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May 25, 2022

Uncovering the Sysrv-Hello Crypto-Jacking Bonet

Discover the cyber kill chain of a Sysrv-hello botnet infection in France and gain insights into the latest TTPs of the botnet in March and April 2022.
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
Shuh Chin Goh
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25
May 2022

In recent years, the prevalence of crypto-jacking botnets has risen in tandem with the popularity and value of cryptocurrencies. Increasingly crypto-mining malware programs are distributed by botnets as they allow threat actors to harness the cumulative processing power of a large number of machines (discussed in our other Darktrace blogs.1 2 One of these botnets is Sysrv-hello, which in addition to crypto-mining, propagates aggressively across the Internet in a worm-like manner by trolling for Remote Code Execution (RCE) vulnerabilities and SSH worming from the compromised victim devices. This all has the purpose of expanding the botnet.

First identified in December 2020, Sysrv-hello’s operators constantly update and change the bots’ behavior to evolve and stay ahead of security researchers and law enforcement. As such, infected systems can easily go unnoticed by both users and organizations. This blog examines the cyber kill chain sequence of a Sysrv-hello botnet infection detected at the network level by Darktrace DETECT/Network, as well as the botnet’s tactics, techniques, and procedures (TTPs) in March and April 2022.

Figure 1: Timeline of the attack

Delivery and exploitation

The organization, which was trialing Darktrace, had deployed the technology on March 2, 2022. On the very same day, the initial host infection was seen through the download of a first-stage PowerShell loader script from a rare external endpoint by a device in the internal network. Although initial exploitation of the device happened prior to the installation and was not observed, this botnet is known to target RCE vulnerabilities in various applications such as MySQL, Tomcat, PHPUnit, Apache Solar, Confluence, Laravel, JBoss, Jira, Sonatype, Oracle WebLogic and Apache Struts to gain initial access to internal systems.3 Recent iterations have also been reported to have been deployed via drive-by-downloads from an empty HTML iframe pointing to a malicious executable that downloads to the device from a user visiting a compromised website.4

Initial intrusion

The Sysrv-hello botnet is distributed for both Linux and Windows environments, with the corresponding compatible script pulled based on the architecture of the system. In this incident, the Windows version was observed.

On March 2, 2022 at 15:15:28 UTC, the device made a successful HTTP GET request to a malicious IP address5 that had a rarity score of 100% in the network. It subsequently downloaded a malicious PowerShell script named ‘ldr.ps1'6 onto the system. The associated IP address ‘194.145.227[.]21’ belongs to ‘ASN AS48693 Rices Privately owned enterprise’ and had been identified as a Sysrv-hello botnet command and control (C2) server in April the previous year. 3

Looking at the URI ‘/ldr.ps1?b0f895_admin:admin_81.255.222.82:8443_https’, it appears some form of query was being executed onto the object. The question mark ‘?’ in this URI is used to delimit the boundary between the URI of the queryable object and the set of strings used to express a query onto that object. Conventionally, we see the set of strings contains a list of key/value pairs with equal signs ‘=’, which are separated by the ampersand symbol ‘&’ between each of those parameters (e.g. www.youtube[.]com/watch?v=RdcCjDS0s6s&ab_channel=SANSCyberDefense), though the exact structure of the query string is not standardized and different servers may parse it differently. Instead, this case saw a set of strings with the hexadecimal color code #b0f895 (a light shade of green), admin username and password login credentials, and the IP address ‘81.255.222[.]82’ being applied during the object query (via HTTPS protocol on port 8443). In recent months this French IP has also had reports of abuse from the OSINT community.7

On March 2, 2022 at 15:15:33 UTC, the PowerShell loader script further downloaded second-stage executables named ‘sys.exe’ and ‘xmrig.2 sver.8 9 These have been identified as the worm and cryptocurrency miner payloads respectively.

