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November 8, 2022

How Raccoon Stealer v2 Infects Systems

Learn about Raccoon Stealer v2's infection process and its implications for cybersecurity. Discover effective strategies to protect your systems.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Sam Lister
SOC Analyst
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08
Nov 2022

Raccoon Stealer Malware

Since the release of version 2 of Raccoon Stealer in May 2022, Darktrace has observed huge volumes of Raccoon Stealer v2 infections across its client base. The info-stealer, which seeks to obtain and then exfiltrate sensitive data saved on users’ devices, displays a predictable pattern of network activity once it is executed. In this blog post, we will provide details of this pattern of activity, with the goal of helping security teams to recognize network-based signs of Raccoon Stealer v2 infection within their own networks. 

What is Raccoon Stealer?

Raccoon Stealer is a classic example of information-stealing malware, which cybercriminals typically use to gain possession of sensitive data saved in users’ browsers and cryptocurrency wallets. In the case of browsers, targeted data typically includes cookies, saved login details, and saved credit card details. In the case of cryptocurrency wallets (henceforth, ‘crypto-wallets’), targeted data typically includes public keys, private keys, and seed phrases [1]. Once sensitive browser and crypto-wallet data is in the hands of cybercriminals, it will likely be used to conduct harmful activities, such as identity theft, cryptocurrency theft, and credit card fraud.

How do you obtain Raccoon Stealer?

Like most info-stealers, Raccoon Stealer is purchasable. The operators of Raccoon Stealer sell Raccoon Stealer samples to their customers (called ‘affiliates’), who then use the info-stealer to gain possession of sensitive data saved on users’ devices. Raccoon Stealer affiliates typically distribute their samples via SEO-promoted websites providing free or cracked software. 

Is Raccoon Stealer Still Active?

On the 25th of March 2022, the operators of Raccoon Stealer announced that they would be suspending their operations because one of their core developers had been killed during the Russia-Ukraine conflict [2]. The presence of the hardcoded RC4 key ‘edinayarossiya’ (Russian for ‘United Russia’) within observed Raccoon Stealer v2 samples [3] provides potential evidence of the Raccoon Stealer operators’ allegiances.

Recent details shared by the US Department of Justice [4]/[5] indicate that it was in fact the arrest, rather than the death, of an operator which led the Raccoon Stealer team to suspend their operations [6]. As a result of the FBI, along with law enforcement partners in Italy and the Netherlands, dismantling Raccoon Stealer infrastructure in March 2022 [4], the Raccoon Stealer team was forced to build a new version of the info-stealer.  

On the 17th May 2022, the completion of v2 of the info-stealer was announced on the Raccoon Stealer Telegram channel [7].  Since its release in May 2022, Raccoon Stealer v2 has become extremely popular amongst cybercriminals. The prevalence of Raccoon Stealer v2 in the wider landscape has been reflected in Darktrace’s client base, with hundreds of infections being observed within client networks on a monthly basis.   

Since Darktrace’s SOC first saw a Raccoon Stealer v2 infection on the 22nd May 2022, the info-stealer has undergone several subtle changes. However, the info-stealer’s general pattern of network activity has remained essentially unchanged.  

How Does Raccoon Stealer v2 Infection Work?

A Raccoon Stealer v2 infection typically starts with a user attempting to download cracked or free software from an SEO-promoted website. Attempting to download software from one of these cracked/free software websites redirects the user’s browser (typically via several .xyz or .cfd endpoints) to a page providing download instructions. In May, June, and July, many of the patterns of download behavior observed by Darktrace’s SOC matched the pattern of behavior observed in a cracked software campaign reported by Avast in June [8].   

webpage whose download instructions led to a Raccoon Stealer v2
Figure 1: Above is a webpage whose download instructions led to a Raccoon Stealer v2 sample hosted on Discord CDN
example of a webpage whose download instructions led to a Raccoon Stealer v2
Figure 2: Above is an example of a webpage whose download instructions led to a Raccoon Stealer v2 sample hosted on Bitbucket
example of a webpage whose download instructions led to a Raccoon Stealer v2
Figure 3: Above is an example of a webpage whose download instructions led to a Raccoon Stealer v2 sample hosted on MediaFire

Following the instructions on the download instruction page causes the user’s device to download a password-protected RAR file from a file storage service such as ‘cdn.discordapp[.]com’, ‘mediafire[.]com’, ‘mega[.]nz’, or ‘bitbucket[.]org’. Opening the downloaded file causes the user’s device to execute Raccoon Stealer v2. 

The Event Log for an infected device,
Figure 4: The Event Log for an infected device, taken from Darktrace’s Threat Visualiser interface, shows a device contacting two cracked software websites (‘crackedkey[.]org’ and ‘crackedpc[.]co’) before contacting a webpage (‘premiumdownload[.]org) providing instructions to download Raccoon Stealer v2 from Bitbucket

Once Raccoon Stealer v2 is running on a device, it will make an HTTP POST request with the target URI ‘/’ and an unusual user-agent string (such as ‘record’, ‘mozzzzzzzzzzz’, or ‘TakeMyPainBack’) to a C2 server. This POST request consists of three strings: a machine GUID, a username, and a 128-bit RC4 key [9]. The posted data has the following form:

machineId=X | Y & configId=Z (where X is a machine GUID, Y is a username and Z is a 128-bit RC4 key) 

PCAP showing a device making an HTTP POST request with the User Agent header ‘record’ 
Figure 5:PCAP showing a device making an HTTP POST request with the User Agent header ‘record’ 
PCAP showing a device making an HTTP POST request with the User Agent header ‘mozzzzzzzzzzz’
Figure 6: PCAP showing a device making an HTTP POST request with the User Agent header ‘mozzzzzzzzzzz’
PCAP showing a device making an HTTP POST request with the User Agent header ‘TakeMyPainBack’
Figure 7: PCAP showing a device making an HTTP POST request with the User Agent header ‘TakeMyPainBack’

The C2 server responds to the info-stealer’s HTTP POST request with custom-formatted configuration details. These configuration details consist of fields which tell the info-stealer what files to download, what data to steal, and what target URI to use in its subsequent exfiltration POST requests. Below is a list of the fields Darktrace has observed in the configuration details retrieved by Raccoon Stealer v2 samples:

