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May 3, 2021

Understanding Modern-Day Cyber Attacks

Discover how Darktrace detects and mitigates threats in IoT ecosystems and globalized supply chains that are constantly evolving.
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
Brianna Luong (Leddy)
Sr. Technical Alliances Manager
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03
May 2021

It’s ten to five on a Friday afternoon. A technician has come in to perform a routine check on an electronic door. She enters the office with no issues – she works for a trusted third-party vendor, employees see her every week. She opens her laptop and connects to the Door Access Control Unit, a small Internet of Things (IoT) device used to operate the smart lock. Minutes later, trojans have been downloaded onto the company network, a crypto-mining operation has begun, and there is evidence of confidential data being exfiltrated. Where did things go wrong?

Threats in a business: A new dawn surfaces

As organizations keep pace with the demands of digital transformation, the attack surface has become broader than ever before. There are numerous points of entry for a cyber-criminal – from vulnerabilities in IoT ecosystems, to blind spots in supply chains, to insiders misusing their access to the business. Darktrace sees these threats every day. Sometimes, like in the real-world example above, which will be examined in this blog, they can occur in the very same attack.

Insider threats can use their familiarity and level of access to a system as a critical advantage when evading detection and launching an attack. But insiders don’t necessarily have to be malicious. Every employee or contractor is a potential threat: clicking on a phishing link or accidentally releasing data often leads to wide-scale breaches.

At the same time, connectivity in the workspace – with each IoT device communicating with the corporate network and the Internet on its own IP address – is an urgent security issue. Access control systems, for example, add a layer of physical security by tracking who enters the office and when. However, these same control systems imperil digital security by introducing a cluster of sensors, locks, alarm systems, and keypads, which hold sensitive user information and connect to company infrastructure.

Furthermore, a significant proportion of IoT devices are built without security in mind. Vendors prioritize time-to-market and often don’t have the resources to invest in baked-in security measures. Consider the number of start-ups which manufacture IoT – over 60% of home automation companies have fewer than ten employees.

Insider threat detected by Cyber AI

In January 2021, a medium-sized North American company suffered a supply chain attack when a third-party vendor connected to the control unit for a smart door.

Figure 1: The attack lasted 3.5 hours in total, commencing 16:50 local time.

The technician from the vendor’s company had come in to perform scheduled maintenance. They had been authorized to connect directly to the Door Access Control Unit, yet were unaware that the laptop they were using, brought in from outside of the organization, had been infected with malware.

As soon as the laptop connected with the control unit, the malware detected an open port, identified the vulnerability, and began moving laterally. Within minutes, the IoT device was seen making highly unusual connections to rare external IP addresses. The connections were made using HTTP and contained suspicious user agents and URIs.

Darktrace then detected that the control unit was attempting to download trojans and other payloads, including upsupx2.exe and 36BB9658.moe. Other connections were used to send base64 encoded strings containing the device name and the organization’s external IP address.

Cryptocurrency mining activity with a Monero (XMR) CPU miner was detected shortly afterwards. The device also utilized an SMB exploit to make external connections on port 445 while searching for vulnerable internal devices using the outdated SMBv1 protocol.

One hour later, the device connected to an endpoint related to the third-party remote access tool TeamViewer. After a few minutes, the device was seen uploading over 15 MB to a 100% rare external IP.

Figure 2: Timeline of the connections made by an example device on the days around an incident (blue). The connections associated with the compromise are a significant deviation from the device’s normal pattern of life, and result in multiple unusual activity events and repeated model breaches (orange).

Security threats in the supply chain

Cyber AI flagged the insider threat to the customer as soon as the control unit had been compromised. The attack had managed to bypass the rest of the organization’s security stack, for the simple reason that it was introduced directly from a trusted external laptop, and the IoT device itself was managed by the third-party vendor, so the customer had little visibility over it.

Traditional security tools are ineffective against supply chain attacks such as this. From the SolarWinds hack to Vendor Email Compromise, 2021 has put the nail in the coffin for signature-based security – proving that we cannot rely on yesterday’s attacks to predict tomorrow’s threats.

International supply chains and the sheer number of different partners and suppliers which modern organizations work with thus pose a serious security dilemma: how can we allow external vendors onto our network and keep an airtight system?

