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
Brianna Leddy
Director of Analyst Operations
Share
06
Sep 2021
The deployment of ransomware is the endgame of a cyber-attack. A threat actor must have accomplished several previous steps – including lateral movement and privilege escalation – to reach this final position. The ability to detect and counter the early moves is therefore just as important as detecting the encryption itself.
Attackers are using diverse strategies – such as ‘Living off the Land’ and carefully crafting their command and control (C2) – to blend in with normal network traffic and evade traditional security defenses. The analysis below examines the Tactics, Techniques and Procedures (TTPs) used by many ransomware actors by unpacking a compromise which occurred at a defense contractor in Canada.
Phases of a ransomware attack
Figure 1: Timeline of the attack.
The opening: Initial access to privileged account
The first indicator of compromise was a login on a server with an unusual credential, followed by unusual admin activity. The attacker may have gained access to the username and password in a number of ways, from credential stuffing to buying them on the Dark Web. As the attacker had privileged access from the get-go, there was no need for privilege escalation.
Lateral movement
Two days later, the attacker began to spread from the initial server. The compromised server began to send out unusual Windows Management Instrumentation (WMI) commands.
It began remotely controlling four other devices – authenticating on them with a single admin credential. One of the destinations was a domain controller (DC), another was a backup server.
By using WMI – a common admin tool – for lateral movement, the attacker opted to ‘live off the land’ rather than introduce a new lateral movement tool, aiming to remain unnoticed by the company’s security stack. The unusual use of WMI was picked up by Darktrace and the timings of the unusual WMI connections were pieced together by Cyber AI Analyst.
Models:
New or Uncommon WMI Activity
AI Analyst / Extensive Chain of Administrative Connections
Establish C2
The four devices then connected to the IP 185.250.151[.]172. Three of them, including the DC and backup server, established SSL beacons to the IP using the dynamic DNS domain goog1e.ezua[.]com.
The C2 endpoints had very little open-source intelligence (OSINT) available, but it seems that a Cobalt Strike-style script had used the endpoint in the past. This suggests complex tooling, as the attacker used dynamic SSL and spoofed Google to mask their beaconing.
Interestingly, through the entirety of the attack, only these three devices used SSL connections for beaconing, while later C2 occurred over unencrypted protocols. It appears these three critical devices were treated differently to the other infected devices on the network.
Models:
Immediate breach of Anomalous External Activity from Critical Network Device, then several model breaches involving beaconing and SSL to dynamic DNS. (Domain Controller DynDNS SSL or HTTP was particularly specific to this activity.)
The middle game: Internal reconnaissance and further lateral movement
The attack chain took the form of two cycles of lateral movement, followed by establishing C2 at the newly controlled destinations.
Figure 2: Observed chain of lateral movement and C2.
So, after establishing C2, the DC made WMI requests to 20 further IPs over an extended period. It also scanned 234 IPs via ICMP pings, presumably in an attempt to find more hosts.
Many of these were eventually found with ransom notes, in particular when the targeted devices were hypervisors. The ransomware was likely deployed with remote commands via WMI.
Models:
AI Analyst / Suspicious Chain of Administrative Connections (from the initial server to the DC to the hypervisor)
AI Analyst / Extensive Suspicious WMI Activity (from the DC)
Device / ICMP Address Scan, Scanning of Multiple Devices AI Analyst incident (from the DC)
Further C2
As the second stage of lateral movement stopped, a second stage of unencrypted C2 was seen from five new devices. Each started with GET requests to the IP seen in the SSL C2 (185.250.151[.]172), which used the spoofed hostname google[.]com.
Activity started on each device with HTTP requests for a URI ending in .png, before a more consistent beaconing to the URI /books/. Eventually, the devices made POST requests to the URI /ebooks/?k= (a unique identifier for each device). All this appears to be a way of concealing a C2 beacon in what looks like plausible traffic to Google.
In this way, by encrypting some C2 connections with SSL to a Dynamic DNS domain, while crafting other unencrypted HTTP to look like traffic to google[.]com, the attacker managed to operate undetected by the company’s antivirus tools.
Darktrace identified this anomalous activity and generated a large number of external connectivity model breaches.
