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December 14, 2021

Log4Shell Vulnerability Detection & Response With Darktrace

Dec 2021

Learn how Darktrace's AI detects and responds to Log4Shell attacks. Explore real-world examples and see how Darktrace identified and mitigated cyber threats.

In this blog, we’ll take a look at the Log4Shell vulnerability and provide real-world examples of how Darktrace detects and responds to attacks attempting to leverage Log4Shell in the wild.

Log4Shell is now the well-known name for CVE-2021-44228 – a severity 10 zero-day exploiting a well-known Java logging utility known as Log4j. Vulnerabilities are discovered daily, and some are more severe than others, but the fact that this open source utility is nested into nearly everything, including the Mars Ingenuity drone, makes this that much more menacing. Details and further updates about Log4Shell are still emerging at the publication date of this blog.

Typically, zero-days with the power to reach this many systems are held close to the chest and only used by nation states for high value targets or operations. This one, however, was first discovered being used against Minecraft gaming servers, shared in chat amongst gamers.

While all steps should be taken to deploy mitigations to the Log4Shell vulnerability, these can take time. As evidenced here, behavioral detection can be used to look for signs of post-exploitation activity such as scanning, coin mining, lateral movement, and other activities.

Darktrace initially detected the Log4Shell vulnerability targeting one of our customers’ Internet-facing servers, as you will see in detail in an actual anonymized threat investigation below. This was highlighted and reported using Cyber AI Analyst, unpacked here by our SOC team. Please take note that this was using pre-existing algorithms without retraining classifiers or adjusting response mechanisms in reaction to Log4Shell cyber-attacks.

How Log4Shell works

The vulnerability works by taking advantage of improper input validation by the Java Naming and Directory Interface (JNDI). A command comes in from an HTTP user-agent, encrypted HTTPS connection, or even a chat room message, and the JNDI sends that to the target system in which it gets executed. Most libraries and applications have checks and protections in place to prevent this from happening, but as seen here, they get missed at times.

Various threat actors have started to leverage the vulnerability in attacks, ranging from indiscriminate crypto-mining campaigns to targeted, more sophisticated attacks.

Real-world example 1: Log4Shell exploited on CVE ID release date

Darktrace saw this first example on December 10, the same day the CVE ID was released. We often see publicly documented vulnerabilities being weaponized within days by threat actors. This attack hit an Internet-facing device in an organization’s demilitarized zone (DMZ). Darktrace had automatically classified the server as an Internet-facing device based on its behavior.

The organization had deployed Darktrace in the on-prem network as one of many coverage areas that include cloud, email and SaaS. In this deployment, Darktrace had good visibility of the DMZ traffic. Antigena was not active in this environment, and Darktrace was in detection-mode only. Despite this fact, the client in question was able to identify and remediate this incident within hours of the initial alert. The attack was automated and had the goal of deploying a crypto-miner known as Kinsing.

In this attack, the attacker made it harder to detect the compromise by encrypting the initial command injection using HTTPS over the more common HTTP seen in the wild. Despite this method being able to bypass traditional rules and signature-based systems Darktrace was able to spot multiple unusual behaviors seconds after the initial connection.

Initial compromise details

Through peer analysis Darktrace had previously learned what this specific DMZ device and its peer group normally do in the environment. During the initial exploitation, Darktrace detected various subtle anomalies that taken together made the attack obvious.

15:45:32 Inbound HTTPS connection to DMZ server from rare Russian IP — 45.155.205[.]233;
15:45:38 DMZ server makes new outbound connection to the same rare Russian IP using two new user agents: Java user agent and curl over a port that is unusual to serve HTTP compared to previous behavior;
15:45:39 DMZ server uses an HTTP connection with another new curl user agent (‘curl/7.47.0’) to the same Russian IP. The URI contains reconnaissance information from the DMZ server.

All this activity was detected not because Darktrace had seen it before, but because it strongly deviated from the regular ‘pattern of life’ for this and similar servers in this specific organization.

This server never reached out to rare IP addresses on the Internet, using user agents it never used before, over protocol and port combinations it never uses. Every point-in-time anomaly itself may have presented slightly unusual behavior – but taken together and analyzed in the context of this particular device and environment, the detections clearly tell a bigger story of an ongoing cyber-attack.

