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March 7, 2024

Defending Against the New Normal in Cybercrime: AI

This blog outlines research & data points on the evolving threat landscape, the impact of malicious AI, and why proactive cyber readiness is essential.
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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07
Mar 2024

AI in Cyber Security

Over the last 18 months, discussions about artificial intelligence (AI) – specifically generative AI – ranged from excitement and optimism about its transformative potential to fear and uncertainty about the new risks it introduces.  

New research1 commissioned by Darktrace shows that 89 percent of IT security teams polled globally believe AI-augmented cyber threats will have a significant impact on their organization within the next two years, yet 60 percent believe they are currently unprepared to defend against these attacks. Their concerns include increased volume and sophistication of malware that targets known vulnerabilities and increased exposure of sensitive or proprietary information from using generative AI tools.  

At Darktrace, we monitor trends across our global customer base to understand how the challenges facing security teams are evolving alongside industry advancements in AI. We’ve observed that AI, automation, and cybercrime-as-a-service have increased the speed, sophistication and efficacy of cyber security attacks.  

How AI Impacts Phishing Attempts

Darktrace has observed immediate impacts on phishing, which remains one of the most common forms of attack. In April 2023, Darktrace shared research that found a 135 percent increase in ‘novel social engineering attacks’ in the first two months of 2023, corresponding with the widespread adoption of ChatGPT2. These phishing attacks showed a strong linguistic deviation – semantically and syntactically – compared to other phishing emails, which suggested to us that generative AI is providing an avenue for threat actors to craft sophisticated and targeted attacks at speed and scale. A year later, we’ve seen this trend continue. Darktrace customers received approximately 2,867,000 phishing emails in December 2023 alone, a 14 percent increase on what was observed months prior in September3. Between September and December 2023, phishing attacks that used novel social engineering techniques grew by 35 percent on average across the Darktrace customer base4.  

These observations reinforce trends that others in the industry have shared. For example, Microsoft and OpenAI recently published research on tactics, techniques, and procedures (TTPs) augmented by large language models (LLMs) that they have observed nation-state threat actors using. That includes using LLMs to draft and generate social engineering attacks, inform reconnaissance, assist with vulnerability research and more.  

The Rise of Cybercrime-as-as-a-Service

The increasing cyber challenge facing defenders cannot be attributed to AI alone. The rise of cybercrime as-a-service is also changing the dynamic. Darktrace’s 2023 End of Year Threat Report found that cybercrime-as-a-service continue to dominate the threat landscape, with malware-as-a-Service (MaaS) and ransomware-as-a-Service (RaaS) tools making up most malicious tools in use by attackers. The as-a-Service ecosystem can provide attackers with everything from pre-made malware to templates for phishing emails, payment processing systems and even helplines to enable bad actors to mount attacks with limited technical knowledge.  

These trends make it clear that attackers now have a more widely accessible toolbox that reduces their barriers.

AI Enabling Accidental Insider Threats

However, the new risks facing businesses aren’t from external threat actors alone. Use of generative AI tools within the enterprise introduces a new category of accidental insider threats. Employees using generative AI tools now have easier access to more organizational data than ever before. Even the most well-intentioned employee could unintentionally leak or access restricted, sensitive data via these tools. In the second half of 2023, we observed that approximately half of Darktrace customers had employees accessing generative AI services. As this continues to increase, organizations need policies in place to guide the use cases for generative AI tools as well as strong data governance and the ability to enforce these policies to minimize risk.  

It is inevitable that AI will increase the risks and threats facing an organization, but this is not an unsolvable challenge from a defensive perspective. While advancements in generative AI may be worsening issues like novel social engineering and creating new types of accidental insider threats, AI itself offers a strong defense.  

The Shift to Proactive Cyber Readiness

According to the World Economic Forum’s Global Cybersecurity Outlook 2024, the number of organizations that “maintain minimum viable cyber resilience is down 30 percent compared to 2023”, and “while large organizations have demonstrated gains in cyber resilience, small and medium-sized companies showed significant decline.” The importance of cyber resilience cannot be understated in the face of today’s increasingly as-a-service, automated, and AI-augmented threat landscape.  

