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
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12
Dec 2022
This blog demonstrates how we use EDR integration in Darktrace for detection & investigation. We’ll look at four key features, which are summarized with an example below:
1) Contextualizing existing Darktrace information – E.g. ‘There was a Microsoft Defender for Endpoint (MDE) alert 5 minutes after Darktrace saw the device beacon to an unusual destination on the internet. Let me pivot back into the Defender UI’ 2) Cross-data detection engineering – ‘Darktrace, create an alert or trigger a response if you see a specific MDE alert and a native Darktrace detection on the same entity over a period of time’ 3) Applying unsupervised machine learning to third-party EDR alerts – ‘Darktrace, create an alert or trigger a response if there is a specific MDE alert that is unusual for the entity, given the context’ 4) Use third-party EDR alerts to trigger AI Analyst – ‘AI Analyst, this low-fidelity MDE alert flagged something on the endpoint. Please take a deep look at that device at the time of the Defender alert, conduct an investigation on Darktrace data and share your conclusions about whether there is more to it or not’
MDE is used as an example above, but Darktrace’s EDR integration capabilities extend beyond MDE to other EDRs as well, for example to Sentinel One and CrowdStrike EDR.
Darktrace brings its Self-Learning AI to your data, no matter where it resides. The data can be anywhere – in email environments, cloud, SaaS, OT, endpoints, or the network, for example. Usually, we want to get as close to the raw data as possible to get the maximum context for our machine learning.
We will explain how we leverage high-value integrations from our technology partners to bring further context to Darktrace, but also how we apply our Self-Learning AI to third-party data. While there are a broad range of integrations and capabilities available, we will primarily look at Microsoft Defender for Endpoint, CrowdStrike, and SentinelOne and focus on detection in this blog post.
The Nuts and Bolts – Setting up the Integration
Darktrace is an open platform – almost everything it does is API-driven. Our system and machine learning are flexible enough to ingest new types of data & combine it with already existing information.
The EDR integrations mentioned here are part of our 1-click integrations. All it requires is the right level of API access from the EDR solutions and the ability for Darktrace to communicate with the EDR’s API. This type of integration can be setup within minutes – it currently doesn’t require additional Darktrace licenses.
Figure 1: Set-up of Darktrace Graph Security API integration
As soon as the setup is complete, it enables various additional capabilities. Let’s look at some of the key detection & investigation-focussed capabilities step-by-step.
Contextualizing Existing Darktrace Information
The most basic, but still highly-useful integration is enriching existing Darktrace information with EDR alerts. Darktrace shows a chronological history of associated telemetry and machine learning for each entity observed in the entities event log.
With an EDR integration enabled, we now start to see EDR alerts for the respective entities turn up in the entity’s event log at the correct point in time – with a ton of context and a 1-click pivot back to the native EDR console:
Figure 2: A pivot from the Darktrace Threat Visualizer to Microsoft Defender
This context is extremely useful to have in a single screen during investigations. Context is king – it reduces time-to-meaning and skill required to understand alerts.
Cross-Data Detection Engineering
When an EDR integration is activated, Darktrace enables an additional set of detections that leverage the new EDR alerts. This comes out of the box and doesn’t require any further detection engineering. It is worth mentioning though that the new EDR information is being made available in the background for bespoke detection engineering, if advanced users want to leverage these as custom metrics.
The trick here is that the added context provided by the additional EDR alerts allows for more refined detections – primarily to detect malicious activity with higher confidence. A network detection showing us beaconing over an unusual protocol or port combination to a rare destination on the internet is great – but seeing within Darktrace that CrowdStrike detected a potentially hostile file or process three minutes prior to the beaconing detection on the same device will greatly help to prioritize the detections and aid a subsequent investigation.
Here is an example of what this looks like in Darktrace:
Figure 3: A combined model breach in the Threat Visualizer
Applying Unsupervised Machine Learning to Third-Party EDR Alerts
Once we start seeing EDR alerts in Darktrace, we can start treating it like any other data – by applying unsupervised machine learning to it. This means we can then understand how unusual a given EDR detection is for each device in question. This is extremely powerful – it allows to reduce noisy alerts without requiring ongoing EDR alert tuning and opens a whole world of new detection capabilities.