Darktrace detected this activity with various models, for example:

Anomalous Connection / New User Agent to IP Without Hostname
Anomalous Connection / Callback on Web Facing Device

Further tooling and crypto-miner download

Less than 90 minutes after the initial compromise, the infected server started downloading malicious scripts and executables from a rare Ukrainian IP 80.71.158[.]12.

The following payloads were subsequently downloaded from the Ukrainian IP in order:

hXXp://80.71.158[.]12//lh.sh
hXXp://80.71.158[.]12/Expl[REDACTED].class
hXXp://80.71.158[.]12/kinsing
hXXp://80.71.158[.]12//libsystem.so
hXXp://80.71.158[.]12/Expl[REDACTED].class

Using no threat intelligence or detections based on static indicators of compromise (IoC) such as IPs, domain names or file hashes, Darktrace detected this next step in the attack in real time.

The DMZ server in question never communicated with this Ukrainian IP address in the past over these uncommon ports. It is also highly unusual for this device and its peers to download scripts or executable files from this type of external destination, in this fashion. Shortly after these downloads, the DMZ server started to conduct crypto-mining.

Darktrace detected this activity with various models, for example:

Anomalous File / Script from Rare External Location
Anomalous File / Internet Facing System File Download
Device / Internet Facing System with High Priority Alert

Surfacing the Log4Shell incident immediately

In addition to Darktrace detecting each individual step of this attack in real time, Darktrace Cyber AI Analyst also surfaced the overarching security incident, containing a cohesive narrative for the overall attack, as the most high-priority incident within a week’s worth of incidents and alerts in Darktrace. This means that this incident was the most obvious and immediate item highlighted to human security teams as it unfolded. Darktrace’s Cyber AI Analyst found each stage of this incident and asked the very questions you would expect of your human SOC analysts. From the natural language report generated by the Cyber AI Analyst, a summary of each stage of the incident followed by the vital data points human analysts need, is presented in an easy to digest format. Each tab signifies a different part of this incident outlining the actual steps taken during each investigative process.

The result of this is no sifting through low-level alerts, no need to triage point-in-time detections, no putting the detections into a bigger incident context, no need to write a report. All of this was automatically completed by the AI Analyst saving human teams valuable time.

The below incident report was automatically created and could be downloaded as a PDF in various languages.

Figure 1: Darktrace’s Cyber AI Analyst surfaces multiple stages of the attack and explains its investigation process

Real-world example 2: Responding to a different attack using Log4Shell

On December 12, another organization’s Internet-facing server was initially compromised via Log4Shell. While the details of the compromise are different – other IoCs are involved – Darktrace detected and surfaced the attack similarly to the first example.

Interestingly, this organization had Darktrace Antigena in autonomous mode on their server, meaning the AI can take autonomous actions to respond to ongoing cyber-attacks. These responses can be delivered via a variety of mechanisms, for instance, API interactions with firewalls, other security tools, or native responses issued by Darktrace.

In this attack the rare external IP 164.52.212[.]196 was used for command and control (C2) communication and malware delivery, using HTTP over port 88, which was highly unusual for this device, peer group and organization.

Antigena reacted in real time in this organization, based on the specific context of the attack, without any human in the loop. Antigena interacted with the organization’s firewall in this case to block any connections to or from the malicious IP address – in this case 164.52.212[.]196 – over port 88 for 2 hours with the option of escalating the block and duration if the attack appears to persist. This is seen in the illustration below:

Figure 2: Antigena’s response

Here comes the trick: thanks to Self-Learning AI, Darktrace knows exactly what the Internet-facing server usually does and does not do, down to each individual data point. Based on the various anomalies, Darktrace is certain that this represents a major cyber-attack.

Antigena now steps in and enforces the regular pattern of life for this server in the DMZ. This means the server can continue doing whatever it normally does – but all the highly anomalous actions are interrupted as they occur in real time, such as speaking to a rare external IP over port 88 serving HTTP to download executables.

Of course the human can change or lift the block at any given time. Antigena can also be configured to be in human confirmation mode, having the human in the loop at certain times during the day (e.g. office hours) or at all times, depending on an organization’s needs and requirements.

Conclusion

This blog illustrates further aspects of cyber-attacks leveraging the Log4Shell vulnerability. It also demonstrates how Darktrace detects and responds to zero-day attacks if Darktrace has visibility of the attacked entities.

While Log4Shell is dominating the IT and security news, similar vulnerabilities have surfaced in the past and will appear in the future. We’ve spoken about our approach to detecting and responding to similar vulnerabilities and surrounding cyber-attacks before, for instance:

the recent Gitlab vulnerability;
the ProxyShell Exchange Server vulnerabilities when they were still a zero-day;
and the Citrix Netscaler vulnerability.

