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July 24, 2024

The State of AI in Cybersecurity: Understanding AI Technologies

Part 4: This blog explores the findings from Darktrace’s State of AI Cybersecurity Report on security professionals' understanding of the different types of AI used in security programs. Get the latest insights into the evolving challenges, growing demand for skilled professionals, and the need for integrated security solutions by downloading the full report.
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.
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24
Jul 2024

About the State of AI Cybersecurity Report

Darktrace surveyed 1,800 CISOs, security leaders, administrators, and practitioners from industries around the globe. Our research was conducted to understand how the adoption of new AI-powered offensive and defensive cybersecurity technologies are being managed by organizations.

This blog continues the conversation from “The State of AI in Cybersecurity: Unveiling Global Insights from 1,800 Security Practitioners”. This blog will focus on security professionals’ understanding of AI technologies in cybersecurity tools.

To access download the full report, click here.

How familiar are security professionals with supervised machine learning

Just 31% of security professionals report that they are “very familiar” with supervised machine learning.

Many participants admitted unfamiliarity with various AI types. Less than one-third felt "very familiar" with the technologies surveyed: only 31% with supervised machine learning and 28% with natural language processing (NLP).

Most participants were "somewhat" familiar, ranging from 46% for supervised machine learning to 36% for generative adversarial networks (GANs). Executives and those in larger organizations reported the highest familiarity.

Combining "very" and "somewhat" familiar responses, 77% had familiarity with supervised machine learning, 74% generative AI, and 73% NLP. With generative AI getting so much media attention, and NLP being the broader area of AI that encompasses generative AI, these results may indicate that stakeholders are understanding the topic on the basis of buzz, not hands-on work with the technologies.  

If defenders hope to get ahead of attackers, they will need to go beyond supervised learning algorithms trained on known attack patterns and generative AI. Instead, they’ll need to adopt a comprehensive toolkit comprised of multiple, varied AI approaches—including unsupervised algorithms that continuously learn from an organization’s specific data rather than relying on big data generalizations.  

Different types of AI

Different types of AI have different strengths and use cases in cyber security. It’s important to choose the right technique for what you’re trying to achieve.  

Supervised machine learning: Applied more often than any other type of AI in cyber security. Trained on human attack patterns and historical threat intelligence.  

Large language models (LLMs): Applies deep learning models trained on extremely large data sets to understand, summarize, and generate new content. Used in generative AI tools.  

Natural language processing (NLP): Applies computational techniques to process and understand human language.  

Unsupervised machine learning: Continuously learns from raw, unstructured data to identify deviations that represent true anomalies.  

What impact will generative AI have on the cybersecurity field?

More than half of security professionals (57%) believe that generative AI will have a bigger impact on their field over the next few years than other types of AI.

Chart showing the types of AI expected to impact security the most
Figure 1: Chart from Darktrace's State of AI in Cybersecurity Report

Security stakeholders are highly aware of generative AI and LLMs, viewing them as pivotal to the field's future. Generative AI excels at abstracting information, automating tasks, and facilitating human-computer interaction. However, LLMs can "hallucinate" due to training data errors and are vulnerable to prompt injection attacks. Despite improvements in securing LLMs, the best cyber defenses use a mix of AI types for enhanced accuracy and capability.

AI education is crucial as industry expectations for generative AI grow. Leaders and practitioners need to understand where and how to use AI while managing risks. As they learn more, there will be a shift from generative AI to broader AI applications.

Do security professionals fully understand the different types of AI in security products?

Only 26% of security professionals report a full understanding of the different types of AI in use within security products.

Confusion is prevalent in today’s marketplace. Our survey found that only 26% of respondents fully understand the AI types in their security stack, while 31% are unsure or confused by vendor claims. Nearly 65% believe generative AI is mainly used in cybersecurity, though it’s only useful for identifying phishing emails. This highlights a gap between user expectations and vendor delivery, with too much focus on generative AI.

Key findings include:

  • Executives and managers report higher understanding than practitioners.
  • Larger organizations have better understanding due to greater specialization.

As AI evolves, vendors are rapidly introducing new solutions faster than practitioners can learn to use them. There's a strong need for greater vendor transparency and more education for users to maximize the technology's value.

To help ease confusion around AI technologies in cybersecurity, Darktrace has released the CISO’s Guide to Cyber AI. A comprehensive white paper that categorizes the different applications of AI in cybersecurity. Download the White Paper here.  

Do security professionals believe generative AI alone is enough to stop zero-day threats?

No! 86% of survey participants believe generative AI alone is NOT enough to stop zero-day threats

This consensus spans all geographies, organization sizes, and roles, though executives are slightly less likely to agree. Asia-Pacific participants agree more, while U.S. participants agree less.

Despite expecting generative AI to have the most impact, respondents recognize its limited security use cases and its need to work alongside other AI types. This highlights the necessity for vendor transparency and varied AI approaches for effective security across threat prevention, detection, and response.

Stakeholders must understand how AI solutions work to ensure they offer advanced, rather than outdated, threat detection methods. The survey shows awareness that old methods are insufficient.

To access the full report, click here.

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.
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The Darktrace Community

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March 2, 2026

What the Darktrace Annual Threat Report 2026 Means for Security Leaders

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The challenge for today’s CISOs

At the broadest level, the defining characteristic of cybersecurity in 2026 is the sheer pace of change shaping the environments we protect. Organizations are operating in ecosystems that are larger, more interconnected, and more automated than ever before – spanning cloud platforms, distributed identities, AI-driven systems, and continuous digital workflows.  