Establish foothold

On March 2, 2022 at 17:46:55 UTC, after the downloads of the worm and cryptocurrency miner payloads, the device initiated multiple SSL connections in a regular, automated manner to Pastebin – a text storage website. This technique was used as a vector to download/upload data and drop further malicious scripts onto the host. OSINT sources suggest the JA3 client SSL fingerprint (05af1f5ca1b87cc9cc9b25185115607d) is associated with PowerShell usage, corroborating with the observation that further tooling was initiated by the PowerShell script ‘ldr.ps1’.

Continual Pastebin C2 connections were still being made by the device almost two months since the initiation of such connections. These Pastebin C2 connections point to new tactics and techniques employed by Sysrv-hello — reports earlier than May do not appear to mention any usage of the file storage site. These new TTPs serve two purposes: defense evasion using a web service/protocol and persistence. Persistence was likely achieved through scheduling daemons downloaded from this web service and shellcode executions at set intervals to kill off other malware processes, as similarly seen in other botnets.10 Recent reports have seen other malware programs also switch to Pastebin C2 tunnels to deliver subsequent payloads, scrapping the need for traditional C2 servers and evading detection.11

Figure 2: A section of the constant SSL connections that the device was still making to ‘pastebin[.]com’ even in the month of April, which resembles beaconing scheduled activity

Throughout the months of March and April, suspicious SSL connections were made from a second potentially compromised device in the internal network to the infected breach device. The suspicious French IP address ‘81.255.222[.]82’ previously seen in the URI object query was revealed as the value of the Server Name Indicator (SNI) in these SSL connections where, typically, a hostname or domain name is indicated.

After an initial compromise, attackers usually aim to gain long-term remote shell access to continue the attack. As the breach device does not have a public IP address and is most certainly behind a firewall, for it to be directly accessible from the Internet a reverse shell would need to be established. Outgoing connections often succeed because firewalls generally filter only incoming traffic. Darktrace observed the device making continuous outgoing connections to an external host listening on an unusual port, 8443, indicating the presence of a reverse shell for pivoting and remote administration.

Figure 3: SSL connections to server name ‘81.255.222[.]8’ at end of March and start of April

Accomplish mission

On March 4, 2022 at 15:07:04 UTC, the device made a total of 16,029 failed connections to a large volume of external endpoints on the same port (8080). This behavior is consistent with address scanning. From the country codes, it appears that public IP addresses for various countries around the world were contacted (at least 99 unique addresses), with the US being the most targeted.

From 19:44:36 UTC onwards, the device performed cryptocurrency mining using the Minergate mining pool protocol to generate profits for the attacker. A login credential called ‘x’ was observed in the Minergate connections to ‘194.145.227[.]21’ via port 5443. JSON-RPC methods of ‘login’ and ‘submit’ were seen from the connection originator (the infected breach device) and ‘job’ was seen from the connection responder (the C2 server). A high volume of connections using the JSON-RPC application protocol to ‘pool-fr.supportxmr[.]com’ were also made on port 80.

When the botnet was first discovered in December 2020, mining pools MineXMR and F2Pool were used. In February 2021, MineXMR was removed and in March 2021, Nanopool mining pool was added,12 before switching to the present SupportXMR and Minergate mining pools. Threat actors utilize such proxy pools to help hide the actual crypto wallet address where the contributions are made by the crypto-mining activity. From April onwards, the device appears to download the ‘xmrig.exe’ executable from a rare IP address ‘61.103.177[.]229’ in Korea every few days – likely in an attempt to establish persistency and ensure the cryptocurrency mining payload continues to exist on the compromised system for continued mining.

