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February 9, 2022

The Impact of Conti Ransomware on OT Systems

Learn how ransomware can spread throughout converged IT/OT environments, and how Self-Learning AI empowers organizations to contain these threats.
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
Oakley Cox
Director of Product
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09
Feb 2022

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

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

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

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

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

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

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

Compromised OT devices

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

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

Attack lifecycle

Opening stages

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

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

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

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

Device encryption and lateral spread

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

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

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

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

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

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

Examples of files being encrypted and moved:

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

Detonation of ransomware

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

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

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

How the attack bypassed the rest of the security stack

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

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

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

Darktrace insights

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

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

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

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

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

Ransomware and interconnected IT/OT systems

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

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

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

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

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

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

Discover more on how Darktrace protects OT environments from ransomware

Darktrace model detections

HMI in chronological order at time of detonation:

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

Historian

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

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

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July 3, 2025

Top Eight Threats to SaaS Security and How to Combat Them

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The latest on the identity security landscape

Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.

On average, a single organization uses 130 different Software-as-a-Service (SaaS) applications, and 45% of organizations reported experiencing a cybersecurity incident through a SaaS application in the last year.

As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.

What is SaaS security?

SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.

Below are the top eight threats that target SaaS security and user identities.

1.  Account Takeover (ATO)

Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.

2. Privilege escalation

Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.

3. Lateral movement

Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.

4. Multi-Factor Authentication (MFA) bypass and session hijacking

Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.

5. OAuth token abuse

Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.

6. Insider threats

Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.

7. Application Programming Interface (API)-based attacks

SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.

8. Business Email Compromise (BEC) via SaaS

Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.

BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.

Protecting against these SaaS threats

Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.

However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.

AI-powered SaaS security stays ahead of the threat landscape

New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.

[related-resource]

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Carlos Gray
Senior Product Marketing Manager, Email

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July 2, 2025

Pre-CVE Threat Detection: 10 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability

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Vulnerabilities are weaknesses in a system that can be exploited by malicious actors to gain unauthorized access or to disrupt normal operations. Common Vulnerabilities and Exposures (or CVEs) are a list of publicly disclosed cybersecurity vulnerabilities that can be tracked and mitigated by the security community.

When a vulnerability is discovered, the standard practice is to report it to the vendor or the responsible organization, allowing them to develop and distribute a patch or fix before the details are made public. This is known as responsible disclosure.

With a record-breaking 40,000 CVEs reported for 2024 and a predicted higher number for 2025 by the Forum for Incident Response and Security Teams (FIRST) [1], anomaly-detection is essential for identifying these potential risks. The gap between exploitation of a zero-day and disclosure of the vulnerability can sometimes be considerable, and retroactively attempting to identify successful exploitation on your network can be challenging, particularly if taking a signature-based approach.

Detecting threats without relying on CVE disclosure

Abnormal behaviors in networks or systems, such as unusual login patterns or data transfers, can indicate attempted cyber-attacks, insider threats, or compromised systems. Since Darktrace does not rely on rules or signatures, it can detect malicious activity that is anomalous even without full context of the specific device or asset in question.

For example, during the Fortinet exploitation late last year, the Darktrace Threat Research team were investigating a different Fortinet vulnerability, namely CVE 2024-23113, for exploitation when Mandiant released a security advisory around CVE 2024-47575, which aligned closely with Darktrace’s findings.

Retrospective analysis like this is used by Darktrace’s threat researchers to better understand detections across the threat landscape and to add additional context.

Below are ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

Trends in pre-cve exploitation

Often, the disclosure of an exploited vulnerability can be off the back of an incident response investigation related to a compromise by an advanced threat actor using a zero-day. Once the vulnerability is registered and publicly disclosed as having been exploited, it can kick off a race between the attacker and defender: attack vs patch.

Nation-state actors, highly skilled with significant resources, are known to use a range of capabilities to achieve their target, including zero-day use. Often, pre-CVE activity is “low and slow”, last for months with high operational security. After CVE disclosure, the barriers to entry lower, allowing less skilled and less resourced attackers, like some ransomware gangs, to exploit the vulnerability and cause harm. This is why two distinct types of activity are often seen: pre and post disclosure of an exploited vulnerability.

Darktrace saw this consistent story line play out during several of the Fortinet and PAN OS threat actor campaigns highlighted above last year, where nation-state actors were seen exploiting vulnerabilities first, followed by ransomware gangs impacting organizations [2].

The same applies with the recent SAP Netweaver exploitations being tied to a China based threat actor earlier this spring with subsequent ransomware incidents being observed [3].

Autonomous Response

Anomaly-based detection offers the benefit of identifying malicious activity even before a CVE is disclosed; however, security teams still need to quickly contain and isolate the activity.

For example, during the Ivanti chaining exploitation in the early part of 2025, a customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device.

This pre-CVE detection and response by Darktrace occurred 11 days before any public disclosure, demonstrating the value of an anomaly-based approach.

In some cases, customers have even reported that Darktrace stopped malicious exploitation of devices several days before a public disclosure of a vulnerability.

For example, During the ConnectWise exploitation, a customer informed the team that Darktrace had detected malicious software being installed via remote access. Upon further investigation, four servers were found to be impacted, while Autonomous Response had blocked outbound connections and enforced patterns of life on impacted devices.

Conclusion

By continuously analyzing behavioral patterns, systems can spot unusual activities and patterns from users, systems, and networks to detect anomalies that could signify a security breach.

Through ongoing monitoring and learning from these behaviors, anomaly-based security systems can detect threats that traditional signature-based solutions might miss, while also providing detailed insights into threat tactics, techniques, and procedures (TTPs). This type of behavioral intelligence supports pre-CVE detection, allows for a more adaptive security posture, and enables systems to evolve with the ever-changing threat landscape.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO), Emma Fougler (Global Threat Research Operations Lead), Ryan Traill (Analyst Content Lead)

References and further reading:

  1. https://www.first.org/blog/20250607-Vulnerability-Forecast-for-2025
  2. https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575
  3. https://thehackernews.com/2025/05/china-linked-hackers-exploit-sap-and.html

Related Darktrace blogs:

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

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