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July 16, 2025

Introducing the AI Maturity Model for Cybersecurity

The AI Maturity Model for Cybersecurity is the most detailed guide of its kind, grounded in real use cases and expert insight. It empowers CISOs to make strategic decisions, not just about what AI to adopt, but how to do it in a way that strengthens their organization over time and achieves successful outcomes.
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
Ashanka Iddya
Senior Director, Product Marketing
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16
Jul 2025

AI adoption in cybersecurity: Beyond the hype

Security operations today face a paradox. On one hand, artificial intelligence (AI) promises sweeping transformation from automating routine tasks to augmenting threat detection and response. On the other hand, security leaders are under immense pressure to separate meaningful innovation from vendor hype.

To help CISOs and security teams navigate this landscape, we’ve developed the most in-depth and actionable AI Maturity Model in the industry. Built in collaboration with AI and cybersecurity experts, this framework provides a structured path to understanding, measuring, and advancing AI adoption across the security lifecycle.

Overview of AI maturity levels in cybersecurity

Why a maturity model? And why now?

In our conversations and research with security leaders, a recurring theme has emerged:

There’s no shortage of AI solutions, but there is a shortage of clarity and understanding of AI uses cases.

In fact, Gartner estimates that “by 2027, over 40% of Agentic AI projects will be canceled due to escalating costs, unclear business value, or inadequate risk controls. Teams are experimenting, but many aren’t seeing meaningful outcomes. The need for a standardized way to evaluate progress and make informed investments has never been greater.

That’s why we created the AI Security Maturity Model, a strategic framework that:

  • Defines five clear levels of AI maturity, from manual processes (L0) to full AI Delegation (L4)
  • Delineating the outcomes derived between Agentic GenAI and Specialized AI Agent Systems
  • Applies across core functions such as risk management, threat detection, alert triage, and incident response
  • Links AI maturity to real-world outcomes like reduced risk, improved efficiency, and scalable operations

[related-resource]

How is maturity assessed in this model?

The AI Maturity Model for Cybersecurity is grounded in operational insights from nearly 10,000 global deployments of Darktrace's Self-Learning AI and Cyber AI Analyst. Rather than relying on abstract theory or vendor benchmarks, the model reflects what security teams are actually doing, where AI is being adopted, how it's being used, and what outcomes it’s delivering.

This real-world foundation allows the model to offer a practical, experience-based view of AI maturity. It helps teams assess their current state and identify realistic next steps based on how organizations like theirs are evolving.

Why Darktrace?

AI has been central to Darktrace’s mission since its inception in 2013, not just as a feature, but the foundation. With over a decade of experience building and deploying AI in real-world security environments, we’ve learned where it works, where it doesn’t, and how to get the most value from it.

We've learned that modern businesses operate within a vast, interconnected ecosystem which introduces new complexities and vulnerabilities that make traditional cybersecurity approaches unsustainable. While many vendors use machine learning, not all AI tools are the same, and not all are created equal.

Darktrace’s Self-Learning AI uses a multi-layered AI approach, learning your unique organization to deliver proactive and resilient defense against today’s sophisticated threats. By strategically integrating a diverse set of AI techniques, such as machine learning, deep learning, LLMs, and natural language processing, both sequentially and hierarchically, our multi-layered AI approach provides a robust defense mechanism that is unique to your organization and adapts to the evolving threat landscape.

This model reflects that insight, helping security leaders find the right path forward for their people, processes, and tools.

Security teams today are asking big, important questions:

  • What should we actually use AI for?
  • How are other teams using it — and what’s working?
  • What are vendors offering, and what’s just hype?
  • Will AI ever replace people in the SOC?

These questions are valid, and they’re not always easy to answer. That’s why we created this model: to help security leaders move past buzzwords and build a clear, realistic plan for applying AI across the SOC.

The structure: From experimentation to autonomy

The model outlines five levels of maturity :

L0 – Manual Operations: Processes are mostly manual with limited automation of some tasks.

L1 – Automation Rules: Manually maintained or externally-sourced automation rules and logic are used wherever possible.