The first answer is zero-trust access. This involves treating every device as malicious, inside and outside the corporate network, and demanding verification at all stages. The second answer is visibility and response. Security products must shed a clear light into cloud and IoT infrastructure, and react autonomously as soon as subtle anomalies emerge across the enterprise.

IoT investigated

Darktrace’s Cyber AI Analyst reported on every stage of the attack, including the download of the first malicious executable file.

Figure 3: Example of Cyber AI Analyst detecting anomalous behavior on a device, including C2 connectivity and suspicious file downloads.

Cyber AI Analyst investigated the C2 connectivity, providing a high-level summary of the activity. The IoT device had accessed suspicious MOE files with randomly generated alphanumeric names.

Figure 4: A Cyber AI Analyst summary of C2 connectivity for a device.

Not only did the AI detect every stage of the activity, but the customer was also alerted via a Proactive Threat Notification following a high scoring model breach at 16:59, just minutes after the attack had commenced.

Stranger danger

Third parties coming in to tweak device settings and adjust the network can have unintended consequences. The hyper-connected world which we’re living in, with the advent of 5G and Industry 4.0, has become a digital playground for cyber-criminals.

In the real-world case study above, the IoT device was unsecured and misconfigured. With rushed creations of IoT ecosystems, intertwining supply chains, and a breadth of individuals and devices connecting to corporate infrastructure, modern-day organizations cannot expect simple security tools which rely on pre-defined rules to stop insider threats and other advanced cyber-attacks.

The organization did not have visibility over the management of the Door Access Control Unit. Despite this, and despite no prior knowledge of the attack type or the vulnerabilities present in the IoT device, Darktrace detected the behavioral anomalies immediately. Without Cyber AI, the infection could have remained on the customer’s environment for weeks or months, escalating privileges, silently crypto-mining, and exfiltrating sensitive company data.

Thanks to Darktrace analyst Grace Carballo for her insights on the above threat find.

Learn more about insider threats

Darktrace model detections:

  • Anomalous File/Anomalous Octet Stream
  • Anomalous Connection/New User Agent to IP Without Hostname
  • Unusual Activity/Unusual External Connectivity
  • Device/Increased External Connectivity
  • Anomalous Server Activity/Outgoing from Server
  • Device/New User Agent and New IP
  • Compliance/Cryptocurrency Mining Activity
  • Compliance/External Windows Connectivity
  • Anomalous File/Multiple EXE from Rare External Locations
  • Anomalous File/EXE from Rare External Location
  • Device/Large Number of Model Breaches
  • Anomalous File/Internet Facing System File Download
  • Device/Initial Breach Chain Compromise
  • Device/SMB Session Bruteforce
  • Device/Network Scan- Low Anomaly Score
  • Device/Large Number of Connections to New Endpoint
  • Anomalous Server Activity/Outgoing from Server
  • Compromise/Beacon to Young Endpoint
  • Anomalous Server Activity/Rare External from Server
  • Device/Multiple C2 Model Breaches
  • Compliance/Remote Management Tool on Server
  • Anomalous Connection/Data Sent to New External Device

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
Brianna Luong (Leddy)
Sr. Technical Alliances Manager

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April 28, 2026

State of AI Cybersecurity 2026: 87% of security professionals are seeing more AI-driven threats, but few feel ready to stop them

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The findings in this blog are taken from Darktrace’s annual State of AI Cybersecurity Report 2026.

In part 1 of this blog series, we explored how AI is remaking the attack surface, with new tools, models, agents — and vulnerabilities — popping up just about everywhere. Now embedded in workflows across the enterprise, and often with far-reaching access to sensitive data, AI systems are quickly becoming a favorite target of cyber threat actors.

Among bad actors, though, AI is more often used as a tool than a target. Nearly 62% of organizations  experienced a social engineering attack involving a deepfake, or an incident in which bad actors used AI-generated video or audio to try to trick a biometric authentication system, compared to 32% that reported an AI prompt injection attack.

In the hands of attackers, AI can do many things. It’s being used across the entire kill chain: to supercharge reconnaissance, personalize phishing, accelerate lateral movement, and automate data exfiltration. Evidence from Anthropic demonstrates that threat actors have harnessed AI to orchestrate an entire cyber espionage campaign from end to end, allegedly running it with minimal human involvement.

CISOs inhabit a world where these increasingly sophisticated attacks are ubiquitous. Naturally, combatting AI-powered threats is top of mind among security professionals, but many worry about whether their capabilities are up to the challenge.

