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May 28, 2025

PumaBot: Novel Botnet Targeting IoT Surveillance Devices

Darktrace investigated “PumaBot,” a Go-based Linux botnet targeting IoT devices. It avoids internet-wide scanning, instead using a C2 server to get targets and brute-force SSH credentials. Once inside, it executes remote commands and ensures persistence.
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
password login screen on computerDefault blog image
28
May 2025

Introduction: PumaBot attacking IoT devices

Darktrace researchers have identified a custom Go-based Linux botnet named “PumaBot” targeting embedded Linux Internet of Things (IoT) devices. Rather than scanning the Internet, the malware retrieves a list of targets from a command-and-control (C2) server and attempts to brute-force SSH credentials. Upon gaining access, it receives remote commands and establishes persistence using system service files. This blog post provides a breakdown of its key functionalities, and explores binaries related to the campaign.

Technical Analysis

Filename: jierui

md5: cab6f908f4dedcdaedcdd07fdc0a8e38

The Go-based botnet gains initial access through brute-forcing SSH credentials across a list of harvested IP addresses. Once it identifies a valid credential pair, it logs in, deploys itself, and begins its replication process.

Overview of Jierui functions
Figure 1: Overview of Jierui functions.

The domain associated with the C2 server did not resolve to an IP address at the time of analysis. The following details are a result of static analysis of the malware.

The malware begins by retrieving a list of IP addresses of likely devices with open SSH ports from the C2 server (ssh.ddos-cc[.]org) via the getIPs() function. It then performs brute-force login attempts on port 22 using credential pairs also obtained from the C2 through the readLinesFromURL(), brute(), and trySSHLogin() functions.

Within trySSHLogin(), the malware performs several environment fingerprinting checks. These are used to avoid honeypots and unsuitable execution environments, such as restricted shells. Notably, the malware checks for the presence of the string “Pumatronix”, a manufacturer of surveillance and traffic camera systems, suggesting potential IoT targeting or an effort to evade specific devices [1].

Fingerprinting of “Pumatronix”.
Figure 2: Fingerprinting of “Pumatronix”.

If the environment passes these checks, the malware executes uname -a to collect basic system information, including the OS name, kernel version, and architecture. This data, along with the victim's IP address, port, username, and password, is then reported back to the C2 in a JSON payload.

Of note, the bot uses X-API-KEY: jieruidashabi, within a custom header when it communicates with the C2 server over HTTP.

The malware writes itself to /lib/redis, attempting to disguise itself as a legitimate Redis system file. It then creates a persistent systemd service in /etc/systemd/system, named either redis.service or mysqI.service (note the spelling of mysql with a capital I) depending on what has been hardcoded into the malware. This allows the malware to persist across reboots while appearing benign.

[Unit]
Description=redis Server Service

[Service]
Type=simple
Restart=always
RestartSec=1
User=root
ExecStart=/lib/redis e

[Install]
WantedBy=multi-user.target

In addition to gaining persistence with a systemd service, the malware also adds its own SSH keys into the users’ authorized_keys file. This ensures that access can be maintained, even if the service is removed.

A function named cleankill() contains an infinite loop that repeatedly attempts to execute the commands “xmrig” and “networkxm”. These are launched without full paths, relying on the system's PATH variable suggesting that the binaries may be downloaded or unpacked elsewhere on the system. The use of “time.Sleep” between attempts indicates this loop is designed to ensure persistence and possibly restart mining components if they are killed or missing.

During analysis of the botnet, Darktrace discovered related binaries that appear to be part of a wider campaign targeting Linux systems.

Filename: ddaemon
Md5: 48ee40c40fa320d5d5f8fc0359aa96f3

Ddaemon is a Go-based backdoor. The malware begins by parsing command line arguments and if conditions are met, enters a loop where it periodically verifies the MD5 hash of the binary. If the check fails or an update is available, it downloads a new version from a C2 server (db.17kp[.]xyz/getDdaemonMd5), verifies it and replaces the existing binary with a file of the same name and similar functionality (8b37d3a479d1921580981f325f13780c).