As an example – let’s imagine a low-level malware alert keeps appearing from the EDR on a specific device. This might be a false-positive in the EDR, or just not of interest for the security team, but they may not have the resources or knowledge to further tune their EDR and get rid of this noisy alert.
While Darktrace keeps adding this as contextual information in the device’s event log, it could, depending on the context of the device, the EDR alert, and the overall environment, stop alerting on this particular EDR malware alert on this specific device if it stops being unusual. Over time, noise is reduced across the environment – but if that particular EDR alert appears on another device, or on the same device in a different context, it might get flagged again, as it now is unusual in the given context.
Darktrace then goes a step further, taking those unusual EDR alerts and combining them with unusual activity seen in other Darktrace coverage areas, like the network for example. Combining an unusual EDR alert with an unusual lateral movement attempt, for example, allows it to find these combined, high-precision, cross-data set anomalous events that are highly indicative of an active cyber-attack – without having to pre-define the exact nature of what ‘unusual’ looks like.
Figure 4: Combined EDR & network detection using unsupervised machine learning in Darktrace
Use Third-Party EDR Alerts to Trigger AI Analyst
Everything we discussed so far is great for improving precision in initial detections, adding context, and cutting through alert-noise. We don’t stop there though – we can also now use the third-party EDR alerts to trigger our investigation engine, the AI Analyst.
Cyber AI Analyst replicates and automates typical level 1 and level 2 Security Operations Centre (SOC) workflows. It is usually triggered by every native Darktrace detection. This is not a SOAR where playbooks are statically defined – AI Analyst builds hypotheses, gathers data, evaluates the data & reports on its findings based on the context of each individual scenario & investigation.
Darktrace can use EDR alerts as starting points for its investigation, with every EDR alert ingested now triggering AI Analyst. This is similar to giving a (low-level) EDR alert to a human analyst and telling them: ‘Go and take a look at information in Darktrace and try to conclude whether there is more to this EDR alert or not.’
The AI Analyst subsequently looks at the entity which had triggered the EDR alert and investigates all available Darktrace data on that entity, over a period of time, in light of that EDR alert. It does not pivot outside Darktrace itself for that investigation (e.g. back into the Microsoft console) but looks at all of the context natively available in Darktrace. If concludes that there is more to this EDR alert – e.g. a bigger incident – it will report on that and clearly flag it. The report can of course be directly downloaded as a PDF to be shared with other stakeholders.
This comes in handy for a variety of reasons – primarily to further automate security operations and alleviate pressure from human teams. AI Analyst’s investigative capabilities sit on top of everything we discussed so far (combining EDR detections with detections from other coverage areas, applying unsupervised machine learning to EDR detections, …).
However, it can also come in handy to follow up on low-severity EDR alerts for which you might not have the human resources to do so.
The below screenshot shows an example of a concluded AI Analyst investigation that was triggered by an EDR alert:
Figure 5: An AI Analyst incident trained on third-party data
The Impact of EDR Integrations
The purpose behind all of this is to augment human teams, save them time and drive further security automation.
By ingesting third-party endpoint alerts, combining it with our existing intelligence and applying unsupervised machine learning to it, we achieve that further security automation.
Analysts don’t have to switch between consoles for investigations. They can leverage our high-fidelity detections that look for unusual endpoint alerts, in combination with our already powerful detections across cloud and email systems, zero trust architecture, IT and OT networks, and more.
In our experience, this pinpoints the needle in the haystack – it cuts through noise and reduces the mean-time-to-detect and mean-time-to-investigate drastically.