  • a ‘libs_mozglue’ field, which specifies a download address for a Firefox library named ‘mozglue.dll’
  • a ‘libs_nss3’ field, which specifies a download address for a Network System Services (NSS) library named ‘nss3.dll’ 
  • a ‘libs_freebl3’ field, which specifies a download address for a Network System Services (NSS) library named ‘freebl3.dll’
  • a ‘libs_softokn3’ field, which specifies a download address for a Network System Services (NSS) library named ‘softokn3.dll’
  • a ‘libs_nssdbm3’ field, which specifies a download address for a Network System Services (NSS) library named ‘nssdbm3.dll’
  • a ‘libs_sqlite3’ field, which specifies a download address for a SQLite command-line program named ‘sqlite3.dll’
  • a ‘libs_ msvcp140’ field, which specifies a download address for a Visual C++ runtime library named ‘msvcp140.dll’
  • a ‘libs_vcruntime140’ field, which specifies a download address for a Visual C++ runtime library named ‘vcruntime140.dll’
  • a ‘ldr_1’ field, which specifies the download address for a follow-up payload for the sample to download 
  • ‘wlts_X’ fields (where X is the name of a crypto-wallet application), which specify data for the sample to obtain from the specified crypto-wallet application
  • ‘ews_X’ fields (where X is the name of a crypto-wallet browser extension), which specify data for the sample to obtain from the specified browser extension
  • ‘xtntns_X’ fields (where X is the name of a password manager browser extension), which specify data for the sample to obtain from the specified browser extension
  • a ‘tlgrm_Telegram’ field, which specifies data for the sample to obtain from the Telegram Desktop application 
  • a ‘grbr_Desktop’ field, which specifies data within a local ‘Desktop’ folder for the sample to obtain 
  • a ‘grbr_Documents’ field, which specifies data within a local ‘Documents’ folder for the sample to obtain
  • a ‘grbr_Recent’ field, which specifies data within a local ‘Recent’ folder for the sample to obtain
  • a ‘grbr_Downloads’ field, which specifies data within a local ‘Downloads’ folder for the sample to obtain
  • a ‘sstmnfo_System Info.txt’ field, which specifies whether the sample should gather and exfiltrate a profile of the infected host 
  • a ‘scrnsht_Screenshot.jpeg’ field, which specifies whether the sample should take and exfiltrate screenshots of the infected host
  • a ‘token’ field, which specifies a 32-length string of hexadecimal digits for the sample to use as the target URI of its HTTP POST requests containing stolen data 

After retrieving its configuration data, Raccoon Stealer v2 downloads the library files specified in the ‘libs_’ fields. Unusual user-agent strings (such as ‘record’, ‘qwrqrwrqwrqwr’, and ‘TakeMyPainBack’) are used in the HTTP GET requests for these library files. In all Raccoon Stealer v2 infections seen by Darktrace, the paths of the URLs specified in the ‘libs_’ fields have the following form:

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/X (where X is the name of the targeted DLL file) 

Advanced Search logs for an infected host
Figure 8: Advanced Search logs for an infected host, found on Darktrace’s Advanced Search interface, show a device making an HTTP POST request to retrieve configuration details, and then making HTTP GET requests with the User Agent header ‘record’ for DLL files
Advanced Search logs for an infected host
Figure 9: Advanced Search logs for an infected host, found on Darktrace’s Advanced Search interface, show a device making an HTTP POST request to retrieve configuration details, and then making HTTP GET requests with the User Agent header ‘qwrqrwrqwrqwr’ for DLL files
Advanced Search logs for an infected host
Figure 10: Advanced Search logs for an infected host, found on Darktrace’s Advanced Search interface, show a device making an HTTP POST request to retrieve configuration details, and then making HTTP GET requests with the User Agent header ‘TakeMyPainBack’ for DLL files

Raccoon Stealer v2 uses the DLLs which it downloads to gain access to sensitive data (such as cookies, credit card details, and login details) saved in browsers running on the infected host.  

Depending on the data provided in the configuration details, Raccoon Stealer v2 will typically seek to obtain, in addition to sensitive data saved in browsers, the following information:

  • Information about the Operating System and applications installed on the infected host
  • Data from specified crypto-wallet software
  • Data from specified crypto-wallet browser extensions
  • Data from specified local folders
  • Data from Telegram Desktop
  • Data from specified password manager browser extensions
  • Screenshots of the infected host 

Raccoon Stealer v2 exfiltrates the data which it obtains to its C2 server by making HTTP POST requests with unusual user-agent strings (such as ‘record’, ‘rc2.0/client’, ‘rqwrwqrqwrqw’, and ‘TakeMyPainBack’) and target URIs matching the 32-length string of hexadecimal digits specified in the ‘token’ field of the configuration details. The stolen data exfiltrated by Raccoon Stealer typically includes files named ‘System Info.txt’, ‘---Screenshot.jpeg’, ‘\cookies.txt’, and ‘\passwords.txt’. 

Advanced Search logs for an infected host
Figure 11: Advanced Search logs for an infected host, found on Darktrace’s Advanced Search interface, show a device retrieving configuration details via a POST request, downloading several DLLs, and then exfiltrating files named ‘System Info.txt’ and ‘---Screenshot.jpeg’
Advanced Search logs for an infected host
Figure 12: Advanced Search logs for an infected host, found on Darktrace’s Advanced Search interface, show a device retrieving configuration details via a POST request, downloading several DLLs, and then exfiltrating a file named ‘System Info.txt’ 
Advanced Search logs for an infected host
Figure 13: Advanced Search logs for an infected host, found on Darktrace’s Advanced Search interface, show a device retrieving configuration details via a POST request, downloading several DLLs, and then exfiltrating files named ‘System Info.txt’, ‘\cookies.txt’ and ‘\passwords.txt’
Advanced Search logs for an infected host
Figure 14: Advanced Search logs for an infected host, found on Darktrace’s Advanced Search interface, show a device retrieving configuration details via a POST request, downloading several DLLs, and then exfiltrating a file named ‘System Info.txt’

If a ‘ldr_1’ field is present in the retrieved configuration details, then Raccoon Stealer will complete its operation by downloading the binary file specified in the ‘ldr_1’ field. In all observed cases, the paths of the URLs specified in the ‘ldr_1’ field end in a sequence of digits, followed by ‘.bin’. The follow-up payload seems to vary between infections, likely due to this additional-payload feature being customizable by Raccoon Stealer affiliates. In many cases, the info-stealer, CryptBot, was delivered as the follow-up payload. 