As always, companies should aim for a defense-in-depth strategy combining preventative security controls with detection and response mechanisms, as well as strong patch management.

Thanks to Brianna Leddy (Darktrace’s Director of Analysis) for her insights on the above threat find.

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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.

Author

Max Heinemeyer

Global Field CISO

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

Justin Fier

SVP, Red Team Operations

Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.

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Email

February 13, 2025

Why Darktrace / EMAIL excels against APTs

What are APTs?

An Advanced Persistent Threat (APT) describes an adversary with sophisticated levels of expertise and significant resources, with the ability to carry out targeted cyber campaigns. These campaigns may penetrate an organization and remain undetected for long periods, allowing attackers to gather intelligence or cause damage over time.

Over the last few decades, the term APT has evolved from being almost exclusively associated with nation-state actors to a broader definition that includes highly skilled, well-resourced threat groups. While still distinct from mass, opportunistic cybercrime or "spray and pray" attacks, APT now refers to the elite tier of adversaries, whether state-sponsored or not, who demonstrate advanced capabilities, persistence, and a clear strategic focus. This shift reflects the growing sophistication of cyber threats, where non-state actors can now rival nation-states in executing covert, methodical intrusions to achieve long-term objectives.

These attacks are resource-intensive for threat actors to execute, but the potential rewards—ranging from financial gain to sensitive data theft—can be significant. In 2020, Business Email Compromise (BEC) attacks netted cybercriminals over $1.8 billion.¹

And recently, the advent of AI has helped to automate launching these attacks, lowering the barriers to entry and making it more efficient to orchestrate the kind of attack that might previously have taken weeks to create. Research shows that AI can do 90% of a threat actor’s work² – reducing time-to-target by automating tasks rapidly and avoiding errors in phishing communications. Email remains the most popular vector for initiating these sophisticated attacks, making it a critical battleground for cyber defense.

What makes APTs so successful?

The success of Advanced Persistent Threats (APTs) lies in their precision, persistence, and ability to exploit human and technical vulnerabilities. These attacks are carefully tailored to specific targets, using techniques like social engineering and spear phishing to gain initial access.

Once inside, attackers move laterally through networks, often remaining undetected for months or even years, silently gathering intelligence or preparing for a decisive strike. Alternatively, they might linger inside an account within the M365 environment, which could be even more valuable in terms of gathering information – in 2023 the average time to identify a breach in 2023 was 204 days.³‍

The subtle and long-term outlook nature of APTs makes them highly effective, as traditional security measures often fail to identify the subtle signs of compromise.

How Darktrace’s approach is designed to catch the most advanced threats

Luckily for our customers, Darktrace’s AI approach is uniquely equipped to detect and neutralize APTs. Unlike the majority of email security solutions that rely on static rules and signatures, or that train their AI on previous known-bad attack patterns, Darktrace leverages Self-Learning AI that baselines normal patterns of behavior within an organization, to immediately detect unusual activity that may signal an APT in progress.

But in the modern era of email threats, no email security solution can guarantee 100% effectiveness. Because attackers operate with great sophistication, carefully adapting their tactics to evade detection – whether by altering attachments, leveraging compromised accounts, or moving laterally across an organization – a siloed security approach risks missing these subtle, multi-domain threats. That’s why a robust defense-in-depth strategy is essential to mitigate APTs.

Real-world threat finds: Darktrace / EMAIL in action

Let’s take a look at some real-world scenarios where Darktrace / EMAIL stopped tactics associated with APT campaigns in their tracks – from adversary-in-the-middle attacks to suspicious lateral movement.

1: How Darktrace disrupted an adversary-in-the-middle attack by identifying abnormal login redirects and blocking credential exfiltration

In October 2024, Darktrace detected an adversary-in-the-middle (AiTM) attack targeting a Darktrace customer. The attack began with a phishing email from a seemingly legitimate Dropbox address, which contained multiple link payloads inviting the recipient to access a file. Other solutions would have struggled to catch this attack, as the initial AitM attack was launched through delivering a malicious URL through a trusted vendor or service. Once compromised, the threat actor could have laid low on the target account, gathering reconnaissance, without detection from the email security solution.