The malware uses main_downloadNetwork() to retrieve the binary “networkxm” into /usr/src/bao/networkxm. Additionally, the bash script “installx.sh” is also retrieved from the C2 and executed. The binary ensures persistence by writing a custom systemd service unit that auto starts on boot and executes ddaemon.

Filename: networkxm
Md5: be83729e943d8d0a35665f55358bdf88

The networkxm binary functions as an SSH brute-force tool, similar to the botnet. First it checks its own integrity using MD5 hashes and contacts the C2 server (db.17kp[.]xyz) to compare its hash with the latest version. If an update is found, it downloads and replaces itself.

Part of networkxm checking MD5 hash.
Figure 3: Part of networkxm checking MD5 hash.
MD5 hash
Figure 4: MD5 hash

After verifying its validity, it enters an infinite loop where it fetches a password list from the C2 (/getPassword), then attempts SSH connections across a list of target IPs from the /getIP endpoint. As with the other observed binaries, a systemd service is created if it doesn’t already exist for persistence in /etc/systemd/system/networkxm.service.

Bash script installx.sh.
Figure 5: Bash script installx.sh.

Installx.sh is a simple bash script used to retrieve the script “jc.sh” from 1.lusyn[.]xyz, set permissions, execute and clear bash history.

Figure 6: Snippet of bash script jc.sh.

The script jc.sh starts by detecting the operating system type Debian-based or Red Hat-based and determines the location of the pam_unix.so file. Linux Pluggable Authentication Modules (PAM) is a framework that allows for flexible and centralized user authentication on Linux systems. PAM allows system administrators to configure how users are authenticated for services like login, SSH, or sudo by plugging in various authentication modules.

Jc.sh then attempts to fetch the current version of PAM installed on the system and formats that version to construct a URL. Using either curl or wget, the script downloads a replacement pam_unix.so file from a remote server and replaces the existing one, after disabling file immutability and backing up the original.

The script also downloads and executes an additional binary named “1” from the same remote server. Security settings are modified including enabling PAM in the SSH configuration and disabling SELinux enforcement, before restarting the SSH service. Finally, the script removes itself from the system.

Filename: Pam_unix.so_v131
md5: 1bd6bcd480463b6137179bc703f49545

Based on the PAM version that is retrieved from the bash query, the new malicious PAM replaces the existing PAM file. In this instance, pam_unix.so_v131 was retrieved from the server based on version 1.3.1. The purpose of this binary is to act as a rootkit that steals credentials by intercepting successful logins. Login data can include all accounts authenticated by PAM, local and remote (SSH). The malware retrieves the logged in user, the password and verifies that the password is valid. The details are stored in a file “con.txt” in /usr/bin/.

Function storing logins to con.txt
Figure 7: Function storing logins to con.txt

Filename: 1

md5: cb4011921894195bcffcdf4edce97135

In addition to the malicious PAM file, a binary named “1” is also retrieved from the server http://dasfsdfsdfsdfasfgbczxxc[.]lusyn[.]xyz/jc/1. The binary “1” is used as a watcher for the malicious PAM file using inotify to monitor for “con.txt” being written or moved to /usr/bin/.

Following the daemonize() function, the binary is run daemonized ensuring it runs silently in the background. The function read_and_send_files() is called which reads the contents of “/usr/bin/con.txt”, queries the system IP with ifconfig.me, queries SSH ports and sends the data to the remote C2 (http://dasfsdfsdfsdfasfgbczxxc[.]lusyn[.]xyz/api/).

Command querying SSH ports.
Figure 8: Command querying SSH ports.

For persistence, a systemd service (my_daemon.service) is created to autostart the binary and ensure it restarts if the service has been terminated. Finally, con.txt is deleted, presumably to remove traces of the malware.

Conclusion

The botnet represents a persistent Go-based SSH threat that leverages automation, credential brute-forcing, and native Linux tools to gain and maintain control over compromised systems. By mimicking legitimate binaries (e.g., Redis), abusing systemd for persistence, and embedding fingerprinting logic to avoid detection in honeypots or restricted environments, it demonstrates an intent to evade defenses.