All of this is done out of the box in Darktrace once the endpoint integrations are enabled. It does not need a data scientist to make the machine learning work. Nor does it need a detection engineer or threat hunter to create bespoke, meaningful detections. We want to reduce the barrier to entry for using detection and investigation solutions – in terms of skill and experience required. The system is still flexible, transparent, and open, meaning that advanced users can create their own combined detections, leveraging unsupervised machine learning across different data sets with a few clicks.
There are of course more endpoint integration capabilities available than what we covered here, and we will explore these in future blog posts.
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.
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Darktrace detected a potential ClearFake‑related incident involving signs of EtherHiding activity and interactions with blockchain‑based infrastructure. A single device showed repeated suspicious command‑line behavior, primarily involving Microsoft HTML Application Host. The activity occurred over the course of a day and indicated early‑stage attempts to load malicious content associated with the ClearFake campaign.
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When Reality Diverges from the Playbook: Darktrace Identifies Encryption in a World Leaks Ransomware Attack
As-a-Service Cybercrime Models
As-a-Service cybercrime models reduce the barrier to entry for cyber criminals as they no longer need expertise in every domain. Threat actors can increasingly outsource or supplement missing skills through the broader cybercrime-as-a-service ecosystem, and thus these models continue to grow in popularity within the cybercriminal underground. This has led to multiple templates in this sphere, such as Phishing-as-a-Service, Botnet-as-a-Service, DDoS-as-a-Service, and notably Ransomware-as-a-Service (RaaS) [1].
What is Extortion-as-a-Service?
Extortion-as-a-Service (EaaS) businesses function as a formalized way for cyber threat actors to offer extortion services to others for a fee or profit share and represents an evolution of extortion operations from the double-extortion ransomware model. Advancing from the RaaS model, extortion has become a distinct profit stream, separate from the encryption payload. This separation of functions, data theft, negotiation, and publicity, sets the stage for EaaS [1].
The EaaS model reflects a broader trend in cybercriminal activity, in which threat actors increasingly prioritize data theft and public exposure over traditional ransomware encryption. This shift reduces operational complexity while increasing pressure on victims through reputational damage. This approach has become increasingly popular among threat actors as, unlike encryption-based attacks, these operations are more difficult to detect and remediate [2]. It reflects a trend of ‘hack-and-leak’ operations that prioritize stealth, speed, and reputational damage over traditional encryption-based ransomware attacks [3].
World Leaks Overview
World Leaks emerged in early 2024 as a direct rebrand of the Hunters International ransomware group, which was notorious for encrypting victims’ data and demanding payment for decryption keys. In mid-2025, Hunters International shifted to an extortion-only model due to law enforcement scrutiny and reduced profitability, rebranding itself as World Leaks.
World Leaks functions as an affiliate-based EaaS operation which provides proprietary Storage Software exfiltration tooling to affiliates while maintaining a four-platform infrastructure consisting of a main data leak site hosted on the Dark Web where victim data is published, a victim negotiation portal with live chat, an affiliate management panel, and an insider journalist platform granting media outlets 24-hour advance access to stolen data before public release [4]. Since its emergence, World Leaks has published data stolen from dozens of organizations globally on its data leak site, serving both as a pressure tactic and a means for building reputation among cyber criminals.
World Leaks (known associations include Hive Ransomware, Secp0 Ransomware, and UNC6148) have been known to target the industrial (manufacturing) sector, along with healthcare organizations, technology firms and more generally, industries with valuable intellectual property [4]. Victims targeted have spanned multiple countries, with most located in the US, as well as Canada and several countries across Europe [5].
World Leaks’ Tactics, Techniques, and Procedures (TTPs) [3][4]
World Leaks’ typical attack pattern involves the exploitation of credentials with inadequate access controls, e.g. lacking multi-factor authentication (MFA), moving through reconnaissance, lateral movement and data exfiltration, notably without an encryption element.
Initial Access:
Initial access is typically gained through the exploitation of compromised virtual private network (VPN) credentials lacking MFA through valid accounts, as well as phishing campaigns. The targeting of internet-facing VPN infrastructure, RDP, and public-facing applications also represent common attack vectors in World Leaks incidents.
