N-Day Vulnerabilities: Minimizing Risk With Self-Learning AI
See how Darktrace PREVENT, a self-learning AI program, can help your security team measure risk & address N-Day vulnerabilities before an attack occurs.
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
Oakley Cox
Director of Product
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27
Jul 2022
Responding to the latest critical vulnerability has become a regular routine in the daily life of cyber security professionals.
In the last two years, there has been a carousel of patches for vulnerabilities affecting email servers (ProxyLogon), remote working infrastructure (Atlassian Confluence), third party tools (Kaseya), and supply chain software (Log4j).
In the days following the public disclosure of such vulnerabilities, any associated exploit is referred to as an “N-day”. The release of a patch marks day 1, but over the following days any unpatched systems are at risk of attack from exploits which target the vulnerability. This contrasts with zero-day attacks, which exploit vulnerabilities for which no patch is available, often because knowledge of the vulnerability isn’t yet in the public domain.
N-days occupy a unique space in cyber risk analysis. Headline-grabbing zero-day attacks have the potential to be high impact, but in reality such attacks are rare and have a low likelihood. A more common cyber-attack, using commodity malware which has been well documented in the wild, may have a high likelihood but will have a low impact when faced with a mature security stack. But in the hours and days following the publication of a new vulnerability, there is a high likelihood of a high impact attack against an organization which makes use of a new exploit.
Table 1: A potential qualitative risk analysis comparing three cyber risks: a threat group targets an organization using either commodity malware, a zero-day exploit, or by leveraging an N-day vulnerability.
After a critical vulnerability is published, security teams battle against time and resourcing constraints to apply the appropriate patch or patches, all the while trying to protect assets without a playbook of what an attack may look like. Darktrace has found that 85% of high-risk vulnerabilities are not patched within one week and 70% remain unpatched after a month. In the meantime, threat groups have become armed with a new attack method: an N-day exploit.
In their latest research, Darktrace’s Inside the SOC team detail how the techniques used by Self-Learning AI to detect zero-day attacks can also be leveraged by organizations to Detect and Respond to N-day attacks.
But with Darktrace PREVENT, defenders can go one step further, enabling security teams to harden defenses before the next attack vector is even published.
The Darktrace PREVENT product family empowers defenders to model likely attack paths, intelligently prioritize critical servers or highly exposed people in the organization, and test vulnerable pathways by emulating real-world attacks. Darktrace PREVENT then feeds data back into Darktrace DETECT + RESPOND to harden defenses around critical attack paths or assets and further enhance cyber resilience. For example, if Darktrace PREVENT discovers that a critical database is serving high-risk users, it can feed that information back into Darktrace DETECT, which in turn increases the level of scrutiny around that asset.
Figure 1: Visualising Darktrace’s technology vision of a Cyber AI Loop: four interconnected AI engines continuously enhancing each other’s capabilities.
While Darktrace DETECT + RESPOND wrap what amounts to an ‘AI safety blanket’ around vulnerable assets and attack paths, Darktrace PREVENT presents prioritized recommendations for long term risk mitigation. Stretched security teams therefore know, based on Darktrace’s deep and evolving understanding of the entire business, where to focus their time and resources in order to reduce risk to the greatest extent.
As a result, when the next N-day vulnerability comes around, defenders have the confidence that any prospective impact has already been minimized and the potential cyber risk is low.
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.
Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents
This blog introduces new innovations in Darktrace / Proactive Exposure Management that bring precision and clarity to vulnerability prioritization. Learn how No-Telemetry Endpoints provide real device context without network data and how new Cost-Benefit Analysis capabilities quantify patching ROI—helping teams cut noise, act faster, and strengthen proactive risk management.
Darktrace Announces Extended Visibility Between Confirmed Assets and Leaked Credentials from the Deep and Dark Web
This blog explores how Continuous Threat Exposure Management (CTEM) is reshaping defense strategies and how new Darktrace / Attack Surface Management capabilities, including Exploit Prediction Assessment and Deep & Dark Web Monitoring, help organizations turn CTEM from strategy into action.
Pre-CVE Threat Detection: 10 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability
Darktrace leverages AI-driven anomaly detection to identify cyber threats before public CVE disclosures. By analyzing behavioral patterns, Darktrace can help organizations detect and contain zero-day exploits early. This proactive approach strengthens cybersecurity posture against nation-state actors, ransomware gangs, and evolving threats across the threat landscape.