AI-powered threats at scale: no longer hypothetical

AI-driven threats share signature characteristics. They operate at speed and scale. Automated tools can probe multiple attack paths, search for multiple vulnerabilities and send out a barrage of phishing emails, all within seconds. The ability to attack everywhere at once, at a pace that no human operator could sustain, is the hallmark of an AI-powered threat. AI-powered threats are also dynamic. They can adapt their behavior to spread across a network more efficiently or rewrite their own code to evade detection.

Security teams are seeing the signs that they’re fighting AI-powered threats at every stage of the kill chain, and the sophistication of these threats is testing their resolve and their resources.

  • 73% say that AI-powered cyber threats are having a significant impact on their organization
  • 92% agree that these threats are forcing them to upgrade their defenses
  • 87% agree that AI is significantly increasing the sophistication and success rate of malware
  • 87% say AI is significantly increasing the workload of their security operations team

These teams now confront a challenge unlike anything they’ve seen before in their careers, and the risks are compounding across workflows, tools, data, and identities. It’s no surprise that 66% of security professionals say their role is more stressful today than it was five years ago, or that 47% report feeling overwhelmed at work.

Up all night: Security professionals’ worry list is long

Traditional security methods were never built to handle the complexity and subtlety of AI-driven behavior. Working in the trenches, defenders have deep firsthand experience of how difficult it can be to detect and stop AI-assisted threats.

Increasingly effective social engineering attacks are among their top concerns. 50% of security leaders mentioned hyper-personalized phishing campaigns as one of their biggest worries, while 40% voiced apprehension about deepfake voice fraud. These concerns are legitimate: AI-generated phishing emails are increasingly tailored to individual organizations, business activities, or individuals. Gone are the telltale signs – like grammar or spelling mistakes – that once distinguished malicious communications. Notably, 33% of the malicious emails Darktrace observed in 2025 contained over 1,000 characters, indicating probable LLM usage.

Security leaders also worry about how bad actors can leverage AI to make attacks even faster and more dynamic. 45% listed automated vulnerability scanning and exploit chaining among their biggest concerns, while 40% mentioned adaptive malware.

Confidence is lacking

Protecting against AI demands capabilities that many organizations have not yet built. It requires interpreting new indicators, uncovering the subtle intent within interactions, and recognizing when AI behavior – human or machine – could be suspicious. Leaders know that their current tools aren’t prepared for this. Nearly half don’t feel confident in their ability to defend against AI-powered attacks.

We’ve asked participants in our survey about their confidence for the last three years now. In 2024, 60% said their organizations were not adequately prepared to defend against AI-driven threats. Last year, that percentage shrunk to 45%, a possible indicator that security programs were making progress. Since then, however, the progress has apparently stalled. 46% of security leaders now feel inadequately prepared to protect their organizations amidst the current threat landscape.

Some of these differences are accentuated across different cultures. Respondents in Japan are far less confident (77% say they are not adequately prepared) than respondents in Brazil (where only 21% don’t feel prepared).

Where security programs are falling short

It’s no longer the case that cybersecurity is overlooked or underfunded by executive leadership. Across industries, management recognizes that AI-powered threats are a growing problem, and insufficient budget is near the bottom of most CISO’s list of reasons that they struggle to defend against AI-powered threats.  

It’s the things that money can’t buy – experience, knowledge, and confidence – that are holding programs back. Near the top of the list of inhibitors that survey participants mention is “insufficient knowledge or use of AI-driven countermeasures.” As bad actors embrace AI technologies en masse, this challenge is coming into clearer focus: attack-centric security tools, which rely on static rules, signatures, and historical attack patterns, were never designed to handle the complexity and subtlety of AI-driven attacks. These challenges feel new to security teams, but they are the core problems Darktrace was built to solve.  

Our Self-Learning AI develops a deep understanding of what “normal” looks like for your organization –including unique traffic patterns, end user habits, application and device profiles – so that it can detect and stop novel, dynamic threats at the first encounter. By focusing on learning the business, rather than the attack, our AI can keep pace with AI-powered threats as they evolve.

Explore the full State of AI Cybersecurity 2026 report for deeper insights into how security leaders are responding to AI-driven risks.

Learn more about securing AI in your enterprise.