Historically, organizations wait for incidents to happen and rely on known attack data for threat detection and response, making it nearly impossible to identify never-before-seen threats. The traditional security stack has also relied heavily on point solutions focused on protecting different pieces of the digital environment, with individual tools for endpoint, email, network, on-premises data centers, SaaS applications, cloud, OT and beyond. These point solutions fail to correlate disparate incidents to form a complete picture of an orchestrated attack. Even with the addition of tools that can stitch together events from across the enterprise, they are in a reactive state that focuses heavily on threat detection and response.  

Organizations need to evolve from a reactive posture to a stance of proactive cyber readiness. To do so, they need an approach that proactively identifies internal and external vulnerabilities, identifies gaps in security policy and process before an attack occurs, breaks down silos to investigate all threats (known and unknown) during an attack, and uplifts the human analyst beyond menial tasks to incident validation and recovery after an attack.  

AI can help break down silos within the SOC and provide a more proactive approach to scale up and augment defenders. It provides richer context when it is fed information from multiple systems, data sets, and tools within the stack and can build an in-depth, real-time behavioural understanding of a business that humans alone cannot.

Lessons From AI in the SOC

At Darktrace, we’ve been applying AI to the challenge of cyber security for more than ten years, and we know that proactive cyber readiness requires the right mix of people, process, and technology.  

When the right AI is applied responsibly to the right cyber security challenge, the impact on both the human security team and the business is profound.

AI can bring machine speed and scale to some of the most time-intensive, error-prone, and psychologically draining components of cyber security, helping humans focus on the value-added work that only they can provide. Incident response and continuous monitoring are two areas where AI has already been proven to effectively augment defenders. For example, a civil engineering company used Darktrace’s AI to uplift its SOC team from the repetitive, manual tasks of analyzing and responding to email incidents. The analysts estimated they were each spending 10 hours per week on email incident analysis. With AI autonomously analyzing and responding to email incidents, the analysts could gain approximately 20 percent of their time back to focus on proactive cyber security measures

An effective human-AI partnership is key to proactive cyber readiness and can directly benefit the work-life of defenders. It can help to reduce burnout, support data-driven decision-making, and reduce the reliance on hard-to-find, specialized talent that has created a skills shortage in cyber security for many years. Most importantly, AI can free up team members to focus on more meaningful tasks, such as compliance initiatives, user education, and sophisticated threat hunting.  

Advancements in AI are happening at a rapid pace. As we’ve already observed, attackers will be watching these developments and looking for ways to use it to their advantage. Luckily, AI has already proved to be an asset for defenders, and embracing a proactive approach to cyber resilience can help organizations increase their readiness for this next phase. Prioritizing cyber security will be an enabler of innovation and progress as AI development continues.  

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Join Darktrace on 9 April for a virtual event to explore the latest innovations needed to get ahead of the rapidly evolving threat landscape. Register today to hear more about our latest innovations coming to Darktrace’s offerings.

References

[1] The survey was undertaken by AimPoint Group & Dynata on behalf Darktrace between December 2023 & January 2024. The research polled 1773 security professionals in positions across the security team from junior roles to CISOs, across 14 countries – Australia, Brazil, France, Germany, Italy, Japan, Mexico, Netherlands, Singapore, Spain, Sweden, UAE, UK, and USA.

[2] Based on the average change in email attacks between January and February 2023 detected across Darktrace/Email deployments with control of outliers.

[3] Average calculated across Darktrace customers from 31st August to 21st December.

[4] Average calculated across Darktrace customers from 31st August to 21st December. Novel social engineering attacks use linguistic techniques that are different to techniques used in the past, as measured by a combination of semantics, phrasing, text volume, punctuation, and sentence length.