Lateral Movement:
SMB, RDP, and SSH are used for lateral movement via remote services. Notably, the group is also known to use PsExec and Rclone as part of their lateral movement activities.
Data exfiltration is carried out through custom storage software tooling via TOR connections. Cloud storage services used for exfiltration particularly include MEGA. World Leaks also carry out direct data transfer through established command-and-control (C2) infrastructure.
Unlike Hunters International, which combined encryption with extortion, World Leaks claims to have abandoned the use of encryption. Some reports note that operations since January 2025 represent a pivot toward eliminating encryption entirely, instead relying on custom exfiltration tooling with SOCKSv5 proxy and TOR-based communications [4]. However, in early 2026, Darktrace detected an incident that directly contradicted this claim: World Leaks carried out an attack that involved both the exfiltration and encryption of customer data.
Darktrace’s Coverage of World Leaks Ransomware
Organizations today face a growing challenge: keeping pace with increasingly fast-moving threats. This incident highlights a common problem, when time-limited mitigations expire or human security teams cannot respond quickly enough, attackers are often able to regain the upper hand. A recent Darktrace detection of World Leaks ransomware provides a clear example of this challenge in practice.
In January 2026, Darktrace identified the presence of ransomware and data encryption linked to World Leaks within the network of an organization within the healthcare sector. Although Darktrace’s Autonomous Response capability was active in the customer’s environment and initially blocking suspicious connectivity, buying time for the customer to remediate, the attack continued once these mitigative actions expired. Darktrace continued to apply Autonomous Response actions as the attack progressed, working to inhibit the attackers at each stage of the intrusion.
Investigations carried out by Darktrace revealed that threat actors likely gained initial access via a Fortigate appliance in mid-October, indicating a three-month dwell time, before employing living-off-the-land (LOTL) techniques for lateral movement. C2 communications were established using Cloudflare Tunnel (formerly Argo Tunnel). As part of the Actions on Objectives attack phase, a significant volume of data was exfiltrated to the MEGA cloud storage platform, followed by the encryption of customer data.
Initial access/ Lateral movement
Darktrace analysts identified the likely patient-zero device within the network as a Fortigate appliance. In October 2025, this device was seen conducting brute-force activity using the compromised ‘administrator’ credential to gain a foothold deeper within the customer’s environment. Masquerading as a privileged user, the threat actor then went on to launch activity on remote devices via PsExec, a common administrative tool that allows users to execute processes on remote systems without manually installing client software, providing significant power to attackers when abused. Around the time, Darktrace detected an unknown device on the network attempting to authenticate via NTLM. As this device had not previously been seen on the network, it likely belonged to the attacker.
Reconnaissance
As part of the reconnaissance phase of the attack, port and network scanning was carried out in an attempt to identify open UDP and TCP ports within the network.
Lateral movement & C2
Around one month after entering the customer’s network, the World Leaks threat actors began tunnelling activity using Cloudflare Tunnel. Darktrace detected connections to several hostnames including: region2.v2.argotunnel[.]com; h2.cftunnel[.]com; region1.v2.argotunnel[.]com. This tunnelling activity continued until January of 2026, when encryption occurred. Cloudflare tunnels are known to be abused by attackers as they enable the use of temporary infrastructure to scale operations, allowing rapid deployment and teardown. Furthermore, leveraging of Cloudflare’s infrastructure to create these rate-limited tunnels (used to relay traffic from an attacker-controlled server to a local machine) makes such malicious activity harder to detect by both defenders and traditional security measures, particularly those that rely on static blocklists [6].
Further lateral movement was carried out using common remote management tools such as Windows Remote Management (WinRM) RDP, allowing the World Leaks threat actors to access local devices within the victim organization’s network.
As this attack progressed, Darktrace detected multiple files being written over SMB. These files included Windows\Temp\chromeremotedesktophost.msi, which was written from the patient-zero device to another internal device as part of lateral movement efforts. Following this transfer, and prior to subsequent data exfiltration activity, a network server was observed connecting to the hostname remotedesktop-pa[.]googleapis[.]com, an API endpoint required for Chrome Remote Desktop, indicating that Chrome RDP was used by the threat actor in this stage of the attack.
