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Mirai Malware: Impact on CCTV Cameras

Learn how Darktrace’s AI identified the Mirai malware in an Internet-connected CTV camera, breaking down each stage of the attack life cycle.
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
Max Heinemeyer
Global Field CISO
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Introduction: Mirai Malware attack on IoT devices

The rise of Internet of Things (IoT) devices, like Internet-connected cameras used in CCTV surveillance, has introduced new vulnerabilities to both personal and business environments.

With attackers exploiting the inadequate security measures typically associated with IoT devices, traditional antivirus and legacy security solutions fall short. To address this critical gap, Darktrace’s Cyber AI Platform provides advanced protection for these increasingly essential yet vulnerable technologies.

Attack Overview: Mirai Malware

In late May, Darktrace detected the Mirai malware infecting an internet-facing DVR camera owned by a logistics company in Canada.

Mirai, first discovered in 2016, continuously scans the Internet for the IP addresses of vulnerable devices in the Internet of Things (IoT), and then turns these devices into bots that can be used as part of botnets for large-scale network attacks. These attacks are often difficult to detect, as IoT devices seamlessly integrate into digital infrastructure, creating a vastly expanded attack surface for organizations.

By drawing on a bespoke, evolving understanding of what is normal for the network, Darktrace caught each stage in this attack’s lifecycle. However, because this company was still conducting their 30-day Proof of Value, Darktrace's Autonomous Response was not in active and the attack continued past the point of initial compromise. Had Darktrace's Autonomous Response been in active mode, the attack would not have advanced past initial compromise.

Attack Timeline

This timeline roughly outlines the major attack phases over three days of activity
Figure 1: This timeline roughly outlines the major attack phases over three days of activity

Technical analysis

At the time of the initial breach, this specific botnet’s infrastructure was not yet known to open source intelligence (OSINT). Darktrace, however, detected an EXE download from a location not previously visited by the network.

After the first anomalous EXE download, another was downloaded approximately twenty minutes later. The malware then reached out to multiple IP addresses that were statistically rare for the network. Specifically, the compromised device began transferring large amounts of data to an IP address in China.

n overview of Darktrace detections
Figure 2: An overview of Darktrace detections

Darktrace, by leveraging machine learning algorithms in a protocol agnostic capacity, analyzed this individual device’s transfers within the context of a continuously evolving understanding of what is normal both for this device and for the wider organization. It was therefore able to immediately flag all of these transfers as unusual.

This activity was fully investigated and reported on by Darktrace’s Cyber AI Analyst. A sample of the AI Analyst’s report is shown below. The Suspicious File Download, the Unusual Repeated Connections, and the Unusual External Data Transfer are all presented as unexpected events that call for further investigation. The destination IP of the suspicious download was determined to have 100% hostname rarity relative to what is normal for the organization.

 Darktrace’s Cyber AI Analyst autonomously triages the attack
Figure 3: Darktrace’s Cyber AI Analyst autonomously triages the attack

Moreover, the hash of the file, highlighted in a red box in the figure above, revealed that it was a well-known file related to the Mirai Botnet. However, with no antivirus or other security defending the IoT camera, this had gone undetected.

A one-click analysis of the infected device shows a timeline of the model breaches that occurred and graphs the activity to give the report’s readers a quick understanding of the successive stages of the attack. Here, we see the second and third stages of the attack’s lifecycle, in which it starts DDoS against other devices in order to complete its mission while simultaneously continuing outgoing connections to rare destinations in order to sustain its presence.

The device event log showing the list of model breaches on May 23
Figure 4: The device event log showing the list of model breaches on May 23

Conclusion

Interestingly, the client saw no indicators of this activity beyond a sluggish network. This change in network activity was only explained after being identified by Darktrace. Once the client was promptly notified, the compromise was deescalated, and discovering it was a DVR security camera, the client took the device offline.

As this customer was still concluding their trial deployment, Darktrace was not in full autonomous mode. However, if it had been, Darktrace would have responded with a two-tiered action to prevent the device from communicating with the malicious endpoint, cutting the compromised connection before the attack had gained its foothold.

Darktrace model breaches:

  • Anomalous Connection / Uncommon 1GiB Outbound
  • Unusual Activity / Unusual External Activity
  • Unusual Activity / Enhanced Unusual External Data Transfer
  • Unusual Activity / Unusual External Data to New IPs
  • Device / Initial Breach Chain Compromise
  • Anomalous Server Activity / Outgoing from Server
  • Anomalous Connection / Data Sent to New External Device
  • Anomalous Connection / Multiple Connections to New External UDP Port
  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Internet Facing System File Download
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
Max Heinemeyer
Global Field CISO

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June 2, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

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Núclea is a Brazilian data and technology company that supports the country’s financial system by delivering digital services exclusively to banks and financial institutions. Operating in an environment where trust, availability, and data integrity are critical, the company faces a threat landscape that has evolved rapidly—particularly with the rise of AI-driven cyberattacks.