Models:
Eight breaches of Compromise / HTTP Beaconing to New Endpoint from the affected devices
Accomplish mission: Checkmate
Finally, the attacker deployed ransomware. In the ransom note, they stated that sensitive information had been exfiltrated and would be leaked if the company did not pay.
However, this was a lie. Darktrace confirmed that no data had been exfiltrated, as the C2 communications had sent far too little data. Lying about data exfiltration in order to extort a ransom is a common tactic for attackers, and visibility is crucial to determine whether a threat actor is bluffing.
In addition, Antigena – Darktrace’s Autonomous Response technology – blocked an internal download from one of the servers compromised in the first round of lateral movement, because it was an unusual incoming data volume for the client device. This was most likely the attacker attempting to transfer data in preparation for the end goal, so the block may have prevented this data from being moved for exfiltration.
Figure 3: Antigena model breach.
Figure 4: Device is blocked from SMB communication with the compromised server three seconds later.
Models:
Unusual Incoming Data Volume
High Volume Server Data Transfer
Unfortunately, Antigena was not active on the majority of the devices involved in the incident. If in active mode, Antigena would have stopped the early stages of this activity, including the unusual administrative logins and beaconing. The customer is now working to fully configure Antigena, so they benefit from 24/7 Autonomous Response.
Cyber AI Analyst investigates
Darktrace’s AI spotted and reported on beaconing from several devices including the DC, which was the highest scoring device for unusual behavior at the time of the activity. It condensed this information into three incidents – ‘Possible SSL Command and Control’, ‘Extensive Suspicious Remote WMI Activity’, and ‘Scanning of Remote Devices’.
Crucially, Cyber AI Analyst not only summarized the admin activity from the DC but also linked it back to the first device through an unusual chain of administrative connections.
Figure 5: Cyber AI Analyst incident showing a suspicious chain of administrative connections linking the first device in the chain of connections to a hypervisor where a ransom note was found via the compromised DC, saving valuable time in the investigation. It also highlights the credential common to all of the lateral movement connections.
Finding lateral movement chains manually is a laborious process well suited to AI. In this case, it enabled the security team to quickly trace back to the device which was the likely source of the attack and find the common credential in the connections.
Play the game like a machine
To get the full picture of a ransomware attack, it is important to look beyond the final encryption to previous phases of the kill chain. In the attack above, the encryption itself did not generate network traffic, so detecting the intrusion at its early stages was vital.
Despite the attacker ‘Living off the Land’ and using WMI with a compromised admin credential, as well as spoofing the common hostname google[.]com for C2 and applying dynamic DNS for SSL connections, Darktrace was able to identify all the stages of the attack and immediately piece them together into a meaningful security narrative. This would have been almost impossible for a human analyst to achieve without labor-intensive checking of the timings of individual connections.
With ransomware infections becoming faster and more frequent, with the threat of offensive AI looming closer and the Dark Web marketplace thriving, with security teams drowning under false positives and no time left on the clock, AI is now an essential part of any security solution. The board is set, the time is ticking, the stakes are higher than ever. Your move.
Thanks to Darktrace analyst Daniel Gentle for his insights on the above threat find.
IoCs:
IoCComment185.250.151[.]172IP address used for both HTTP and SSL C2goog1e.ezua[.]comDynamic DNS Hostname used for SSL C2
Darktrace model detections:
AI Analyst models:
Extensive Suspicious WMI Activity
Suspicious Chain of Administrative Connections
Scanning of Multiple Devices
Possible SSL Command and Control
Meta model:
Device / Large Number of model breaches
External connectivity models:
Anonymous Server Activity / Domain Controller DynDNS SSL or HTTP
Compromise / Suspicious TLS Beaconing to Rare External
Compromise / Beaconing Activity To External Rare
Compromise / SSL to DynDNS
Anomalous Server Activity / External Activity from Critical Network Device
Compromise / Sustained SSL or HTTP Increase
Compromise / Suspicious Beaconing Behaviour
Compromise / HTTP Beaconing to New Endpoint
Internal activity models:
Device / New or Uncommon WMI Activity
User / New Admin Credentials on Client
Device / ICMP Address Scan
Anomalous Connection / Unusual Incoming Data Volume
Unusual Activity / High Volume Server Data Transfer
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.
