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April 16, 2025

Force Multiply Your Security Team with Agentic AI: How the Industry’s Only True Cyber AI Analyst™ Saves Time and Stop Threats

See how Darktrace Cyber AI Analyst™, an agentic AI virtual analyst, cuts through alert noise, accelerates threat response, and strengthens your security team — all without adding headcount.
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
Ed Metcalf
Senior Director of Product Marketing, AI & Innovation Products
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16
Apr 2025

With 90million investigations in 2024 alone, Darktrace Cyber AI Analyst TM is transforming security operations with AI and has added up to 30 Full Time Security Analysts to almost 10,000 security teams.

In today’s high-stakes threat landscape, security teams are overwhelmed — stretched thin by burnout, alert fatigue, and a constant barrage of fast-moving attacks. As traditional tools can’t keep up, many are turning to AI to solve these challenges. But not all AI is created equal, and no single type of AI can perform all the functions necessary to effectively streamline security operations, safeguard your organization and rapidly respond to threats.

Thus, a multi-layered AI approach is critical to enhance threat detection, investigation, and response and augment security teams. By leveraging multiple AI methods, such as machine learning, deep learning, and natural language processing, security systems become more adaptive and resilient, capable of identifying and mitigating complex cyber threats in real time. This comprehensive approach ensures that no single AI method's limitations compromise the overall security posture, providing a robust defense against evolving threats.

As leaders in AI in cybersecurity, Darktrace has been utilizing a multi-layered AI approach for years, strategically combining and layering a range of AI techniques to provide better security outcomes. One key component of this is our Cyber AI Analyst – a sophisticated agentic AI system that avoids the pitfalls of generative AI. This approach ensures expeditious and scalable investigation and analysis, accurate threat detection and rapid automated response, empowering security teams to stay ahead of today's sophisticated cyber threats.

In this blog we will explore:

  • What agentic AI is and why security teams are adopting it to deliver a set of critical functions needed in cybersecurity
  • How Darktrace’s Cyber AI AnalystTM is a sophisticated agentic AI system that uses a multi-layered AI approach to achieve better security outcomes and enhance SOC analysts
  • Introduce two new innovative machine learning models that further augment Cyber AI Analyst’s investigation and evaluation capabilities

The rise of agentic AI

To combat the overwhelming volume of alerts, the shortage of security professionals, and burnout, security teams need AI that can perform complex tasks without human intervention, also known as agentic AI. The ability of these systems to act autonomously can significantly improve efficiency and effectiveness. However, many attempts to implement agentic AI rely on generative AI, which has notable drawbacks.

Broadly speaking, agentic AI refers to artificial intelligence systems that act autonomously as "agents," capable of carrying out complex tasks, making decisions, and interacting with tools or external systems with no or limited human intervention. Unlike traditional AI models that perform predefined tasks, it uses advanced techniques to mimic human decision-making processes, dynamically adapting to new challenges and responding to varied inputs. In a narrower definition, agentic AI often uses generative large language models (LLMs) as its core, using this to plan tasks and interactions with other systems, iteratively feeding its output into its input to accomplish more tasks than are traditionally possible with a single prompt. When described in terms of technology rather than functionality, agentic AI would be deemed as AI using this kind of generative system.

In cybersecurity, agentic AI systems can be used to autonomously monitor traffic, identify unusual patterns or anomalies indicating potential threats, and take action to respond to these possible attacks. For example, they can handle incident response tasks such as isolating affected systems or patching vulnerabilities, and triaging alerts. This reduces the reliance on human analysts for routine tasks, allowing them to focus on high-priority incidents and strategic initiatives, thereby increasing the overall efficiency and effectiveness of the SOC.

Despite their potential, agentic AI systems with a generative AI core have notable limitations. Whether based on widely used foundation models or fully custom proprietary implementations, generative AI often struggles with poor reasoning and can produce incorrect conclusions. These models are prone to "hallucinations," where they generate false information, which can be magnified through iterative processes. Additionally, generative AI systems are particularly susceptible to inheriting biases from training data, leading to incorrect outcomes, and are vulnerable to adversarial attacks, such as prompt injection that manipulates the AI's decision-making process.