Darktrace / EMAIL identified the abnormal login redirects and flagged the suspicious activity. Darktrace / IDENTITY then detected unusual login patterns and blocked credential exfiltration attempts, effectively disrupting the attack and preventing the adversary from gaining unauthorized access. Read more.

Figure 1: Overview of the malicious email in the Darktrace / EMAIL console, highlighting Dropbox associated content/link payloads

2: How Darktrace stopped lateral movement to block NTLM hash theft

In early 2024, Darktrace detected an attack by the TA577 threat group, which aimed to steal NTLM hashes to gain unauthorized access to systems. The attack began with phishing emails containing ZIP files that connected to malicious infrastructure.

A traditional email security solution would have likely missed this attack by focusing too heavily on analyzing the zip file payloads or relying on reputation analysis to understand whether the infrastructure was registered as bad before this activity was a recognized IoC.

Because it correlates activity across domains, Darktrace identified unusual lateral movement within the network and promptly blocked the attempts to steal NTLM hashes, effectively preventing the attackers from accessing sensitive credentials and securing the network. Read more.

Figure 2: A summary of anomaly indicators seen for a campaign email sent by TA577, as detected by Darktrace / EMAIL

3: How Darktrace prevented the WarmCookie backdoor deployment embedded in phishing emails

In mid-2024, Darktrace identified a phishing campaign targeting organizations with emails impersonating recruitment firms. These emails contained malicious links that, when clicked, deployed the WarmCookie backdoor.

These emails are difficult to detect, as they use social engineering tactics to manipulate users into engaging with emails and following the embedded malicious links – but if a security solution is not analysing content and context, these could be allowed through.

In several observed cases across customer environments, Darktrace detected and blocked the suspicious behavior associated with WarmCookie that had already managed to evade customers’ native email security. By using behavioral analysis to correlate anomalous activity across the digital estate, Darktrace was able to identify the backdoor malware strain and notify customers. Read more.

Conclusion

These threat examples highlight a key principle of the Darktrace approach – that a backwards-facing approach grounded in threat intelligence will always be one step behind.

Most threat actors operate in campaigns, carefully crafting attacks and testing them across multiple targets. Once a campaign is identified, good defenders and traditional security solutions quickly update their defenses with new threat intelligence, rules, and signatures. However, APTs have the resources to rapidly adapt – spinning up new infrastructure, modifying payloads and altering their attack footprint to evade detection.

This is where Darktrace / EMAIL excels. Only by analyzing each user, message and interaction can an email security solution hope to catch the types of highly-sophisticated attacks that have the potential to cause major reputational and financial damage. Darktrace / EMAIL ensures that even the most subtle threats are detected and blocked with autonomous response, before causing impact – helping organizations remain one step ahead of increasingly adaptive threat actors.

Download the Darktrace / EMAIL Solution Brief

Discover the most advanced cloud-native AI email security solution to protect your domain and brand while preventing phishing, novel social engineering, business email compromise, account takeover, and data loss.

Gain up to 13 days of earlier threat detection and maximize ROI on your current email security
Experience 20-25% more threat blocking power with Darktrace / EMAIL
Stop the 58% of threats bypassing traditional email security

‍

References

[1] FBI Internet Crime Report 2020

[2] https://www.optiv.com/insights/discover/blog/future-security-automation-how-ai-machine-learning-and-automation-are

[3] IBM Cost of a Data Breach Report 2023

‍

About the author

Carlos Gray

Product Manager

Blog

Compliance

February 11, 2025

NIS2 Compliance: Interpreting 'State-of-the-Art' for Organisations

NIS2 Background

17 October 2024 marked the deadline for European Union (EU) Member States to implement the NIS2 Directive into national law. The Directive aims to enhance the EU’s cybersecurity posture by establishing a high common level of cybersecurity for critical infrastructure and services. It builds on its predecessor, the 2018 NIS Directive, by expanding the number of sectors in scope, enforcing greater reporting requirements and encouraging Member States to ensure regulated organisations adopt ‘state-of-the-art' security measures to protect their networks, OT and IT systems.

The challenge of NIS2 & 'state-of-the-art'

Preamble (51) - "Member States should encourage the use of any innovative technology, including artificial intelligence, the use of which could improve the detection and prevention of cyberattacks, enabling resources to be diverted towards cyberattacks more effectively."

Article 21 - calls on Member States to ensure that essential and important entities “take appropriate and proportionate” cyber security measures, and that they do so by “taking into account the state-of-the-art and, where applicable, relevant European and international standards, as well as the cost of implementation.”