CastleLoader & CastleRAT: Behind TAG150’s Modular Malware Delivery System
What is TAG-150?
TAG-150, a relatively new Malware-as-a-Service (MaaS) operator, has been active since March 2025, demonstrating rapid development and an expansive, evolving infrastructure designed to support its malicious operations. The group employs two custom malware families, CastleLoader and CastleRAT, to compromise target systems, with a primary focus on the United States [1]. TAG-150’s infrastructure included numerous victim-facing components, such as IP addresses and domains functioning as command-and-control (C2) servers associated with malware families like SecTopRAT and WarmCookie, in addition to CastleLoader and CastleRAT [2].
As of May 2025, CastleLoader alone had infected a reported 469 devices, underscoring the scale and sophistication of TAG-150’s campaign [1].
What are CastleLoader and CastleRAT?
CastleLoader is a loader malware, primarily designed to download and install additional malware, enabling chain infections across compromised systems [3]. TAG-150 employs a technique known as ClickFix, which uses deceptive domains that mimic document verification systems or browser update notifications to trick victims into executing malicious scripts. Furthermore, CastleLoader leverages fake GitHub repositories that impersonate legitimate tools as a distribution method, luring unsuspecting users into downloading and installing malware on their devices [4].
CastleRAT, meanwhile, is a remote access trojan (RAT) that serves as one of the primary payloads delivered by CastleLoader. Once deployed, CastleRAT grants attackers extensive control over the compromised system, enabling capabilities such as keylogging, screen capturing, and remote shell access.
TAG-150 leverages CastleLoader as its initial delivery mechanism, with CastleRAT acting as the main payload. This two-stage attack strategy enhances the resilience and effectiveness of their operations by separating the initial infection vector from the final payload deployment.
How are they deployed?
Castleloader uses code-obfuscation methods such as dead-code insertion and packing to hinder both static and dynamic analysis. After the payload is unpacked, it connects to its command-and-control server to retrieve and running additional, targeted components.
Its modular architecture enables it to function both as a delivery mechanism and a staging utility, allowing threat actors to decouple the initial infection from payload deployment. CastleLoader typically delivers its payloads as Portable Executables (PEs) containing embedded shellcode. This shellcode activates the loader’s core module, which then connects to the C2 server to retrieve and execute the next-stage malware.[6]
Following this, attackers deploy the ClickFix technique, impersonating legitimate software distribution platforms like Google Meet or browser update notifications. These deceptive sites trick victims into copying and executing PowerShell commands, thereby initiating the infection kill chain. [1]
When a user clicks on a spoofed Cloudflare “Verification Step” prompt, a background request is sent to a PHP script on the distribution domain (e.g., /s.php?an=0). The server’s response is then automatically copied to the user’s clipboard using the ‘unsecuredCopyToClipboard()’ function. [7].
The Python-based variant of CastleRAT, known as “PyNightShade,” has been engineered with stealth in mind, showing minimal detection across antivirus platforms [2]. As illustrated in Figure 1, PyNightShade communicates with the geolocation API service ip-api[.]com, demonstrating both request and response behavior
Figure 1: Packet Capture (PCAP) of PyNightShade, the Python-based variant of CastleRAT, communicating with the geolocation API service ip-api[.]com.
Darktrace Coverage
In mid-2025, Darktrace observed a range of anomalous activities across its customer base that appeared linked to CastleLoader, including the example below from a US based organization.
The activity began on June 26, when a device on the customer’s network was observed connecting to the IP address 173.44.141[.]89, a previously unseen IP for this network along with the use of multiple user agents, which was also rare for the user. It was later determined that the IP address was a known indicator of compromise (IoC) associated with TAG-150’s CastleRAT and CastleLoader operations [2][5].
Figure 2: Darktrace’s detection of a device making unusual connections to the malicious endpoint 173.44.141[.]89.
The device was observed downloading two scripts from this endpoint, namely ‘/service/download/data_5x.bin’ and ‘/service/download/data_6x.bin’, which have both been linked to CastleLoader infections by open-source intelligence (OSINT) [8]. The archives contains embedded shellcode, which enables attackers to execute arbitrary code directly in memory, bypassing disk writes and making detection by endpoint detection and response (EDR) tools significantly more difficult [2].