Darktrace Coverage of Raccoon Stealer

Once a user’s device becomes infected with Raccoon Stealer v2, it will immediately start to communicate over HTTP with a C2 server. The HTTP requests made by the info-stealer have an empty Host header (although Host headers were used by early v2 samples) and highly unusual User Agent headers. When Raccoon Stealer v2 was first observed in May 2022, the user-agent string ‘record’ was used in its HTTP requests. Since then, it appears that the operators of Raccoon Stealer have made several changes to the user-agent strings used by the info-stealer,  likely in an attempt to evade signature-based detections. Below is a timeline of the changes to the info-stealer’s user-agent strings, as observed by Darktrace’s SOC:

  • 22nd May 2022: Samples seen using the user-agent string ‘record’
  • 2nd July 2022: Samples seen using the user-agent string ‘mozzzzzzzzzzz’
  • 29th July 2022: Samples seen using the user-agent string ‘rc2.0/client’
  • 10th August 2022: Samples seen using the user-agent strings ‘qwrqrwrqwrqwr’ and ‘rqwrwqrqwrqw’
  • 16th Sep 2022: Samples seen using the user-agent string ‘TakeMyPainBack’

The presence of these highly unusual user-agent strings within infected devices’ HTTP requests causes the following Darktrace DETECT/Network models to breach:

  • Device / New User Agent
  • Device / New User Agent and New IP
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Device / Three or More New User Agents

These DETECT models look for devices making HTTP requests with unusual user-agent strings, rather than specific user-agent strings which are known to be malicious. This method of detection enables the models to continually identify Raccoon Stealer v2 HTTP traffic, despite the changes made to the info-stealer’s user-agent strings.   

After retrieving configuration details from a C2 server, Raccoon Stealer v2 samples make HTTP GET requests for several DLL libraries. Since these GET requests are directed towards highly unusual IP addresses, the downloads of the DLLs cause the following DETECT models to breach:

  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Script from Rare External Location
  • Anomalous File / Multiple EXE from Rare External Locations

Raccoon Stealer v2 samples send data to their C2 server via HTTP POST requests with an absent Host header. Since these POST requests lack a Host header and have a highly unusual destination IP, their occurrence causes the following DETECT model to breach:

  • Anomalous Connection / Posting HTTP to IP Without Hostname

Certain Raccoon Stealer v2 samples download (over HTTP) a follow-up payload once they have exfiltrated data. Since the target URIs of the HTTP GET requests made by v2 samples end in a sequence of digits followed by ‘.bin’, the samples’ downloads of follow-up payloads cause the following DETECT model to breach:

  • Anomalous File / Numeric File Download

If Darktrace RESPOND/Network is configured within a customer’s environment, then Raccoon Stealer v2 activity should cause the following inhibitive actions to be autonomously taken on infected systems: 

  • Enforce pattern of life — This action results in a device only being able to make connections which are normal for it to make
  • Enforce group pattern of life — This action results in a device only being able to make connections which are normal for it or any of its peers to make
  • Block matching connections — This action results in a device being unable to make connections to particular IP/Port pairs
  • Block all outgoing traffic — This action results in a device being unable to make any connections 
The Event Log for an infected device
Figure 15: The Event Log for an infected device, taken from Darktrace’s Threat Visualiser interface, shows Darktrace RESPOND taking inhibitive actions in response to the HTTP activities of a Raccoon Stealer v2 sample downloaded from MediaFire

Given that Raccoon Stealer v2 infections move extremely fast, with the time between initial infection and data exfiltration sometimes less than a minute, the availability of Autonomous Response technology such as Darktrace RESPOND is vital for the containment of Raccoon Stealer v2 infections.  

Timeline of Darktrace stopping raccoon stealer.
Figure 16: Figure displaying the steps of a Raccoon Stealer v2 infection, along with the corresponding Darktrace detections

Conclusion

Since the release of Raccoon Stealer v2 back in 2022, the info-stealer has relentlessly infected the devices of unsuspecting users. Once the info-stealer infects a user’s device, it retrieves and then exfiltrates sensitive information within a matter of minutes. The distinctive pattern of network behavior displayed by Raccoon Stealer v2 makes the info-stealer easy to spot. However, the changes which the Raccoon Stealer operators make to the User Agent headers of the info-stealer’s HTTP requests make anomaly-based methods key for the detection of the info-stealer’s HTTP traffic. The operators of Raccoon Stealer can easily change the superficial features of their malware’s C2 traffic, however, they cannot easily change the fact that their malware causes highly unusual network behavior. Spotting this behavior, and then autonomously responding to it, is likely the best bet which organizations have at stopping a Raccoon once it gets inside their networks.  

Thanks to the Threat Research Team for its contributions to this blog.

References

[1] https://www.microsoft.com/security/blog/2022/05/17/in-hot-pursuit-of-cryware-defending-hot-wallets-from-attacks/

[2] https://twitter.com/3xp0rtblog/status/1507312171914461188

[3] https://www.esentire.com/blog/esentire-threat-intelligence-malware-analysis-raccoon-stealer-v2-0

[4] https://www.justice.gov/usao-wdtx/pr/newly-unsealed-indictment-charges-ukrainian-national-international-cybercrime-operation

[5] https://www.youtube.com/watch?v=Fsz6acw-ZJ

[6] https://riskybiznews.substack.com/p/raccoon-stealer-dev-didnt-die-in

[7] https://medium.com/s2wblog/raccoon-stealer-is-back-with-a-new-version-5f436e04b20d

