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June 9, 2021

Enhancing Cybersecurity: Attack Surface Management

Explore effective strategies and learn how organizations can enhance Attack Surface Management using artificial intelligence (AI) automation. Read more.
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
Vincent Thiele
Deputy CISO
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Jun 2021

Effective attack surface management breaks down into four key parts:

  • Discovery
  • Assessment and prioritisation
  • Risk prevention
  • Integration

Discovery

The most important part of any attack surface management process is the discovery phase. As we’ve mentioned previously, most organizations miss as much as 30 to 50 percent of their true attack surface. This creates huge blind spots when it comes to understanding the real risks your organization is facing. In fact, we believe that something like 80% of all organizations’ cybersecurity problems exist due to blind spots in their attack surface. Eliminating those blind spots should be your core goal when setting out to discover your attack surface.

One of the biggest contributing factors to these blind spots is scoping. Organizations tend to work within a predefined scope when it comes to discovery – whether that’s within a defined IT infrastructure or a set of IP addresses that the organization uses and wants to protect.

However, the reality is that any would-be attackers out there do not care about your scope. Whether you have a vulnerability in-house, via an external supplier, or in a cloud environment; an attacker will find it and try to misuse it.

On top of this, with modern organizations having so many external dependencies, regulatory bodies are starting to insist that financial services companies look beyond the boundaries of their own networks when analysing risk.

For example, the Digital Operational Resilience of the financial sector (DORA), extends the focus of risk management to cover all external assets of the parties they have relationships with (such as fourth and fifth parties, or parties that you even don't know you have a relationship with), as well as any services and infrastructure that can impact on the organization’s day-to-day resilience.

Taking a zero-scope approach to your attack surface is therefore essential. This means that tracking down the full extent of your attack surface is not something that can be left to human endeavour. Relying on people to trace and discover your connections would be hugely expensive, time consuming, and error prone. So, a prerequisite of effective discovery is automation. AI and algorithmic-based discovery is the only way to uncover the bulk of your attack surface.

Assessment and Prioritization

Monitoring your attack surface is not a one-time, set-and-forget process because your attack surface is not static; it’s constantly evolving and changing. This means you need to be continuously monitoring it for changes, and you need to be alerted when those changes occur, so that you can decide whether or not something needs your attention. This data needs to be dynamic and as close to real-time as you can get.Only once you know what your full attack surface looks like can you really start to analyse the risk types presented to the business. These risks can be extensive and need prioritisation according to the threat presented to the brand. As the discovery process continues, you need an automated risk assessment tool to save time and effort. It will tell you what the most pressing risks are, so you can focus on the mitigating process. Then, even when the discovery process is ongoing, new risks are automatically reported on, and added to right lists. This ensures you stay up-to-date on the actual risks to the organization – removing a lot of the stress from the process for CISOs.

Risk Prevention

There is a flipside to seeing your whole attack surface. Having a comprehensive overview of every risk your organization faces can be terrifying – you are going to uncover a multitude of things you’d never considered. This can leave you facing one big question: “Do I really want to know all of this?” Most CISOs and cybersecurity professionals are already busy with all the things they do know about, so you need to have a way of striping out and solving some of the possibly lower priority but easier to solve risks in your report. This is again where automation can come into play. Automatically categorizing similar risk types throughout your attack surface will save time and effort when reducing risks.

Integration

Finally, it doesn’t matter how much data you have on something; if it’s not actionable it’s ultimately not going to be practical to use. So you need to be able to connect all that data coming from your attack surface monitoring into your existing internal processes and systems (your PSA, ITSM, or ESM tools etc). That way you can build it into your existing cybersecurity structure and minimise extra work.

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
Vincent Thiele
Deputy CISO

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January 30, 2026

ClearFake: From Fake CAPTCHAs to Blockchain-Driven Payload Retrieval

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What is ClearFake?

As threat actors evolve their techniques to exploit victims and breach target networks, the ClearFake campaign has emerged as a significant illustration of this continued adaptation. ClearFake is a campaign observed using a malicious JavaScript framework deployed on compromised websites, impacting sectors such as e‑commerce, travel, and automotive. First identified in mid‑2023, ClearFake is frequently leveraged to socially engineer victims into installing fake web browser updates.

In ClearFake compromises, victims are steered toward compromised WordPress sites, often positioned by attackers through search engine optimization (SEO) poisoning. Once on the site, users are presented with a fake CAPTCHA. This counterfeit challenge is designed to appear legitimate while enabling the execution of malicious code. When a victim interacts with the CAPTCHA, a PowerShell command containing a download string is retrieved and executed.

Attackers commonly abuse the legitimate Microsoft HTML Application Host (MSHTA) in these operations. Recent campaigns have also incorporated Smart Chain endpoints, such as “bsc-dataseed.binance[.]org,” to obtain configuration code. The primary payload delivered through ClearFake is typically an information stealer, such as Lumma Stealer, enabling credential theft, data exfiltration, and persistent access [1].

Darktrace’s Coverage of ClearFake

Darktrace / ENDPOINT first detected activity likely associated with ClearFake on a single device on over the course of one day on November 18, 2025. The system observed the execution of “mshta.exe,” the legitimate Microsoft HTML Application Host utility. It also noted a repeated process command referencing “weiss.neighb0rrol1[.]ru”, indicating suspicious external activity. Subsequent analysis of this endpoint using open‑source intelligence (OSINT) indicated that it was a malicious, domain generation algorithm (DGA) endpoint [2].

Figure 1: The process line referencing weiss.neighb0rrol1[.]ru, as observed by Darktrace / ENDPOINT.