Under Medusa’s Gaze: How Darktrace Uncovers RMM Abuse in Ransomware Campaigns
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Under Medusa’s Gaze: How Darktrace Uncovers RMM Abuse in Ransomware Campaigns
What is Medusa Ransomware in 2025?
In 2025, the Medusa Ransomware-as-a-Service (RaaS) emerged as one of the top 10 most active ransomware threat actors [1]. Its growing impact prompted a joint advisory from the US Cybersecurity and Infrastructure Security Agency (CISA) and the Federal Bureau of Investigation (FBI) [3]. As of January 2026, more than 500 organizations have fallen victim to Medusa ransomware [2].
Darktrace previously investigated Medusa in a 2024 blog, but the group’s rapid expansion and new intelligence released in late 2025 has lead Darktrace’s Threat Research team to investigate further. Recent findings include Microsoft’s research on Medusa actors exploiting a vulnerability in Fortra’s GoAnywhere MFT License Servlet (CVE-2025-10035)[4] and Zencec’s report on Medusa’s abuse of flaws in SimpleHelp’s remote support software (CVE-2024-57726, CVE-2024-57727, CVE-2024-57728) [5].
Reports vary on when Medusa first appeared in the wild. Some sources mention June 2021 as the earliest sightings, while others point to late 2022, when its developers transitioned to the RaaS model, as the true beginning of its operation [3][11].
Madusa Ransomware history and background
The group behind Medusa is known by several aliases, including Storm-1175 and Spearwing [4] [7]. Like its mythological namesake, Medusa has many “heads,” collaborating with initial access brokers (IABs) and, according to some evidence, affiliating with Big Game Hunting (BGH) groups such as Frozen Spider, as well as the cybercriminal group UNC7885 [3][6][13].
Use of Cyrillic in its scripts, activity on Russian-language cybercrime forums, slang unique to Russian criminal subcultures, and avoidance of targets in Commonwealth of Independent States (CIS) countries suggest that Medusa operates from Russia or an allied state [11][12].
Medusa ransomware should not be confused with other similarly named malware, such as the Medusa Android Banking Trojan, the Medusa Botnet/Medusa Stealer, or MedusaLocker ransomware. It is easily distinguishable from these variants because it appends the extension .MEDUSA to encrypted files and drops the ransom note !!!READ_ME_MEDUSA!!!.txt on compromised systems [8].
Who does Madusa Ransomware target?
The group appears to show little restraint, indiscriminately attacking organizations across all sectors, including healthcare, and is known to employ triple extortion tactics whereby sensitive data is encrypted, victims are threatened with data leaks, and additional pressure is applied through DDoS attacks or contacting the victim’s customers, rather than the more common double extortion model [13].
Madusa Ransomware TTPs
To attain initial access, Medusa actors typically purchase access to already compromised devices or accounts via IABs that employ phishing, credential stuffing, or brute-force attacks, and also target vulnerable or misconfigured Internet-facing systems.
Between December 2023 and November 2025, Darktrace observed multiple cases of file encryption related to Medusa ransomware across its customer base. When enabled, Darktrace’s Autonomous Response capability intervened early in the attack chain, blocking malicious activity before file encryption could begin.
Some of the affected were based in Europe, the Middle East and Africa (EMEA), others in the Americas (AMS), and the remainder in the Asia-Pacific and Japan region. The most impacted sectors were financial services and the automotive industry, followed by healthcare, and finally organizations in arts, entertainment and recreation, ICT, and manufacturing.
Remote Monitoring and Management (RMM) tool abuse
In most customer environments where Medusa file encryption attempts were observed, and in one case where the compromise was contained before encryption, unusual external HTTP connections associated with JWrapper were also detected. JWrapper is a legitimate tool designed to simplify the packaging, distribution, and management of Java applications, enabling the creation of executables that run across different operating systems. Many of the destination IP addresses involved in this activity were linked to SimpleHelp servers or associated with Atera.
