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How Conti ransomware took down Operational Technology

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09
Feb 2022
09
Feb 2022
This blog demonstrates how ransomware can spread throughout converged IT/OT environments, and how Self-Learning AI empowers organizations to contain these threats.

Ransomware has taken the world by storm, and IT is not the only technology affected. Operational Technology (OT), which is increasingly blending with IT, is also susceptible to ransomware tactics, techniques, and procedures (TTPs). And when ransomware strikes OT, the effects have the potential to be devastating.

Here, we will look at a ransomware attack that spread from IT to OT systems. The attack was detected by Darktrace AI.

This threat find demonstrates a use case of Darktrace’s technology that delivers immense value to organizations with OT: spotting and stopping ransomware at its earliest stages, before the damage is done. This is particularly helpful for organizations with interconnected enterprise and industrial environments, as it means:

  1. Emerging attacks can be contained in IT before they spread laterally into OT, and even before they spread from device to device in IT;
  2. Organizations gain granular visibility into their industrial environments, detecting deviations from normal activity, and quick identification of remediating actions.

Threat find: Ransomware and crypto-mining hijack affecting IT and OT systems

Darktrace recently identified an aggressive attack targeting an OT R&D investment firm in EMEA. The attack originally started as a crypto-mining campaign and later evolved into ransomware. This organization deployed Darktrace in a digital estate containing both IT and OT assets that spanned over 3,000 devices.

If the organization had deployed Darktrace’s Autonomous Response technology in active mode, this threat would have been stopped in its earliest stages. Even in the absence of Autonomous Response, however, mere human attention would have stopped this attack’s progression. Darktrace’s Self-Learning AI gave clear indications of an ongoing compromise in the month prior to the detonation of ransomware. In this case, however, the security team was not monitoring Darktrace’s interface, and so the attack was allowed to proceed.

Compromised OT devices

This threat find will focus on the attack techniques used to take over two OT devices, specifically, a HMI (human machine interface), and an ICS Historian used to collect and log industrial data. These OT devices were both VMware virtual machines running Windows OS, and were compromised as part of a wider Conti ransomware infection. Both devices were being used primarily within an industrial control system (ICS), running a popular ICS software package and making regular connections to an industrial cloud platform.

These devices were thus part of an ICSaaS (ICS-as-a-Service) environment, using virtualised and Cloud platforms to run analytics, update threat intelligence, and control the industrial process. As previously highlighted by Darktrace, the convergence of cloud and ICS increases a network’s attack surface and amplifies cyber risk.

Attack lifecycle

Opening stages

The initial infection of the OT devices occurred when a compromised Domain Controller (DC) made unusual Active Directory requests. The devices made subsequent DCE-RPC binds for epmapper, often used by attackers for command execution, and lsarpc, used by attackers to abuse authentication policies and escalate privileges.

The payload was delivered when the OT devices used SMB to connect to the sysvol folder on the DC and read a malicious executable file, called SetupPrep.exe.

Figure 1: Darktrace model breaches across the whole network from initial infection on October 21 to the detonation on November 15.

Figure 2: ICS reads on the HMI in the lead up, during, and following detonation of the ransomware.

Device encryption and lateral spread

The malicious payload remained dormant on the OT devices for three weeks. It seems the attacker used the time to install crypto-mining malware elsewhere on the network and consolidate their foothold.

On the day the ransomware detonated, the attacker used remote management tools to initiate encryption. The PSEXEC tool was used on an infected server (separate from the original DC) to remotely execute malicious .dll files on the compromised OT devices.

The devices then attempted to make command and control (C2) connections to rare external endpoints using suspicious ports. Like in many ICS networks, sufficient network segregation had been implemented to prevent the HMI device from making successful connections to the Internet and the C2 communications failed. But worryingly, the failed C2 did not prevent the attack from proceeding or the ransomware from detonating.

The Historian device made successful C2 connections to around 40 unique external endpoints. Darktrace detected beaconing-type behavior over suspicious TCP/SSL ports including 465, 995, 2078, and 2222. The connections were made to rare destination IP addresses that did not specify the Server Name Indication (SNI) extension hostname and used self-signed and/or expired SSL certificates.

Both devices enumerated network SMB shares and wrote suspicious shell scripts to network servers. Finally, the devices used SMB to encrypt files stored in network shares, adding a file extension which is likely to be unique to this victim and which will be called ABCXX for the purpose of this blog. Most encrypted files were uploaded to the folder in which the file was originally located, but in some instances were moved to the images folder.