Regulartory expectations and ambiguity of NIS2

While organisations in scope can rely on technical guidance provided by ENISA¹ , the EU’s agency for cybersecurity, or individual guidelines provided by Member States or Public-Private Partnerships where they have been published,² the mention of ‘state-of-the-art' remains up to interpretation in most Member States. The use of the phrase implies that cybersecurity measures must evolve continuously to keep pace with emerging threats and technological advancements without specifying what ‘state-of-the-art’ actually means for a given context and risk.³

This ambiguity makes it difficult for organisations to determine what constitutes compliance at any given time and could lead to potential inconsistencies in implementation and enforcement. Moreover, the rapid pace of technological change means that what is considered "state-of-the-art" today will become outdated, further complicating compliance efforts.

However, this is not unique to NIS regulation. As EU scholars have noted, while “state-of-the-art" is widely referred to in legal text relating to technology, there is no standardised legal definition of what it actually constitutes.⁴

Defining state-of-the-art cybersecurity

In this blog, we outline technical considerations for state-of-the-art cybersecurity. We draw from expertise within our own business and in academia as well as guidelines and security standards set by national agencies, such as Germany’s Federal Office for Information Security (BSI) or Spain’s National Security Framework (ENS), to put forward five criteria to define state-of-the-art cybersecurity.

The five core criteria include:

Continuous monitoring
Incident correlation
Detection of anomalous activity
Autonomous response
Proactive cyber resilience

These principles build on long-standing security considerations, such as business continuity, vulnerability management and basic security hygiene practices.

Although these considerations are written in the context of the NIS2 Directive, they are likely to also be relevant for other jurisdictions. We hope these criteria help organisations understand how to best meet their responsibilities under the NIS2 Directive and assist Competent Authorities in defining compliance expectations for the organisations they regulate.

Ultimately, adopting state-of-the-art cyber defences is crucial for ensuring that organisations are equipped with the best tools to combat new and fast-growing threats. Leading technical authorities, such as the UK National Cyber Security Centre (NCSC), recognise that adoption of AI-powered cyber defences will offset the increased volume and impact of AI on cyber threats.⁵

State of the art cybersecurity in the context of NIS2

1. Continuous monitoring

Continuous monitoring is required to protect an increasingly complex attack surface from attackers.

First, organisations' attack surfaces have expanded following the widespread adoption of hybrid or cloud infrastructures and the increased adoption of connected Internet of Things (IoT) devices.⁶ This exponential growth creates a complex digital environment for organisations, making it difficult for security teams to track all internet-facing assets and identify potential vulnerabilities.

Second, with the significant increase in the speed and sophistication of cyber-attacks, organisations face a greater need to detect security threats and non-compliance issues in real-time.

Continuous monitoring, defined by the U.S. National Institute of Standards and Technology (NIST) as the ability to maintain “ongoing awareness of information security, vulnerabilities, and threats to support organizational risk management decisions,”⁷ has therefore become a cornerstone of an effective cybersecurity strategy. By implementing continuous monitoring, organisations can ensure a real-time understanding of their attack surface and that new external assets are promptly accounted for. For instance, Spain’s technical guidelines for regulation, as set forth by the National Security Framework (Royal Decree 311/2022), highlight the importance of adopting continuous monitoring to detect anomalous activities or behaviours and to ensure timely responses to potential threats (article 10).⁸

This can be achieved through the following means:

All assets that form part of an organisation's estate, both known and unknown, must be identified and continuously monitored for current and emerging risks. Germany’s BSI mandates the continuous monitoring of all protocol and logging data in real-time (requirement #110).⁹ This should be conducted alongside any regular scans to detect unknown devices or cases of shadow IT, or the use of unauthorised or unmanaged applications and devices within an organisation, which can expose internet-facing assets to unmonitored risks. Continuous monitoring can therefore help identify potential risks and high-impact vulnerabilities within an organisation's digital estate and eliminate potential gaps and blind spots.

Organisations looking to implement more efficient continuous monitoring strategies may turn to automation, but, as the BSI notes, it is important for responsible parties to be immediately warned if an alert is raised (reference 110).¹⁰ Following the BSI’s recommendations, the alert must be examined and, if necessary, contained within a short period of time corresponding with the analysis of the risk at hand.