[8] https://blog.avast.com/fakecrack-campaign

[9] https://blog.sekoia.io/raccoon-stealer-v2-part-2-in-depth-analysis/

Appendices

MITRE ATT&CK Mapping

Resource Development

• T1588.001 — Obtain Capabilities: Malware

• T1608.001 — Stage Capabilities: Upload Malware

• T1608.005 — Stage Capabilities: Link Target

• T1608.006 — Stage Capabilities: SEO Poisoning

Execution

•  T1204.002 — User Execution: Malicious File

Credential Access

• T1555.003 — Credentials from Password Stores:  Credentials from Web Browsers

• T1555.005 — Credentials from Password Stores:  Password Managers

• T1552.001 — Unsecured Credentials: Credentials  In Files

Command and Control

•  T1071.001 — Application Layer Protocol: Web Protocols

•  T1105 — Ingress Tool Transfer

IOCS

Type

IOC

Description

User-Agent String

record

String used in User Agent header of  Raccoon Stealer v2’s HTTP requests

User-Agent  String

mozzzzzzzzzzz

String used inUser Agent header of Raccoon Stealer v2’s HTTP requests

User-Agent String

rc2.0/client

String used in User Agent header of  Raccoon Stealer v2’s HTTP requests

User-Agent  String

qwrqrwrqwrqwr

String used in  User Agent header of Raccoon Stealer v2’s HTTP requests

User-Agent String

rqwrwqrqwrqw

String used in User Agent header of  Raccoon Stealer v2’s HTTP requests

User-Agent  String

TakeMyPainBack

String used in  User Agent header of Raccoon Stealer v2’s HTTP requests

Domain Name

brain-lover[.]xyz  

Raccoon Stealer v2 C2 infrastructure

Domain  Name

polar-gift[.]xyz

Raccoon Stealer  v2 C2 infrastructure

Domain Name

cool-story[.]xyz

Raccoon Stealer v2 C2 infrastructure

Domain  Name

fall2sleep[.]xyz

Raccoon Stealer  v2 C2 infrastructure

Domain Name

broke-bridge[.]xyz

Raccoon Stealer v2 C2 infrastructure

Domain  Name

use-freedom[.]xyz

Raccoon Stealer  v2 C2 infrastructure

Domain Name

just-trust[.]xyz

Raccoon Stealer v2 C2 infrastructure

Domain  Name

soft-viper[.]site

Raccoon Stealer  v2 C2 infrastructure

Domain Name

tech-lover[.]xyz

Raccoon Stealer v2 C2 infrastructure

Domain  Name

heal-brain[.]xyz

Raccoon Stealer  v2 C2 infrastructure

Domain Name

love-light[.]xyz

Raccoon Stealer v2 C2 infrastructure

IP  Address

104.21.80[.]14

Raccoon Stealer  v2 C2 infrastructure

IP Address

107.152.46[.]84

Raccoon Stealer v2 C2 infrastructure

IP  Address

135.181.147[.]255

Raccoon Stealer  v2 C2 infrastructure

IP Address

135.181.168[.]157

Raccoon Stealer v2 C2 infrastructure

IP  Address

138.197.179[.]146

Raccoon Stealer  v2 C2 infrastructure

IP Address

141.98.169[.]33

Raccoon Stealer v2 C2 infrastructure

IP  Address

146.19.170[.]100

Raccoon Stealer  v2 C2 infrastructure

IP Address

146.19.170[.]175

Raccoon Stealer v2 C2 infrastructure

IP  Address

146.19.170[.]98

Raccoon Stealer  v2 C2 infrastructure

IP Address

146.19.173[.]33

Raccoon Stealer v2 C2 infrastructure

IP  Address

146.19.173[.]72

Raccoon Stealer  v2 C2 infrastructure

IP Address

146.19.247[.]175

Raccoon Stealer v2 C2 infrastructure

IP  Address

146.19.247[.]177

Raccoon Stealer  v2 C2 infrastructure

IP Address

146.70.125[.]95

Raccoon Stealer v2 C2 infrastructure

IP  Address

152.89.196[.]234

Raccoon Stealer  v2 C2 infrastructure

IP Address

165.225.120[.]25

Raccoon Stealer v2 C2 infrastructure

IP  Address

168.100.10[.]238

Raccoon Stealer  v2 C2 infrastructure

IP Address

168.100.11[.]23

Raccoon Stealer v2 C2 infrastructure

IP  Address

168.100.9[.]234

Raccoon Stealer  v2 C2 infrastructure

IP Address

170.75.168[.]118

Raccoon Stealer v2 C2 infrastructure

IP  Address

172.67.173[.]14

Raccoon Stealer  v2 C2 infrastructure

IP Address

172.86.75[.]189

Raccoon Stealer v2 C2 infrastructure

IP  Address

172.86.75[.]33

Raccoon Stealer  v2 C2 infrastructure

IP Address

174.138.15[.]216

Raccoon Stealer v2 C2 infrastructure

IP  Address

176.124.216[.]15

Raccoon Stealer  v2 C2 infrastructure

IP Address

185.106.92[.]14

Raccoon Stealer v2 C2 infrastructure

IP  Address

185.173.34[.]161

Raccoon Stealer  v2 C2 infrastructure

IP Address

185.173.34[.]161  

Raccoon Stealer v2 C2 infrastructure

IP  Address

185.225.17[.]198

Raccoon Stealer  v2 C2 infrastructure

IP Address

185.225.19[.]190

Raccoon Stealer v2 C2 infrastructure

IP  Address

185.225.19[.]229

Raccoon Stealer  v2 C2 infrastructure

IP Address

185.53.46[.]103

Raccoon Stealer v2 C2 infrastructure

IP  Address

185.53.46[.]76

Raccoon Stealer  v2 C2 infrastructure

IP Address

185.53.46[.]77

Raccoon Stealer v2 C2 infrastructure

IP  Address

188.119.112[.]230

Raccoon Stealer  v2 C2 infrastructure

IP Address

190.117.75[.]91

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.106.191[.]182

Raccoon Stealer  v2 C2 infrastructure

IP Address

193.149.129[.]135

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.149.129[.]144

Raccoon Stealer  v2 C2 infrastructure

IP Address

193.149.180[.]210

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.149.185[.]192

Raccoon Stealer  v2 C2 infrastructure

IP Address

193.233.193[.]50

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.43.146[.]138

Raccoon Stealer  v2 C2 infrastructure

IP Address

193.43.146[.]17

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.43.146[.]192

Raccoon Stealer  v2 C2 infrastructure

IP Address

193.43.146[.]213

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.43.146[.]214

Raccoon Stealer  v2 C2 infrastructure

IP Address

193.43.146[.]215

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.43.146[.]26

Raccoon Stealer  v2 C2 infrastructure

IP Address

193.43.146[.]45

Raccoon Stealer v2 C2 infrastructure

IP  Address

193.56.146[.]177

Raccoon Stealer  v2 C2 infrastructure

IP Address

194.180.174[.]180

Raccoon Stealer v2 C2 infrastructure

IP  Address

195.201.148[.]250

Raccoon Stealer  v2 C2 infrastructure

IP Address

206.166.251[.]156

Raccoon Stealer v2 C2 infrastructure

IP  Address

206.188.196[.]200

Raccoon Stealer  v2 C2 infrastructure

IP Address

206.53.53[.]18

Raccoon Stealer v2 C2 infrastructure

IP  Address

207.154.195[.]173

Raccoon Stealer  v2 C2 infrastructure

IP Address

213.252.244[.]2

Raccoon Stealer v2 C2 infrastructure

IP  Address

38.135.122[.]210

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.10.20[.]248

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.11.19[.]99

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.133.216[.]110

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.133.216[.]145

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.133.216[.]148

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.133.216[.]249

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.133.216[.]71

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.140.146[.]169

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.140.147[.]245

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.142.212[.]100

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.142.213[.]24

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.142.215[.]91

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.142.215[.]91  

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.142.215[.]92

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.144.29[.]18

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.144.29[.]243

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.15.156[.]11

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.15.156[.]2

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.15.156[.]31

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.15.156[.]31

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.150.67[.]156

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.153.230[.]183

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.153.230[.]228

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.159.251[.]163

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.159.251[.]164

