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Implications of NIS2 on cybersecurity and AI

Explore the key aspects of the NIS2 Directive, the latest EU cyber security legislation coming into effect in 2024. Learn how it impacts AI and security teams.
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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.
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The NIS2 Directive requires member states to adopt laws that will improve the cyber resilience of organizations within the EU. It impacts organizations that are “operators of essential services”. Under NIS 1, EU member states could choose what this meant. In an effort to ensure more consistent application, NIS2 has set out its own definition. It eliminates the distinction between operators of essential services and digital service providers from NIS1, instead defining a new list of sectors:

  • Energy (electricity, district heating and cooling, gas, oil, hydrogen)
  • Transport (air, rail, water, road)
  • Banking (credit institutions)
  • Financial market infrastructures
  • Health (healthcare providers and pharma companies)
  • Drinking water (suppliers and distributors)
  • Digital infrastructure (DNS, TLD registries, telcos, data center providers, etc.)
  • ICT service providers (B2B): MSSPs and managed service providers
  • Public administration (central and regional government institutions, as defined per member state)
  • Space
  • Postal and courier services
  • Waste management
  • Chemicals
  • Food
  • Manufacturing of medical devices
  • Computers and electronics
  • Machinery and equipment
  • Motor vehicles, trailers and semi-trailers and other transport equipment
  • Digital providers (online market places, online search engines, and social networking service platforms) and research organizations.

With these updates, it becomes harder to try and find industry segments not included within the scope. NIS2 represents legally binding cyber security requirements for a significant region and economy. Standout features that have garnered the most attention include the tight timelines associated with notification requirements. Under NIS 2, in-scope entities must submit an initial report or “early warning” to the competent national authority or computer security incident response team (CSIRT) within 24 hours from when the entity became aware of a significant incident. This is a new development from the first iteration of the Directive, which used more vague language of the need to notify authorities “without undue delay”.

Another aspect gaining attention is oversight and regulation – regulators are going to be empowered with significant investigation and supervision powers including on-site inspections.

The stakes are now higher, with the prospect of fines that are capped at €10 million or 2% of an offending organization’s annual worldwide turnover – whichever is greater. Added to that, the NIS2 Directive includes an explicit obligation to hold members of management bodies personally responsible for breaches of their duties to ensure compliance with NIS2 obligations – and members can be held personally liable.  

The risk management measures introduced in the Directive are not altogether surprising – they reflect common best practices. Many organizations (especially those that are newly in scope for NIS2) may have to expand their cyber security capabilities, but there’s nothing controversial or alarming in the required measures.  For organizations in this situation, there are various tools, best practices, and frameworks they can leverage.  Darktrace in particular provides capabilities in the areas of visibility, incident handling, and reporting that can help.

NIS2 and Cyber AI

The use of AI is not an outright requirement within NIS2 – which may be down to lack of knowledge and expertise in the area, and/or the immaturity of the sector. The clue to this might be in the timing: the provisional agreement on the NIS2 text was reached in May 2022 – six months before ChatGPT and other open-source Generative AI tools propelled broader AI technology into the forefront of public consciousness. If the language were drafted today, it's not far-fetched to imagine AI being mentioned much more prominently and perhaps even becoming a requirement.

NIS2 does, however, very clearly recommend that “member states should encourage the use of any innovative technology, including artificial intelligence”[1].  Another section speaks directly to essential and important entities, saying that they should “evaluate their own cyber security capabilities, and where appropriate, pursue the integration of cyber security enhancing technologies, such as artificial intelligence or machine learning systems…”[2]

One of the recitals states that “member states should adopt policies on the promotion of active cyber protection”.  Where active cyber protection is defined as “the prevention, detection, monitoring, analysis and mitigation of network security breaches in an active manner.”[3]  

From a Darktrace perspective, our self-learning Cyber AI technology is precisely what enables our technology to deliver active cyber protection – protecting organizations and uplifting security teams at every stage of an incident lifecycle – from proactively hardening defenses before an attack is launched, to real-time threat detection and response, through to recovering quickly back to a state of good health.  

The visibility provided by Darktrace is vital to understanding the effectiveness of policies and ensuring policy compliance. NIS2 also covers incident handling and business continuity, which Darktrace HEAL addresses through AI-enabled incident response, readiness reports, simulations, and secure collaborations.

Reporting is integral to NIS2 and organizations can leverage Darktrace’s incident reporting features to present the necessary technical details of an incident and provide a jump start to compiling a full report with business context and impact.  

What’s next for NIS2

We don’t yet know the details for how EU member states will transpose NIS2 into national law – they have until 17th October 2024 to work this out. The Commission also commits to reviewing the functioning of the Directive every three years. Given how much our overall understanding and appreciation for not only the dangers of AI but also its power (perhaps even necessity in the realm of cyber security) is changing, we may see many member states will leverage the recitals’ references to AI in order to make a strong push if not a requirement that essential and important organizations within their jurisdiction leverage AI.

Organizations are starting to prepare now to meet the forthcoming legislation related to NIS2. Download our CISO’s Guide to NIS2 Preparedness, which includes everything you need to know to get ahead of the directive.