Finally, risk scoring and vulnerability mapping are also essential parts of this process. Looking across the Atlantic, the US’ National Institute of Standards and Technology (NIST) defines continuous monitoring as “maintaining ongoing awareness of information security, vulnerabilities, and threats to support organizational risk management decisions”.¹¹ Continuous monitoring helps identify potential risks and significant vulnerabilities within an organisation's digital assets, fostering a dynamic understanding of risk. By doing so, risk scoring and vulnerability mapping allows organisations to prioritise the risks associated with their most critically exposed assets.

2. Correlation of incidents across your entire environment

Viewing and correlating incident alerts when working with different platforms and tools poses significant challenges to SecOps teams. Security professionals often struggle to cross-reference alerts efficiently, which can lead to potential delays in identifying and responding to threats. The complexity of managing multiple sources of information can overwhelm teams, making it difficult to maintain a cohesive understanding of the security landscape.

This fragmentation underscores the need for a centralised approach that provides a "single pane of glass" view of all cybersecurity alerts. These systems streamline the process of monitoring and responding to incidents, enabling security teams to act more swiftly and effectively. By consolidating alerts into a unified interface, organisations can enhance their ability to detect and mitigate threats, ultimately improving their overall security posture.

To achieve consolidation, organisations should consider the role automation can play when reviewing and correlating incidents. This is reflected in Spain’s technical guidelines for national security regulations regarding the requirements for the “recording of activity” (reinforcement R5).¹² Specifically, the guidelines state that:

"The system shall implement tools to analyses and review system activity and audit information, in search of possible or actual security compromises. An automatic system for collection of records, correlation of events and automatic response to them shall be available”.¹³

Similarly, the German guidelines stress that automated central analysis is essential not only for recording all protocol and logging data generated within the system environment but also to ensure that the data is correlated to ensure that security-relevant processes are visible (article 115).¹⁴

Correlating disparate incidents and alerts is especially important when considering the increased connectivity between IT and OT environments driven by business and functional requirements. Indeed, organisations that believe they have air-gapped systems are now becoming aware of points of IT/OT convergence within their systems. It is therefore crucial for organisations managing both IT and OT environments to be able to visualise and secure devices across all IT and OT protocols in real-time to identify potential spillovers.

By consolidating data into a centralised system, organisations can achieve a more resilient posture. This approach exposes and eliminates gaps between people, processes, and technology before they can be exploited by malicious actors. As seen in the German and Spanish guidelines, a unified view of security alerts not only enhances the efficacy of threat detection and response but also ensures comprehensive visibility and control over the organisation's cybersecurity posture.

3. Detection of anomalous activity

Recent research highlights the emergence of a "new normal" in cybersecurity, marked by an increase in zero-day vulnerabilities. Indeed, for the first time since sharing their annual list, the Five Eyes intelligence alliance reported that in 2023, the majority of the most routinely exploited vulnerabilities were initially exploited as zero-days.¹⁵

To effectively combat these advanced threats, policymakers, industry and academic stakeholders alike recognise the importance of anomaly-based techniques to detect both known and unknown attacks.

As AI-enabled threats become more prevalent,¹⁶ traditional cybersecurity methods that depend on lists of "known bads" are proving inadequate against rapidly evolving and sophisticated attacks. These legacy approaches are limited because they can only identify threats that have been previously encountered and cataloged. However, cybercriminals are constantly developing new, never-before-seen threats, such as signatureless ransomware or living off the land techniques, which can easily bypass these outdated defences.

The importance of anomaly detection in cybersecurity can be found in Spain’s technical guidelines, which states that “tools shall be available to automate the prevention and response process by detecting and identifying anomalies¹⁷” (reinforcement R4 prevention and automatic response to "incident management”).

Similarly, the UK NCSC’s Cyber Assessment Framework (CAF) highlights how anomaly-based detection systems are capable of detecting threats that “evade standard signature-based security solutions” (Principle C2 - Proactive Security Event Discovery¹⁸). The CAF’s C2 principle further outlines:

“The science of anomaly detection, which goes beyond using pre-defined or prescriptive pattern matching, is a challenging area. Capabilities like machine learning are increasingly being shown to have applicability and potential in the field of intrusion detection.”¹⁹

By leveraging machine learning and multi-layered AI techniques, organisations can move away from static rules and signatures, adopting a more behavioural approach to identifying and containing risks. This shift not only enhances the detection of emerging threats but also provides a more robust defence mechanism.