Other files written over SMB included the script programdata\syc\OpenSSHUtils.psm1 (which can be used legitimately to configure OpenSSH) and the executable programdata\syc\ssh‑sk‑helper.exe (a legitimate OpenSSH component used to support security keys). These files were written from the suspected patient‑zero device to an internal domain controller using the ‘administrator’ credential.
Thereafter, SSH connections to external IP address 51.15.109[.]222 were observed, providing another channel between the malicious actors and victim machines. Darktrace recognized that the use of SSH by the devices seen connecting to this IP address was highly anomalous, indicating that this suspicious activity formed part of the attack.
Writes of the script programdata\syc\OpenSSHUtils.psm1 were also observed into January, highlighting the continuation of the attack that had begun three months earlier.
On December 19 and 20, Darktrace detected a DNS server within the customer’s network making anomalous outgoing connections to an external IP address not previously seen in the environment: 193.161.193[.]99. This IP address has been reported by open-source-intelligence (OSINT) as being associated with C2 infrastructure, having been linked to several remote access trojans (RATs) and botnets in the past.
This activity a shift towards the infrastructure-as-a-service (IaaS) model, underscoring the growing trend around As-a-Service Cybercrime models and the increasing the industrialization of botnets. The presence of extensive digital botnets, often leased to other criminal organizations, means the group gaining initial access is not necessarily the same group conducting ransomware deployment or data theft; botnets now act as shared underlying infrastructure enabling multiple forms of cybercriminal activity [7].
Furthermore, connections to this IP address (193.161.193[.]99) were made over port 1194, which is associated with OpenVPN, suggesting that World Leaks may have leveraged it to obfuscate C2 communication with attacker-controlled infrastructure.
Figure 1: Darktrace’s detection of the IP address 193.161.193[.]99, noting that it was first seen within the customer’s network on December 19, 2025.
Data exfiltration
In November, Darktrace detected the threat actors carrying out one of their Attack on Objective tactics: data exfiltration. Multiple local devices within the compromised network began transferring data to Backblaze and MEGA domains, both of which provide cloud storage services; 80+GB of data was transferred to MEGA in late December 2025. Endpoints associated with this activity included: backblazeb2[.]com and gfs302n520[.]userstorage[.]mega[.]co[.]nz, as well as related user agents such as AS40401 BACKBLAZE) and MegaClient/10.3.0/64.
Notably, Darktrace researchers identified two known World Leaks TTPs in this attack: the use of MEGA, a known tool abused by the group, and Rclone, a command-line tool used to manage files on cloud storage, which was observed in the user agent of the MEGA data-transfer connections: rclone/v1.69.0 [4].
Figure 2: Cyber AI Analyst Incident highlighting data upload activity to backblaze[.]com endpoints.\
Ransomware deployment & encryption
The encryption stage of this attack was confirmed by the presence of a ransom note found on the network in a file with a seemingly randomized nine-character string preceding README.txt, attributing the incident to World Leaks, along with an extension with the same nine characters appended to encrypted files. Darktrace also observed SMB writes of files named world.exe and task.bat, with the compromised ‘localadmin’ credential used during the SMB logins. It is likely that these files served as the vector for the ransomware payload.
Figure 3: Packet Capture (PCAP) of the ransom note claiming that the attack was carried out by World Leaks.
Conclusion
Though traditional ransomware relies on encryption, recent trends show that cyber threat actors no longer need to rely on noisy encryption tools and can eliminate much of the risk and technical complexity associated with encrypting systems. This is the model reportedly preferred by World Leaks after their rebrand from Hunters International.
