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April 10, 2023

Detecting Malicious Email Activity & AI Impersonating

Discover how two different phishing attempts from some known and unknown senders used a payroll diversion and credential sealing box link to harm users.
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
Isabelle Cheong
Cyber Security Analyst
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10
Apr 2023

Social engineering has become widespread in the cyber threat landscape in recent years, and the near-universal use of social media today has allowed attackers to research and target victims more effectively. Social engineering involves manipulating users to carry out actions such as revealing sensitive information like login credentials or credit card details. It can also lead to user account compromises, causing huge disruption to an organization’s digital estate. 

As people use social media platforms not only for personal reasons, but also for business purposes, attackers gain information they can exploit in social engineering attacks. For example, a threat actor may attempt to impersonate a known individual or legitimate service to take advantage of a user’s established trust. This is a highly successful method of social engineering because mimicking known contacts makes it difficult for traditional security tools that rely on deny-lists to detect the attack.

In October 2022, Darktrace identified and responded to two separate malicious email campaigns in which threat actors attempted to impersonate known contacts in an effort to compromise customer devices. As it learns the normal behavior of every user in the email system, Darktrace was able to instantly detect these threats and mitigate them autonomously, preventing significant disruption to the customer networks.

Payroll Diversion Fraud Attempt Impersonating a Former Employee 

While a customer in the Canadian energy sector was trialing Darktrace in October 2022, Darktrace/Email™ identified a suspicious email seemingly sent from an employee within the organization. The email was sent to the Senior Director of Human Resources (HR) with a subject line of “Change in payroll Direct Deposit.” The email requested a change in bank account information for an employee. However, Darktrace recognized that the sender was using a free mail address that contained random letters, indicating it may have been algorithmically generated. Since this incident occurred during a trial, Darktrace/Email was not configured to take action. Otherwise, it would have prevented the email from landing in the inbox. In this case though, the email went through, bypassing all other security tools in place.

Although the email was from an unknown sender, the HR director believed the email could have been legitimate as the employee who appeared to be the sender had left the organization seven days prior and no longer had access to their corporate email account. However, after reviewing it in the Darktrace/Email dashboard, the customer grew suspicious and contacted the former employee directly to verify if the request was legitimate. The former employee validated the suspicions by confirming they had sent no such email.

Further investigation by the customer revealed that the former employee had been vocal about their departure on various social media platforms. This gave threat actors valuable information to believably impersonate the former employee and defraud the organization. 

Such attempts to target organizations’ HR departments and divert payroll are common tactics for cyber-criminals and are often identified by Darktrace/Email across the customer base. Darktrace/Email is able to instantly identify the indicators associated with these spoofing attempts and immediately bring them to the attention of the customer’s security team. 

Using Legitimate File Sharing Service to Share a Phishing Link 

On October 7, 2022, a customer in the Singaporean construction sector was targeted by a phishing campaign attempting to impersonate a law firm known to the organization. Almost 200 employees received an email with the subject line “Accepted: Valuation Agreement.” 

Figure 1: Sample of an UI view of the message held showing anomaly indicators, history, association, and validation.

Four days earlier, Darktrace observed communication between another email address associated with the law firm and an employee of the customer. Darktrace/Email noted that it was the first time this correspondent had sent emails to the customer. 

Figure 2: Metrics showing how well the sender’s domain is known within the digital environment.

The emails contained a highly unusual link to a file sharing service, (hxxps://ssvilvensstokes[.]app[.]box[.]com/notes), hidden behind the text “PREVIEW OR PRINT COPY OF DOCUMENT HERE.” Darktrace analysts investigated this event further and found that around 30 similar URLs had been identified as suspicious using OSINT security tools in October 2022, suggesting the customer was not the only target of this phishing campaign.

Figure 3: Preview of the phishing email’s body.
Figure 4: Darktrace’s evaluation of the link contained in the phishing email.

Additional OSINT work revealed that the link directed to a website which appeared to host a PDF file named “Valuation Agreement.” The recipient would then be prompted to follow another link (hulking-citrine-krypton[.]glitch[.]me), again hidden behind the text “OPEN OR ACCESS DOCUMENT HERE” to view the file. Subsequently, the user would be prompted to enter their Microsoft 365 credentials. 

Figure 5: The page displayed when the phishing link was clicked, viewed in a sandbox environment.
Figure 6: Example of a page shown when recipient clicks the second link, accessing “hulking-citrine-krypton[.]glitch[.]me”. 