On March 9, 2022 from 18:16:20 UTC onwards, trolling for various RCE vulnerabilities (including but not limited to these four) was observed over HTTP connections to public IP addresses:

  1. Through March, the device made around 5,417 HTTP POSTs with the URI ‘/vendor/phpunit/phpunit/src/Util/PHP/eval-stdin.php’ to at least 99 unique public IPs. This appears to be related to CVE-2017-9841, which in PHPUnit allows remote attackers to execute arbitrary PHP code via HTTP POST data beginning with a ‘13 PHPUnit is a common testing framework for PHP, used for performing unit tests during application development. It is used by a variety of popular Content Management Systems (CMS) such as WordPress, Drupal and Prestashop. This CVE has been called “one of the most exploitable CVEs of 2019,” with around seven million attack attempts being observed that year.14 This framework is not designed to be exposed on the critical paths serving web pages and should not be reachable by external HTTP requests. Looking at the status messages of the HTTP POSTs in this incident, some ‘Found’ and ‘OK’ messages were seen, suggesting the vulnerable path could be accessible on some of those endpoints.

Figure 4: PCAP of CVE-2017-9841 vulnerability trolling

Figure 5: The CVE-2017-9841 vulnerable path appears to be reachable on some endpoints

  1. Through March, the device also made around 5,500 HTTP POSTs with the URI ‘/_ignition/execute-solution’ to at least 99 unique public IPs. This appears related to CVE-2021-3129, which allows unauthenticated remote attackers to execute arbitrary code using debug mode with Laravel, a PHP web application framework in versions prior to 8.4.2.15 The POST request below makes the variable ‘username’ optional, and the ‘viewFile’ parameter is empty, as a test to see if the endpoint is vulnerable.16

Figure 6: PCAP of CVE-2021-3129 vulnerability trolling

  1. The device made approximately a further 252 HTTP GETs with URIs containing ‘invokefunction&function’ to another minimum of 99 unique public IPs. This appears related to a RCE vulnerability in ThinkPHP, an open-source web framework.17

Figure 7: Some of the URIs associated with ThinkPHP RCE vulnerability

  1. A HTTP header related to a RCE vulnerability for the Jakarta Multipart parser used by Apache struts2 in CVE-2017-563818 was also seen during the connection attempts. In this case the payload used a custom Content-Type header.

Figure 8: PCAP of CVE-2017-5638 vulnerability trolling

Two widely used methods of SSH authentication are public key authentication and password authentication. After gaining a foothold in the network, previous reports3 19 have mentioned that Sysrv-hello harvests private SSH keys from the compromised device, along with identifying known devices. Being a known device means the system can communicate with the other system without any further authentication checks after the initial key exchange. This technique was likely performed in conjunction with password brute-force attacks against the known devices. Starting from March 9, 2022 at 20:31:25 UTC, Darktrace observed the device making a large number of SSH connections and login failures to public IP ranges. For example, between 00:05:41 UTC on March 26 and 05:00:02 UTC on April 14, around 83,389 SSH connection attempts were made to 31 unique public IPs.

Figure 9: Darktrace’s Threat Visualizer shows large spikes in SSH connections by the breach device

Figure 10: Beaconing SSH connections to a single external endpoint, indicating a potential brute-force attack

Darktrace coverage

Cyber AI Analyst was able to connect the events and present them in a digestible, chronological order for the organization. In the aftermath of any security incidents, this is a convenient way for security users to conduct assisted investigations and reduce the workload on human analysts. However, it is good to note that this activity was also easily observed in real time from the model section on the Threat Visualizer due to the large number of escalating model breaches.

Figure 11: Cyber AI Analyst consolidating the events in the month of March into a summary

Figure 12: Cyber AI Analyst shows the progression of the attack through the month of March

As this incident occurred during a trial, Darktrace RESPOND was enabled in passive mode – with a valid license to display the actions that it would have taken, but with no active control performed. In this instance, no Antigena models breached for the initial compromised device as it was not tagged to be eligible for Antigena actions. Nonetheless, Darktrace was able to provide visibility into these anomalous connections.