During the encryption, the device was using the machine account to authenticate SMB sessions. This is in contrast to other ransomware incidents that Darktrace has observed, in which admin or service accounts are compromised and abused by the attacker. It is possible that in this instance the attacker was able to use ‘Living off the Land’ techniques (for example the use of lsarpc pipe) to give the machine account admin privileges.

Examples of files being encrypted and moved:

  • SMB move success
  • File: new\spbr0007\0000006A.bak
  • Renamed: new\spbr0007\0000006A.bak.ABCXX
  • SMB move success
  • File: ActiveMQ\readme.txt
  • Renamed: Images\10j0076kS1UA8U975GC2e6IY.488431411265952821382.png.ABCXX

Detonation of ransomware

Upon detonation, the ransomware note readme.txt was written by the ICS to targeted devices as part of the encryption activity.

The final model breached by the device was “Unresponsive ICS Device” as the device either stopped working due to the effects of the ransomware, or was removed from the network.

Figure 3: abc-histdev — external connections filtered on destination port 995 shows C2 connections starting around one hour before encryption began.

How the attack bypassed the rest of the security stack

In this threat find, there were a number of factors which resulted in the OT devices becoming compromised.

The first is IT/OT convergence. The ICS network was insufficiently segregated from the corporate network. This means that devices could be accessed by the compromised DC during the lateral movement stage of the attack. As OT becomes more reliant on IT, ensuring sufficient segregation is in place, or that an attacker can not circumvent such segregation, is becoming an ever increasing challenge for security teams.

Another reason is that the attacker used attack methods which leverage Living off the Land techniques to compromise devices with no discrimination as to whether they were part of an IT or OT network. Many of the machines used to operate ICS networks, including the devices highlighted here, rely on operating systems vulnerable to the kinds of TTPs observed here and that are regularly employed by ransomware groups.

Darktrace insights

Darktrace’s Cyber AI Analyst was able to stitch together many disparate forms of unusual activity across the compromised devices to give a clear security narrative containing details of the attack. The incident report for the Historian server is shown below. This provides a clear illustration of how Cyber AI Analyst can close any skills or communication gap between IT and OT specialists.

Figure 4: Cyber AI Analyst of the Historian server (abc-histdev). It investigated and reported the C2 communication (step 2) that started just before network reconnaissance using TCP scanning (step 3) and the subsequent file encryption over SMB (step 4).

In total, the attacker’s dwell time within the digital estate was 25 days. Unfortunately, it lead to disruption to operational technology, file encryption and financial loss. Altogether, 36 devices were crypto-mining for over 20 days – followed by nearly 100 devices (IT and OT) becoming encrypted following the detonation of the ransomware.

If it were active, Autonomous Response would have neutralized this activity, containing the damage before it could escalate into crisis. Darktrace’s Self-Learning AI gave clear indications of an ongoing compromise in the month prior to the detonation of ransomware, and so any degree of human attention toward Darktrace’s revelations would have stopped the attack.

Autonomous Response is highly configurable, and so, in industrial environments — whether air-gapped OT or converged IT/OT ecosystems — Antigena can be deployed in a variety of manners. In human confirmation mode, human operators need to give the green light before the AI takes action. Antigena can also be deployed only in the higher levels of the Purdue model, or the “IT in OT,” protecting the core assets from fast-moving attacks like ransomware.

Ransomware and interconnected IT/OT systems

ICS networks are often operated by machines that rely on operating systems which can be affected by TTPs regularly employed by ransomware groups — that is, TTPs such as Living off the Land, which do not discriminate between IT and OT.

The threat that ransomware poses to organizations with OT, including critical infrastructure, is so severe that the Cyber Infrastructure and Security Agency (CISA) released a fact sheet concerning these threats in the summer of 2021, noting the risk that IT attacks pose to OT networks:

“OT components are often connected to information technology (IT) networks, providing a path for cyber actors to pivot from IT to OT networks… As demonstrated by recent cyber incidents, intrusions affecting IT networks can also affect critical operational processes even if the intrusion does not directly impact an OT network.”

Major ransomware attacks against the Colonial Pipeline and JBS Foods demonstrate the potential for ransomware affecting OT to cause severe economic disruption on a national and international scale. And ransomware can wreak havoc on OT systems regardless of whether they directly target OT systems.

As industrial environments continue to converge and evolve — be they IT/OT, ICSaaS, or simply poorly segregated legacy systems — Darktrace stands ready to contain attacks before the damage is done. It is time for organizations with industrial environments to take the quantum leap forward that Darktrace’s Self-Learning AI is uniquely positioned to provide.

Thanks to Darktrace analysts Ash Brice and Andras Balogh for their insights on the above threat find.