Medusa actors appear to favor RMM tools such as SimpleHelp. Unpatched or misconfigured SimpleHelp RMM servers can serve as an initial access vector to the victims’ infrastructure. After gaining access to SimpleHelp management servers, the threat actors edit server configuration files to redirect existing SimpleHelp RMM agents to communicate with unauthorized servers under their control.
The SimpleHelp tool is not only used for command-and-control (C2) and enabling persistence but is also observed during lateral movement within the network, downloading additional attack tools, data exfiltration, and even ransomware binary execution. Other legitimate remote access tools abused by Medusa in a similar manner to evade detection include Atera, AnyDesk, ScreenConnect, eHorus, N-able, PDQ Deploy/Inventory, Splashtop, TeamViewer, NinjaOne, Navicat, and MeshAgent [4][5][15][16][17].
Data exfiltration
Another correlation among Darktrace customers affected by Medusa was observed during the data exfiltration phase. In several environments, data was exfiltrated to the endpoints erp.ranasons[.]com or pruebas.pintacuario[.]mx (143.110.243[.]154, 144.217.181[.]205) over ports 443, 445, and 80. erp.ranasons[.]com was seemingly active between November 2024 and September 2025, while pruebas.pintacuario[.]mx was seen from November 2024 to March 2025. Evidence suggests that pruebas.pintacuario[.]mx previously hosted a SimpleHelp server [22][23].
Apart from RMM tools, Medusa is also known to use Rclone and Robocopy for data exfiltration [3][19]. During one Medusa compromise detected in mid-2024, the customer’s data was exfiltrated to external destinations associated with the Ngrok proxy service using an SSH-2.0-rclone client.
Medusa Compromise Leveraging SimpleHelp
In Q4 2025, Darktrace assisted a European company impacted by Medusa ransomware. The organization had partial Darktrace / NETWORK coverage and had configured Darktrace’s Autonomous Response capability to require manual confirmation for all actions. Despite these constraints, data received through the customer’s security integration with CrowdStrike Falcon enabled Darktrace analysts to reconstruct the attack chain, although the initial access vector remains unclear due to limited visibility.
In late September 2025, a device out of the scope of Darktrace's visibility began scanning the network and using RDP, NTLM/SMB, DCE_RPC, and PowerShell for lateral movement.
CrowdStrike “Defense Evasion: Disable or Modify Tools” alerts related to a suspicious driver (c:\windows\[0-9a-b]{4}.exe) and a PDQ Deploy executable (share=\\<device_hostname>\ADMIN$ file=AdminArsenal\PDQDeployRunner\service-1\exec\[0-9a-b]{4}.exe) suggest that the attackers used the Bring Your Own Vulnerable Driver (BYOVD) technique to terminate antivirus processes on network devices, leveraging tools such as KillAV or AbyssWorker along with the PDQ Software Deployment solution [19][26].
A few hours later, Darktrace observed the same device that had scanned the network writing Temp\[a-z]{2}.exe over SMB to another device on the same subnet. According to data from the CrowdStrike alert, this executable was linked to an RMM application located at C:\Users\<compromised_user>\Documents\[a-z]{2}.exe. The same compromised user account later triggered a CrowdStrike “Command and Control: Remote Access Tools” alert when accessing C:\ProgramData\JWrapper-Remote Access\JWrapper-Remote Access Bundle-[0-9]{11}\JWrapperTemp-[0-9]{10}-[0-9]{1}-app\bin\windowslauncher.exe [27].
Figure 1: An executable file associated with the SimpleHelp RMM tool being written to other devices using the SMB protocol, as detected by Darktrace.
Soon after, the destination device and multiple other network devices began establishing connections to 31.220.45[.]120 and 213.183.63[.]41, both of which hosted malicious SimpleHelp RMM servers. These C2 connections continued for more than 20 days after the initial compromise.
CrowdStrike integration alerts for the execution of robocopy . "c:\windows\\" /COPY:DT /E /XX /R:0 /W:0 /NP /XF RunFileCopy.cmd /IS /IT commands on several Windows servers, suggested that this utility was likely used to stage files in preparation for data exfiltration [19].