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.61.136[.]67

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.61.138[.]162

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.67.228[.]8

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.67.231[.]202

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.67.34[.]152

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.67.34[.]234

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.8.144[.]187

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.8.144[.]54

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.8.144[.]55

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.8.145[.]174

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.8.145[.]83

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.8.147[.]39

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.8.147[.]79

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.84.0.152

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.86.86[.]78

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.89.54[.]110

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.89.54[.]110

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.89.54[.]95

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.89.55[.]115

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.89.55[.]117

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.89.55[.]193

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.89.55[.]198

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.89.55[.]20

Raccoon Stealer  v2 C2 infrastructure

IP Address

45.89.55[.]84

Raccoon Stealer v2 C2 infrastructure

IP  Address

45.92.156[.]150

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.182.36[.]154

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.182.36[.]230

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.182.36[.]231

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.182.36[.]232

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.182.36[.]233

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.182.39[.]34

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.182.39[.]74

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.182.39[.]75

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.182.39[.]77

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.252.118[.]33

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.252.176[.]62

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.252.177[.]217

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.252.177[.]234

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.252.177[.]43

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.252.177[.]47

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.252.177[.]92

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.252.177[.]98

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.252.22[.]142

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.252.23[.]100

Raccoon Stealer v2 C2 infrastructure

IP  Address

5.252.23[.]25

Raccoon Stealer  v2 C2 infrastructure

IP Address

5.252.23[.]76

Raccoon Stealer v2 C2 infrastructure

IP  Address

51.195.166[.]175

Raccoon Stealer  v2 C2 infrastructure

IP Address

51.195.166[.]176

Raccoon Stealer v2 C2 infrastructure

IP  Address

51.195.166[.]194

Raccoon Stealer  v2 C2 infrastructure

IP Address

51.81.143[.]169

Raccoon Stealer v2 C2 infrastructure

IP  Address

62.113.255[.]110

Raccoon Stealer  v2 C2 infrastructure

IP Address

65.109.3[.]107

Raccoon Stealer v2 C2 infrastructure

IP  Address

74.119.192[.]56

Raccoon Stealer  v2 C2 infrastructure

IP Address

74.119.192[.]73

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.232.39[.]101

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.73.133[.]0

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.73.133[.]4

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.73.134[.]45

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.75.230[.]25

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.75.230[.]39

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.75.230[.]70

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.75.230[.]93

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.91.100[.]101

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.91.102[.]12

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.91.102[.]230

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.91.102[.]44

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.91.102[.]57

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.91.102[.]84

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.91.103[.]31

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.91.73[.]154

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.91.73[.]213

Raccoon Stealer  v2 C2 infrastructure

IP Address

77.91.73[.]32

Raccoon Stealer v2 C2 infrastructure

IP  Address

77.91.74[.]67

Raccoon Stealer  v2 C2 infrastructure

IP Address

78.159.103[.]195

Raccoon Stealer v2 C2 infrastructure

IP  Address

78.159.103[.]196

Raccoon Stealer  v2 C2 infrastructure

IP Address

80.66.87[.]23

Raccoon Stealer v2 C2 infrastructure

IP  Address

80.66.87[.]28

Raccoon Stealer  v2 C2 infrastructure

IP Address

80.71.157[.]112

Raccoon Stealer v2 C2 infrastructure

IP  Address

80.71.157[.]138

Raccoon Stealer  v2 C2 infrastructure

IP Address

80.92.204[.]202

Raccoon Stealer v2 C2 infrastructure

IP  Address

87.121.52[.]10

Raccoon Stealer  v2 C2 infrastructure

IP Address

88.119.175[.]187

Raccoon Stealer v2 C2 infrastructure

IP  Address

89.185.85[.]53

Raccoon Stealer  v2 C2 infrastructure

IP Address

89.208.107[.]42

Raccoon Stealer v2 C2 infrastructure

IP  Address

89.39.106[.]78

Raccoon Stealer  v2 C2 infrastructure

IP Address

91.234.254[.]126

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.131.104[.]16

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.131.104[.]17

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.131.104[.]18

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.131.106[.]116

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.131.106[.]224

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.131.107[.]132

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.131.107[.]138

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.131.96[.]109

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.131.97[.]129

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.131.97[.]53

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.131.97[.]56

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.131.97[.]57

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.131.98[.]5

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.158.244[.]114

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.158.244[.]119

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.158.244[.]21

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.158.247[.]24

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.158.247[.]26

Raccoon Stealer v2 C2 infrastructure

IP  Address

94.158.247[.]30

Raccoon Stealer  v2 C2 infrastructure

IP Address

94.158.247[.]44

Raccoon Stealer v2 C2 infrastructure

IP  Address

95.216.109[.]16

Raccoon Stealer  v2 C2 infrastructure

IP Address

95.217.124[.]179

Raccoon Stealer v2 C2 infrastructure

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/mozglue.dll

URI used in  download of library file

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/nss3.dll

URI used in download of library file

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/freebl3.dll

URI used in  download of library file

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/softokn3.dll

URI used in download of library file

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/nssdbm3.dll

URI used in  download of library file

