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April 15, 2021

AI Neutralizes Hafnium Cyber Attack in December 2020

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15
Apr 2021
Protect your business from cyber attacks with AI technology. Learn how Darktrace neutralized the Hafnium attack against Exchange servers in December 2020.

In early December 2020, Darktrace AI autonomously detected and investigated a sophisticated cyber-attack that targeted a customer’s Exchange server. On March 2, 2021, Microsoft disclosed an ongoing campaign by the Hafnium threat actor group leveraging Exchange server zero-days.

Based on similarities in techniques, tools and procedures (TTPs) observed, Darktrace has now assessed with high confidence that the attack in December was the work of the Hafnium group. Although it is not possible to determine whether this attack leveraged the same Exchange zero-days as reported by Microsoft, the finding suggests that Hafnium’s campaign was active several months earlier than assumed.

As a result, organizations may want to go back as far as early December 2020 to check security logs and tools for signs of initial intrusion into their Internet-facing Exchange servers.

As Darktrace does not rely on rules or signatures, it doesn’t require a constant cloud connection. Most customers therefore operate our technology themselves, and we don’t centrally monitor their detections.

At the time of detection in December, this was one of many uncategorized, sophisticated intrusions that affected only a single customer, and was not indicative of a broader campaign.

This means that while we protect our customers from individual intrusions, we are not in a position to do global campaign tracking like other companies which focus primarily on threat intelligence and threat actor tracking.

In this blog, we will analyze the attack to aid organizations in their ongoing investigations, and to raise awareness that the Hafnium campaign may have been active for longer than previously disclosed.

Overview of the Exchange attack

The intrusion was detected at an organization in the critical national infrastructure sector in South Asia. One hypothesis is that the Hafnium group was testing out and refining its TTPs, potentially including the Exchange server exploit, before running a broad-scale campaign against Western organizations in early 2021.

The threat actor used many of the same techniques that were observed in the later Hafnium attacks, including the deployment of the low-activity China Chopper web shell, quickly followed by post-exploitation activity – attempting to move laterally and spread to critical devices in the network.

The following analysis demonstrates how Darktrace’s Enterprise Immune System detected the malicious activity, how Cyber AI Analyst automatically investigated on the incident and surfaced the alert as a top priority, and how Darktrace RESPOND (formerly known as 'Antigena') would have responded autonomously to shut down the attack, had it been in active mode.

All the activity took place in early December 2020, almost three months before Microsoft released information about the Hafnium campaign.

Figure 1: Timeline of the attack from early December 2020

Initial compromise

Unfortunately, the victim organization did not keep any logs or forensic artefacts from their Exchange server in December 2020, which would have allowed Darktrace to ascertain the exploit of the zero-day. However, there is circumstantial evidence suggesting that these Exchange server vulnerabilities were abused.

Darktrace observed no signs of compromise or change in behavior from the Internet-facing Exchange server – no prior internal admin connections, no broad-scale brute-force attempts, no account takeovers, no malware copied to the server via internal channels – until all of a sudden, it began to scan the internal network.

While this is not conclusive evidence that no other avenue of initial intrusion was present, the change in behavior on an administrative level points to a complete takeover of the Exchange server, rather than the compromise of a single Outlook Web Application account.

To conduct a network scan from an Exchange server, a highly privileged, operating SYSTEM-level account is required. The patch level of the Exchange server at the time of compromise appears to have been up-to-date, at least not offering a threat actor the ability to target a known vulnerability to instantly get SYSTEM-level privileges.

For this reason, Darktrace has inferred that the Exchange server zero-days that became public in early March 2021 were possibly being used in this attack observed in early December 2020.

Internal reconnaissance

As soon as the attackers gained access via the web shell, they used the Exchange server to scan all IPs in a single subnet on ports 80, 135, 445, 8080.

This particular Exchange server had never made such a large number of new failed internal connections to that specific subnet on those key ports. As a result, Darktrace instantly alerted on the anomalous behavior, which was indicative of a network scan.

Autonomous Response

Darktrace RESPOND was in passive mode in the environment, so was not able to take action. In active mode, it would have responded by enforcing the previously learned, normal ‘pattern of life’ of the Exchange server – allowing the server to continue normal business operations (sending and receiving emails) but preventing the network scan and any subsequent activity. These actions would have been carried out via various integrations with the customer’s existing security stack, including Firewalls and Network Access Controls.

Specifically, when the network scanning started, the ‘Antigena Network Scan Block’ was triggered. This means that for several hours, Darktrace RESPOND (Antigena) would have blocked any new outgoing connections from the Exchange server to the scanned subnet on port 80, 135, 445, or 8080, preventing the infected Exchange server from conducting network scanning.

As a result, the attackers would not have been able to conclude anything from their reconnaissance — all their scanning would have returned closed ports. At this point, they would need to stop their attack or resort to other means, likely triggering further detections and further Autonomous Response.

The network scan was the first step touching the internal network. This is therefore a clear case of how Darktrace RESPOND can intercept an attack in seconds, acting at the earliest possible evidence of the intrusion.