While it does not appear to propagate automatically like a traditional worm, it does maintain worm-like behavior by brute-forcing targets, suggesting a semi-automated botnet campaign focused on device compromise and long-term access.

[related-resource]

Recommendations

  1. Monitor for anomalous SSH login activity, especially failed login attempts across a wide IP range, which may indicate brute-force attempts.
  2. Audit systemd services regularly. Look for suspicious entries in /etc/systemd/system/ (e.g., misspelled or duplicate services like mysqI.service) and binaries placed in non-standard locations such as /lib/redis.
  3. Inspect authorized_keys files across user accounts for unknown SSH keys that may enable unauthorized access.
  4. Filter or alert on outbound HTTP requests with non-standard headers, such as X-API-KEY: jieruidashabi, which may indicate botnet C2 communication.
  5. Apply strict firewall rules to limit SSH exposure rather than exposing port 22 to the internet.

Appendices

References

1.     https://pumatronix.com/

Indicators of Compromise (IoCs)

Hashes

cab6f908f4dedcdaedcdd07fdc0a8e38 - jierui

a9412371dc9247aa50ab3a9425b3e8ba - bao

0e455e06315b9184d2e64dd220491f7e - networkxm

cb4011921894195bcffcdf4edce97135 - 1
48ee40c40fa320d5d5f8fc0359aa96f3 - ddaemon
1bd6bcd480463b6137179bc703f49545 - pam_unix.so_v131

RSA Key

ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQC0tH30Li6Gduh0Jq5A5dO5rkWTsQlFttoWzPFnGnuGmuF+fwIfYvQN1z+WymKQmX0ogZdy/CEkki3swrkq29K/xsyQQclNm8+xgI8BJdEgTVDHqcvDyJv5D97cU7Bg1OL5ZsGLBwPjTo9huPE8TAkxCwOGBvWIKUE3SLZW3ap4ciR9m4ueQc7EmijPHy5qds/Fls+XN8uZWuz1e7mzTs0Pv1x2CtjWMR/NF7lQhdi4ek4ZAzj9t/2aRvLuNFlH+BQx+1kw+xzf2q74oBlGEoWVZP55bBicQ8tbBKSN03CZ/QF+JU81Ifb9hy2irBxZOkyLN20oSmWaMJIpBIsh4Pe9 @root

Network

http://ssh[.]ddos-cc.org:55554

http://ssh[.]ddos-cc.org:55554/log_success

http://ssh[.]ddos-cc.org:55554/get_cmd

http://ssh[.]ddos-cc.org:55554/pwd.txt

https://dow[.]17kp.xyz/

https://input[.]17kp.xyz/

https://db[.]17kp[.]xyz/

http://1[.]lusyn[.]xyz

http://1[.]lusyn[.]xyz/jc/1

http://1[.]lusyn[.]xyz/jc/jc.sh

http://1[.]lusyn[.]xyz/jc/aa

http://1[.]lusyn[.]xyz/jc/cs

http://dasfsdfsdfsdfasfgbczxxc[.]lusyn[.]xyz/api

http://dasfsdfsdfsdfasfgbczxxc[.]lusyn[.]xyz/jc

Detection Rule

rule Linux_PumaBot

{

  meta:

      description = "Rule to match on PumaBot samples"

      author = "[email protected]"

  strings:

      $xapikey = "X-API-KEY" ascii

      $get_ips = "?count=5000" ascii

      $exec_start = "ExecStart=/lib/redis" ascii

      $svc_name1 = "redis.service" ascii

      $svc_name2 = "mysqI.service" ascii

      $uname = "uname -a" ascii

      $pumatronix = "Pumatronix" ascii

  condition:

      uint32(0) == 0x464c457f and

      all of (

          $xapikey,

          $uname,

          $get_ips,

          $exec_start

      ) and any of (

          $svc_name1,

          $svc_name2

      ) and $pumatronix

}

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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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June 9, 2026

Healthcare’s OT Cybersecurity Gap: Why Hospitals Must Make the Same Security Investments as Regulated Critical Infrastructures

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Rethinking the healthcare attack surface

When most people think about Operational Technology (OT) cybersecurity, they think about oil & gas pipelines, utilities, manufacturing plants, or power grids. However, hospitals & healthcare systems have quickly become a point of focus in the OT cybersecurity community as they do employ a variety of OT in the form of IoMT (Internet of Medical Things) networked devices such as: infusion pumps, imaging systems, patient monitoring equipment, laboratory systems, and traditional industrial control systems (ICS) in the form of smart building management systems (BMS) and even on site power generation control systems. 