In addition to reducing noise around these attacks, extortion‑only operations may be favored by threat actors over encryption‑focused ones for several reasons, including the fact that traditional security tools may struggle to detect data theft compared to encryption, that attackers leave less evidence behind when encryption is avoided, and that the long‑term impacts of stolen data on organizations can be greater than the loss of systems caused by encryption processes, which can be restored [8]. This is supported by analysis of data leak sites suggesting that almost 1,500 incidents in 2025 relied on data theft alone. Attackers can simply steal victim data and attempt to extort a ransom by threatening to publish it, without needing to deploy ransomware at all [9]. Furthermore, although World Leaks aims to function as an affiliate‑based EaaS operation, security teams should remain aware that their affiliates may have different criminal objectives.
Contrary to reports that World Leaks’ typical attack style has an extortion‑only objective, Darktrace detected an incident in which a World Leaks attack did end with the encryption of customer data. This highlights the need for adaptive defenses and reinforces the importance of network defenders staying proactive in the face of attacks, particularly as they may progress in ways that are unexpected compared to previous trends associated with a given threat actor.
Credit to Tiana Kelly (Senior Cyber Analyst and Analyst Manager) and Emily Megan Lim (Senior Cyber Analyst)
Edited by Ryan Traill (Content Manager)
Appendices
IoCs
world.exe – Executable File – Possible Ransomware Payload
task.bat – Script File – Possible Ransomware Payload
NetSupport RAT: How Legitimate Tools Can Be as Damaging as Malware
What is NetSupport Manager?
NetSupport Manager is a legitimate IT tool used by system administrators for remote support, monitoring, and management. In use since 1989, NetSupport Manager enables users to remotely access and navigate systems across different platforms and operating systems [1].
What is NetSupport RAT?
Although NetSupport Manager is a legitimate tool that can be used by IT and security professionals, there has been a rising number of cases in which it is abused to gain unauthorized access to victim systems. This misuse has become so prevalent that, in recent years, security researchers have begun referring to NetSupport as a Remote Access Trojan (RAT), a term typically used for malware that enables a threat actor to remotely access or control an infected device [2][3][4].
NetSupport RAT activity summary
The initial stages of NetSupport RAT infection may vary depending on the source of the initial compromise. Using tactics such as the social engineering tactic ClickFix, threat actors attempt to trick users into inadvertently executing malicious PowerShell commands under the guise of resolving a non-existent issue or completing a fake CAPTCHA verification [5]. Other attack vectors such as phishing emails, fake browser updates, malicious websites, search engine optimization (SEO) poisoning, malvertising and drive-by downloads are also employed to direct users to fraudulent pages and fake reCAPTCHA verification checks, ultimately inducing them to execute malicious PowerShell commands [5][6][7]. This leads to the successful installation of NetSupport Manager on the compromised device, which is often placed in non-standard directories such as AppData, ProgramData, or Downloads [3][8].
Once installed, the adversary is able to gain remote access to the affected machine, monitor user activity, exfiltrate data, communicate with the command-and-control (C2) server, and maintain persistence [5]. External research has also highlighted that post-exploitation of NetSupport RAT has involved the additional download of malicious payloads [2][5].
Figure 1: Attack flow diagram highlighting key events across each phase of the attack phase [2][5].
Darktrace coverage
In November of 2025, suspicious behavior indicative of the malicious abuse of NetSupport Manager was observed on multiple customers across Europe, the Middle East, and Africa (EMEA) and the Americas (AMS).
While open-source intelligence (OSINT) has reported that, in a recent campaign, a threat actor impersonated government entities to trick users in organizations in the InformationTechnology, Government and FinancialServices sectors in CentralAsia into downloading NetSupport Manager [8], approximately a third of Darktrace’s affected customers in November were based in the US while the rest were based in EMEA. This contrast underscores how widely NetSupport Manager is leveraged by threat actors and highlights its accessibility as an initial access tool.
The Darktrace customers affected were in sectors including Information andCommunication, Manufacturing and Arts, entertainment and recreation.
The ClickFix social engineering tactic typically used to distribute the NetSupport RAT is known to target multiple industries, including Technology, Manufacturing and Energy sectors [9]. It also reflects activity observed in the campaign targeting Central Asia, where the Information Technology sector was among those affected [8].