L2 – AI Assistance: AI assists research but is not trusted to make good decisions. This includes GenAI agents requiring manual oversight for errors.

L3 – AI Collaboration: Specialized cybersecurity AI agent systems  with business technology context are trusted with specific tasks and decisions. GenAI has limited uses where errors are acceptable.

L4 – AI Delegation: Specialized AI agent systems with far wider business operations and impact context perform most cybersecurity tasks and decisions independently, with only high-level oversight needed.

Each level reflects a shift, not only in technology, but in people and processes. As AI matures, analysts evolve from executors to strategic overseers.

Strategic benefits for security leaders

The maturity model isn’t just about technology adoption it’s about aligning AI investments with measurable operational outcomes. Here’s what it enables:

SOC fatigue is real, and AI can help

Most teams still struggle with alert volume, investigation delays, and reactive processes. AI adoption is inconsistent and often siloed. When integrated well, AI can make a meaningful difference in making security teams more effective

GenAI is error prone, requiring strong human oversight

While there is a lot of hype around GenAI agentic systems, teams will need to account for inaccuracy and hallucination in Agentic GenAI systems.

AI’s real value lies in progression

The biggest gains don’t come from isolated use cases, but from integrating AI across the lifecycle, from preparation through detection to containment and recovery.

Trust and oversight are key initially but evolves in later levels

Early-stage adoption keeps humans fully in control. By L3 and L4, AI systems act independently within defined bounds, freeing humans for strategic oversight.

People’s roles shift meaningfully

As AI matures, analyst roles consolidate and elevate from labor intensive task execution to high-value decision-making, focusing on critical, high business impact activities, improving processes and AI governance.

Outcome, not hype, defines maturity

AI maturity isn’t about tech presence, it’s about measurable impact on risk reduction, response time, and operational resilience.

[related-resource]

Outcomes across the AI Security Maturity Model

The Security Organization experiences an evolution of cybersecurity outcomes as teams progress from manual operations to AI delegation. Each level represents a step-change in efficiency, accuracy, and strategic value.

L0 – Manual Operations

At this stage, analysts manually handle triage, investigation, patching, and reporting manually using basic, non-automated tools. The result is reactive, labor-intensive operations where most alerts go uninvestigated and risk management remains inconsistent.

L1 – Automation Rules

At this stage, analysts manage rule-based automation tools like SOAR and XDR, which offer some efficiency gains but still require constant tuning. Operations remain constrained by human bandwidth and predefined workflows.

L2 – AI Assistance

At this stage, AI assists with research, summarization, and triage, reducing analyst workload but requiring close oversight due to potential errors. Detection improves, but trust in autonomous decision-making remains limited.

L3 – AI Collaboration

At this stage, AI performs full investigations and recommends actions, while analysts focus on high-risk decisions and refining detection strategies. Purpose-built agentic AI systems with business context are trusted with specific tasks, improving precision and prioritization.

L4 – AI Delegation

At this stage, Specialized AI Agent Systems performs most security tasks independently at machine speed, while human teams provide high-level strategic oversight. This means the highest time and effort commitment activities by the human security team is focused on proactive activities while AI handles routine cybersecurity tasks

Specialized AI Agent Systems operate with deep business context including impact context to drive fast, effective decisions.

Join the webinar

Get a look at the minds shaping this model by joining our upcoming webinar using this link. We’ll walk through real use cases, share lessons learned from the field, and show how security teams are navigating the path to operational AI safely, strategically, and successfully.

Find your place in the AI maturity model

Get the self-guided assessment designed to help you benchmark your current maturity level, identify key gaps, and prioritize next steps.

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
Ashanka Iddya
Senior Director, Product Marketing

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February 13, 2026

CVE-2026-1731: How Darktrace Sees the BeyondTrust Exploitation Wave Unfolding

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Note: Darktrace's Threat Research team is publishing now to help defenders. We will update continue updating this blog as our investigations unfold.

Background

On February 6, 2026, the Identity & Access Management solution BeyondTrust announced patches for a vulnerability, CVE-2026-1731, which enables unauthenticated remote code execution using specially crafted requests.  This vulnerability affects BeyondTrust Remote Support (RS) and particular older versions of Privileged Remote Access (PRA) [1].