A key component of this strategy is behavioral zero trust, which focuses on identifying unauthorized and out-of-character attempts by users, devices, or systems. Implementing a robust procedure to verify each user and issuing the minimum required access rights based on their role and established patterns of activity is essential. Organisations should therefore be encouraged to follow a robust procedure to verify each user and issue the minimum required access rights based on their role and expected or established patterns of activity. By doing so, organisations can stay ahead of emerging threats and embrace a more dynamic and resilient cybersecurity strategy.

4. Autonomous response

The speed at which cyber-attacks occur means that defenders must be equipped with tools that match the sophistication and agility of those used by attackers. Autonomous response tools are thus essential for modern cyber defence, as they enable organisations to respond to both known and novel threats in real time.

These tools leverage a deep contextual and behavioral understanding of the organisation to take precise actions, effectively containing threats without disrupting business operations.

To avoid unnecessary business disruptions and maintain robust security, especially in more sensitive networks such as OT environments, it is crucial for organisations to determine the appropriate response depending on their environment. This can range from taking autonomous and native actions, such as isolating or blocking devices, or integrating their autonomous response tool with firewalls or other security tools to taking customized actions.

Autonomous response solutions should also use a contextual understanding of the business environment to make informed decisions, allowing them to contain threats swiftly and accurately. This means that even as cyber-attacks evolve and become more sophisticated, organisations can maintain continuous protection without compromising operational efficiency.

Indeed, research into the adoption of autonomous cyber defences points to the importance of implementing “organisation-specific" and “context-informed” approaches.²⁰ To decide the appropriate level of autonomy for each network action, it is argued, it is essential to use evidence-based risk prioritisation that is customised to the specific operations, assets, and data of individual enterprises.²¹

By adopting autonomous response solutions, organisations can ensure their defences are as dynamic and effective as the threats they face, significantly enhancing their overall security posture.

5. Proactive cyber resilience

Adopting a proactive approach to cybersecurity is crucial for organisations aiming to safeguard their operations and reputation. By hardening their defences enough so attackers are unable to target them effectively, organisations can save significant time and money. This proactive stance helps reduce business disruption, reputational damage, and the need for lengthy, resource-intensive incident responses.

Proactive cybersecurity incorporates many of the strategies outlined above. This can be seen in a recent survey of information technology practitioners, which outlines four components of a proactive cybersecurity culture: (1) visibility of corporate assets, (2) leveraging intelligent and modern technology, (3) adopting consistent and comprehensive training methods and (4) implementing risk response procedures.²² To this, we may also add continuous monitoring which allows organisations to understand the most vulnerable and high-value paths across their architectures, allowing them to secure their critical assets more effectively.

Alongside these components, a proactive cyber strategy should be based on a combined business context and knowledge, ensuring that security measures are aligned with the organisation's specific needs and priorities.

This proactive approach to cyber resilience is reflected in Spain’s technical guidance (article 8.2): “Prevention measures, which may incorporate components geared towards deterrence or reduction of the exposure surface, should eliminate or reduce the likelihood of threats materializing.”²³ It can also be found in the NCSC’s CAF, which outlines how organisations can achieve “proactive attack discovery” (see Principle C2).²⁴ Likewise, Belgium’s NIS2 transposition guidelines mandate the use of preventive measures to ensure the continued availability of services in the event of exceptional network failures (article 30).²⁵

Ultimately, a proactive approach to cybersecurity not only enhances protection but also lowers regulatory risk and supports the overall resilience and stability of the organisation.

Looking forward

The NIS2 Directive marked a significant regulatory milestone in strengthening cybersecurity across the EU.²⁶ Given the impact of emerging technologies, such as AI, on cybersecurity, it is to see that Member States are encouraged to promote the adoption of ‘state-of-the-art' cybersecurity across regulated entities.

In this blog, we have sought to translate what state-of-the-art cybersecurity may look like for organisations looking to enhance their cybersecurity posture. To do so, we have built on existing cybersecurity guidance, research and our own experience as an AI-cybersecurity company to outline five criteria: continuous monitoring, incident correlation, detection of anomalous activity, autonomous response, and proactive cyber resilience.

By embracing these principles and evolving cybersecurity practices in line with the state-of-the-art, organisations can comply with the NIS2 Directive while building a resilient cybersecurity posture capable of withstanding evolutions in the cyber threat landscape. Looking forward, it will be interesting to see how other jurisdictions embrace new technologies, such as AI, in solving the cybersecurity problem.

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