Around two hours later, Darktrace detected another device connecting to the attacker’s SimpleHelp RMM servers. This internal server had ‘doc’ in its hostname, indicating it was likely a file server. It was observed downloading documents from another internal server over SMB and uploading approximately 70 GiB of data to erp.ranasons[.]com (143.110.243[.]154:443).
Figure 2: Data uploaded to erp.ranasons[.]com and the number of model alerts from the exfiltrating device, represented by yellow and orange dots.
Darktrace’s Cyber AI Analyst autonomously investigated the unusual connectivity, correlating the separate C2 and data exfiltration events into a single incident, providing greater visibility into the ongoing attack.
Figure 3: Cyber AI Analyst identified a file server making C2 connections to an attacker-controlled SimpleHelp server (213.183.63[.]41) and exfiltrating data to erp.ranasons[.]com.
Figure 4: The same file server that connected to 213.183.63[.]41 and exfiltrated data to erp.ranasons[.]com was also observed attempting to connect to an IP address associated with Moscow, Russia (193.37.69[.]154:7070).
One of the devices connecting to the attacker's SimpleHelp RMM servers was also observed downloading 35 MiB from [0-9]{4}.filemail[.]com. Filemail, a legitimate file-sharing service, has reportedly been abused by Medusa actors to deliver additional malicious payloads [11].
Figure 5: A device controlled remotely via SimpleHelp downloading additional tooling from the Filemail file-sharing service.
Finally, integration alerts related to the ransomware binary, such as c:\windows\system32\gaze.exe and <device_hostname>\ADMIN$ file=AdminArsenal\PDQDeployRunner\service-1\exec\gaze.exe, along with “!!!READ_ME_MEDUSA!!!.txt” ransom notes were observed on network devices. This indicates that file encryption in this case was most likely carried out directly on the victim hosts rather than via the SMB protocol [3].
Conclusion
Threat actors, including nation-state actors and ransomware groups like Medusa, have long abused legitimate commercial RMM tools, typically used by system administrators for remote monitoring, software deployment, and device configuration, instead of relying on remote access trojans (RATs).
Attackers employ existing authorized RMM tools or install new remote administration software to enable persistence, lateral movement, data exfiltration, and ingress tool transfer. By mimicking legitimate administrative behavior, RMM abuse enables attackers to evade detection, as security software often implicitly trusts these tools, allowing attackers to bypass traditional security controls [28][29][30].
To mitigate such risks, organizations should promptly patch publicly exposed RMM servers and adopt anomaly-based detection solutions, like Darktrace / NETWORK, which can distinguish legitimate administrative activity from malicious behavior, applying rapid response measures through its Autonomous Response capability to stop attacks in their tracks.
Darktrace delivers comprehensive network visibility and Autonomous Response capabilities, enabling real-time detection of anomalous activity and rapid mitigation, even if an organization fall under Medusa’s gaze.
Credit to Signe Zaharka (Principal Cyber Analyst) and Emma Foulger (Global Threat Research Operations Lead
Edited by Ryan Traill (Analyst Content Lead)
Appendices
List of Indicators of Compromise (IoCs)
IoC - Type - Description + Confidence + Time Observed
185.108.129[.]62 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - March 7, 2023
185.126.238[.]119 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - November 26-27, 2024
213.183.63[.]41 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - November 28, 2024 - Sep 30, 2025
213.183.63[.]42 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - July 4 -9 , 2024
31.220.45[.]120 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - September 12 - Oct 20 , 2025
91.92.246[.]110 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - May 24, 2024
45.9.149[.]112:15330 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - June 21, 2024
89.36.161[.]12 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - June 26-28, 2024
193.37.69[.]154:7070 IP address Suspicious RU IP seen on a device being controlled via SimpleHelp and exfiltrating data to a Medusa related endpoint - September 30 - October 20, 2025
erp.ranasons[.]com·143.110.243[.]154 Hostname Data exfiltration destination - November 27, 2024 - September 30, 2025
pruebas.pintacuario[.]mx·144.217.181[.]205 - Hostname Data exfiltration destination - November 27, 2024 - March 26, 2025
lirdel[.]com · 44.235.83[.]125/a.msi (1b9869a2e862f1e6a59f5d88398463d3962abe51e19a59) File & hash Atera related file downloaded with PowerShell - June 20, 2024