These healthcare environments are no longer just traditional IT ecosystems, they are cyber-physical environments where disruption can directly impact patient care, operational continuity, and ultimately patient safety.

The OT cybersecurity expertise gap in healthcare organizations

Our research in the OT cybersecurity space revealed a concerning trend. Many hospitals and healthcare networks lack dedicated OT cybersecurity teams, OT security full time employees (FTE) and even OT expertise in the form of OT security certifications when compared to other critical infrastructure sectors.

On the other hand, within industries such as energy and manufacturing, we encounter more mature OT security programs that employ full time employees  dedicated to OT cybersecurity with OT security certifications and expertise to secure industrial and operational environments and lead investment in OT security processes and technology.

When reviewing the top 20 U.S. Hospitals by market cap, given what is publicly available on LinkedIn, only one FTE with an OT cybersecurity certification was found. The certifications that were searched for include: GIAC GICSP, GIAC GRID, GIAC GCIP and all ISA/IEC 62443 certifications. When replicating this same search across the top 20 utility providers in the US, 73 FTEs with OT related certifications were identified. As a control group, we looked within financial services, an industry NOT expected to have OT systems worth investing in FTEs to protect. However, the top 20 US financial institutions had 18 FTEs with OT related certifications. 

What these findings reveal

Overall, the findings regarding healthcare investment in OT security FTEs are surprising given how operationally dependent modern healthcare has become on OT. So why aren't hospitals investing in OT security personnel at the rate of peer critical infrastructures? It could just be lack of awareness; however, there are other, more plausible reasons.  

Based on historical trends in cyber incidents within the healthcare space, one could speculate that there is significantly greater likelihood of being victim to an attack that  focuses on extortion or data theft rather than an attack on specific OT systems. The amount of ransomware events incurred in healthcare, that historically do not target OT systems, may divert attention and security investment to the parts of the attack surface most likely to be targeted by ransomware. Additionally, data theft is a relevant threat objective for hospitals given PHI, PCI and PII, and data theft does not traditionally align with attacks targeting OT.  

However, with focused investment to address data theft and with adversaries new capability to string together chains of vulnerabilities of different severity scores using advancements in AI, we could be entering a threat landscape where adversaries pivot their tactics to target exposed and under protected devices and systems like OT. For example, although not a patient records database, predominant IOMT protocols HL7 and DICOM are unencrypted plaintext protocols and unless encrypted it is very simple for adversaries, who are sniffing traffic, to identify protected health information (PHI) in these communication protocols.

Why OT cybersecurity expertise can be effective for healthcare organizations

The convergence of IT, OT, and IoMT is already here, and threat actors are increasingly aware of the operational vulnerabilities that come with it. Additionally, as AI solutions such as agentic or generative applications are adopted and deployed, the attack surface will continue to change as permissions, and new connections will exist to support AI efficiency. From a cybersecurity standpoint, the reality is that many healthcare organizations are still working to establish consistent visibility and governance across their enterprise-connected devices and systems as their attack surface is changing in real time.  As the healthcare sector remains a significant target for cyber-attacks, hospitals would be well advised to begin addressing their operational environments OT as a critical component of their attack surface and invest in securing them first with people, then process and technology. 

What can healthcare organizations do to secure their OT

Including OT in current cybersecurity processes such as red teaming and testing incident response plans that take OT into account alongside building dedicated OT security capabilities including improving OT network visibility, leveraging OT network anomaly detection, micro-segmentation, and secure remote access will become essential steps in strengthening healthcare resilience. 