Had Antigena been deployed in active mode, and the breach device appropriately tagged with Antigena All or Antigena External Threat, Darktrace would have been able to respond and neutralize different stages of the attack through network inhibitors Block Matching Connections and Enforce Group Pattern of Life, and relevant Antigena models such as Antigena Suspicious File Block, Antigena Suspicious File Pattern of Life Block, Antigena Pastebin Block and Antigena Crypto Currency Mining Block. The first of these inhibitors, Block Matching Connections, will block the specific connection and all future connections that matches the same criteria (e.g. all future outbound HTTP connections from the breach device to destination port 80) for a set period of time. Enforce Group Pattern of Life allows a device to only make connections and data transfers that it or any of its peer group typically make.

Conclusion

Resource hijacking results in unauthorized consumption of system resources and monetary loss for affected organizations. Compromised devices can potentially be rented out to other threat actors and botnet operators could switch from conducting crypto-mining to other more destructive illicit activities (e.g. DDoS or dropping of ransomware) whilst changing their TTPs in the future. Defenders are constantly playing catch-up to this continual evolution, and retrospective rules and signatures solutions or threat intelligence that relies on humans to spot future threats will not be able to keep up.

In this case, it appears the botnet operator has added an object query in the URL of the initial PowerShell loader script download, added Pastebin C2 for evasion and persistence, and utilized new cryptocurrency mining pools. Despite this, Darktrace’s Self-Learning AI was able to identify the threats the moment attackers changed their approach, detecting every step of the attack in the network without relying on known indicators of threat.

Appendix

Darktrace model detections

  • Anomalous File / Script from Rare Location
  • Anomalous File / EXE from Rare External Location
  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / Beaconing Activity To External Rare
  • Device / External Address Scan
  • Compromise / Crypto Currency Mining Activity
  • Compromise / High Priority Crypto Currency Mining
  • Compromise / High Volume of Connections with Beacon Score
  • Compromise / SSL Beaconing to Rare Destination
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
  • Device / Large Number of Model Breaches
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Anomalous Connection / SSH Brute Force
  • Compromise / SSH Beacon
  • Compliance / SSH to Rare External AWS
  • Compromise / High Frequency SSH Beacon
  • Compliance / SSH to Rare External Destination
  • Device / Multiple C2 Model Breaches
  • Anomalous Connection / POST to PHP on New External Host

MITRE ATT&CK techniques observed:

IoCs

Thanks to Victoria Baldie and Yung Ju Chua for their contributions.

Footnotes

1. https://www.darktrace.com/en/blog/crypto-botnets-moving-laterally

2. https://www.darktrace.com/en/blog/how-ai-uncovered-outlaws-secret-crypto-mining-operation

3. https://www.lacework.com/blog/sysrv-hello-expands-infrastructure

4. https://www.riskiq.com/blog/external-threat-management/sysrv-hello-cryptojacking-botnet

5. https://www.virustotal.com/gui/ip-address/194.145.227.21

6. https://www.virustotal.com/gui/url/c586845daa2aec275453659f287dcb302921321e04cb476b0d98d731d57c4e83?nocache=1

7. https://www.abuseipdb.com/check/81.255.222.82

8. https://www.virustotal.com/gui/file/586e271b5095068484446ee222a4bb0f885987a0b77e59eb24511f6d4a774c30

9. https://www.virustotal.com/gui/file/f5bef6ace91110289a2977cfc9f4dbec1e32fecdbe77326e8efe7b353c58e639

10. https://www.ironnet.com/blog/continued-exploitation-of-cve-2021-26084

11. https://www.zdnet.com/article/njrat-trojan-operators-are-now-using-pastebin-as-alternative-to-central-command-server

12. https://blogs.juniper.net/en-us/threat-research/sysrv-botnet-expands-and-gains-persistence

13. https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2017-9841

14. https://www.imperva.com/blog/the-resurrection-of-phpunit-rce-vulnerability

15. https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-3129

16. https://isc.sans.edu/forums/diary/Laravel+v842+exploit+attempts+for+CVE20213129+debug+mode+Remote+code+execution/27758

17. https://securitynews.sonicwall.com/xmlpost/thinkphp-remote-code-execution-rce-bug-is-actively-being-exploited

18. https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2017-5638

19. https://sysdig.com/blog/crypto-sysrv-hello-wordpress

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
Shuh Chin Goh

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November 25, 2025

UK Cyber Security & Resilience Bill: What Organizations Need to Know

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Why the Bill has been introduced

The UK’s cyber threat landscape has evolved dramatically since the 2018 NIS regime was introduced. Incidents such as the Synnovis attack against hospitals and the British Library ransomware attack show how quickly operational risk can become public harm. In this context, the UK Department for Science, Innovation and Technology estimates that cyber-attacks cost UK businesses around £14.7 billion each year.