Lateral movement

Less than an hour after the internal network scan, the compromised Exchange server was observed writing further web shells to other Exchange servers via internal SMB. Darktrace alerted on this as the initially compromised Exchange server had never accessed the other Exchange servers in this fashion over SMB, let alone writing .aspx files to Program Files remotely.

A single click allowed the security team to pivot from the alert into Darktrace’s Advanced Search, revealing further details about the written files. The full file path for the newly deployed web shells was:

Program Files\Microsoft\Exchange Server\V15\FrontEnd\HttpProxy\owa\auth\Current\themes\errorFS.aspx

The attackers thus used internal SMB to compromise further Exchange servers and deploy more web shells, rather than using the Exchange zero-day exploit again to achieve the same goal. The reason for this is clear: exploits can often be unstable, and an adversary would not want to show their hand unnecessarily if it could be avoided.

While the China Chopper web shell has been deployed with many different names in the past, the file path and file name of the actual .aspx web shell bear very close resemblance to the Hafnium campaign details published by Microsoft and others in March 2021.

As threat actors often reuse naming conventions / TTPs in coherent campaigns, it again indicates that this particular attack was in some way part of the broader campaign observed in early 2021.

Further lateral movement

Minutes later, the attacker conducted further lateral movement by making more SMB drive writes to Domain Controllers. This time the attackers did not upload web shells, but malware, in the form of executables and Windows .bat files.

Darktrace alerted the security team as it was extremely unusual for the Exchange server and its peer group to make SMB drive writes to hidden shares to a Domain Controller, particularly using executables and batch files. The activity was presented to the team in the form of a high-confidence alert such as the anonymized example below.

Figure 2: Example graphic of Darktrace detecting unusual connectivity

The batch file was called ‘a.bat’. At this point, the security team could have created a packet capture for the a.bat file in Darktrace with the click of a button, inspecting the content and details of that script at the time of the intrusion.

Darktrace also listed the credentials involved in the activity, providing context into the compromised accounts. This allows an analyst to pivot rapidly around the data and further understand the scope of the intrusion.

Bird’s-eye perspective

In addition to detecting the malicious activity outlined above, Darktrace’s Cyber AI Analyst autonomously summarized the incident and reported on it, outlining the internal reconnaissance and lateral movement activity in a single, cohesive incident.

The organization has several thousand devices covered by Darktrace’s Enterprise Immune System. Nevertheless, over the period of one week, the Hafnium intrusion was in the top five incidents highlighted in Cyber AI Analyst. Even a small or resource-stretched security team, with only a few minutes available per week to review the highest-severity incidents, could have seen and inspected this threat.

Below is a graphic showing a similar Cyber AI Analyst incident created by Darktrace.

Figure 3: A Cyber AI Analyst report showing unusual SMB activity

How to stop a zero-day

Large scale campaigns which target Internet-facing infrastructure and leverage zero-day exploits will continue to occur regularly, and such attacks will always succeed in evading signature-based detection. However, organizations are not helpless against the next high-profile zero-day or supply chain attack.

Detecting the movements of attackers inside a system and responding to contain in-progress threats is possible before IoCs have been provided. The methods of detection outlined above protected the company against this attack in December, and the same techniques will continue to protect the company against unknown threats in the future.

Learn more about how Darktrace AI has stopped Hafnium cyber-attacks and similar threat actors

Darktrace model detections:

  • Device / New or Uncommon WMI Activity
  • Executable Uploaded to DC
  • Compliance / High Priority Compliance Model Breach
  • Compliance / SMB Drive Write
  • Antigena / Network / Insider Threat / Antigena Network Scan Block
  • Device / Network Scan - Low Anomaly Score
  • Unusual Activity / Unusual Internal Connections

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
Max Heinemeyer
Chief Product Officer

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

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December 11, 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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Introduction: Spike in exploitation and post-exploitation activity affecting Palo Alto firewall devices

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 supplying an HTTP request where a Palo Alto related authentication header can be set to “off”.  Users can supply this header value to the Nginx reverse proxy server fronting the application which will then send it 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 cryptomining 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.

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

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.
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 Spectre RAT, a remote access trojan with capabilities including remote command execution, payload delivery, process manipulation, file transfers, and data theft [3][4].

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 an incorrect certificate to the requesting client when multiple sites are hosted on the same IP. SSL connectivity without SNI specification suggests a potentially malicious running process as most software establishing TLS sessions typically supply this information during the handshake. 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 [5].

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 [6]. Investigations yielded evidence of both English word encoding within Sliver, identified through PCAP analysis, and Gzip formatting.

Sample of URIs observed in Advanced Searchhighlighting HTTP requests to 77.221.158[.]154 for Gzip content suggest of Sliver communication.
Figure 4: Sample of URIs observed in Advanced Searchhighlighting HTTP requests to 77.221.158[.]154 for Gzip content suggest of Sliver communication.
PCAP showing English word encoding for Sliver communication observed during post-exploitation C2 activity.
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. 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 [7]. 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.

Model alert connection logs detailing the uncommon failed NTLM logins using an anonymous user account following PAN-OS exploitation.
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://labs.watchtowr.com/pots-and-pans-aka-an-sslvpn-palo-alto-pan-os-cve-2024-0012-and-cve-2024-9474/

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

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

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

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

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

[7] 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

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December 11, 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.
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