A Proof of Concept (PoC) exploit for this vulnerability was released publicly on February 10, and open-source intelligence (OSINT) reported exploitation attempts within 24 hours [2].

Previous intrusions against Beyond Trust technology have been cited as being affiliated with nation-state attacks, including a 2024 breach targeting the U.S. Treasury Department. This incident led to subsequent emergency directives from  the Cybersecurity and Infrastructure Security Agency (CISA) and later showed attackers had chained previously unknown vulnerabilities to achieve their goals [3].

Additionally, there appears to be infrastructure overlap with React2Shell mass exploitation previously observed by Darktrace, with command-and-control (C2) domain  avg.domaininfo[.]top seen in potential post-exploitation activity for BeyondTrust, as well as in a React2Shell exploitation case involving possible EtherRAT deployment.

Darktrace Detections

Darktrace’s Threat Research team has identified highly anomalous activity across several customers that may relate to exploitation of BeyondTrust since February 10, 2026. Observed activities include:

-              Outbound connections and DNS requests for endpoints associated with Out-of-Band Application Security Testing; these services are commonly abused by threat actors for exploit validation.  Associated Darktrace models include:

o    Compromise / Possible Tunnelling to Bin Services

-              Suspicious executable file downloads. Associated Darktrace models include:

o    Anomalous File / EXE from Rare External Location

-              Outbound beaconing to rare domains. Associated Darktrace models include:

o   Compromise / Agent Beacon (Medium Period)

o   Compromise / Agent Beacon (Long Period)

o   Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

o   Compromise / Beacon to Young Endpoint

o   Anomalous Server Activity / Rare External from Server

o   Compromise / SSL Beaconing to Rare Destination

-              Unusual cryptocurrency mining activity. Associated Darktrace models include:

o   Compromise / Monero Mining

o   Compromise / High Priority Crypto Currency Mining

And model alerts for:

o    Compromise / Rare Domain Pointing to Internal IP

IT Defenders: As part of best practices, we highly recommend employing an automated containment solution in your environment. For Darktrace customers, please ensure that Autonomous Response is configured correctly. More guidance regarding this activity and suggested actions can be found in the Darktrace Customer Portal.  

Appendices

Potential indicators of post-exploitation behavior:

·      217.76.57[.]78 – IP address - Likely C2 server

·      hXXp://217.76.57[.]78:8009/index.js - URL -  Likely payload

·      b6a15e1f2f3e1f651a5ad4a18ce39d411d385ac7  - SHA1 - Likely payload

·      195.154.119[.]194 – IP address – Likely C2 server

·      hXXp://195.154.119[.]194/index.js - URL – Likely payload

·      avg.domaininfo[.]top – Hostname – Likely C2 server

·      104.234.174[.]5 – IP address - Possible C2 server

·      35da45aeca4701764eb49185b11ef23432f7162a – SHA1 – Possible payload

·      hXXp://134.122.13[.]34:8979/c - URL – Possible payload

·      134.122.13[.]34 – IP address – Possible C2 server

·      28df16894a6732919c650cc5a3de94e434a81d80 - SHA1 - Possible payload

References:

1.        https://nvd.nist.gov/vuln/detail/CVE-2026-1731

2.        https://www.securityweek.com/beyondtrust-vulnerability-targeted-by-hackers-within-24-hours-of-poc-release/

3.        https://www.rapid7.com/blog/post/etr-cve-2026-1731-critical-unauthenticated-remote-code-execution-rce-beyondtrust-remote-support-rs-privileged-remote-access-pra/

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About the author
Emma Foulger
Global Threat Research Operations Lead

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February 13, 2026

How AI is redefining cybersecurity and the role of today’s CIO

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Why AI is essential to modern security

As attackers use automation and AI to outpace traditional tools and people, our approach to cybersecurity must fundamentally change. That’s why one of my first priorities as Withum's CIO was to elevate cybersecurity from a technical function to a business enabler.