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/sqlite3.dll

URI used in download of library file

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/msvcp140.dll

URI used in  download of library file

URI

/aN7jD0qO6kT5bK5bQ4eR8fE1xP7hL2vK/vcruntime140.dll

URI used in download of library file

URI

/C9S2G1K6I3G8T3X7/56296373798691245143.bin

URI used in  download of follow-up payload

URI

/O6K3E4G6N9S8S1/91787438215733789009.bin

URI used in download of follow-up  payload

URI

/Z2J8J3N2S2Z6X2V3S0B5/45637662345462341.bin

URI used in  download of follow-up payload

URI

/rgd4rgrtrje62iuty/19658963328526236.bin

URI used in download of follow-up  payload

URI

/sd325dt25ddgd523/81852849956384.bin

URI used in  download of follow-up payload

URI

/B0L1N2H4R1N5I5S6/40055385413647326168.bin

URI used in download of follow-up  payload

URI

/F5Q8W3O3O8I2A4A4B8S8/31427748106757922101.bin

URI used in  download of follow-up payload

URI

/36141266339446703039.bin

URI used in download of follow-up  payload

URI

/wH0nP0qH9eJ6aA9zH1mN/1.bin

URI used in  download of follow-up payload

URI

/K2X2R1K4C6Z3G8L0R1H0/68515718711529966786.bin

URI used in download of follow-up  payload

URI

/C3J7N6F6X3P8I0I0M/17819203282122080878.bin

URI used in  download of follow-up payload

URI

/W9H1B8P3F2J2H2K7U1Y7G5N4C0Z4B/18027641.bin

URI used in download of follow-up  payload

URI

/P2T9T1Q6P7Y5J3D2T0N0O8V/73239348388512240560937.bin

URI used in  download of follow-up payload

URI

/W5H6O5P0E4Y6P8O1B9D9G0P9Y9G4/671837571800893555497.bin

URI used in download of follow-up  payload

URI

/U8P2N0T5R0F7G2J0/898040207002934180145349.bin

URI used in  download of follow-up payload

URI

/AXEXNKPSBCKSLMPNOMNRLUEPR/3145102300913020.bin

URI used in download of follow-up  payload

URI

/wK6nO2iM9lE7pN7e/7788926473349244.bin

URI used in  download of follow-up payload

URI

/U4N9B5X5F5K2A0L4L4T5/84897964387342609301.bin

URI used in download of follow-up  payload

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

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OT

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June 11, 2025

Proactive OT security: Lessons on supply chain risk management from a rogue Raspberry Pi

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Understanding supply chain risk in manufacturing

For industries running Industrial Control Systems (ICS) such as manufacturing and fast-moving consumer goods (FMCG), complex supply chains mean that disruption to one weak node can have serious impacts to the entire ecosystem. However, supply chain risk does not always originate from outside an organization’s ICS network.  

The implicit trust placed on software or shared services for maintenance within an ICS can be considered a type of insider threat [1], where defenders also need to look ‘from within’ to protect against supply chain risk. Attackers have frequently mobilised this form of insider threat:

  • Many ICS and SCADA systems were compromised during the 2014 Havex Watering Hole attack, where via operators’ implicit trust in the trojanized versions of legitimate applications, on legitimate but compromised websites [2].
  • In 2018, the world’s largest manufacturer of semiconductors and processers shut down production for three days after a supplier installed tainted software that spread to over 10,000 machines in the manufacturer’s network [3].
  • During the 2020 SolarWinds supply chain attack, attackers compromised a version of Orion software that was deployed from SolarWinds’ own servers during a software update to thousands of customers, including tech manufacturing companies such as Intel and Nvidia [4].

Traditional approaches to ICS security have focused on defending against everything from outside the castle walls, or outside of the ICS network. As ICS attacks become more sophisticated, defenders must not solely rely on static perimeter defenses and prevention. 

A critical part of active defense is understanding the ICS environment and how it operates, including all possible attack paths to the ICS including network connections, remote access points, the movement of data across zones and conduits and access from mobile devices. For instance, original equipment manufacturers (OEMs) and vendors often install remote access software or third-party equipment in ICS networks to facilitate legitimate maintenance and support activities, which can unintentionally expand the ICS’ attack surface.  

This blog describes an example of the convergence between supply chain risk and insider risk, when a vendor left a Raspberry Pi device in a manufacturing customer’s ICS network without the customer’s knowledge.

Case study: Using unsupervised machine learning to detect pre-existing security issues

Raspberry Pi devices are commonly used in SCADA environments as low-cost, remotely accessible data collectors [5][6][7]. They are often paired with Industrial Internet of Things (IIoT) for monitoring and tracking [8]. However, these devices also represent a security risk because their small physical size and time-consuming nature of physical inspection makes them easy to overlook. This poses a security risk, as these devices have previously been used to carry out USB-based attacks or to emulate Ethernet-over-USB connections to exfiltrate sensitive data [8][9].

In this incident, a Darktrace customer was unaware that their supplier had installed a Raspberry Pi device on their ICS network. Crucially, the installation occurred prior to Darktrace’s deployment on the customer’s network. 

For other anomaly detection tools, this order of events meant that this third-party device would likely have been treated as part of the customer’s existing infrastructure. However, after Darktrace was deployed, it analyzed the metadata from the encrypted HTTPS and DNS connections that the Raspberry Pi made to ‘call home’ to the supplier and determined that these connections were  unusual compared to the rest of the devices in the network, even in the absence of any malicious indicators of compromise (IoCs).  

Darktrace triggered the following alerts for this unusual activity that consequently notified the customer to the pre-existing threat of an unmanaged device already present in their network:

  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Agent Beacon (Short Period)
  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Long Period)
  • Tags / New Raspberry Pi Device
  • Device / DNS Requests to Unusual Server
  • Device / Anomaly Indicators / Spike in Connections to Rare Endpoint Indicator
Darktrace’s External Sites Summary showing the rarity of the external endpoint that the Raspberry Pi device ‘called home’ to and the model alerts triggered.  
Figure 1: Darktrace’s External Sites Summary showing the rarity of the external endpoint that the Raspberry Pi device ‘called home’ to and the model alerts triggered.  

Darktrace’s Cyber AI Analyst launched an autonomous investigation into the activity, correlating related events into a broader incident and generating a report outlining the potential threat along with supporting technical details.

Darktrace’s anomaly-based detection meant that the Raspberry Pi device did not need to be observed performing clearly malicious behavior to alert the customer to the security risk, and neither can defenders afford to wait for such escalation.

Why is this significant?

In 2021 a similar attack took place. Aiming to poison a Florida water treatment facility, attackers leveraged a TeamViewer instance that had been dormant on the system for six months, effectively allowing the attacker to ‘live off the land’ [10].  

The Raspberry Pi device in this incident also remained outside the purview of the customer’s security team at first. It could have been leveraged by a persistent attacker to pivot within the internal network and communicate externally.