Discover more on how Darktrace protects OT environments from ransomware

Darktrace model detections

HMI in chronological order at time of detonation:

  • Anomalous Connection / SMB Enumeration
  • Anomalous File / Internal / Unusual SMB Script Write
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Compromise / Ransomware / Suspicious SMB Activity [Enhanced Monitoring]
  • ICS / Unusual Data Transfer By OT Device
  • ICS / Unusual Unresponsive ICS Device

Historian

  • ICS / Rare External from OT Device
  • Anomalous Connection / Anomalous SSL without SNI to New External
  • Anomalous Connection / Multiple Connections to New External TCP Port
  • ICS / Unusual Activity From OT Device
  • Anomalous Connection / SMB Enumeration
  • Anomalous Connection / Suspicious Activity On High Risk Device
  • Unusual Activity / SMB Access Failures
  • Device / Large Number of Model Breaches
  • ICS / Unusual Data Transfer By OT Device
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Device / SMB Lateral Movement
  • Compromise / Ransomware / Suspicious SMB Activity [Enhanced Monitoring]
  • Device / Multiple Lateral Movement Model Breaches [Enhanced Monitoring]

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
Oakley Cox
Director of Product

Oakley is a Product Manager within the Darktrace R&D team. He collaborates with global customers, including all critical infrastructure sectors and Government agencies, to ensure Darktrace/OT remains the first in class solution for OT Cyber Security. He draws on 7 years’ experience as a Cyber Security Consultant to organizations across EMEA, APAC and ANZ. His research into cyber-physical security has been published by Cyber Security journals and by CISA. Oakley has a Doctorate (PhD) from the University of Oxford.

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A Busy Agenda: Darktrace’s Detection of Qilin Ransomware-as-a-Service Operator

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04
Jul 2024

Qilin ransomware has recently dominated discussions across the cyber security landscape following its deployment in an attack on Synnovis, a UK-based medical laboratory company. The ransomware attack ultimately affected patient services at multiple National Health Service (NHS) hospitals that rely on Synnovis diagnostic and pathology services. Qilin’s origins, however, date back further to October 2022 when the group was observed seemingly posting leaked data from its first known victim on its Dedicated Leak Site (DLS) under the name Agenda[1].

The Darktrace Threat Research team investigated network artifacts related to Qilin and identified three probable cases of the ransomware across the Darktrace customer base between June 2022 and May 2024.

Qilin Ransomware-as-a-Service Operator

Qilin operates as a Ransomware-as-a-Service (RaaS) that employs double extortion tactics, whereby harvested data is exfiltrated and threatened of publication on the group's DLS, which is hosted on Tor. Qilin ransomware has samples written in both the Golang and Rust programming languages, making it compilable with various operating systems, and is highly customizable. When building Qilin ransomware variants to be used on their target(s), affiliates can configure settings such as the encryption mode (i.e., skip-step, percent, and speed), the file extension being appended, files, extensions and directories to be skipped during the encryption, and the processes and services to be terminated, among others[1] [2].  

Trend Micro analysts, who were the first to discover Qilin samples in August 2022, when the name "Agenda" was still used in ransom notes, found that each analyzed sample was customized for the intended victims and that "unique company IDs were used as extensions of encrypted files" [3]. This information is configurable from within the Qilin's affiliate panel's 'Targets' section, shown below. The panel's background image features the eponym Chinese legendary chimerical creature Qilin (pronounced “Ke Lin”). Despite this Chinese mythology reference, Russian language was observed being used by a Qilin operator in an underground forum post aimed at hiring affiliates and advertising their RaaS operation[2].

Figure 1: Qilin ransomware’s affiliate panel.

Qilin's RaaS program purportedly has an attractive affiliates' payment structure, with affiliates allegedly able to earn 80% of ransom payments of USD 3m or less and 85% for payments above that figure[2], making it a possibly appealing option in the RaaS ecosystem.  Publication of stolen data and ransom payment negotiations are purportedly handled by Qilin operators. Qilin affiliates have been known to target companies located around the world and within a variety of industries, including critical sectors such as healthcare and energy.

As Qilin is a RaaS operation, the choice of targets does not necessarily reflect Qilin operators' intentions, but rather that of its affiliates.  Similarly, the tactics, techniques, procedures (TTPs) and indicators of compromise (IoC) identified by Darktrace are associated with the given affiliate deploying Qilin ransomware for their own purpose, rather than TTPs and IoCs of the Qilin group. Likewise, initial vectors of infection may vary from affiliate to affiliate. Previous studies show that initial access to networks were gained via spear phishing emails or by leveraging exposed applications and interfaces.

