February 20, 2020

Lessons Learned from a Sodinokibi Ransomware Attack

Gain insights into a targeted Sodinokibi ransomware attack and learn how to better prepare your organization for potential cyber threats.

Written by

Max Heinemeyer

Global Field CISO

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

Max Heinemeyer

Global Field CISO

Feb 2020

Introduction

Last week, Darktrace detected a targeted Sodinokibi ransomware attack during a 4-week trial with a mid-sized company.

This blog post will go through every stage of the attack lifecycle and detail the attacker’s techniques, tools and procedures used, and how Darktrace detected the attack.

The Sodinokibi group is an innovative threat-actor that is sometimes referred to as a ‘double-threat’, due to their ability to run targeted attacks using ransomware while simultaneously exfiltrating their victim’s data. This enables them to threaten to make the victim’s data publicly available if the ransom is not paid.

While Darktrace’s AI was able to identify the attack in real time as it was emerging, unfortunately the security team didn’t have eyes on the technology and was unable to action the alerts — nor was Antigena set in active mode, which would have slowed down and contained the threat instantaneously.

Timeline

The timeline below provides a rough overview of the major attack phases. Most of the attack took place over the course of a week, with the majority of activity distributed over the last three days.

Technical analysis

Darktrace detected two main devices being hit by the attack: an internet-facing RDP server (‘RDP server’) and a Domain Controller (‘DC’), that also acts as a SMB file server.

In previous attacks, Sodinokibi has used host-level encryption for ransomware activity where the encryption takes place on the compromised host itself — in contrast to network-level encryption where the bulk of the ransomware activity takes place over network protocols such as SMB.

Initial compromise

Over several days, the victim’s external-facing RDP server was receiving successful RDP connections from a rare external IP address located in Ukraine.

Shortly before the initial reconnaissance started, Darktrace saw another RDP connection coming into the RDP server with the same RDP account as seen before. This connection lasted for almost an hour.

It is highly likely that the RDP credential used in this attack had been compromised prior to the attack, either via common brute-force methods, credential stuffing attacks, or phishing.

Thanks to Darktrace’s Deep-Packet Inspection, we can clearly see the connection and all related information.

Suspicious RDP connection information:

Time: 2020-02-10 16:57:06 UTC
Source: 46.150.70[.]86 (Ukraine)
Destination: 192.168.X.X
Destination Port: 64347
Protocol: RDP
Cookie: [REDACTED]
Duration: 00h41m40s
Data out: 8.44 MB
Data in: 1.86 MB

Darktrace detects incoming RDP connections from IP addresses that usually do not connect to the organization.

Attack tools download

Approximately 45 minutes after the suspicious RDP connection from Ukraine, the RDP server connected to the popular file sharing platform, Megaupload, and downloaded close to 300MB from there.

Darktrace’s AI recognized that neither this server, nor its automatically detected peer group, nor, in fact, anyone else on the network commonly utilized Megaupload — and therefore instantly detected this as anomalous behavior, and flagged it as unusual.

As well as the full hostname and actual IP used for the download, Megaupload is 100% rare for this organization.

Later on, we will see over 40GB being uploaded to Megaupload. This initial download of 300MB however is likely additional tooling and C2 implants downloaded by the threat-actor into the victim’s environment.

Internal reconnaissance

Only 3 minutes after the download from Megaupload onto the RDP server, Darktrace alerted on the RDP server doing an anomalous network scan:

The RDP server scanned 9 other internal devices on the same subnet on 7 unique ports: 21, 80, 139, 445, 3389, 4899, 8080  . Anybody with some offensive security know-how will recognize most of these ports as default ports one would scan for in a Windows environment for lateral movement. Since this RDP server does not usually conduct network scans, Darktrace again identified this activity as highly anomalous.

Later on, we see the threat-actor do more network scanning. They become bolder and use more generic scans — one of them showing that they are using Nmap with a default user agent:

Additional Command and Control traffic

While the initial Command and Control traffic was most likely using predominantly RDP, the threat-actor now wanted to establish more persistence and create more resilient channels for C2.

Shortly after concluding the initial network scans (ca. 19:17 on 10th February 2020), the RDP server starts communicating with unusual external services that are unique and unusual for the victim’s environment.

Communications to Reddcoin

Again, nobody else is using Reddcoin on the network. The combination of application protocol and external port is extremely unusual for the network as well.

The communications also went to the Reddcoin API, indicating the installation of a software agent rather than manual communications. This was detected as Reddcoin was not only rare for the network, but also ‘young’ — i.e. this particular external destination had never been seen to be contacted before on the network until 25 minutes before.

Communications to the Reddcoin API

Communications to Exceptionless[.]io

As we can see, the communications to exceptionalness[.]io were done in a beaconing manner, using a Let’s Encrypt certificate, being rare for the network and using an unusual JA3 client hash. All of this indicates the presence of new software on the device, shortly after the threat-actor downloaded their 300MB of tooling.

While most of the above network activity started directly after the threat-actor dropped their tooling on the RDP server, the exact purpose of interfacing with Reddcoin and Exceptionless is unclear. The attacker seems to favor off-the-shelf tooling (Megaupload, Nmap, …) so they might use these services for C2 or telemetry-gathering purposes.

This concluded most of the activity on February 10.

More Command and Control traffic

Why would an attacker do this? Surely using all this C2 at the same time is much noisier than just using 1 or 2 channels?

Another significant burst of activity was observed on February 12 and 13.