Brazil has experienced a wave of successful cyber incidents targeting financial institutions, many of them enabled by insiders or compromised credentials. The result was a noticeable shift in attacker strategy: instead of focusing on end customers, threat actors began targeting the institutions and platforms that underpin the financial ecosystem itself.

“Attacks became far more directed and contextual,” explains Guilherme, who leads incident response within Núclea’s security platform engineering team. “They weren’t noisy or obviously malicious—they were precise, patient, and designed to blend into normal operations.”

That precision was on full display in January 2026, when Núclea faced one of the most convincing phishing attacks the team had seen.

A real attack, built on trust and context

The attack began with a seemingly routine email.

It was sent from a real Brazilian government institution, using legitimate infrastructure and valid credentials that were later confirmed to have been compromised. Núclea had an established, ongoing relationship with this organization, and the email’s language, tone, and subject matter aligned perfectly with the type of communication the recipient team handled every day.

Attached to the email was a PDF document containing content that looked entirely legitimate.

The problem? A single URL embedded inside that PDF.

“The message itself was correct. The sender was real. The context was familiar. Even the document content made sense,” Guilherme explains. “There was just one small element that didn’t belong.”

That small detail was enough to initiate a full attack chain.

What the attackers were trying to do

If clicked, the URL would have downloaded a malicious payload designed to:

  • Collect information about the user and device
  • Identify where the system was located within the financial ecosystem
  • Install remote access tools to maintain control
  • Deploy an infostealer to extract sensitive data
  • Execute anti-forensic scripts to erase traces of the intrusion

In other words, it was a carefully engineered operation designed for persistence and stealth, not immediate disruption.

The attack also employed urgency—a classic social engineering technique. When the link didn’t open as expected, employees requested assistance from the security team, insisting the document was important and needed to be accessed quickly.

This is precisely the kind of scenario where traditional security tools struggle: almost everything about the interaction is legitimate.

Where Darktrace made the difference

Instead of blocking the entire message or relying on known indicators of compromise, Darktrace focused on behavioral context.

Darktrace recognized:

  • That the sending organization was normally trusted
  • That the communication pattern matched historical behavior
  • That the PDF content itself was not suspicious

But it also identified that the URL embedded within the document deviated from established behavioral patterns.

Rather than disrupting business operations, Darktrace took precise action: it rewrote the URL, preventing the malicious download while leaving the rest of the email untouched.

“When we analyzed it afterward, it became clear how dangerous the attack would have been,” says Guilherme. “But it never progressed—because Darktrace acted at exactly the right point.”

Subsequent forensic analysis confirmed the payload’s malicious intent. The attack never succeeded.

Precision over disruption

For Núclea, this incident reinforced a critical lesson: modern attacks don’t always look malicious—they hide within normal activity.

“What stands out to me is the precision,” Guilherme says. “Darktrace doesn’t rely on big, obvious signals. It’s effective in situations that fall outside the standard patterns we all know.”

Building resilience in a high trust ecosystem

For Núclea, cybersecurity is not just a defensive measure—it’s a business enabler.

Availability failures or successful breaches in the financial ecosystem can have immediate, large-scale consequences, from financial loss to reputational damage. Preventing those outcomes protects not just Núclea, but its partners and customers as well.

“Cyber resilience means keeping the business running—even under attack,” Guilherme explains. “And that requires people, processes, and technology working together.”

As AI continues to accelerate both attacks and defenses, the role of security is evolving. Precision, behavioral understanding, and intelligent automation are no longer optional—they’re essential.

“The easy days were yesterday,” Guilherme says. “The challenges ahead are bigger. We need to be prepared—internally and with partners that help us build resilience.”

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About the author
Mariana Pereira
VP, Field CISO

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June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

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Modern attacks don’t always announce themselves, follow obvious patterns, or rely on known malware. Often, they move quietly inside trusted systems, authenticated sessions, and everyday behavior.

They don’t break in. They blend in.

That’s why an AI-powered defense is essential. It turns invisible signals into actionable insights at a scale neither analysts nor traditional tools can achieve alone.

Confidence is creating risk

One of the most dangerous assumptions in cybersecurity today is that strong controls equal strong protection.