Differences have been observed in terms of data exfiltration and potential C2 external endpoints, suggesting the below investigations are not all related to the same group or actor(s).

Darktrace’s Threat Research Investigation

June 2022

Darktrace first detected an instance of Qilin ransomware back in June 2022, when an attacker was observed successfully accessing a customer’s Virtual Private Network (VPN) and compromising an administrative account, before using RDP to gain access to the customer’s Microsoft System Center Configuration Manager (SCCM) server

From there, an attack against the customer's VMware ESXi hosts was launched. Fortunately, a reboot of their virtual machines (VM) caught the attention of the security team who further uncovered that custom profiles had been created and remote scripts executed to change root passwords on their VM hosts. Three accounts were found to have been compromised and three systems encrypted by ransomware.  

Unfortunately, Darktrace was not configured to monitor the affected subnets at the time of the attack. Despite this, the customer was able to work directly with Darktrace analysts via the Ask the Expert (ATE) service to add the subnets in question to Darktrace’s visibility, allowing it to monitor for any further unusual behavior.

Once visibility over the compromised SCCM server was established, Darktrace observed a series of unusual network scanning activities and the use of Kali (a Linux distribution designed for digital forensics and penetration testing). Furthermore, the server was observed making connections to multiple rare external hosts, many using the “[.]ru” Top Level Domain (TLD). One of the external destinations the server was attempting to connect was found to be related to SystemBC, a malware that turns infected hosts into SOCKS5 proxy bots and provides command-and-control (C2) functionality.

Additionally, the server was observed making external connections over ports 993 and 143 (typically associated with the use of the Interactive Message Access Protocol (IMAP) to multiple rare external endpoints. This was likely due to the presence of Tofsee malware on the device.

After the compromise had been contained, Darktrace identified several ransom notes following the naming convention “README-RECOVER-<extension/company_id>.txt”” on the network. This naming convention, as well as the similar “<company_id>-RECOVER-README.txt” have been referenced by open-source intelligence (OSINT) providers as associated with Qilin ransom notes[5] [6] [7].

April 2023

The next case of Qilin ransomware observed by Darktrace took place in April 2023 on the network of a customer in the manufacturing sector in APAC. Unfortunately for the customer in this instance, Darktrace RESPOND™ was not active on their environment and no autonomous response actions were taken to contain the compromise.

Over the course of two days, Darktrace identified a wide range of malicious activity ranging from extensive initial scanning and lateral movement attempts to the writing of ransom notes that followed the aforementioned naming convention (i.e., “README-RECOVER-<extension/company_id>.txt”).

Darktrace observed two affected devices attempting to move laterally through the SMB, DCE-RPC and RDP network protocols. Default credentials (e.g., UserName, admin, administrator) were also observed in the large volumes of SMB sessions initiated by these devices. One of the target devices of these SMB connections was a domain controller, which was subsequently seen making suspicious WMI requests to multiple devices over DCE-RPC and enumerating SMB shares by binding to the ‘server service’ (srvsvc) named pipe to a high number of internal devices within a short time frame. The domain controller was further detected establishing an anomalously high number of connections to several internal devices, notably using the RDP administrative protocol via a default admin cookie.  

Repeated connections over the HTTP and SSL protocol to multiple newly observed IPs located in the 184.168.123.0/24 range were observed, indicating C2 connectivity.  WebDAV user agent and a JA3 fingerprint potentially associated with Cobalt Strike were notably observed in these connections. A few hours later, Darktrace detected additional suspicious external connections, this time to IPs associated with the MEGA cloud storage solution. Storage solutions such as MEGA are often abused by attackers to host stolen data post exfiltration. In this case, the endpoints were all rare for the network, suggesting this solution was not commonly used by legitimate users. Around 30 GB of data was exfiltrated over the SSL protocol.

Darktrace did not observe any encryption-related activity on this customer’s network, suggesting that encryption may have taken place locally or within network segments not monitored by Darktrace.

May 2024

The most recent instance of Qilin observed by Darktrace took place in May 2024 and involved a customer in the US. In this case, Darktrace initially detected affected devices using unusual administrative and default credentials, before additional internal systems were observed making extensive suspicious DCE-RPC requests to a range of internal locations, performing network scanning, making unusual internal RDP connections, and transferring suspicious executable files like 'a157496.exe' and '83b87b2.exe'.  SMB writes of the file "LSM_API_service" were also observed, activity which was considered 100% unusual by Darktrace; this is an RPC service that can be abused to enumerate logged-in users and steal their tokens. Various repeated connections likely representative of C2 communications were detected via both HTTP and SSL to rare external endpoints linked in OSINT to Cobalt Strike use. During these connections, HTTP GET requests for the following URIs were observed:

/asdffHTTPS

/asdfgdf

/asdfgHTTP

/download/sihost64.dll

Notably, this included a GET request a DLL file named "sihost64.dll" from a domain controller using PowerShell.  