At the same time, the widespread adoption of AI has expanded organisations’ attack surfaces and empowered threat actors to launch more effective and sophisticated activities, including crafting convincing phishing campaigns, exploiting vulnerabilities and initiating ransomware attacks at unprecedented speed and scale.  

The CSRB responds to these challenges by widening who is regulated, accelerating incident reporting and tightening supply chain accountability, while enabling rapid updates that keep pace with technology and emerging risks.

Key provisions of the Cyber Security and Resilience Bill

A wider set of organisations in scope

The Bill significantly broadens the range of organisations regulated under the NIS framework.

  • Managed service providers (MSPs) - medium and large MSPs, including MSSPs, managed SOCs, SIEM providers and similar services,will now fall under NIS obligations due to their systemic importance and privileged access to client systems. The Information Commissioner’s Office (ICO) will act as the regulator. Government analysis anticipates that a further 900 to 1,100 MSPs will be in scope.
  • Data infrastructure is now recognised as essential to the functioning of the economy and public services. Medium and large data centres, as well as enterprise facilities meeting specified thresholds, will be required to implement appropriate and proportionate measures to manage cyber risk. Oversight will be shared between DSIT and Ofcom, with Ofcom serving as the operational regulator.
  • Organisations that manage electrical loads for smart appliances, such as those supporting EV charging during peak times, are now within scope.

These additions sit alongside existing NIS-regulated sectors such as transport, energy, water, health, digital infrastructure, and certain digital services (including online marketplaces, search engines, and cloud computing).

Stronger supply chain requirements

Under the CSRB, regulators can now designate third-party suppliers as ‘designated critical suppliers’ (DCS) when certain threshold criteria are met and where disruption could have significant knock-on effects. Designated suppliers will be subject to the same security and incident-reporting obligations as Operators of Essential Services (OES) and Relevant Digital Service Providers (RDSPs).

Government will scope the supply chain duties for OES and RDSPs via secondary legislation, following consultation. infrastructure incidents where a single supplier’s compromise caused widespread disruption.

Faster incident reporting

Sector-specific regulators, 12 in total, will be responsible for implementing the CSRB, allowing for more effective and consistent reporting. In addition, the CSRB introduces a two-stage reporting process and expands incident reporting criteria. Regulated entities must submit an initial notification within 24 hours of becoming aware of a significant incident, followed by an incident report within 72 hours. Incident reporting criteria are also broadened to capture incidents beyond those which actually resulted in an interruption, ensuring earlier visibility for regulators and the National Cyber Security Centre (NCSC). The importance of information sharing across agencies, law enforcement and regulators is also facilitated by the CSRB.

The reforms also require data centres and managed service providers to notify affected customers where they are likely to have been impacted by a cyber incident.

An agile regulatory framework

To keep pace with technological change, the CSRB will enable the Secretary of State to update elements of the framework via secondary legislation. Supporting materials such as the NCSC Cyber Assessment Framework (CAF) are to be "put on a stronger footing” allowing for requirements to be more easily followed, managed and updated. Regulators will also now be able to recover full costs associated with NIS duties meaning they are better resourced to carry out their associated responsibilities.

Relevant Managed Service Providers must identify and take appropriate and proportionate measures to manage risks to the systems they rely on for providing services within the UK. Importantly, these measures must, having regard to the state of the art, ensure a level of security appropriate to the risk posed, and prevent or minimise the impact of incidents.