The velocity of this expansion has outstripped the slower, predictable patterns security teams once relied on. What used to be a stable backdrop is now a living, shifting landscape where technology, risk, and business operations evolve simultaneously. From this vantage point, the central challenge for security leaders isn’t reacting to individual threats, but maintaining strategic control and clarity as the entire environment accelerates around them.

Strategic takeaways from the Annual Threat Report

The Darktrace Annual Threat Report 2026 reinforces a reality every CISO feels: the center of gravity isn’t the perimeter, vulnerability management, or malware, but trust abused via identity. For example, our analysis found that nearly 70% of incidents in the Americas region begin with stolen or misused accounts, reflecting the global shift toward identity‑led intrusions.

Mass adoption of AI agents, cloud-native applications, and machine decision-making means CISOs now oversee systems that act on their own. This creates an entirely new responsibility: ensuring those systems remain safe, predictable, and aligned to business intent, even under adversarial pressure.

Attackers increasingly exploit trust boundaries, not firewalls – leveraging cloud entitlements, SaaS identity transitions, supply-chain connectivity, and automation frameworks. The rise of non-human identities intensifies this: credentials, tokens, and agent permissions now form the backbone of operational risk.

Boards are now evaluating CISOs on business continuity, operational recovery, and whether AI systems and cloud workloads can fail safely without cascading or causing catastrophic impact.

In this environment, detection accuracy, autonomous response, and blast radius minimization matter far more than traditional control coverage or policy checklists.

Every organization will face setbacks; resilience is measured by how quickly security teams can rise, respond, and resume momentum. In 2026, success will belong to those that adapt fastest.

Managing business security in the age of AI

CISO accountability in 2026 has expanded far beyond controls and tooling. Whether we asked for it or not, we now own outcomes tied to business resilience, AI trust, cloud assurance, and continuous availability. The role is less about certainty and more about recovering control in an environment that keeps accelerating.

Every major 2026 initiative – AI agents, third-party risk, cloud, or comms protection – connects to a single board-level question: Are we still in control as complexity and automation scale faster than humans?

Attackers are not just getting more sophisticated; they are becoming more automated. AI changes the economics of attack, lowering cost and increasing speed. That asymmetry is what CISOs are being measured against.

CISOs are no longer evaluated on tool coverage, but on the ability to assure outcomes – trust in AI adoption, resilience across cloud and identity, and being able to respond to unknown and unforeseen threats.

Boards are now explicitly asking whether we can defend against AI-driven threats. No one can predict every new behavior – survival depends on detecting malicious deviations from normal fast and responding autonomously.  

Agents introduce decision-making at machine speed. Governance, CI/CD scanning, posture management, red teaming, and runtime detection are no longer differentiators but the baseline.

Cloud security is no longer architectural, it is operational. Identity, control planes, and SaaS exposure now sit firmly with the CISO.

AI-speed threats already reshaping security in 2026

We’re already seeing clear examples of how quickly the threat landscape has shifted in 2026. Darktrace’s work on React2Shell exposed just how unforgiving the new tempo is: a honeypot stood up with an exposed React was hit in under two minutes. There was no recon phase, no gradual probing – just immediate, automated exploitation the moment the code appeared publicly. Exposure now equals compromise unless defenses can detect, interpret, and act at machine speed. Traditional operational rhythms simply don’t map to this reality.

We’re also facing the first wave of AI-authored malware, where LLMs generate code that mutates on demand. This removes the historic friction from the attacker side: no skill barrier, no time cost, no limit on iteration. Malware families can regenerate themselves, shift structure, and evade static controls without a human operator behind the keyboard. This forces CISOs to treat adversarial automation as a core operational risk and ensure that autonomous systems inside the business remain predictable under pressure.

The CVE-2026-1731 BeyondTrust exploitation wave reinforced the same pattern. The gap between disclosure and active, global exploitation compressed into hours. Automated scanning, automated payload deployment, coordinated exploitation campaigns, all spinning up faster than most organizations can push an emergency patch through change control. The vulnerability-to-exploit window has effectively collapsed, making runtime visibility, anomaly detection, and autonomous containment far more consequential than patching speed alone.

These cases aren’t edge scenarios; they represent the emerging norm. Complexity and automation have outpaced human-scale processes, and attackers are weaponizing that asymmetry.  

The real differentiator for CISOs in 2026 is less about knowing everything and more about knowing immediately when something shifts – and having systems that can respond at the same speed.

[related-resource]

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About the author
Mike Beck
Global CISO

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March 2, 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 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:

  • Compromise / Possible Tunnelling to Bin Services

Suspicious executable file downloads. Associated Darktrace models include:

  • Anomalous File / EXE from Rare External Location

Outbound beaconing to rare domains. Associated Darktrace models include:

  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Long Period)
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Beacon to Young Endpoint
  • Anomalous Server Activity / Rare External from Server
  • Compromise / SSL Beaconing to Rare Destination

Unusual cryptocurrency mining activity. Associated Darktrace models include:

  • Compromise / Monero Mining
  • Compromise / High Priority Crypto Currency Mining

And model alerts for:

  • 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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