Over 102 GB of data may have been transferred to another previously unseen endpoint, 194.165.16[.]13, via the unencrypted File Transfer Protocol (FTP). Additionally, many non-FTP connections to the endpoint could be observed, over which more than 783 GB of data was exfiltrated. Regarding file encryption activity, a wide range of destination devices and shares were targeted.

Figure 2: Advanced Search graph displaying the total volume of data transferred over FTP to a malicious IP.

During investigations, Darktrace’s Threat Research team identified an additional customer, also based in the United States, where similar data exfiltration activity was observed in April 2024. Although no indications of ransomware encryption were detected on the network, multiple similarities were observed with the case discussed just prior. Notably, the same exfiltration IP and protocol (194.165.16[.]13 and FTP, respectively) were identified in both cases. Additional HTTP connectivity was further observed to another IP using a self-signed certificate (i.e., CN=ne[.]com,OU=key operations,O=1000,L=,ST=,C=KM) located within the same ASN (i.e., AS48721 Flyservers S.A.). Some of the URIs seen in the GET requests made to this endpoint were the same as identified in that same previous case.

Information regarding another device also making repeated connections to the same IP was described in the second event of the same Cyber AI Analyst incident. Following this C2 connectivity, network scanning was observed from a compromised domain controller, followed by additional reconnaissance and lateral movement over the DCE-RPC and SMB protocols. Darktrace again observed SMB writes of the file "LSM_API_service", as in the previous case, activity which was also considered 100% unusual for the network. These similarities suggest the same actor or affiliate may have been responsible for activity observed, even though no encryption was observed in the latter case.

Figure 3. First event of the Cyber AI Analyst investigation following the compromise activity.

According to researchers at Microsoft, some of the IoCs observed on both affected accounts are associated with Pistachio Tempest, a threat actor reportedly associated with ransomware distribution. The Microsoft threat actor naming convention uses the term "tempest" to reference criminal organizations with motivations of financial gain that are not associated with high confidence to a known non-nation state or commercial entity. While Pistachio Tempest’s TTPs have changed over time, their key elements still involve ransomware, exfiltration, and extortion. Once they've gained access to an environment, Pistachio Tempest typically utilizes additional tools to complement their use of Cobalt Strike; this includes the use of the SystemBC RAT and the SliverC2 framework, respectively. It has also been reported that Pistacho Tempest has experimented with various RaaS offerings, which recently included Qilin ransomware[4].

Conclusion

Qilin is a RaaS group that has gained notoriety recently due to high-profile attacks perpetrated by its affiliates. Despite this, the group likely includes affiliates and actors who were previously associated with other ransomware groups. These individuals bring their own modus operandi and utilize both known and novel TTPs and IoCs that differ from one attack to another.

Darktrace’s anomaly-based technology is inherently threat-agnostic, treating all RaaS variants equally regardless of the attackers’ tools and infrastructure. Deviations from a device’s ‘learned’ pattern of behavior during an attack enable Darktrace to detect and contain potentially disruptive ransomware attacks.

Credit to: Alexandra Sentenac, Emma Foulger, Justin Torres, Min Kim, Signe Zaharka for their contributions.

References

[1] https://www.sentinelone.com/anthology/agenda-qilin/  

[2] https://www.group-ib.com/blog/qilin-ransomware/

[3] https://www.trendmicro.com/en_us/research/22/h/new-golang-ransomware-agenda-customizes-attacks.html

[4] https://www.microsoft.com/en-us/security/security-insider/pistachio-tempest

[5] https://www.trendmicro.com/en_us/research/22/h/new-golang-ransomware-agenda-customizes-attacks.html

[6] https://www.bleepingcomputer.com/forums/t/790240/agenda-qilin-ransomware-id-random-10-char;-recover-readmetxt-support/

[7] https://github.com/threatlabz/ransomware_notes/tree/main/qilin

Darktrace Model Detections

Internal Reconnaissance

Device / Suspicious SMB Scanning Activity

Device / Network Scan

Device / RDP Scan

Device / ICMP Address Scan

Device / Suspicious Network Scan Activity

Anomalous Connection / SMB Enumeration

Device / New or Uncommon WMI Activity

Device / Attack and Recon Tools

Lateral Movement

Device / SMB Session Brute Force (Admin)