Figure 3: Darktrace’s detection of two scripts from the malicious endpoint.
In addition to this, the affected device exhibited a high volume of internal connections to a broad range of endpoints, indicating potential scanning activity. Such behavior is often associated with reconnaissance efforts aimed at mapping internal infrastructure.
Darktrace / NETWORK correlated these behaviors and generated an Enhanced Monitoring model, a high-fidelity security model designed to detect activity consistent with the early stages of an attack. These high-priority models are continuously monitored and triaged by Darktrace’s Security Operations Center (SOC) as part of the Managed Threat Detection and Managed Detection & Response services, ensuring that subscribed customers are promptly alerted to emerging threats.
Figure 4: Darktrace detected an unusual ZIP file download alongside the anomalous script, followed by internal connectivity. This activity was correlated under an Enhanced Monitoring model.
Darktrace Autonomous Response
Fortunately, Darktrace’s Autonomous Response capability was fully configured, enabling it to take immediate action against the offending device by blocking any further connections external to the malicious endpoint, 173.44.141[.]89. Additionally, Darktrace enforced a ‘group pattern of life’ on the device, restricting its behavior to match other devices in its peer group, ensuring it could not deviate from expected activity, while also blocking connections over 443, shutting down any unwanted internal scanning.
Figure 5: Actions performed by Darktrace’s Autonomous Response to contain the ongoing attack.
Conclusion
The rise of the MaaS ecosystem, coupled with attackers’ growing ability to customize tools and techniques for specific targets, is making intrusion prevention increasingly challenging for security teams. Many threat actors now leverage modular toolkits, dynamic infrastructure, and tailored payloads to evade static defenses and exploit even minor visibility gaps. In this instance, Darktrace demonstrated its capability to counter these evolving tactics by identifying early-stage attack chain behaviors such as network scanning and the initial infection attempt. Autonomous Response then blocked the CastleLoader IP delivering the malicious ZIP payload, halting the attack before escalation and protecting the organization from a potentially damaging multi-stage compromise
Credit to Ahmed Gardezi (Cyber Analyst) Tyler Rhea (Senior Cyber Analyst) Edited by Ryan Traill (Analyst Content Lead)
UK Cyber Security & Resilience Bill: What Organizations Need to Know
Why the Bill has been introduced
The UK’s cyber threat landscape has evolved dramatically since the 2018 NIS regime was introduced. Incidents such as the Synnovis attack against hospitals and the British Library ransomware attack show how quickly operational risk can become public harm. In this context, the UK Department for Science, Innovation and Technology estimates that cyber-attacks cost UK businesses around £14.7 billion each year.
At the same time, the widespread adoption of AI has expanded organisations’ attack surfaces and empowered threat actors to launch more effective and sophisticated activities, including crafting convincing phishing campaigns, exploiting vulnerabilities and initiating ransomware attacks at unprecedented speed and scale.
The CSRB responds to these challenges by widening who is regulated, accelerating incident reporting and tightening supply chain accountability, while enabling rapid updates that keep pace with technology and emerging risks.
Key provisions of the Cyber Security and Resilience Bill
A wider set of organisations in scope
The Bill significantly broadens the range of organisations regulated under the NIS framework.
Managed service providers (MSPs) - medium and large MSPs, including MSSPs, managed SOCs, SIEM providers and similar services,will now fall under NIS obligations due to their systemic importance and privileged access to client systems. The Information Commissioner’s Office (ICO) will act as the regulator. Government analysis anticipates that a further 900 to 1,100 MSPs will be in scope.
Data infrastructure is now recognised as essential to the functioning of the economy and public services. Medium and large data centres, as well as enterprise facilities meeting specified thresholds, will be required to implement appropriate and proportionate measures to manage cyber risk. Oversight will be shared between DSIT and Ofcom, with Ofcom serving as the operational regulator.
Organisations that manage electrical loads for smart appliances, such as those supporting EV charging during peak times, are now within scope.
These additions sit alongside existing NIS-regulated sectors such as transport, energy, water, health, digital infrastructure, and certain digital services (including online marketplaces, search engines, and cloud computing).