The Secretary of State will also be empowered to issue a Statement of Strategic Priorities, setting cross-regime outcomes to drive consistency across the 12 competent authorities responsible for implementation.

Penalties

The enforcement framework will be strengthened, with maximum fines aligned with comparable regimes such as the GDPR, which incorporate maximums tied to turnover. Under the CSRB, maximum penalties for more serious breaches could be up to £17 million or 4% of global turnover, whichever is higher.

Next steps

The Bill is expected to progress through Parliament over the course of 2025 and early 2026, with Royal Assent anticipated in 2026. Once enacted, most operational measures will not take immediate effect. Instead, Government will bring key components into force through secondary legislation following further consultation, providing regulators and industry with time to adjust practices and prepare for compliance.

Anticipated timeline

  • 2025-2026: Parliamentary scrutiny and passage;
  • 2026: Royal Assent;  
  • 2026 consultation: DSIT intends to consult on detailed implementation;
  • From 2026 onwards: Phased implementation via secondary legislation, following further consultation led by DSIT.

How Darktrace can help

The CSRB represents a step change in how the UK approaches digital risk, shifting the focus from compliance to resilience.

Darktrace can help organisations operationalise this shift by using AI to detect, investigate and respond to emerging threats at machine speed, before they escalate into incidents requiring regulatory notification. Proactive tools which can be included in the Darktrace platform allow security teams to stress-test defences, map supply chain exposure and rehearse recovery scenarios, directly supporting the CSRB’s focus on resilience, transparency and rapid response. If an incident does occur, Darktrace’s autonomous agent, Cyber AI Analyst, can accelerate investigations and provide a view of every stage of the attack chain, supporting timely reporting.  

Darktrace’s AI can provide organisations with a vital lens into both internal and external cyber risk. By continuously learning patterns of behaviour across interconnected systems, Darktrace can flag potential compromise or disruption to detect supply chain risk before it impacts your organisation.

In a landscape where compliance and resilience go hand in hand, Darktrace can equip organisations to stay ahead of both evolving threats and evolving regulatory requirements.

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November 20, 2025

Managing OT Remote Access with Zero Trust Control & AI Driven Detection

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The shift toward IT-OT convergence

Recently, industrial environments have become more connected and dependent on external collaboration. As a result, truly air-gapped OT systems have become less of a reality, especially when working with OEM-managed assets, legacy equipment requiring remote diagnostics, or third-party integrators who routinely connect in.

This convergence, whether it’s driven by digital transformation mandates or operational efficiency goals, are making OT environments more connected, more automated, and more intertwined with IT systems. While this convergence opens new possibilities, it also exposes the environment to risks that traditional OT architectures were never designed to withstand.

The modernization gap and why visibility alone isn’t enough

The push toward modernization has introduced new technology into industrial environments, creating convergence between IT and OT environments, and resulting in a lack of visibility. However, regaining that visibility is just a starting point. Visibility only tells you what is connected, not how access should be governed. And this is where the divide between IT and OT becomes unavoidable.

Security strategies that work well in IT often fall short in OT, where even small missteps can lead to environmental risk, safety incidents, or costly disruptions. Add in mounting regulatory pressure to enforce secure access, enforce segmentation, and demonstrate accountability, and it becomes clear: visibility alone is no longer sufficient. What industrial environments need now is precision. They need control. And they need to implement both without interrupting operations. All this requires identity-based access controls, real-time session oversight, and continuous behavioral detection.

The risk of unmonitored remote access

This risk becomes most evident during critical moments, such as when an OEM needs urgent access to troubleshoot a malfunctioning asset.

Under that time pressure, access is often provisioned quickly with minimal verification, bypassing established processes. Once inside, there’s little to no real-time oversight of user actions whether they’re executing commands, changing configurations, or moving laterally across the network. These actions typically go unlogged or unnoticed until something breaks. At that point, teams are stuck piecing together fragmented logs or post-incident forensics, with no clear line of accountability.  