Device / Large Number of Model Breaches from Critical Network Device

Device / Multiple Lateral Movement Model Breaches

Anomalous Connection / Unusual Admin RDP Session

Device / SMB Lateral Movement

Compliance / SMB Drive Write

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / Anomalous DRSGetNCChanges Operation

Anomalous Server Activity / Domain Controller Initiated to Client

User / New Admin Credentials on Client

C2 Communication

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Multiple Connections to New External TCP Port

Anomalous Connection / Anomalous SSL without SNI to New External

Anomalous Connection / Rare External SSL Self-Signed

Device / Increased External Connectivity

Unusual Activity / Unusual External Activity

Compromise / New or Repeated to Unusual SSL Port

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Device / Suspicious Domain

Device / Increased External Connectivity

Compromise / Sustained SSL or HTTP Increase

Compromise / Botnet C2 Behaviour

Anomalous Connection / POST to PHP on New External Host

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous File / EXE from Rare External Location

Exfiltration

Unusual Activity / Enhanced Unusual External Data Transfer

Anomalous Connection / Data Sent to Rare Domain

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Uncommon 1 GiB Outbound

Unusual Activity / Unusual External Data to New Endpoint

Compliance / FTP / Unusual Outbound FTP

File Encryption

Compromise / Ransomware / Suspicious SMB Activity

Anomalous Connection / Sustained MIME Type Conversion

Anomalous File / Internal / Additional Extension Appended to SMB File

Compromise / Ransomware / Possible Ransom Note Write

Compromise / Ransomware / Possible Ransom Note Read

Anomalous Connection / Suspicious Read Write Ratio

IoC List

IoC – Type – Description + Confidence

93.115.25[.]139 IP C2 Server, likely associated with SystemBC

194.165.16[.]13 IP Probable Exfiltration Server

91.238.181[.]230 IP C2 Server, likely associated with Cobalt Strike

ikea0[.]com Hostname C2 Server, likely associated with Cobalt Strike

lebondogicoin[.]com Hostname C2 Server, likely associated with Cobalt Strike

184.168.123[.]220 IP Possible C2 Infrastructure

184.168.123[.]219 IP Possible C2 Infrastructure

184.168.123[.]236 IP Possible C2 Infrastructure

184.168.123[.]241 IP Possible C2 Infrastructure

184.168.123[.]247 IP Possible C2 Infrastructure

184.168.123[.]251 IP Possible C2 Infrastructure

184.168.123[.]252 IP Possible C2 Infrastructure

184.168.123[.]229 IP Possible C2 Infrastructure

184.168.123[.]246 IP Possible C2 Infrastructure

184.168.123[.]230 IP Possible C2 Infrastructure

gfs440n010.userstorage.me ga.co[.]nz Hostname Possible Exfiltration Server. Not inherently malicious; associated with MEGA file storage.

gfs440n010.userstorage.me ga.co[.]nz Hostname Possible Exfiltration Server. Not inherently malicious; associated with MEGA file storage.

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Alexandra Sentenac
Cyber Analyst

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Elevating Network Security: Confronting Trust, Ransomware, & Novel Attacks

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21
Jun 2024

Understanding the Network Security Market

Old tools blind to new threats

With the rise of GenAI and novel attacks, organizations can no longer rely solely on traditional network security solutions that depend on historical attack data, such as signatures and detection rules, to identify threats. However, in many cases network security vendors and traditional solutions like IDS/IPS focus on detecting known attacks using historical data. What happens is organizations are left vulnerable to unknown and novel threats, as these approaches only detect known malicious behavior and cannot keep up with unknown threats or zero-day attacks.

Advanced threats

Darktrace's End of Year Threat Report for 2023 highlights significant changes in the cyber threat landscape, particularly due to advancements in technology such as generative AI. The report notes a substantial increase in sophisticated attacks, including those utilizing generative AI, which have made it more challenging for traditional security measures to keep up. The report also details the rise of multi-functional malware, like Black Basta ransomware, which not only encrypts data for ransom but also spreads other types of malware such as the Qbot banking trojan. These complex attacks are increasingly being deployed by advanced cybercriminal groups, underscoring the need for organizations to adopt advanced security measures that can detect and respond to novel threats in real-time.

Defenders need a solution that can level the playing field, especially when they are operating with limited resources and getting overloaded with endless alerts. Most network security tools on the market have a siloed approach and do not integrate with the rest of an organization’s digital estate, but attackers don’t operate in a single domain.