The prevalence of affected Education customers highlights NetSupport’s marketing focus on the Education sector [10]. This suggests that threat actors are also aware of this marketing strategy and have exploited the trust it creates to deploy NetSupport Manager and gain access to their targets’ systems. While the execution of the PowerShell commands that led to the installation of NetSupport Manager falls outside of Darktrace's purview in cases identified, Darktrace was still able to identify a pattern of devices making connections to multiple rare external domains and IP addresses associated with the NetSupport RAT, using a wide range of ports over the HTTP protocol. A full list of associated domains and IP addresses is provided in the Appendices of this blog.
Although OSINT identifies multiple malicious domains and IP addresses as used as C2 servers, signature-based detections of NetSupport RAT indicators of compromise (IoCs) may miss broader activity, as new malicious websites linked to the RAT continue to appear.
Darktrace’s anomaly‑based approach allows it to establish a normal ‘pattern of life’ for each device on a network and identify when behavior deviates from this baseline, enabling the detection of unusual activity even when it does not match known IoCs or tactics, techniques and procedures (TTPs).
In one customer environment in late 2025, Darktrace / NETWORK detected a device initiating new connections to the rare external endpoint, thetavaluemetrics[.]com (74.91.125[.]57), along with the use of a previously unseen user agent, which it recognized as highly unusual for the network.
Figure 2: Darktrace’s detection of HTTP POST requests to a suspicious URI and new user agent usage.
Darktrace identified that user agent present in connections to this endpoint was the ‘NetSupport Manager/1.3’, initially suggesting legitimate NetSupport Manager activity. Subsequent investigation, however, revealed that the endpoint was in fact a malicious NetSupportRAT C2 endpoint [12]. Shortly after, Darktrace detected the same device performing HTTP POST requests to the URI fakeurl[.]htm. This pattern of activity is consistent with OSINT reporting that details communication between compromised devices and NetSupport Connectivity Gateways functioning as C2 servers [11].
Conclusion
As seen not only with NetSupport Manager but with any legitimate or open‑source software used by IT and security professionals, the legitimacy of a tool does not prevent it from being abused by threat actors. Open‑source software, especially tools with free or trial versions such as NetSupport Manager, remains readily accessible for malicious use, including network compromise. In an age where remote work is still prevalent, validating any anomalous use of software and remote management tools is essential to reducing opportunities for unauthorized access.
Darktrace’s anomaly‑based detection enables security teams to identify malicious use of legitimate tools, even when clear signatures or indicators of compromise are absent, helping to prevent further impact on a network.
Credit to George Kim (Analyst Consulting Lead – AMS), Anna Gilbertson (Senior Cyber Analyst)
Edited by Ryan Traill (Analyst Content Lead)
Appendices
Darktrace Model Alerts
· Compromise / Suspicious HTTP and Anomalous Activity
· Compromise / New User Agent and POST
· Device / New User Agent
· Anomalous Connection / New User Agent to IP Without Hostname
· Anomalous Connection / Posting HTTP to IP Without Hostname
· Anomalous Connection / Multiple Failed Connections to Rare Endpoint
· Anomalous Connection / Application Protocol on Uncommon Port
· Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
· Compromise / Beaconing Activity To External Rare
· Compromise / HTTP Beaconing to Rare Destination
· Compromise / Agent Beacon (Medium Period)
· Compromise / Agent Beacon (Long Period)
· Compromise / Quick and Regular Windows HTTP Beaconing
· Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
![Darktrace’s detection of the IP address 193.161.193[.]99, noting that it was first seen within the customer’s network on December 19, 2025.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69b830390b1bcda7a148f5f9_Screenshot%202026-03-16%20at%209.30.46%E2%80%AFAM.png)
![Cyber AI Analyst Incident highlighting data upload activity to backblaze[.]com endpoints.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69b830939a937990f1f80ad1_Screenshot%202026-03-16%20at%209.31.59%E2%80%AFAM.png)