A proactive approach to active defense that seeks to minimize and continuously monitor the attack surface and network is crucial.  

The growing interest in manufacturing from attackers and policymakers

Significant motivations for targeting the manufacturing sector and increasing regulatory demands make the convergence of supply chain risk, insider risk, and the prevalence of stealthy living-off-the-land techniques particularly relevant to this sector.

Manufacturing is consistently targeted by cybercriminals [11], and the sector’s ‘just-in-time’ model grants attackers the opportunity for high levels of disruption. Furthermore, under NIS 2, manufacturing and some food and beverage processing entities are now designated as ‘important’ entities. This means stricter incident reporting requirements within 24 hours of detection, and enhanced security requirements such as the implementation of zero trust and network segmentation policies, as well as measures to improve supply chain resilience [12][13][14].

How can Darktrace help?

Ultimately, Darktrace successfully assisted a manufacturing organization in detecting a potentially disruptive 'near-miss' within their OT environment, even in the absence of traditional IoCs.  Through passive asset identification techniques and continuous network monitoring, the customer improved their understanding of their network and supply chain risk.  

While the swift detection of the rogue device allowed the threat to be identified before it could escalate, the customer could have reduced their time to respond by using Darktrace’s built-in response capabilities, had Darktrace’s Autonomous Response capability been enabled.  Darktrace’s Autonomous Response can be configured to target specific connections on a rogue device either automatically upon detection or following manual approval from the security team, to stop it communicating with other devices in the network while allowing other approved devices to continue operating. Furthermore, the exportable report generated by Cyber AI Analyst helps security teams to meet NIS 2’s enhanced reporting requirements.  

Sophisticated ICS attacks often leverage insider access to perform in-depth reconnaissance for the development of tailored malware capabilities.  This case study and high-profile ICS attacks highlight the importance of mitigating supply chain risk in a similar way to insider risk.  As ICS networks adapt to the introduction of IIoT, remote working and the increased convergence between IT and OT, it is important to ensure the approach to secure against these threats is compatible with the dynamic nature of the network.  

Credit to Nicole Wong (Principal Cyber Analyst), Matthew Redrup (Senior Analyst and ANZ Team Lead)

[related-resource]

Appendices

MITRE ATT&CK Mapping

  • Infrastructure / New Raspberry Pi Device - INITIAL ACCESS - T1200 Hardware Additions
  • Device / DNS Requests to Unusual Server - CREDENTIAL ACCESS, COLLECTION - T1557 Man-in-the-Middle
  • Compromise / Agent Beacon - COMMAND AND CONTROL - T1071.001 Web Protocols

References

[1] https://www.cisa.gov/topics/physical-security/insider-threat-mitigation/defining-insider-threats

[2] https://www.trendmicro.com/vinfo/gb/threat-encyclopedia/web-attack/139/havex-targets-industrial-control-systems

[3]https://thehackernews.com/2018/08/tsmc-wannacry-ransomware-attack.html

[4] https://www.theverge.com/2020/12/21/22194183/intel-nvidia-cisco-government-infected-solarwinds-hack

[5] https://www.centreon.com/monitoring-ot-with-raspberry-pi-and-centreon/

[6] https://ieeexplore.ieee.org/document/9107689

[7] https://www.linkedin.com/pulse/webicc-scada-integration-industrial-raspberry-pi-devices-mryff

[8] https://www.rowse.co.uk/blog/post/how-is-the-raspberry-pi-used-in-the-iiot

[9] https://sepiocyber.com/resources/whitepapers/raspberry-pi-a-friend-or-foe/#:~:text=Initially%20designed%20for%20ethical%20purposes,as%20cyberattacks%20and%20unauthorized%20access

[10] https://edition.cnn.com/2021/02/10/us/florida-water-poison-cyber/index.html

[11] https://www.mxdusa.org/2025/02/13/top-cyber-threats-in-manufacturing/

[12] https://www.shoosmiths.com/insights/articles/nis2-what-manufacturers-and-distributors-need-to-know-about-europes-new-cybersecurity-regime

[13] https://www.goodaccess.com/blog/nis2-require-zero-trust-essential-security-measure#zero-trust-nis2-compliance

[14] https://logisticsviewpoints.com/2024/11/06/the-impact-of-nis-2-regulations-on-manufacturing-supply-chains/

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About the author
Nicole Wong
Cyber Security Analyst

Blog

/

Compliance

/

June 9, 2025

Modernising UK Cyber Regulation: Implications of the Cyber Security and Resilience Bill

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The need for security and continued cyber resilience

The UK government has made national security a key priority, and the new Cyber Security and Resilience Bill (CSRB) is a direct reflection of that focus. In introducing the Bill, Secretary of State for Science, Innovation and Technology, Peter Kyle, recognised that the UK is “desperately exposed” to cyber threats—from criminal groups to hostile nation-states that are increasingly targeting the UK's digital systems and critical infrastructure[1].

Context and timeline for the new legislation

First announced during the King’s Speech of July 2024, and elaborated in a Department for Science, Innovation and Technology (DSIT) policy statement published in April 2025, the CSRB is expected to be introduced in Parliament during the 2025-26 legislative session.

For now, organisations in the UK remain subject to the 2018 Network and Information Systems (NIS) Regulations – an EU-derived law which was drafted before today’s increasing digitisation of critical services, rise in cloud adoption and emergence of AI-powered threats.

Why modernisation is critical

Without modernisation, the Government believes UK’s infrastructure and economy risks falling behind international peers. The EU, which revised its cybersecurity regulation under the NIS2 Directive, already imposes stricter requirements on a broader set of sectors.

The urgency of the Bill is also underscored by recent high-impact incidents, including the Synnovis attack which targeted the National Health Service (NHS) suppliers and disrupted thousands of patient appointments and procedures[2]. The Government has argued that such events highlight a systemic failure to keep pace with a rapidly evolving threat landscape[3].

What the Bill aims to achieve

This Bill represents a decisive shift. According to the Government, it will modernise and future‑proof the UK’s cyber laws, extending oversight to areas where risk has grown but regulation has not kept pace[4]. While the legislation builds on previous consultations and draws lessons from international frameworks like the EU’s NIS2 directive, it also aims to tailor solutions to the UK’s unique threat environment.

Importantly, the Government is framing cybersecurity not as a barrier to growth, but as a foundation for it. The policy statement emphasises that strong digital resilience will create the stability businesses need to thrive, innovate, and invest[5]. Therefore, the goals of the Bill will not only be to enhance security but also act as an enabler to innovation and economic growth.