This page contained the text “This document has been scanned for viruses by Norton Antivirus Security.” This is another example of threat actors’ employing social engineering techniques by impersonating well-known brands, such as established security vendors, to gain the trust of users and increase their likelihood of success.

It is highly probable that a real employee of the law firm had their account hijacked and that a malicious actor was exploiting it to send out these phishing emails en masse as part of a supply chain attack. In such cases, malicious actors rely on their targets’ trust of known contacts to not question departures from their normal conversations. 

Darktrace was able to instantly detect multiple anomalies in these emails, despite the fact that they were seemingly sent by known correspondents. The activity detected automatically triggered model breaches associated with unexpected and visually prominent links. As a result, Darktrace/Email responded by locking the link, stopping users from being able to click it.

Darktrace subsequently identified additional emails from this sender attempting to target other recipients within the company, triggering the model breaches associated with a surge in email sending indicative of a phishing campaign. In response, Darktrace/Email autonomously acted and filed these emails as junk. As more emails were detected across the customer’s environment, the anomaly score of the sender increased and Darktrace ultimately held back over 160 malicious emails, safeguarding recipients from potential account compromise.           

The following Darktrace/Email models were breached throughout the course of this phishing campaign:

  • Unusual/Sender Surge 
  • Unusual/Undisclosed Recipients 
  • Antigena Anomaly 
  • Association/Unlikely Recipient Association 
  • Link/Low Link Association 
  • Link/Visually Prominent Link 
  • Link/Visually Prominent Link Unexpected For Sender 
  • Unusual/New Sender Wide Distribution
  • Unusual/Undisclosed Recipients + New Address Known Domain

Conclusion

Social engineering plays a role in many of the major threats challenging current email cyber security, as attackers can use it to manipulate users into transferring money, revealing credentials, clicking malicious links, and more. 

The above threat stories happened before language generating AI became mainstream with the release of ChatGPT in December 2022. Now, it is even easier for malicious actors to generate sophisticated social engineering emails. By using social media posts as input, social engineering emails written by generative AI can be highly targeted and produced at scale. They often avoid the flags users are trained to look for, like poor grammar and spelling mistakes, and can hide payloads or forgo them entirely.

To mitigate the risk of possible social engineering attempts, it is recommended that organizations implement social media policies that advise employees to be cautious of what they post online and enact procedures to verify if fund transfer requests are legitimate.

Yet these policies are not enough on their own. Darktrace/Email can identify suspicious email traits, whether an email is sent from a known correspondent or an unknown sender. With Self-Learning AI, it knows an organization’s users better than any impersonator could. In this way, Darktrace/Email detects anomalies within emails and neutralizes malicious components at machine-speed, stopping attacks at their earliest stages, before employees fall victim. 

Appendices

List of Indicators of Compromise (IoCs)

Domain:

hxxps://ssvilvensstokes[.]app[.]box[.]com/notes/*?s=* - 1st external link (seen in email)

hxxps://hulking-citrine-krypton[.]glitch[.]me/flk.html - 2nd external link, masked behind “OPEN OR ACCESS DOCUMENT HERE”

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
Isabelle Cheong
Cyber Security Analyst

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January 15, 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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January 13, 2026

Runtime Is Where Cloud Security Really Counts: The Importance of Detection, Forensics and Real-Time Architecture Awareness

runtime, cloud security, cnaapDefault blog imageDefault blog image

Introduction: Shifting focus from prevention to runtime

Cloud security has spent the last decade focused on prevention; tightening configurations, scanning for vulnerabilities, and enforcing best practices through Cloud Native Application Protection Platforms (CNAPP). These capabilities remain essential, but they are not where cloud attacks happen.

Attacks happen at runtime: the dynamic, ephemeral, constantly changing execution layer where applications run, permissions are granted, identities act, and workloads communicate. This is also the layer where defenders traditionally have the least visibility and the least time to respond.

Today’s threat landscape demands a fundamental shift. Reducing cloud risk now requires moving beyond static posture and CNAPP only approaches and embracing realtime behavioral detection across workloads and identities, paired with the ability to automatically preserve forensic evidence. Defenders need a continuous, real-time understanding of what “normal” looks like in their cloud environments, and AI capable of processing massive data streams to surface deviations that signal emerging attacker behavior.

Runtime: The layer where attacks happen

Runtime is the cloud in motion — containers starting and stopping, serverless functions being called, IAM roles being assumed, workloads auto scaling, and data flowing across hundreds of services. It’s also where attackers:

  • Weaponize stolen credentials
  • Escalate privileges
  • Pivot programmatically
  • Deploy malicious compute
  • Manipulate or exfiltrate data

The challenge is complex: runtime evidence is ephemeral. Containers vanish; critical process data disappears in seconds. By the time a human analyst begins investigating, the detail required to understand and respond to the alert, often is already gone. This volatility makes runtime the hardest layer to monitor, and the most important one to secure.