However, before any of the above processes or investments in technology can be made, these healthcare organizations, like the other critical infrastructure sectors, need to invest in the people with the experience in OT security to lead, implement, manage and audit the investment in OT cybersecurity technology and processes.  In cases where headcount cannot be added, investment in OT security certifications, such as the ones listed in this article, and participation on OT security events focused on practitioner training for existing cybersecurity employees can move the needle in terms of bringing OT expertise to the existing team.  

In an industry where uptime and safety are as mission critical as they are for a power utility, OT cybersecurity FTEs can no longer be viewed as optional for healthcare organizations and must become part of the foundation of modern healthcare cybersecurity strategy. 

[related-resource]

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Daniel Simonds
Director of Operational Technology

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June 9, 2026

Always On, Always Defending: Inside the AI-Driven SOC

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Today’s SOC: A system under pressure

The SOC has been described as the:

  • Control center for security systems management  
  • Operations center for log analysis and alert response
  • Command center for network monitoring and investigation

But the CISO at a manufacturer of industrial power solutions says today’s SOC is far more dynamic:

“The SOC is an active player in a never-ending chess match where the pieces are always moving, the rules are constantly changing, and we’re continuously adjusting our tactical and strategic approaches to keep up.”

This has created a balancing act for cybersecurity professionals:

  • Support expanding digital estates to fuel innovation…or risk limiting business growth
  • Stop advanced cyberattacks at scale…or risk severe financial and reputational impacts

But balancing these responsibilities is increasingly difficult. Attackers are operating at machine speed and scale using sophisticated, adaptive techniques that overwhelm teams and bypass legacy defenses. At the same time, more than half of cybersecurity teams are understaffed, and 65% have unfilled cybersecurity positions (ISACA).

“The SOC is hitting its breaking point,” admits the VP of IT at a U.S.-based risk management services provider.”

“That’s the hard reality,” affirms a Chief Digital and Technology Officer at a North American financial services organization. “SOC teams are drowning in alerts, wasting time researching the most benign incidents while missing critical threats.”

Traditional tools lack the context and autonomous reasoning needed to determine which ones are truly dangerous, requiring analysts to manually review and respond. But with thousands of alerts hitting SOCs daily, the task exceeds human capacity, with recent industry research revealing that 40% to 42% of security alerts now go uninvestigated.

“Our old governance models of throwing bodies at it, that’s not going to work,” says the Group CIO of a multinational holding company. “Attackers move at machine speed, and our defenses have to operate at the same pace. Using AI for cybersecurity is the only way to do that.”

Why AI is essential

AI is about speed, scale, and context.

SOC teams are still expected to find the proverbial “needle in a haystack”, but the haystack keeps growing. As digital infrastructures expand and threat actors use AI to rapidly scale attacks and exploit vulnerabilities, success isn’t about keeping up but changing the approach.

This is where AI comes in, enabling security teams to operate at machine speed and scale by:

  • Analyzing vast amounts of data and correlating signals across domains within seconds
  • Detecting possible threats in real time and taking immediate action to mitigate risk
  • Prioritizing threats by severity and uncovering contextual details for rapid triage

The power of AI isn’t theoretical; it is transforming how today’s businesses operate.

The Chief Digital and Technology Officer at a financial services firm says within a single month of using Darktrace, the solution tracked billions of network events, autonomously investigated tens of millions of those incidents, and added the equivalent of 1,000 analyst hours of investigation. It also found threats that bypassed traditional tools, autonomously responding to contain or disrupt the threat on over 30,000 emails, including 18,000 the firm’s native email filter missed.

When Darktrace says it “takes action on a threat,” it generally means its platform can move beyond just detecting suspicious activity and automatically respond to contain or disrupt the threat—such as isolating a device, slowing or blocking suspicious network traffic, disabling risky user activity, or triggering security workflows—depending on how the system is configured.

AI isn’t about displacing humans.

AI is a powerful tool for handling large-scale data analysis, pattern detection, and repetitive tasks, but it cannot replace human critical thinking. By removing mindless work that does not require judgment, AI frees analysts to focus on what humans do best: applying reasoning, context, and sound decision-making to complex threats.