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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May 12, 2026

Resilience at the Speed of AI: Defending the Modern Campus with Darktrace

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Why higher education is a different cybersecurity battlefield

After four decades in IT, now serving as both CIO and CISO, I’ve learned one simple truth: cybersecurity is never “done.” It’s a constant game of cat and mouse. Criminals evolve. Technologies advance. Regulations expand. But in higher education, the challenge is uniquely complex.

Unlike a bank or a military installation, we can’t lock down networks to a narrow set of approved applications. Higher education environments are open by design. Students collaborate globally, faculty conduct cutting-edge research, and administrators manage critical operations, all of which require seamless access to the internet, global networks, cloud platforms, and connected systems.

Combine that openness with expanding regulatory mandates and tight budgets, and the balancing act becomes clear.

Threat actors don’t operate under the same constraints. Often well-funded and sponsored by nation-states with significant resources, they’re increasingly organized, strategic, and innovative.

That sophistication shows up in the tactics we face every day, from social engineering and ransomware to AI-driven impersonation attacks. We’re dealing with massive volumes of data, countless signals, and a very small window between detection and damage.

No human team, no matter how talented or how numerous, can manually sift through that noise at the speed required.

Discovering a force multiplier

Nothing in cybersecurity is 100% foolproof. I never “set it and forget it.” But for institutions balancing rising threats and finite resources, the Darktrace ActiveAI Security Platform™ offers something incredibly valuable: peace of mind through speed and scale.

It closes the gap between detection and response in a way humans can’t possibly match. At the speed of light, it can quarantine, investigate, and contain anomalous activity.

I’ve purchased and deployed Darktrace three separate times at three different institutions because I’ve seen firsthand what it can do and what it enables teams like mine to achieve.

I first encountered Darktrace while serving as CIO for a large multi-campus college system. What caught my attention was Darktrace's Self-Learning AI, and its ability to learn what "normal" looked like across our network. Instead of relying solely on static signatures or rigid rules, Darktrace built a behavioral baseline unique to our environment and alerted us in real time when something simply didn’t look right.

In higher education, where strict lockdowns aren’t realistic, that behavioral model made all the difference. We deployed it across five campuses, and the impact was immediate. Operating 24/7, Darktrace surfaced threats in ways our team couldn’t replicate manually.

Over time, the Darktrace platform evolved alongside the changing threat landscape, expanding into intrusion prevention, cloud visibility, and email security. At subsequent institutions, including Washington College, Darktrace was one of my first strategic investments.

Revealing the hidden threat other tools missed

One of the most surprising investigations of my career involved a data leak. Leadership suspected sensitive information from high-level meetings was being exposed, but our traditional tools couldn’t provide any answers.

Using Darktrace’s deep network visibility, down to packet-level data, we traced unusual connections to our CCTV camera system, which had been configured with a manufacturer’s default password. A small group of employees had hacked into the CCTV cameras, accessed audio-enabled recordings from boardroom meetings, and stored copies locally.

No other tool in our environment could have surfaced those connections the way Darktrace did. It was a clear example of why using AI to deeply understand how your organization, systems, and tools normally behave, matters: threats and risks don’t always look the way we expect.

Elevating a D-rating into a A-level security program

When I arrived at my last CISO role, the institution had recently experienced a significant ransomware attack. Attackers located  data  which informed their setting  ransom demands to an amount they knew would likely result in payment. It was a sobering example of how calculated and strategic modern cybercriminals have become.

Third-party cyber ratings reflected that reality, with a  D rating.

To raise the bar, we implemented a comprehensive security program and integrated layered defenses; -deploying state of the art tools and methods-  across the environment, with Darktrace at its core.

After a 90-day learning period to establish our behavioral baseline, we transitioned the platform into fully autonomous mode. In a single 30-day span, Darktrace conducted more than 2,500 investigations and autonomously resolved 92% of all false positives.

For a small team, that’s transformative. Instead of drowning in alerts, my staff focused on less than  200 meaningful cases that warranted human review.

Today, we maintain a perfect A rating from third-party assessors and have remained cybersafe.

Peace of mind isn’t about complacency

The effect of Darktrace as a force multiplier has a real human impact.