What Darktrace / CLOUD Brings to Runtime Defence

Darktrace / CLOUD is purpose-built for the cloud execution layer. It unifies the capabilities required to detect, contain, and understand attacks as they unfold, not hours or days later. Four elements define its value:

1. Behavioral, real-time detection

The platform learns normal activity across cloud services, identities, workloads, and data flows, then surfaces anomalies that signify real attacker behavior, even when no signature exists.

2. Automated forensic level artifact collection

The moment Darktrace detects a threat, it can automatically capture volatile forensic evidence; disk state, memory, logs, and process context, including from ephemeral resources. This preserves the truth of what happened before workloads terminate and evidence disappears.

3. AI-led investigation

Cyber AI Analyst assembles cloud behaviors into a coherent incident story, correlating identity activity, network flows, and Cloud workload behavior. Analysts no longer need to pivot across dashboards or reconstruct timelines manually.

4. Live architectural awareness

Darktrace continuously maps your cloud environment as it operates; including services, identities, connectivity, and data pathways. This real-time visibility makes anomalies clearer and investigations dramatically faster.

Together, these capabilities form a runtime-first security model.

Why CNAPP alone isn’t enough

CNAPP platforms excel at pre deployment checks all the way down to developer workstations, identifying misconfigurations, concerning permission combinations, vulnerable images, and risky infrastructure choices. But CNAPP’s breadth is also its limitation. CNAPP is about posture. Runtime defense is about behavior.

CNAPP tells you what could go wrong; runtime detection highlights what is going wrong right now.

It cannot preserve ephemeral evidence, correlate active behaviors across domains, or contain unfolding attacks with the precision and speed required during a real incident. Prevention remains essential, but prevention alone cannot stop an attacker who is already operating inside your cloud environment.

Real-world AWS Scenario: Why Runtime Monitoring Wins

A recent incident detected by Darktrace / CLOUD highlights how cloud compromises unfold, and why runtime visibility is non-negotiable. Each step below reflects detections that occur only when monitoring behavior in real time.

1. External Credential Use

Detection: Unusual external source for credential use: An attacker logs into a cloud account from a never-before-seen location, the earliest sign of account takeover.

2. AWS CLI Pivot

Detection: Unusual CLI activity: The attacker switches to programmatic access, issuing commands from a suspicious host to gain automation and stealth.

3. Credential Manipulation

Detection: Rare password reset: They reset or assign new passwords to establish persistence and bypass existing security controls.

4. Cloud Reconnaissance

Detection: Burst of resource discovery: The attacker enumerates buckets, roles, and services to map high value assets and plan next steps.

5. Privilege Escalation

Detection: Anomalous IAM update: Unauthorized policy updates or role changes grant the attacker elevated access or a backdoor.

6. Malicious Compute Deployment

Detection: Unusual EC2/Lambda/ECS creation: The attacker deploys compute resources for mining, lateral movement, or staging further tools.

7. Data Access or Tampering

Detection: Unusual S3 modifications: They alter S3 permissions or objects, often a prelude to data exfiltration or corruption.

Only some of these actions would appear in a posture scan, crucially after the fact.
Every one of these runtime detections is visible only through real-time behavioral monitoring while the attack is in progress.

The future of cloud security Is runtime-first

Cloud defense can no longer revolve solely around prevention. Modern attacks unfold in runtime, across a fast-changing mesh of workloads, services, and — critically — identities. To reduce risk, organizations must be able to detect, understand, and contain malicious activity as it happens, before ephemeral evidence disappears and before attacker's pivot across identity layers.

Darktrace / CLOUD delivers this shift by turning runtime, the most volatile and consequential layer in the cloud, into a fully defensible control point through unified visibility across behavior, workloads, and identities. It does this by providing:

  • Real-time behavior detection across workloads and identity activity
  • Autonomous response actions for rapid containment
  • Automated forensic level artifact preservation the moment events occur
  • AI-driven investigation that separates weak signals from true attacker patterns
  • Live cloud environment insight to understand context and impact instantly

Cloud security must evolve from securing what might go wrong to continuously understanding what is happening; in runtime, across identities, and at the speed attackers operate. Unifying runtime and identity visibility is how defenders regain the advantage.

[related-resource]

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About the author
Adam Stevens
Senior Director of Product, Cloud | Darktrace
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