“AI is a workforce maximizer,” says the Chief Digital and Technology Officer. “It augments our team by monitoring and detecting threats at a scale beyond human capacity while providing the critical context we need to make faster, more confident decisions.

Rather than replacing people, AI is changing how security professionals work. Analysts can reclaim time previously spent on tedious, manual triage to focus on higher priorities and proactive initiatives like advanced threat hunting, strategic risk management, and security enablement and training.

“Aside from risk mitigation, our biggest ROI is in efficiency,” says the Head of Security at global business services provider. “What used to take 90% of our investigation time is now handled automatically, so we can focus on the final 10%, which requires critical thinking."

For SOC teams under pressure, the impact can be transformative, with security leaders reporting significant real-world outcomes using Darktrace Self-Learning AITM, including:

  • Phishing emails reduced by 99%
  • 1 million+ emails autonomously analyzed each month, with no email-based incidents reported
  • Potential threats autonomously neutralized in under four seconds, on average  
  • 99% of investigations conducted autonomously, surfacing only the high-priority 1% of threats for analyst review

How AI optimizes the SOC

To protect the modern enterprise, you absolutely need the right tools,” says CTO at leading European fashion brand. “Without them you’re a victim. With them, you’re a defender. AI and the machine speed detect/response it enables makes it the most critical tool.”

Replacing chaos with clarity and control  

It’s important to note that different AI solutions address different needs. Companies should clearly understand their specific use case and select the solution that best aligns with their goals, requirements, and operational needs.  

When it comes to choosing cybersecurity in a machine-speed threat landscape, time is the most valuable resource. Organizations require AI that can move from insight to action by:

  • Learning an organization’s unique behavioral patterners
  • Correlating signals across domains to detect anomalous activity
  • Prioritizing events and autonomously responding at scale to the vast majority
  • Quarantining high-impact threats until the SOC can investigate
  • Arming analysts with deep, contextual information to accelerate investigations

“Darktrace AI gives us threat detections based on facts, not guesses,” says the Group CIO. “It moves the SOC beyond alert overload to confident, informed decision-making. When Darktrace flags something, we pay attention. False positives are very rare, so we act with speed and confidence without second-guessing.”

Replacing anxiety with confidence and peace of mind

Every missed alert can have real-world consequences.

The strain of maintaining constant vigilance at scale without holistic visibility and automation is taking its toll on security professionals: 66% report increased stress, and nearly half say it’s the reason they’re leaving the field (ISACA).

The CIO at a professional sports organization says that’s not surprising: “If you don’t know what’s going on, anything could be happening. Operating with that level of uncertainty and control is incredibly stressful.”

AI gives SOCs the power to be proactive by unifying telemetry across network, email, identity, and cloud environments to provide a complete picture and a stronger foundation for action. The benefits for analysts, both personally and professionally, are significant:

  • Achieve greater work-life balance: “Knowing that Darktrace has our backs 24/7 and will take immediate action to stop threats  means we can now work normal hours and take vacations without worrying,” says the Chief Digital and Technology Officer.
  • Feel in control with deeper insights: “It not only stops and quarantines threats but also provides the deep context we need to quickly investigate and respond,” explains the Head of Security.  
  • Gain confidence the business is protected 24/7: “We can sleep at night. With Darktrace I’m confident that even with a small team we can protect the business 24/7,” adds the former retail CIO.

The modern SOC: A system of balance

Elevated to a core pillar of business strategy, the modern SOC is now considered:

  • The nerve center of cyber risk and proactive defense
  • The AI-powered command center for operational resilience
  • The strategic hub for contextual decision-making at scale

The SOC has evolved from a reactive center responsible for managing systems into a proactive, frontline defender and strategic business enabler—integral to innovation and growth.

AI is the key to balancing these responsibilities.

“We can only grow as fast as we can secure the business,” says the Head of Security. “AI gives us the speed, scale, and confidence to do both.”

*Metrics are based on the customer’s interview, data and sourced from its monthly Cyber AI Insights reporting.

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