By leveraging the right AI solution across this diverse data set, we understand the behaviour of your on-premises workloads and how they interact with cloud systems, spotting unusual connectivity or data flow activity during and after the migration process.

This unified visibility enables proactive detection of anomalies, ensures seamless monitoring across hybrid environments, and provides actionable insights to mitigate risks during and after the migration process.

3. Securing Productivity Suites: The Last Mile

Cloud productivity suites like Microsoft 365 (M365) are essential for modern businesses and are often the first step for an organization on a journey to Infrastructure as a Service (IaaS) or Platform as a Service (PaaS) use cases. They also represent a prime target for attackers. Consider a scenario where an attacker gains access to an M365 account, and proceeds to; access sensitive emails, downloading files from SharePoint, and impersonating the user to send phishing emails to internal employees and external partners. Without a system to detect these behaviours, the attack may go unnoticed until significant damage is done.

How Darktrace helps:

Darktrace’s Active AI platform integrates with M365 and establishes an understanding of normal business activity, enabling the detection of abnormalities across its suite including Email, SharePoint and Teams. By identifying subtle deviations in behaviour, such as:

   •    Unusual file accesses

   •    Anomalous login attempts from unexpected locations or devices.

   •    Suspicious email forwarding rules created by compromised accounts.

Darktrace’s Autonomous Response can act precisely to block malicious actions, by disabling compromised accounts and containing threats before they escalate. Precise actions also ensure that critical business operations are maintained even when a response is triggered.  

4. Agent Fatigue: The Visibility Struggle

To secure cloud environments, visibility is critical. If you don’t know what’s there, how can you secure it? Many solutions require agents to be deployed on every server, workload, and endpoint. But managing and deploying agents across sprawling hybrid environments can be both complex and time-consuming when following change controls, and especially as cloud resources scale dynamically.

How Darktrace / CLOUD Helps:

Darktrace reduces or eliminates the need for widespread agent deployment. Its agentless by default, integrating directly with cloud environments and providing instant visibility without the operational headache. Darktrace ensures coverage with minimal friction. By intelligently graphing the relationships between assets and logically grouping your deployed Cloud resources, you are equipped with real-time visibility to quickly understand and protect your environment.

So why Darktrace / CLOUD?

Darktrace’s Self-Learning AI redefines cloud security by adapting to your unique environment, detecting threats as they emerge, and responding in real-time. From spotting misconfigurations to protecting productivity suites and securing hybrid environments. Darktrace / CLOUD simplifies cloud security challenges without adding operational burdens.

From Chaos to Clarity

Cloud security doesn’t have to be a game of endless whack-a-mole. With Darktrace / CLOUD, CISOs can achieve the visibility, control, and proactive protection they need to navigate today’s complex cloud ecosystems confidently.

[1] https://hbr.org/2024/02/why-data-breaches-spiked-in-2023

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About the author
Adam Stevens
Director of Product, Cloud Security
Your data. Our AI.
Elevate your network security with Darktrace AI