wizarr.manate[.]ch/108.215.180[.]161:8585/$/1dIL5 File Suspicious file observed on one of the devices exhibiting unusual activity during a Medusa compromise - February 28, 2024
!!!READ_ME_MEDUSA!!!.txt" File - Ransom note
*.MEDUSA - File extension File extension added to encrypted files
gaze.exe – File - Ransomware binary
Darktrace Model Coverage
Darktrace / NETWORK model detections triggered during connections to attacker controlled SimpleHelp servers:
Anomalous Connection/Anomalous SSL without SNI to New External
Anomalous Connection/Multiple Connections to New External UDP Port
Anomalous Connection/New User Agent to IP Without Hostname
How a leading bank is prioritizing risk management to power a resilient future
As one of the region’s most established financial institutions, this bank sits at the heart of its community’s economic life – powering everything from daily transactions to business growth and long-term wealth planning. Its blend of physical branches and advanced digital services gives customers the convenience they expect and the personal trust they rely on. But as the financial world becomes more interconnected and adversaries more sophisticated, safeguarding that trust requires more than traditional cybersecurity. It demands a resilient, forward-leaning approach that keeps pace with rising threats and tightening regulatory standards.
A complex risk landscape demands a new approach
The bank faced a challenge familiar across the financial sector: too many tools, not enough clarity. Vulnerability scans, pen tests, and risk reports all produced data, yet none worked together to show how exposures connected across systems or what they meant for day-to-day operations. Without a central platform to link and contextualize this data, teams struggled to see how individual findings translated into real exposure across the business.
Fragmented risk assessments: Cyber and operational risks were evaluated in silos, often duplicated across teams, and lacked the context needed to prioritize what truly mattered.
Limited executive visibility: Leadership struggled to gain a complete, real-time view of trends or progress, making risk ownership difficult to enforce.
Emerging compliance pressure: This gap also posed compliance challenges under the EU’s Digital Operational Resilience Act (DORA), which requires financial institutions to demonstrate continuous oversight, effective reporting, and the ability to withstand and recover from cyber and IT disruptions.
“The issue wasn’t the lack of data,” recalls the bank’s Chief Technology Officer. “The challenge was transforming that data into a unified, contextualized picture we could act on quickly and decisively.”
As the bank advanced its digital capabilities and embraced cloud services, its risk environment became more intricate. New pathways for exploitation emerged, human factors grew harder to quantify, and manual processes hindered timely decision-making. To maintain resilience, the security team sought a proactive, AI-powered platform that could consolidate exposures, deliver continuous insight, and ensure high-value risks were addressed before they escalated.
Choosing Darktrace to unlock proactive cyber resilience
To reclaim control over its fragmented risk landscape, the bank selected Darktrace / Proactive Exposure Management™ for cyber risk insight. The solution’s ability to consolidate scanner outputs, pen test results, CVE data, and operational context into one AI-powered view made it the clear choice. Darktrace delivered comprehensive visibility the team had long been missing.
By shifting from a reactive model to proactive security, the bank aimed to:
Improve resilience and compliance with DORA
Prioritize remediation efforts with greater accuracy
Eliminate duplicated work across teams
Provide leadership with a complete view of risk, updated continuously
Reduce the overall likelihood of attack or disruption
The CTO explains: “We needed a solution that didn’t just list vulnerabilities but showed us what mattered most for our business – how risks connected, how they could be exploited, and what actions would create the biggest reduction in exposure. Darktrace gave us that clarity.”
Targeting the risks that matter most
Darktrace / Proactive Exposure Management offered the bank a new level of visibility and control by continuously analyzing misconfigurations, critical attack paths, human communication patterns, and high-value assets. Its AI-driven risk scoring allowed the team to understand which vulnerabilities had meaningful business impact, not just which were technically severe.
Unifying exposure across architectures
Darktrace aggregates and contextualizes data from across the bank’s security stack, eliminating the need to manually compile or correlate findings. What once required hours of cross-team coordination now appears in a single, continuously updated dashboard.
