Employee-Conscious Email Security Solutions in the Workforce
Email threats commonly affect organizations. Read Darktrace's expert insights on how to safeguard your business by educating employees about email security.
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
Dan Fein
VP, Product
Written by
Carlos Gray
Senior Product Marketing Manager, Email
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10
Apr 2023
When considering email security, IT teams have historically had to choose between excluding employees entirely, or including them but giving them too much power and implementing unenforceable, trust-based policies that try to make up for it.
However, just because email security should not rely on employees, this does not mean they should be excluded entirely. Employees are the ones interacting with emails daily, and their experiences and behaviors can provide valuable security insights and even influence productivity.
AI technology supports employee engagement in this non-intrusive, nuanced way to not only maintain email security, but also enhance it.
Finding a Balance of Employee Involvement in Security Strategies
Historically, security solutions offered ‘all or nothing’ approaches to employee engagement. On one hand, when employees are involved, they are unreliable. Employees cannot all be experts in security on top of their actual job responsibilities, and mistakes are bound to happen in fast-paced environments.
Although there have been attempts to raise security awareness, they often have shortcomings, as training emails lack context and realism, leaving employees with poor understandings that often lead to reporting emails that are actually safe. Having users constantly triaging their inboxes and reporting safe emails wastes time that takes away from their own productivity as well as the productivity of the security team.
Other historic forms of employee involvement also put security at risk. For example, users could create blanket rules through feedback, which could lead to common problems like safe-listing every email that comes from the gmail.com domain. Other times, employees could choose for themselves to release emails without context or limitations, introducing major risks to the organization. While these types of actions include employees to participate in security, they do so at the cost of security.
Even lower stakes employee involvement can prove ineffective. For example, excessive warnings when sending emails to external contacts can lead to banner fatigue. When employees see the same warning message or alert at the top of every message, it’s human nature that they soon become accustomed and ultimately immune to it.
On the other hand, when employees are fully excluded from security, an opportunity is missed to fine-tune security according to the actual users and to gain feedback on how well the email security solution is working.
So, both options of historically conventional email security, to include or exclude employees, prove incapable of leveraging employees effectively. The best email security practice strikes a balance between these two extremes, allowing more nuanced interactions that maintain security without interrupting daily business operations. This can be achieved with AI that tailors the interactions specifically to each employee to add to security instead of detracting from it.
Reducing False Reports While Improving Security Awareness Training
Humans and AI-powered email security can simultaneously level up by working together. AI can inform employees and employees can inform AI in an employee-AI feedback loop.
By understanding ‘normal’ behavior for every email user, AI can identify unusual, risky components of an email and take precise action based on the nature of the email to neutralize them, such as rewriting links, flattening attachments, and moving emails to junk. AI can go one step further and explain in non-technical language why it has taken a specific action, which educates users. In contrast to point-in-time simulated phishing email campaigns, this means AI can share its analysis in context and in real time at the moment a user is questioning an email.
The employee-AI feedback loop educates employees so that they can serve as additional enrichment data. It determines the appropriate levels to inform and teach users, while not relying on them for threat detection.
In the other direction, the AI learns from users’ activity in the inbox and gradually factors this into its decision-making. This is not a ‘one size fits all’ mechanism – one employee marking an email as safe will never result in blanket approval across the business – but over time, patterns can be observed and autonomous decision-making enhanced.
Figure 1: The employee-AI feedback loop increases employee understanding without putting security at risk.
The employee-AI feedback loop draws out the maximum potential benefits of employee involvement in email security. Other email security solutions only consider the security team, enhancing its workflow but never considering the employees that report suspicious emails. Employees who try to do the right thing but blindly report emails never learn or improve and end up wasting their own time. By considering employees and improving security awareness training, the employee-AI feedback loop can level up users. They learn from the AI explanations how to identify malicious components, and so then report fewer emails but with greater accuracy.
While AI programs have classically acted like black boxes, Darktrace trains its AI on the best data, the organization’s actual employees, and invites both the security team and employees to see the reasoning behind its conclusions. Over time, employees will trust themselves more as they better learn how to discern unsafe emails.
Leveraging AI to Generate Productivity Gains
Uniquely, AI-powered email security can have effects outside of security-related areas. It can save time by managing non-productive email. As the AI constantly learns employee behavior in the inbox, it becomes extremely effective at detecting spam and graymail – emails that aren't necessarily malicious, but clutter inboxes and hamper productivity. It does this on a per-user basis, specific to how each employee treats spam, graymail, and newsletters. The AI learns to detect this clutter and eventually learns which to pull from the inbox, saving time for the employees. This highlights how security solutions can go even further than merely protecting the email environment with a light touch, to the point where AI can promote productivity gains by automating tasks like inbox sorting.
Preventing Email Mishaps: How to Deal with Human Error
Improved user understanding and decision making cannot stop natural human error. Employees are bound to make mistakes and can easily send emails to the wrong people, especially when Outlook auto-fills the wrong recipient. This can have effects ranging anywhere from embarrassing to critical, with major implications on compliance, customer trust, confidential intellectual property, and data loss.
However, AI can help reduce instances of accidentally sending emails to the wrong people. When a user goes to send an email in Outlook, the AI will analyze the recipients. It considers the contextual relationship between the sender and recipients, the relationships the recipients have with each other, how similar each recipient’s name and history is to other known contacts, and the names of attached files.
If the AI determines that the email is outside of a user’s typical behavior, it may alert the user. Security teams can customize what the AI does next: it can block the email, block the email but allow the user to override it, or do nothing but invite the user to think twice. Since the AI analyzes each email, these alerts are more effective than consistent, blanket alerts warning about external recipients, which often go ignored. With this targeted approach, the AI prevents data leakage and reduces cyber risk.
Since the AI is always on and continuously learning, it can adapt autonomously to employee changes. If the role of an employee evolves, the AI will learn the new normal, including common behaviors, recipients, attached file names, and more. This allows the AI to continue effectively flagging potential instances of human error, without needing manual rule changes or disrupting the employee’s workflow.
Email Security Informed by Employee Experience
As the practical users of email, employees should be considered when designing email security. This employee-conscious lens to security can strengthen defenses, improve productivity, and prevent data loss.
In these ways, email security can benefit both employees and security teams. Employees can become another layer of defense with improved security awareness training that cuts down on false reports of safe emails. This insight into employee email behavior can also enhance employee productivity by learning and sorting graymail. Finally, viewing security in relation to employees can help security teams deploy tools that reduce data loss by flagging misdirected emails. With these capabilities, Darktrace/Email™ enables security teams to optimize the balance of employee involvement in email security.
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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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)