With the time reclaimed through automation, we expanded community education programs and implemented simulated phishing exercises. Through sustained training and awareness efforts, we reduced social engineering susceptibility from nearly 45% to under 5%.

On a personal level, Darktrace allows me to sleep better at night and take time off knowing we have intelligent systems monitoring and responding around the clock. For any CIO or CISO carrying institutional risk on their shoulders, that matters.

The next era: AI vs. AI

A new chapter in cybersecurity is unfolding as adversaries leverage AI to enhance scale, speed, and believability. Phishing campaigns are more personalized, impersonation attempts are more precise, and deepfake video technology, including live video, is disturbingly authentic. At the same time, organizations are rapidly adopting AI across their own environments —from GenAI assistants to embedded tools to autonomous agents. These systems don’t operate within fixed rules. They act across email, cloud, SaaS, and identity systems, often with broad permissions, and their behavior can evolve over time in ways that are difficult to predict or control.

That creates a new kind of security challenge. It’s not just about defending against AI-powered threats but understanding and governing how AI behaves within your environment, including what it can access, how it acts, and where risk begins to emerge.

From my perspective, this is a natural next step for Darktrace.

Darktrace brings a level of maturity and behavioral understanding uniquely suited to the complexity of AI environments. Self-Learning AI learns the normal patterns of each business to interpret context, uncover subtle intent, and detect meaningful deviations without relying on predefined rules or signatures. Extending into securing AI by bringing real-time visibility and control to GenAI assistants, AI agents, development environments and Shadow AI, feels like the logical evolution of what Darktrace already does so well.

Just as importantly, Darktrace is already built for dynamic, cross-domain environments where risk doesn’t sit in a single tool or control plane. In higher education, activity already spans multiple systems and, with AI, that interconnection only accelerates.

Having deployed Darktrace multiple times, I have confidence it’s uniquely positioned to lead in this space and help organizations adopt AI with greater visibility and control.

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Since authoring this blog, Irving Bruckstein has transitioned to the role of Chief Executive Officer of the Cyberaigroup.

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About the author
Irving Bruckstein
CEO CyberAIgroup

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May 11, 2026

The Next Step After Mythos: Defending in a World Where Compromise is Expected

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Is Anthropic’s Mythos a turning point for cybersecurity?

Anthropic’s recent announcements around their Mythos model, alongside the launch of Project Glasswing, have generated significant interest across the cybersecurity industry.

The closed-source nature of the Mythos model has understandably attracted a degree of skepticism around some of the claims being made. Additionally, Project Glasswing was initially positioned as a way for software vendors to accelerate the proactive discovery of vulnerabilities in their own code; however, much of the attention has focused on the potential for AI to identify exploitable vulnerabilities for those with malicious intent.

Putting questions around the veracity of those claims to one side – which, for what it’s worth, do appear to be at least partially endorsed by independent bodies such as the UK’s AI Security Institute – this should not be viewed as a critical turning point for the industry. Rather, it reflects the natural direction of travel.

How Mythos affects cybersecurity teams  

At Darktrace, extolling the virtues of AI within cybersecurity is understandably close to our hearts. However, taking a step back from the hype, we’d like to consider what developments like this mean for security teams.

Whether it’s Mythos or another model yet to be released, it’s worth remembering that there is no fundamental difference between an AI discovered vulnerability and one discovered by a human. The change is in the pace of discovery and, some may argue, the lower the barrier to entry.

In the hands of a software developer, this is unquestionably positive. Faster discovery enables earlier remediation and more proactive security. But in the hands of an attacker, the same capability will likely lead to a greater number of exploitable vulnerabilities being used in the wild and, critically, vulnerabilities that are not yet known to either the vendor or the end user.

That said, attackers have always been able to find exploitable vulnerabilities and use them undetected for extended periods of time. The use of AI does not fundamentally change this reality, but it does make the process faster and, unfortunately, more likely to occur at scale.