Multi-factor authentication (MFA), for example, is widely viewed as a foundational safeguard. But as the CISO for a professional sports organization explains, that confidence can be misplaced. “A lot of organizations assume that once you have MFA, those accounts are safe. That’s not true.”

In one instance, his team identified a sophisticated attack where a threat actor bypassed MFA entirely, not by breaking it, but by going around it. A user’s authenticated session was hijacked and re-used, allowing the attacker to impersonate them without triggering traditional controls.

“Darktrace picked up that a session had been re-injected by the hacker, and we were able to block it right away,” he explains.

Attackers anticipate what we miss

Even well-trained users can become entry points.

“An email bypassed our existing security tools,” shares the VP of IT at a U.S.-based risk management services provider.  “The user missed one signal and entered their credentials into a malicious site. That’s what the bad guys count on.”

The organization responded quickly, but not before damage was done. Crucially, this occurred while Darktrace was in “watch mode,” before autonomous response was fully enabled. “Darktrace would have seen that and shut it down immediately,” he notes.

Mistakes and oversights like misconfigurations, forgotten machines, and missed patches can create serious vulnerabilities.

The CIO of a utility services organization shares an instance when Darktrace detected a breach to a client’s network via their ZTNA VPN due to misconfigured MFA. “Darktrace alerted us and autonomously blocked the scanning, preventing what could have been a ransomware-type incident.”  

The most dangerous threats are already inside

The Head of Security at a global business services provider knows firsthand how blind spots can persist inside environments. His team uncovered evidence of dormant ransomware artifacts sitting unnoticed within a company’s environment ¬¬– long before modern detection was in place.

“During a routine file transfer, Darktrace flagged the suspicious activity, identified the ransomware, and immediately quarantined the server,” he recalls.  While the attack was never executed, the implication was significant: the risk existed long before it was finally detected.

Cyber threats are also successful because they take advantage of normal human behavior, exploiting moments of cognitive overload, urgency, and trust.

The Executive Director of IT and Business Applications at a pharmaceutical lab describes the time Darktrace flagged an employee logging into Microsoft 365 from Singapore, despite him being physically located in the U.S. Darktrace immediately cut off his access and within minutes revealed that the employee’s son was using a VPN to play a video game.

While the threat was benign, it demonstrated the strength of AI to use contextual information to detect threats other tools miss. The information also saved security analysts hours of investigation and minimized downtime for the employee. “That level of precision and speed isn’t just convenient, it’s game changing.”

“Unusual” behavior is the new red flag

Detecting modern threats requires an understanding of what “normal” looks like and recognizing when something subtly deviates.

One security leader  at an AI technology enterprise described a scenario in which an employee connected to a proxy service in China. The service itself was legitimate, and although traditional tools didn’t flag it, the behavior was unusual for that user specifically.

“That’s what Darktrace picked up on. The activity turned out to be benign, but without visibility into behavioral deviations, it could just as easily have been something more serious.”

AI shifts defense from reaction to anticipation

These stories point to a fundamental shift by cyber attackers, both tactically and strategically. Because traditional security tools were built to detect what’s already known, modern attacks are often:

  • Credential-based, not malware-based
  • Behavioral, not signature-based
  • Subtle, not overt

They may operate within the boundaries of what appears normal, exploiting what organizations trust, not what they block:

  • Trusted sessions
  • Legitimate services
  • Human error

This is where AI is changing the equation. Rather than relying on predefined rules or known threat signatures, AI can:

  • Establish a baseline of normal behavior
  • Detect subtle anomalies in real time
  • Act autonomously to contain potential threats

Resilience, not perfection, is the new security standard

As these frontline experiences show, the organizations that lead are those that move beyond reactive defense and embrace AI as a core part of their strategy.

It eliminates the blind spots and uncertainty, says the CISO of a professional sports organization. “If you lack visibility, you’re not managing risk, you’re assuming it. AI gives you the actionable insights needed to turn uncertainty into control.”

And it provides the speed and agility that are vital when seconds matter, says the Executive Director of IT and Business Applications. “When Darktrace alerted us at 3:00 am to a ransomware attack, it had already quarantined the affected systems, blocked the attacker’s access, and provided us with the critical details and time needed to investigate. That action likely saved us hundreds of thousands, if not millions, of dollars.”

The modern SOC has become a cornerstone of enterprise resilience, responsible for protecting data and operational continuity while enabling digital growth and innovation. For today’s security professional, that means success is no longer measured by what they keep out, but by what they protect: revenue, reputation, and trust.

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