This activity indicates that mshta.exe was used to contact a remote server, “weiss.neighb0rrol1[.]ru/rpxacc64mshta,” and execute the associated HTA file to initiate the next stage of the attack. OSINT sources have since heavily flagged this server as potentially malicious [3].

The first argument in this process uses the MSHTA utility to execute the HTA file hosted on the remote server. If successful, MSHTA would then run JavaScript or VBScript to launch PowerShell commands used to retrieve malicious payloads, a technique observed in previous ClearFake campaigns. Darktrace also detected unusual activity involving additional Microsoft executables, including “winlogon.exe,” “userinit.exe,” and “explorer.exe.” Although these binaries are legitimate components of the Windows operating system, threat actors can abuse their normal behavior within the Windows login sequence to gain control over user sessions, similar to the misuse of mshta.exe.

EtherHiding cover

Darktrace also identified additional ClearFake‑related activity, specifically a connection to bsc-testnet.drpc[.]org, a legitimate BNB Smart Chain endpoint. This activity was triggered by injected JavaScript on the compromised site www.allstarsuae[.]com, where the script initiated an eth_call POST request to the Smart Chain endpoint.

Figure 2: Example of a fake CAPTCHA on the compromised site www.allstarsuae[.]com.

EtherHiding is a technique in which threat actors leverage blockchain technology, specifically smart contracts, as part of their malicious infrastructure. Because blockchain is anonymous, decentralized, and highly persistent, it provides threat actors with advantages in evading defensive measures and traditional tracking [4].

In this case, when a user visits a compromised WordPress site, injected base64‑encoded JavaScript retrieved an ABI string, which was then used to load and execute a contract hosted on the BNB Smart Chain.

Figure 3: JavaScript hosted on the compromised site www.allstaruae[.]com.

Conducting malware analysis on this instance, the Base64 decoded into a JavaScript loader. A POST request to bsc-testnet.drpc[.]org was then used to retrieve a hex‑encoded ABI string that loads and executes the contract. The JavaScript also contained hex and Base64‑encoded functions that decoded into additional JavaScript, which attempted to retrieve a payload hosted on GitHub at “github[.]com/PrivateC0de/obf/main/payload.txt.” However, this payload was unavailable at the time of analysis.

Figure 4: Darktrace’s detection of the POST request to bsc-testnet.drpc[.]org.

Figure 5: Darktrace’s detection of the executable file and the malicious hostname.

Autonomous Response

As Darktrace’s Autonomous Response capability was enabled on this customer’s network, Darktrace was able to take swift mitigative action to contain the ClearFake‑related activity early, before it could lead to potential payload delivery. The affected device was blocked from making external connections to a number of suspicious endpoints, including 188.114.96[.]6, *.neighb0rrol1[.]ru, and neighb0rrol1[.]ru, ensuring that no further malicious connections could be made and no payloads could be retrieved.

Autonomous Response also acted to prevent the executable mshta.exe from initiating HTA file execution over HTTPS from this endpoint by blocking the attempted connections. Had these files executed successfully, the attack would likely have resulted in the retrieval of an information stealer, such as Lumma Stealer.

Figure 6: Autonomous Response’s intervention against the suspicious connectivity observed.

Conclusion

ClearFake continues to be observed across multiple sectors, but Darktrace remains well‑positioned to counter such threats. Because ClearFake’s end goal is often to deliver malware such as information stealers and malware loaders, early disruption is critical to preventing compromise. Users should remain aware of this activity and vigilant regarding fake CAPTCHA pop‑ups. They should also monitor unusual usage of MSHTA and outbound connections to domains that mimic formats such as “bsc-dataseed.binance[.]org” [1].

In this case, Darktrace was able to contain the attack before it could successfully escalate and execute. The attempted execution of HTA files was detected early, allowing Autonomous Response to intervene, stopping the activity from progressing. As soon as the device began communicating with weiss.neighb0rrol1[.]ru, an Autonomous Response inhibitor triggered and interrupted the connections.

As ClearFake continues to rise, users should stay alert to social engineering techniques, including ClickFix, that rely on deceptive security prompts.

Credit to Vivek Rajan (Senior Cyber Analyst) and Tara Gould (Malware Research Lead)


Edited by Ryan Traill (Analyst Content Lead)

Appendices

Darktrace Model Detections

Process / New Executable Launched

Endpoint / Anomalous Use of Scripting Process

Endpoint / New Suspicious Executable Launched

Endpoint / Process Connection::Unusual Connection from New Process

Autonomous Response Models

Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block

List of Indicators of Compromise (IoCs)

  • weiss.neighb0rrol1[.]ru – URL - Malicious Domain
  • 188.114.96[.]6 – IP – Suspicious Domain
  • *.neighb0rrol1[.]ru – URL – Malicious Domain

MITRE Tactics

Initial Access, Drive-by Compromise, T1189

User Execution, Execution, T1204

Software Deployment Tools, Execution and Lateral Movement, T1072

Command and Scripting Interpreter, T1059

System Binary Proxy Execution: MSHTA, T1218.005

References

1.        https://www.kroll.com/en/publications/cyber/rapid-evolution-of-clearfake-delivery

2.        https://www.virustotal.com/gui/domain/weiss.neighb0rrol1.ru

3.        https://www.virustotal.com/gui/file/1f1aabe87e5e93a8fff769bf3614dd559c51c80fc045e11868f3843d9a004d1e/community

4.        https://www.packetlabs.net/posts/etherhiding-a-new-tactic-for-hiding-malware-on-the-blockchain/

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Vivek Rajan
Cyber Analyst

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January 30, 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.  

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