Disparate workforce

With so many organizations continuing to support a remote or hybrid working environment, the need to secure devices that are outside the corporate network or off-VPN is increasingly important. While endpoint protection or endpoint detection and response (EDR) tools are a fundamental part of any security stack, it’s not possible to install an agent on every device, which can leave blind spots in an organization’s attack surface. Managing trust and access policies is also necessary to protect identities, however this comes with its own set of challenges in terms of implementation and minimizing business disruption.

This blog will dive into these challenges and show examples of how Darktrace has helped mitigate risk and stop novel and never-before-seen threats.

Network Security Challenge 1: Managing trust

What is trust in cybersecurity?

Trust in cybersecurity means that an entity can be relied upon. This can involve a person, organization, or system to be authorized or authenticated by proving their identity is legitimate and can be trusted to have access to the network or sensitive information.

Why is trust important in cybersecurity?

Granting access and privileges to your workforce and select affiliates has profound implications for cybersecurity, brand reputation, regulatory compliance, and financial liability. In a traditional network security model, traffic gets divided into two categories — trusted and untrusted — with some entities and segments of the network deemed more creditable than others.

How do you manage trust in cybersecurity?

Zero trust is too little, but any is too much.

Modern network security challenges point to an urgent need for organizations to review and update their approaches to managing trust. External pressure to adopt zero trust security postures literally suggests trusting no one, but that impedes your freedom
to do business. IT leaders need a proven but practical process for deciding who should be allowed to use your network and how.

Questions to ask in updating Trusted User policies include:

  • What process should you follow to place trust in third
    parties and applications?
  • Do you subject trusted entities to testing and other due
    diligence first?
  • How often do you review this process — and trusted
    relationships themselves — after making initial decisions?
  • How do you tell when trusted users should no longer be
    trusted?

Once trust has been established, security teams need new and better ways to autonomously verify that those transacting within your network are indeed those trusted users that they claim to be, taking only the authorized actions you’ve allowed them to take.

Exploiting trust in the network

Insider threats have a major head start. The opposite of attacks launched by nameless, faceless strangers, insider threats originate through parties once deemed trustworthy. That might mean a current or former member of your workforce or a partner, vendor, investor, or service provider authorized by IT to access corporate systems and data. Threats also arise when a “pawn” gets unwittingly tricked into disclosing credentials or downloading malware.

Common motives for insider attacks include revenge, stealing or leaking sensitive data, taking down IT systems, stealing assets or IP, compromising your organization’s credibility, and simply harassing your workforce. Put simply, rules and signatures based security solutions won’t flag insider threats because an insider does not immediately present themselves as an intruder. Insider threats can only be stopped by an evolving understanding of ‘normal’ for every user that immediately alerts your team when trusted users do something strange.

“By 2026, 10% of large enterprises will have a comprehensive, mature and measurable zero-trust program in place, up from less than 1% today.” [1]

Use Case: Darktrace spots an insider threat

Darktrace/OT detected a subtle deviation from normal behavior when a reprogram command was sent by an engineering workstation to a PLC controlling a pump, an action an insider threat with legitimized access to OT systems would take to alter the physical process without any malware involved. In this instance, AI Analyst, Darktrace’s investigation tool that triages events to reveal the full security incident, detected the event as unusual based on multiple metrics including the source of the command, the destination device, the time of the activity, and the command itself.  

As a result, AI Analyst created a complete security incident, with a natural language summary, the technical details of the activity, and an investigation process explaining how it came to its conclusion. By leveraging Explainable AI, a security team can quickly triage and escalate Darktrace incidents in real time before it becomes disruptive, and even when performed by a trusted insider.

Read more about insider threats here

Network Security Challenge 2: Stopping Ransomware at every stage    

What is Ransomware?

Ransomware is a type of malware that encrypts valuable files on a victim’s device, denying the account holder access, and demanding money in exchange for the encryption key. Ransomware has been increasingly difficult to deal with, especially with ransom payments being made in crypto currency which is untraceable. Ransomware can enter a system by clicking a link dangerous or downloading malicious files.

Avoiding ransomware attacks ranks at the top of most CISOs’ and risk managers’ priority lists, and with good reason. Extortion was involved in 25% of all breaches in 2022, with front-page attacks wreaking havoc across healthcare, gas pipelines, food processing plants, and other global supply chains. [2]

What else is new?

The availability of “DIY” toolkits and subscription-based ransom- ware-as-a-service (RaaS) on the dark web equips novice threat actors to launch highly sophisticated attacks at machine speed. For less than $500, virtually anyone can acquire and tweak RaaS offerings such as Philadelphia that come with accessible customer interfaces, reviews, discounts, and feature updates — all the signature features of commercial SaaS offerings.                  