[1] (51) on page 11
[2]
(89) on page 17
[3]
(57) on page 12

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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.
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July 3, 2025

Top Eight Threats to SaaS Security and How to Combat Them

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The latest on the identity security landscape

Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.

On average, a single organization uses 130 different Software-as-a-Service (SaaS) applications, and 45% of organizations reported experiencing a cybersecurity incident through a SaaS application in the last year.

As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.

What is SaaS security?

SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.

Below are the top eight threats that target SaaS security and user identities.

1.  Account Takeover (ATO)

Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.

2. Privilege escalation

Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.

3. Lateral movement

Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.

4. Multi-Factor Authentication (MFA) bypass and session hijacking

Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.

5. OAuth token abuse

Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.

6. Insider threats

Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.

7. Application Programming Interface (API)-based attacks

SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.

8. Business Email Compromise (BEC) via SaaS

Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.

BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.

Protecting against these SaaS threats

Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.

However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.

AI-powered SaaS security stays ahead of the threat landscape

New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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July 2, 2025

Pre-CVE Threat Detection: 10 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability

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Vulnerabilities are weaknesses in a system that can be exploited by malicious actors to gain unauthorized access or to disrupt normal operations. Common Vulnerabilities and Exposures (or CVEs) are a list of publicly disclosed cybersecurity vulnerabilities that can be tracked and mitigated by the security community.

When a vulnerability is discovered, the standard practice is to report it to the vendor or the responsible organization, allowing them to develop and distribute a patch or fix before the details are made public. This is known as responsible disclosure.

With a record-breaking 40,000 CVEs reported for 2024 and a predicted higher number for 2025 by the Forum for Incident Response and Security Teams (FIRST) [1], anomaly-detection is essential for identifying these potential risks. The gap between exploitation of a zero-day and disclosure of the vulnerability can sometimes be considerable, and retroactively attempting to identify successful exploitation on your network can be challenging, particularly if taking a signature-based approach.

Detecting threats without relying on CVE disclosure

Abnormal behaviors in networks or systems, such as unusual login patterns or data transfers, can indicate attempted cyber-attacks, insider threats, or compromised systems. Since Darktrace does not rely on rules or signatures, it can detect malicious activity that is anomalous even without full context of the specific device or asset in question.

For example, during the Fortinet exploitation late last year, the Darktrace Threat Research team were investigating a different Fortinet vulnerability, namely CVE 2024-23113, for exploitation when Mandiant released a security advisory around CVE 2024-47575, which aligned closely with Darktrace’s findings.

Retrospective analysis like this is used by Darktrace’s threat researchers to better understand detections across the threat landscape and to add additional context.

Below are ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

Trends in pre-cve exploitation

Often, the disclosure of an exploited vulnerability can be off the back of an incident response investigation related to a compromise by an advanced threat actor using a zero-day. Once the vulnerability is registered and publicly disclosed as having been exploited, it can kick off a race between the attacker and defender: attack vs patch.

Nation-state actors, highly skilled with significant resources, are known to use a range of capabilities to achieve their target, including zero-day use. Often, pre-CVE activity is “low and slow”, last for months with high operational security. After CVE disclosure, the barriers to entry lower, allowing less skilled and less resourced attackers, like some ransomware gangs, to exploit the vulnerability and cause harm. This is why two distinct types of activity are often seen: pre and post disclosure of an exploited vulnerability.

Darktrace saw this consistent story line play out during several of the Fortinet and PAN OS threat actor campaigns highlighted above last year, where nation-state actors were seen exploiting vulnerabilities first, followed by ransomware gangs impacting organizations [2].

The same applies with the recent SAP Netweaver exploitations being tied to a China based threat actor earlier this spring with subsequent ransomware incidents being observed [3].

Autonomous Response

Anomaly-based detection offers the benefit of identifying malicious activity even before a CVE is disclosed; however, security teams still need to quickly contain and isolate the activity.

For example, during the Ivanti chaining exploitation in the early part of 2025, a customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device.

This pre-CVE detection and response by Darktrace occurred 11 days before any public disclosure, demonstrating the value of an anomaly-based approach.

In some cases, customers have even reported that Darktrace stopped malicious exploitation of devices several days before a public disclosure of a vulnerability.

For example, During the ConnectWise exploitation, a customer informed the team that Darktrace had detected malicious software being installed via remote access. Upon further investigation, four servers were found to be impacted, while Autonomous Response had blocked outbound connections and enforced patterns of life on impacted devices.

Conclusion

By continuously analyzing behavioral patterns, systems can spot unusual activities and patterns from users, systems, and networks to detect anomalies that could signify a security breach.

Through ongoing monitoring and learning from these behaviors, anomaly-based security systems can detect threats that traditional signature-based solutions might miss, while also providing detailed insights into threat tactics, techniques, and procedures (TTPs). This type of behavioral intelligence supports pre-CVE detection, allows for a more adaptive security posture, and enables systems to evolve with the ever-changing threat landscape.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO), Emma Fougler (Global Threat Research Operations Lead), Ryan Traill (Analyst Content Lead)

References and further reading:

  1. https://www.first.org/blog/20250607-Vulnerability-Forecast-for-2025
  2. https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575
  3. https://thehackernews.com/2025/05/china-linked-hackers-exploit-sap-and.html

Related Darktrace blogs:

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

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