In environments where uptime is critical and safety is non-negotiable, this level of uncertainty simply isn’t sustainable.

The visibility gap: Who’s doing what, and when?

The fundamental issue we encounter is the disconnect between who has access and what they are doing with it.  

Traditional access management tools may validate credentials and restrict entry points, but they rarely provide real-time visibility into in-session activity. Even fewer can distinguish between expected vendor behavior and subtle signs of compromise, misuse or misconfiguration.  

As a result, OT and security teams are often left blind to the most critical part of the puzzle, intent and behavior.

Closing the gaps with zero trust controls and AI‑driven detection

Managing remote access in OT is no longer just about granting a connection, it’s about enforcing strict access parameters while continuously monitoring for abnormal behavior. This requires a two-pronged approach: precision access control, and intelligent, real-time detection.

Zero Trust access controls provide the foundation. By enforcing identity-based, just-in-time permissions, OT environments can ensure that vendors and remote users only access the systems they’re explicitly authorized to interact with, and only for the time they need. These controls should be granular enough to limit access down to specific devices, commands, or functions. By applying these principles consistently across the Purdue Model, organizations can eliminate reliance on catch-all VPN tunnels, jump servers, and brittle firewall exceptions that expose the environment to excess risk.

Access control is only one part of the equation

Darktrace / OT complements zero trust controls with continuous, AI-driven behavioral detection. Rather than relying on static rules or pre-defined signatures, Darktrace uses Self-Learning AI to build a live, evolving understanding of what’s “normal” in the environment, across every device, protocol, and user. This enables real-time detection of subtle misconfigurations, credential misuse, or lateral movement as they happen, not after the fact.

By correlating user identity and session activity with behavioral analytics, Darktrace gives organizations the full picture: who accessed which system, what actions they performed, how those actions compared to historical norms, and whether any deviations occurred. It eliminates guesswork around remote access sessions and replaces it with clear, contextual insight.

Importantly, Darktrace distinguishes between operational noise and true cyber-relevant anomalies. Unlike other tools that lump everything, from CVE alerts to routine activity, into a single stream, Darktrace separates legitimate remote access behavior from potential misuse or abuse. This means organizations can both audit access from a compliance standpoint and be confident that if a session is ever exploited, the misuse will be surfaced as a high-fidelity, cyber-relevant alert. This approach serves as a compensating control, ensuring that even if access is overextended or misused, the behavior is still visible and actionable.

If a session deviates from learned baselines, such as an unusual command sequence, new lateral movement path, or activity outside of scheduled hours, Darktrace can flag it immediately. These insights can be used to trigger manual investigation or automated enforcement actions, such as access revocation or session isolation, depending on policy.

This layered approach enables real-time decision-making, supports uninterrupted operations, and delivers complete accountability for all remote activity, without slowing down critical work or disrupting industrial workflows.

Where Zero Trust Access Meets AI‑Driven Oversight:

  • Granular Access Enforcement: Role-based, just-in-time access that aligns with Zero Trust principles and meets compliance expectations.
  • Context-Enriched Threat Detection: Self-Learning AI detects anomalous OT behavior in real time and ties threats to access events and user activity.
  • Automated Session Oversight: Behavioral anomalies can trigger alerting or automated controls, reducing time-to-contain while preserving uptime.
  • Full Visibility Across Purdue Layers: Correlated data connects remote access events with device-level behavior, spanning IT and OT layers.
  • Scalable, Passive Monitoring: Passive behavioral learning enables coverage across legacy systems and air-gapped environments, no signatures, agents, or intrusive scans required.

Complete security without compromise

We no longer have to choose between operational agility and security control, or between visibility and simplicity. A Zero Trust approach, reinforced by real-time AI detection, enables secure remote access that is both permission-aware and behavior-aware, tailored to the realities of industrial operations and scalable across diverse environments.

Because when it comes to protecting critical infrastructure, access without detection is a risk and detection without access control is incomplete.

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Pallavi Singh
Product Marketing Manager, OT Security & Compliance
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