Revealing an adversarial view of risk
The solution maps multi-stage, complex attack paths across network, cloud, identity systems, email environments, and endpoints – highlighting risks that traditional CVE lists overlook.
Identifying misconfigurations and controlling gaps
Using Self-Learning AI, Darktrace / Proactive Exposure Management spots misconfigurations and prioritizes them based on MITRE adversary techniques, business context, and the bank’s unique digital environment.
Enhancing red-team and pen test effectiveness
By directing testers to the highest-value targets, Darktrace removes guesswork and validates whether defenses hold up against realistic adversarial behavior.
Supporting DORA compliance
From continuous monitoring to executive-ready reporting, the solution provides the transparency and accountability the bank needs to demonstrate operational resilience frameworks.
Proactive security delivers tangible outcomes
Since deploying Darktrace / Proactive Exposure Management, the bank has significantly strengthened its cybersecurity posture while improving operational efficiency.
Security teams are now saving more than four hours per week previously spent aggregating and analyzing risk data. With a unified view of their exposure, they can focus directly on remediation instead of manually correlating multiple reports.
Because risks are now prioritized based on business impact and real-time operational context, they no longer waste time on low-value tasks. Instead, critical issues are identified and resolved sooner, reducing potential windows for exploitation and strengthening the bank’s ongoing resilience against both known and emerging threats.
“Our goal was to move from reactive to proactive security,” the CTO says. “Darktrace didn’t just help us achieve that, it accelerated our roadmap. We now understand our environment with a level of clarity we simply didn’t have before.”
Leadership clarity and stronger governance
Executives and board stakeholders now receive clear, organization-wide visibility into the bank’s risk posture, supported by consistent reporting that highlights trends, progress, and areas requiring attention. This transparency has strengthened confidence in the bank’s cyber resilience and enabled leadership to take true ownership of risk across the institution.
Beyond improved visibility, the bank has also deepened its overall governance maturity. Continuous monitoring and structured oversight allow leaders to make faster, more informed decisions that strategically align security efforts with business priorities. With a more predictable understanding of exposure and risk movement over time, the organization can maintain operational continuity, demonstrate accountability, and adapt more effectively as regulatory expectations evolve.
Trading stress for control
With Darktrace, leaders now have the clarity and confidence they need to report to executives and regulators with accuracy. The ability to see organization-wide risk in context provides assurance that the right issues are being addressed at the right time. That clarity is also empowering security analysts who no longer shoulder the anxiety of wondering which risks matter most or whether something critical has slipped through the cracks. Instead, they’re working with focus and intention, redirecting hours of manual effort into strategic initiatives that strengthen the bank’s overall resilience.
Prioritizing risk to power a resilient future
For this leading financial institution, Darktrace / Proactive Exposure Management has become the foundation for a more unified, data-driven, and resilient cybersecurity program. With clearer, business-relevant priorities, stronger oversight, and measurable efficiency gains, the bank has strengthened its resilience and met demanding regulatory expectations without adding operational strain.
Most importantly, it shifted the bank’s security posture from a reactive stance to a proactive, continuous program. Giving teams the confidence and intelligence to anticipate threats and safeguard the people and services that depend on them.
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![Data uploaded to erp.ranasons[.]com and the number of model alerts from the exfiltrating device, represented by yellow and orange dots.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69601f43842f8016c3898afd_Screenshot%202026-01-08%20at%201.18.52%E2%80%AFPM.png)
![Cyber AI Analyst identified a file server making C2 connections to an attacker-controlled SimpleHelp server (213.183.63[.]41) and exfiltrating data to erp.ranasons[.]com.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69601f524d01b4d269313c38_Screenshot%202026-01-08%20at%201.19.06%E2%80%AFPM.png)
![The same file server that connected to 213.183.63[.]41 and exfiltrated data to erp.ranasons[.]com was also observed attempting to connect to an IP address associated with Moscow, Russia (193.37.69[.]154:7070).](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69601f6a598a3380572e284e_Screenshot%202026-01-08%20at%201.19.32%E2%80%AFPM.png)