Stronger supply chain requirements
Under the CSRB, regulators can now designate third-party suppliers as ‘designated critical suppliers’ (DCS) when certain threshold criteria are met and where disruption could have significant knock-on effects. Designated suppliers will be subject to the same security and incident-reporting obligations as Operators of Essential Services (OES) and Relevant Digital Service Providers (RDSPs).
Government will scope the supply chain duties for OES and RDSPs via secondary legislation, following consultation. infrastructure incidents where a single supplier’s compromise caused widespread disruption.
Faster incident reporting
Sector-specific regulators, 12 in total, will be responsible for implementing the CSRB, allowing for more effective and consistent reporting. In addition, the CSRB introduces a two-stage reporting process and expands incident reporting criteria. Regulated entities must submit an initial notification within 24 hours of becoming aware of a significant incident, followed by an incident report within 72 hours. Incident reporting criteria are also broadened to capture incidents beyond those which actually resulted in an interruption, ensuring earlier visibility for regulators and the National Cyber Security Centre (NCSC). The importance of information sharing across agencies, law enforcement and regulators is also facilitated by the CSRB.
The reforms also require data centres and managed service providers to notify affected customers where they are likely to have been impacted by a cyber incident.
An agile regulatory framework
To keep pace with technological change, the CSRB will enable the Secretary of State to update elements of the framework via secondary legislation. Supporting materials such as the NCSC Cyber Assessment Framework (CAF) are to be "put on a stronger footing” allowing for requirements to be more easily followed, managed and updated. Regulators will also now be able to recover full costs associated with NIS duties meaning they are better resourced to carry out their associated responsibilities.
Relevant Managed Service Providers must identify and take appropriate and proportionate measures to manage risks to the systems they rely on for providing services within the UK. Importantly, these measures must, having regard to the state of the art, ensure a level of security appropriate to the risk posed, and prevent or minimise the impact of incidents.
The Secretary of State will also be empowered to issue a Statement of Strategic Priorities, setting cross-regime outcomes to drive consistency across the 12 competent authorities responsible for implementation.
Penalties
The enforcement framework will be strengthened, with maximum fines aligned with comparable regimes such as the GDPR, which incorporate maximums tied to turnover. Under the CSRB, maximum penalties for more serious breaches could be up to £17 million or 4% of global turnover, whichever is higher.
Next steps
The Bill is expected to progress through Parliament over the course of 2025 and early 2026, with Royal Assent anticipated in 2026. Once enacted, most operational measures will not take immediate effect. Instead, Government will bring key components into force through secondary legislation following further consultation, providing regulators and industry with time to adjust practices and prepare for compliance.
Anticipated timeline
2025-2026: Parliamentary scrutiny and passage;
2026: Royal Assent;
2026 consultation: DSIT intends to consult on detailed implementation;
From 2026 onwards: Phased implementation via secondary legislation, following further consultation led by DSIT.
How Darktrace can help
The CSRB represents a step change in how the UK approaches digital risk, shifting the focus from compliance to resilience.
Darktrace can help organisations operationalise this shift by using AI to detect, investigate and respond to emerging threats at machine speed, before they escalate into incidents requiring regulatory notification. Proactive tools which can be included in the Darktrace platform allow security teams to stress-test defences, map supply chain exposure and rehearse recovery scenarios, directly supporting the CSRB’s focus on resilience, transparency and rapid response. If an incident does occur, Darktrace’s autonomous agent, Cyber AI Analyst, can accelerate investigations and provide a view of every stage of the attack chain, supporting timely reporting.
Darktrace’s AI can provide organisations with a vital lens into both internal and external cyber risk. By continuously learning patterns of behaviour across interconnected systems, Darktrace can flag potential compromise or disruption to detect supply chain risk before it impacts your organisation.
In a landscape where compliance and resilience go hand in hand, Darktrace can equip organisations to stay ahead of both evolving threats and evolving regulatory requirements.
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![Packet Capture (PCAP) of PyNightShade, the Python-based variant of CastleRAT, communicating with the geolocation API service ip-api[.]com.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69275c5ecce362fa92c1aeaa_Screenshot%202025-11-26%20at%2012.00.24%E2%80%AFPM.png)