The RDP server started making a lot of highly anomalous and rare connections to external destinations. It is inconclusive if all of the below services, IPs, and domains were used for C2 purposes only, but they are linked with high-confidence to the attacker’s activities:

HTTP beaconing to vkmuz[.]net
Significant amount of Tor usage
RDP connections to 198-0-244-153-static.hfc.comcastbusiness[.]net over non-standard RDP port 29348
RDP connections to 92.119.160[.]60 using an administrative account (geo-located in Russia)
Continued connections to Megaupload
Continued SSL beaconing to Exceptionless[.]io
Continued connections to api.reddcoin[.]com
SSL beaconing to freevpn[.]zone
HTTP beaconing to 31.41.116[.]201 to /index.php using a new User Agent
Unusual SSL connections to aj1713[.]online
Connections to Pastebin
SSL beaconing to www.itjx3no[.]com using an unusual JA3 client hash
SSL beaconing to safe-proxy[.]com
SSL connection to westchange[.]top without prior DNS hostname lookups (likely machine-driven)

What is significant here is the diversity in (potential) C2 channels: Tor, RDP going to dynamic ISP addresses, VPN solutions and possibly custom / customized off-the-shelf implants (the DGA-looking domains and HTTP to IP addresses to /index.php).

Why would an attacker do this? Surely using all this C2 at the same time is much noisier than just using 1 or 2 channels?

One answer might be that the attacker cared much more about short-term resilience than about stealth. As the overall attack in the network took less than 7 days, with a majority of the activity taking place over 2.5 days, this makes sense. Another possibility might be that various individuals were involved in parallel during this attack — maybe one attacker prefers the comfort of RDP sessions for hacking while another is more skilled and uses a particular post-exploitation framework.

The overall modus operandi in this financially-motivated attack is much more smash-and-grab than in the stealthy, espionage-related incidents observed in Advanced Persistent Threat campaigns (APT).

Data exfiltration

The DC uploaded around 40GB of data to Megaupload over the course of 24 hours.

While all of the above activity was seen on the RDP server (acting as the initial beach-head), the following data exfiltration activity was observed on a Domain Controller (DC) on the same subnet as the RDP server.

The DC uploaded around 40GB of data to Megaupload over the course of 24 hours.

Darktrace detected this data exfiltration while it was in progress — never did the DC (or any similar devices) upload similar amounts of data to the internet. Neither did any client nor server in the victim’s environment use Megaupload:

Ransom notes

Finally, Darktrace observed unusual files being accessed on internal SMB shares on February 13. These files appear to be ransom notes — they follow a similar, randomly-generated naming convention as other victims of the Sodinokibi group have reported:

413x0h8l-readme.txt
4omxa93-readme.txt

Conclusion and observations

The threat-actor seems to be using mostly off-the-shelf tooling which makes attribution harder — while also making detection more difficult.

This attack is representative of many of the current ransomware attacks: financially motivated, fast-acting, and targeted.

The threat-actor seems to be using mostly off-the-shelf tooling (RDP, Nmap, Mega, VPN solutions) which makes attribution harder — while also making detection more difficult. Using this kind of tooling often allows to blend in with regular admin activity — only once anomaly detection is used can this kind of activity be detected.

How can you spot the one anomalous outbound RDP connection amongst the thousands of regular RDP connections leaving your environment? How do you know when the use of Megaupload is malicious — compared to your users’ normal use of it? This is where the power of Darktrace’s self-learning AI comes into play.

Darktrace detected every stage of the visible attack lifecycle without using any threat intelligence or any static signatures.

The graphics below show an overview of detections on both compromised devices. The compromised devices were the highest-scoring assets for the network — even a level 1 analyst with limited previous exposure to Darktrace could detect such an in-progress attack in real time.

RDP Server

Some of the detections on the RDP server include:

Compliance / File Storage / Mega — using Megaupload in an unusual way
Device / Network Scan — detecting unusual network scans
Anomalous Connection / Application Protocol on Uncommon Port — detecting the use of protocols on unusual ports
Device / New Failed External Connections — detecting unusual failing C2
Compromise / Unusual Connections to Let’s Encrypt — detecting potential C2 over SSL using Let’s Encrypt
Compromise / Beacon to Young Endpoint — detecting C2 to new external endpoints for the network
Device / Attack and Recon Tools — detecting known offensive security tools like Nmap
Compromise / Tor Usage — detecting unusual Tor usage
Compromise / SSL Beaconing to Rare Destination — detecting generic SSL C2
Compromise / HTTP Beaconing to Rare Destination — detecting generic HTTP C2
Device / Long Agent Connection to New Endpoint — detecting unusual services on a device
Anomalous Connection / Outbound RDP to Unusual Port — detecting unusual RDP C2

Some of the detections on the DC include:

Anomalous Activity / Anomalous External Activity from Critical Device — detecting unusual behaviour on dcs
Compliance / File storage / Mega — using Megaupload in an unusual way
Anomalous Connection / Data Sent to New External Device — data exfiltration to unusual locations
Anomalous Connection / Uncommon 1GB Outbound — large amounts of data leaving to unusual destinations
Anomalous Server Activity / Outgoing from Server — likely C2 to unusual endpoint on the internet

‍

Written by

Max Heinemeyer

Global Field CISO

Inside the SOC

Written by

Max Heinemeyer

Global Field CISO

•

June 11, 2025

Nicole Wong

Cyber Security Analyst

Compliance

•

June 5, 2025

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OT

June 11, 2025

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

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

‍*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/

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

Two individuals sitting at a desk working on a document

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:

Is provided to another organisation
Relies on the use of network and information systems to deliver the service
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.
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 AI^TM 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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