Darktrace Cyber AI breaks the ransomware cycle

The preeminence of ransomware keeps security teams on high alert for indicators of attack but hypervigilance — and too many tools churning out too many alerts — quickly exhausts analysts’ bandwidth. To reverse this trend, AI needs to help prioritize and resolve versus merely detect risk.

Darktrace uses AI to recognize and contextualize possible signs of ransomware attacks as they appear in your network and across multiple domains. Viewing behaviors in the context of your organization’s normal ‘pattern of life’ updates and enhances detection that watches for a repeat of previous techniques.

Darktrace's AI brings the added advantage of continuously analyzing behavior in your environment at machine speed.

Darktrace AI also performs Autonomous Response, shutting down attacks at every stage of the ransomware cycle, including the first telltale signs of exfiltration and encryption of data for extortion purposes.

Use Case: Stopping Hive Ransomware attack

Hive is distributed via a RaaS model where its developers update and maintain the code, in return for a percentage of the eventual ransom payment, while users (or affiliates) are given the tools to carry out attacks using a highly sophisticated and complex malware they would otherwise be unable to use.

In early 2022, Darktrace/Network identified several instances of Hive ransomware on the networks of multiple customers. Using its anomaly-based detection, Darktrace was able to successfully detect the attacks and multiple stages of the kill chain, including command and control (C2) activity, lateral movement, data exfiltration, and ultimately data encryption and the writing of ransom notes.

Darktrace’s AI understands customer networks and learns the expected patterns of behavior across an organization’s digital estate. Using its anomaly-based detection Darktrace is able to identify emerging threats through the detection of unusual or unexpected behavior, without relying on rules and signatures, or known IoCs.

Read the full story here

Network Security Challenge 3: Spotting Novel Attacks

You can’t predict tomorrow’s weather by reading yesterday’s forecast, yet that’s essentially what happens when network security tools only look for known attacks.

What are novel attacks?

“Novel attacks” include unknown or previously unseen exploits such as zero-days, or new variations of known threats that evade existing detection rules.

Depending on how threats get executed, the term “novel” can refer to brand new tactics, techniques, and procedures (TTPs), or to subtle new twists on perennial threats like DoS, DDoS, and Domain Name Server (DNS) attacks.

Old tools may be blind to new threats

Stopping novel threats is less about deciding whom to trust than it is about learning to spot something brand new. As we’ve seen with ransomware, the growing “aaS” attack market creates a profound paradigm shift by allowing non-technical perpetrators to tweak, customize, and coin never-before-seen threats that elude traditional network, email, VPN, and cloud security.

Tools based on traditional rules and signatures lack a frame of reference. This is where AI’s ability to spot and analyze abnormalities in the context of normal patterns of life comes into play.                        

Darktrace AI spots what other tools miss                                      

Instead of training in cloud data lakes that pool data from unrelated attacks worldwide, Darktrace AI learns about your unique environment from your environment. By flagging and analyzing everything unusual — instead of only known signs of compromise — Darktrace’s Self-Learning AI keeps security stacks from missing less obvious but potentially more dangerous events.

The real challenge here is achieving faster “time to meaning” and contextualizing behavior that might — or might not — be part of a novel attack. Darktrace/Network does not require a “patient zero” to identify a novel attack, or one exploiting a zero-day vulnerability.

Use Case: Stopping Novel Ransomware Attack

In late May 2023, Darktrace observed multiple instances of Akira ransomware affecting networks across its customer base. Thanks to its anomaly-based approach to threat detection Darktrace successfully identified the novel ransomware attacks and provided full visibility over the cyber kill chain, from the initial compromise to the eventual file encryptions and ransom notes. Darktrace identified Akira ransomware on multiple customer networks, even when threat actors were utilizing seemingly legitimate services (or spoofed versions of them) to carry out malicious activity. While this may have gone unnoticed by traditional security tools, Darktrace’s anomaly-based detection enabled it to recognize malicious activity for what it was. In cases where Darktrace’s autonomous response was enabled these attacks were mitigated in their early stages, thus minimizing any disruption or damage to customer networks.

Read the full story here

References

[1] Gartner, “Gartner Unveils Top Eight Cybersecurity Predictions for 2023-2024,” 28 March 2023.                    

[2] TechTarget, “Ransomware trends, statistics and facts in 2023,” Sean Michael Kerner, 26 January 2023.

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About the author
Mikey Anderson
Product Manager, Network Detection & Response
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