What used to be “IT’s problem” is now a boardroom conversation – and for good reason. Protecting our data, our people, and our clients directly impacts revenue, reputation and competitive positioning.  

As CIOs / CISOs, our responsibilities aren’t just keeping systems running, but enabling trust, protecting our organization's reputation, and giving the business confidence to move forward even as the digital world becomes less predictable. To pull that off, we need to know the business inside-out, understand risk, and anticipate what's coming next. That's where AI becomes essential.

Staying ahead when you’re a natural target

With more than 3,100 team members and over 1,000 CPAs (Certified Public Accountant), Withum’s operates in an industry that naturally attracts attention from attackers. Firms like ours handle highly sensitive financial and personal information, which puts us squarely in the crosshairs for sophisticated phishing, ransomware, and cloud-based attacks.

We’ve built our security program around resilience, visibility, and scale. By using Darktrace’s AI-powered platform, we can defend against both known and unknown threats, across email and network, without slowing our teams down.

Our focus is always on what we’re protecting: our clients’ information, our intellectual property, and the reputation of the firm. With Darktrace, we’re not just keeping up with the massive volume of AI-powered attacks coming our way, we’re staying ahead. The platform defends our digital ecosystem around the clock, detecting potential threats across petabytes of data and autonomously investigating and responding to tens of thousands of incidents every year.

Catching what traditional tools miss

Beyond the sheer scale of attacks, Darktrace ActiveAI Security PlatformTM is critical for identifying threats that matter to our business. Today’s attackers don’t use generic techniques. They leverage automation and AI to craft highly targeted attacks – impersonating trusted colleagues, mimicking legitimate websites, and weaving in real-world details that make their messages look completely authentic.

The platform, covering our network, endpoints, inboxes, cloud and more is so effective because it continuously learns what’s normal for our business: how our users typically behave, the business- and industry-specific language we use, how systems communicate, and how cloud resources are accessed. It picks up on minute details that would sail right past traditional tools and even highly trained security professionals.

Freeing up our team to do what matters

On average, Darktrace autonomously investigates 88% of all our security events, using AI to connect the dots across email, network, and cloud activity to figure out what matters. That shift has changed how our team works. Instead of spending hours sorting through alerts, we can focus on proactive efforts that actually strengthen our security posture.

For example, we saved 1,850 hours on investigating security issues over a ten-day period. We’ve reinvested the time saved into strengthening policies, refining controls, and supporting broader business initiatives, rather than spending endless hours manually piecing together alerts.

Real confidence, real results

The impact of our AI-driven approach goes well beyond threat detection. Today, we operate from a position of confidence, knowing that threats are identified early, investigated automatically, and communicated clearly across our organization.

That confidence was tested when we withstood a major ransomware attack by a well-known threat group. Not only were we able to contain the incident, but we were able to trace attacker activity and provided evidence to law enforcement. That was an exhilarating experience! My team did an outstanding job, and moments like that reinforce exactly why we invest in the right technology and the right people.

Internally, this capability has strengthened trust at the executive level. We share security reporting regularly with leadership, translating technical activity into business-relevant insights. That transparency reinforces cybersecurity as a shared responsibility, one that directly supports growth, continuity, and reputation.

Culturally, we’ve embedded security awareness into daily operations through mandatory monthly training, executive communication, and real-world industry examples that keep cybersecurity top of mind for every employee.

The only headlines we want are positive ones: Withum expanding services, Withum growing year over year. Security plays a huge role in making sure that’s the story we get to tell.

What’s next

Looking ahead, we’re expanding our use of Darktrace, including new cloud capabilities that extend AI-driven visibility and investigation into our AWS and Azure environments.

As I continue shaping our security team, I look for people with passion, curiosity, and a genuine drive to solve problems. Those qualities matter just as much as formal credentials in my view. Combined with AI, these attributes help us build a resilient, engaged security function with low turnover and high impact.

For fellow technology leaders, my advice is simple: be forward-thinking and embrace change. We must understand the business, the threat landscape, and how technology enables both. By augmenting human expertise rather than replacing it, AI allows us to move upstream by anticipating risk, advising the business, and fostering stronger collaboration across teams.

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