While tools such as Darktrace / Attack Surface Management and / Proactive Exposure Management  can help security teams prioritize where to patch, the emergence of AI-driven vulnerability discovery reinforces an important point: patching alone is not a sufficient control against modern cyber-attacks.

Rethinking defense for a world where compromise is expected

Rather than assuming vulnerabilities can simply be patched away, defenders are better served by working from the assumption that their software is already vulnerable - and always will be -and build their security strategy accordingly.

Under that assumption, defenders should expect initial access, particularly across internet exposed assets, to become easier for attackers. What matters then is how quickly that foothold is detected, contained, and prevented from expanding.

For defenders, this places renewed emphasis on a few core capabilities:

  • Secure-by-design architectures and blast radius reduction, particularly around identity, MFA, segmentation, and Zero Trust principles
  • Early, scalable detection and containment, favoring behavioral and context-driven signals over signatures alone
  • Operational resilience, with the expectation of more frequent early-stage incidents that must be managed without burning out teams

How Darktrace helps organizations proactively defend against cyber threats

At Darktrace, we support security teams across all three of these critical capabilities through a multi-layered AI approach. Our Self-Learning AI learns what’s normal for your organization, enabling real-time threat detection, behavioral prediction, incident investigation and autonomous response. - all while empowering your security team with visibility and control.

To learn more about Darktrace’s application of AI to cybersecurity download our White Paper here.  

Reducing blast radius through visibility and control

Secure-by-design principles depend on understanding how users, devices, and systems behave. By learning the normal patterns of identity and network activity, Darktrace helps teams identify when access is being misused or when activity begins to move beyond expected boundaries. This makes it possible to detect and contain lateral movement early, limiting how far an attacker can progress even after initial access.

Detecting and containing threats at the earliest stage  

As AI accelerates vulnerability discovery, defenders need to identify exploitation before it is formally recognized. Darktrace’s behavioral understanding approach enables detection of subtle deviations from normal activity, including those linked to previously unknown vulnerabilities.

A key example of this is our research on identifying cyber threats before public CVE disclosures, demonstrating that assessing activity against what is normal for a specific environment, rather than relying on predefined indicators of compromise, enables detection of intrusions exploiting previously unknown vulnerabilities days or even weeks before details become publicly available.

Additionally, our Autonomous Response capability provides fast, targeted containment focused on the most concerning events, while allowing normal business operations to continue. This has consistently shown that even when attackers use techniques never seen before, Darktrace’s Autonomous Response can contain threats before they have a chance to escalate.

Scaling response without increasing operational burden

As early-stage incidents become more frequent, the ability to investigate and respond efficiently becomes critical. Darktrace’s Cyber AI Analyst’s AI-driven investigation capabilities automatically correlate activity across the environment, prioritizing the most significant threats and reducing the need for manual triage. This allows security teams to respond faster and more consistently, without increasing workload or burnout.

What effective defense looks like in an AI-accelerated landscape

Developments like Mythos highlight a reality that has been building for some time: the window between exposure and exploitation is shrinking, and in many cases, it may disappear entirely. In that environment, relying on patching alone becomes increasingly reactive, leaving little room to respond once access has been established.

The more durable approach is to assume that compromise will occur and focus on controlling what happens next. That means identifying early signs of misuse, containing threats before they spread, and maintaining visibility across the environment so that isolated signals can be understood in context.

AI plays a role on both sides of this equation. While it enables attackers to move faster, it also gives defenders the ability to detect subtle changes in behavior, prioritize what matters, and respond in real time. The advantage will not come from adopting AI in isolation, but from applying it in a way that reduces the gap between detection and action.

AI may be accelerating parts of the attack lifecycle, but the fundamentals of defense, detection, and containment still apply. If anything, they matter more than ever – and AI is just as powerful a tool for defenders as it is for attackers.

To learn more about Darktrace and Mythos read more on our blog: Mythos vs Ethos: Defending in an Era of AI‑Accelerated Vulnerability Discovery

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Toby Lewis
Head of Threat Analysis
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