Recognition that AI changes cyber threats

The CSRB policy statement recognises that AI is fundamentally reshaping the threat landscape, with adversaries now leveraging AI and commercial cyber tools to exploit vulnerabilities in critical infrastructure and supply chains. Indeed, the NCSC has recently assessed that AI will almost certainly lead to “an increase in the frequency and intensity of cyber threats”[6]. Accordingly, the policy statement insists that the UK’s regulatory framework “must keep pace and provide flexibility to respond to future threats as and when they emerge”[7].

To address the threat, the Bill signals new obligations for MSPs and data centres, timely incident reporting and dynamic guidance that can be refreshed without fresh primary legislation, making it essential for firms to follow best practices.

What might change in day-to-day practice?

New organisations in scope of regulation

Under the existing Network and Information Systems (NIS) Regulations[8], the UK already supervises operators in five critical sectors—energy, transport, drinking water, health (Operators of Essential Services, OES) and digital infrastructure (Relevant Digital Service Providers, RDSPs).

The Cyber Security and Resilience Bill retains this foundation and adds Managed Service Providers (MSPs) and data centres to the scope of regulation to “better recognise the increasing reliance on digital services and the vulnerabilities posed by supply chains”[9]. It also grants the Secretary of State for Science, Innovation and Technology the power to add new sectors or sub‑sectors via secondary legislation, following consultation with Parliament and industry.

Managed service providers (MSPs)

MSPs occupy a central position within the UK’s enterprise information‑technology infrastructure. Because they remotely run or monitor clients’ systems, networks and data, they hold privileged, often continuous access to multiple environments. This foothold makes them an attractive target for malicious actors.

The Bill aims to bring MSPs in scope of regulation by making them subject to the same duties as those placed on firms that provide digital services under the 2018 NIS Regulations. By doing so, the Bill seeks to raise baseline security across thousands of customer environments and to provide regulators with better visibility of supply‑chain risk.

The proposed definition for MSPs is a service which:

  1. Is provided to another organisation
  2. Relies on the use of network and information systems to deliver the service
  3. Relates to ongoing management support, active administration and/or monitoring of AI systems, IT infrastructure, applications, and/or IT networks, including for the purpose of activities relating to cyber security.
  4. Involves a network connection and/or access to the customer’s network and information systems.

Data centres

Building on the September 2024 designation of data centres as critical national infrastructure, the CSRB will fold data infrastructure into the NIS-style regime by naming it an “relevant sector" and data centres as “essential service”[10].

About 182 colocation facilities run by 64 operators will therefore come under statutory duties to notify the regulator, maintain proportionate CAF-aligned controls and report significant incidents, regardless of who owns them or what workloads they host.

New requirements for regulated organisations

Incident reporting processes

There could be stricter timelines or broader definitions of what counts as a reportable incident. This might nudge organisations to formalise detection, triage, and escalation procedures.

The Government is proposing to introduce a new two-stage incident reporting process. This would include an initial notification which would be submitted within 24 hours of becoming aware of a significant incident, followed by a full incident report which should be submitted within 72 hours of the same.

Supply chain assurance requirements

Supply chains for the UK's most critical services are becoming increasingly complex and present new and serious vulnerabilities for cyber-attacks. The recent Synnovis ransomware attacks on the NHS[11] exemplify the danger posed by attacks against the supply chains of important services and organisations. This is concerning when reflecting on the latest Cyber Security Breaches survey conducted by DSIT, which highlights that fewer than 25% of large businesses review their supply chain risks[12].

Despite these risks, the UK’s legacy cybersecurity regulatory regime does not explicitly cover supply chain risk management. The UK instead relies on supporting and non-statutory guidance to close this gap, such as the NCSC’s Cyber Assessment Framework (CAF)[13].

The CSRB policy statement acts on this regulatory shortcoming and recognises that “a single supplier’s disruption can have far-reaching impacts on the delivery of essential or digital services”[14].

To address this, the Bill would make in-scope organisations (OES and RDPS) directly accountable for the cybersecurity of their supply chains. Secondary legislation would spell out these duties in detail, ensuring that OES and RDSPs systematically assess and mitigate third-party cyber risks.

Updated and strengthened security requirements

By placing the CAF into a firmer footing and backing it with a statutory Code of Practice, the Government is setting clearer expectations about government expectations on technical standards and methods organisations will need to follow to prove their resilience.

How Darktrace can help support affected organizations

Demonstrate resilience

Darktrace’s Self-Learning AITM continuously monitors your digital estate across cloud, network, OT, email, and endpoint to detect, investigate, and autonomously respond to emerging threats in real time. This persistent visibility and defense posture helps organizations demonstrate cyber resilience to regulators with confidence.

Streamline incident reporting and compliance

Darktrace surfaces clear alerts and automated investigation reports, complete with timeline views and root cause analysis. These insights reduce the time and complexity of regulatory incident reporting and support internal compliance workflows with auditable, AI-generated evidence.

Improve supply chain visibility

With full visibility across connected systems and third-party activity, Darktrace detects early indicators of lateral movement, account compromise, and unusual behavior stemming from vendor or partner access, reducing the risk of supply chain-originated cyber-attacks.

Ensure MSPs can meet new standards

For managed service providers, Darktrace offers native multi-tenant support and autonomous threat response that can be embedded directly into customer environments. This ensures consistent, scalable security standards across clients—helping MSPs address increasing regulatory obligations.

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References

[1] https://www.theguardian.com/uk-news/article/2024/jul/29/uk-desperately-exposed-to-cyber-threats-and-pandemics-says-minister

[2] https://www.england.nhs.uk/2024/06/synnovis-cyber-attack-statement-from-nhs-england/

[3] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[4] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[5] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[6] https://www.ncsc.gov.uk/report/impact-ai-cyber-threat-now-2027

[7] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[8] https://www.gov.uk/government/collections/nis-directive-and-nis-regulations-2018

[9] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[10] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

[11] https://www.england.nhs.uk/2024/06/synnovis-cyber-attack-statement-from-nhs-england/

[12] https://www.gov.uk/government/statistics/cyber-security-breaches-survey-2025/cyber-security-breaches-survey-2025

[13] https://www.ncsc.gov.uk/collection/cyber-assessment-framework

[14] https://www.gov.uk/government/publications/cyber-security-and-resilience-bill-policy-statement/cyber-security-and-resilience-bill-policy-statement

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