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April 24, 2026

Email-Borne Cyber Risk: A Core Challenge for the CISO in the Age of Volume and Sophistication

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The challenge for CISOs

Despite continuous advances in security technologies, humans continue to be exploited by attackers. Credential abuse and social actions like phishing are major factors, accounting for around 60% of all breaches. These attacks rely less on technical vulnerabilities and more on exploiting human behavior and organizational processes. 

From my perspective as a former CISO, protecting humans concentrates three of today’s most pressing challenges: the sheer volume of email-based threats, their increasing sophistication, and the limitations of traditional employee awareness programs in moving the needle on risk. 

My personal experience of security awareness training as a CISO

With over 20 years’ experience as an ICT and Cybersecurity leader across various international organizations, I’ve seen security awareness training (SAT) in many guises. And while the cyber landscape is evolving in every direction, the effectiveness of SAT is reaching a plateau.  

Most programs I’ve seen follow a familiar pattern. Training is delivered through a combination of eLearning modules and internal sessions designed to reinforce IT policies. Employees are typically required to complete a slide deck or video, followed by a multiple-choice quiz. Occasional phishing simulations are distributed throughout the year.

The content is often static and unpersonalized, based on known threats that may already be outdated. Every employee regardless of role or risk exposure receives the same training and the same simulated phishing templates, from front-desk staff to the CEO.

The problem with traditional SAT programs

The issue with the approach to SAT outlined above is that the distribution of power is imbalanced. Humans will always be fallible, particularly when faced with increasingly sophisticated attacks. Providing generic, low-context training risks creating false confidence rather than genuine resilience. Let’s look at some of the problems in detail.

Timing and delivery

Employees today operate under constant cognitive load, making lots of rapid decisions every day to reduce their email volumes. Yet if employees are completing training annually, or on an ad hoc basis, it becomes a standalone occurrence rather than a continuous habit.  

As a result, retention is low. Employees often forget the lessons within weeks, a phenomenon known as the ‘Ebbinghaus Forgetting Curve.’

The graph illustrates that when you first learn something, the information disappears at an exponential rate without retention. In fact, according to the curve, you forget 50% of all new information within a day, and 90% of all new information within a week.  

Simultaneously, most training is conducted within a separate interface. Because it takes place away from the actual moment of decision-making, the "teachable moment" is lost. There is a cognitive disconnect between the action (clicking a link in Outlook) and the education (watching a video in a browser). 

People

In the context of professional risk management, the risks faced by different users are different. Static learning such as everyone receiving the same ‘Password Reset’ email doesn’t help users prepare for the specific threats they are likely to face. It also contributes to user fatigue, driven by repetitive training. And if users receive tests at the same time, news spreads among colleagues, hurting the efficacy of the test.  

Staff turnover introduces further risk. In many organizations, new employees gain access to systems before receiving meaningful training, reducing onboarding to little more than policy acknowledgment.

Measuring success

In my experience, solutions are standalone, without any correlation to other tools in the security stack. In some cases, the programs are delivered by HR rather than the security team, creating a complete silo.  

As a result, SAT is often perceived as a compliance exercise rather than a capability building function. The result is that poor-quality training does little to reduce the likelihood of compromise, regardless of completion rates or quiz performance.

What a modern SAT solution should look like

For today’s CISO, email represents the convergence point of high-volume, high-impact, and human-centric threats. Despite significant security investments, it remains one of the most difficult channels to secure effectively. Given these constraints, CISOs must evolve their approach to SAT.

Success lies in a balanced strategy one that combines advanced technology, attack surface reduction, and pragmatic user enablement, without over-relying on human vigilance as the final line of defense.

This means moving beyond traditional SAT toward continuous, contextual awareness, realistic simulations, and tight integration with security outcomes.

Three requirements for a modern SAT solution

  • Invisible protection: The optimum security solution is one that assists users without impeding their experience. The objective is to enhance human capabilities, rather than simply delivering a lecture. 
  • Real-time feedback: Rather than a monthly quiz, the ideal system would provide a prompt or warning when a user is about to engage with something suspicious. 
  • Positive culture: Shifting the focus away from a "gotcha" culture, which is a contributing factor to a resentment, and instead empowers employees to serve as "sensors" for the company. 

Discover how personalized security coaching can strengthen your human layer and make your email defenses more resilient. Explore Darktrace / Adaptive Human Defense.

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About the author
Karim Benslimane
VP, Field CISO
Your data. Our AI.
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