Thus, choosing the right agentic AI system is crucial for security teams to ensure accurate threat detection, streamline investigations, and minimize false positives. It's essential to look beyond generative AI-based systems, which can lead to false positives and missed threats, and adopt AI that integrates multiple techniques. By considering AI systems that leverage a variety of advanced methods, organizations can build a more robust and comprehensive security strategy.  

Industry’s most experienced agentic AI analyst

First introduced in 2019, Darktrace Cyber AI AnalystTM emerged as a groundbreaking, patented solution in the cybersecurity landscape. As the most experienced AI Analyst deployed to almost 10,000 customers worldwide, Cyber AI Analyst is a sophisticated example of agentic AI, aligning closely with our broad definition. Unlike generative AI-based systems, it uses a multi-layered AI approach - strategically combining and layering various AI techniques, both in parallel and sequentially – to autonomously investigate and triage alerts with speed and precision that outpaces human teams. By utilizing a diverse set of AI methods, including unsupervised machine learning, models trained on expert cyber analysts, and custom security-specific large language models, Cyber AI Analyst mirrors human investigative processes by questioning data, testing hypotheses, and reaching conclusions at machine speed and scale. It integrates data from various sources – including network, cloud, email, OT and even third-party alerts – to identify threats and execute appropriate responses without human input, ensuring accurate and reliable decision-making.

With its ability to learn and adapt using Darktrace's unique understanding of an organization’s environment, Cyber AI Analyst highlights anomalies and passes only the most relevant activity to human users. Every investigation is thoroughly explained with natural language summaries, providing transparent and interpretable AI insights. Unlike generative AI-based agentic systems, Cyber AI Analyst's outputs are based on a comprehensive understanding of the underlying data, avoiding inaccuracies and "hallucinations," thereby dramatically reducing risk of false positives.

90 million investigations. Zero burnout.

Building on six years of innovation since launch, Darktrace's Cyber AI Analyst continues to revolutionize security operations by automating time-consuming tasks and enabling teams to focus on strategic initiatives. In 2024 alone, the sophisticated AI system autonomously conducted 90 million investigations, its analysis and correlation during these investigations resulted in escalating just 3 million incidents for human validation and resulting in fewer than 500,000 incidents deemed critical to the security of the organization. This completely changed the security operations process, providing customers with an ability to investigate every relevant alert as an unprecedented alternative to detection engineering that avoids massive quantities of risk from the traditional approach.  Cyber AI Analyst performed the equivalent of 42 million hours of human investigation for relevant security alerts.

The benefits of Cyber AI Analyst will transform security operations as we know it today:

  • Autonomously investigates thousands of alerts, distilling them into a few critical incidents — saving security teams thousands of hours and removing risk from current “triage few” processes. [See how the State of Oklahoma gained 2,561 hours of investigation time and eliminated 3,142 alerts in 3 months]
  • It decreases critical incident discoverability from hours to minutes, enabling security teams to respond faster to potential threats that will severely impact their organization. Learn how South Coast Water District went from hours to minutes in incident discovery.
  • It reduces false positives by 90%, giving security teams confidence in its accuracy and output.
  • Delivers the output of up to 30 full-time analysts – without the cost, burnout, or ramp-up time, while elevating existing human security analysts to validation and response

Cyber AI Analyst allows security teams to allocate their resources more effectively, focusing on genuine threats rather than sifting through noise. This not only enhances productivity but also ensures that critical alerts are addressed promptly, minimizing potential damage and improving overall cyber resilience.

Always innovating - Next-generation AI models for cybersecurity

As empowering defenders with AI has never been more critical, Darktrace remains committed to driving innovation that helps our customers proactively reduce risk, strengthen their security posture, and uplift their teams. To further enhance security teams, Darktrace is introducing two next-generation AI models for cybersecurity within Cyber AI Analyst, including:

  • Darktrace Incident Graph Evaluation for Security Threats (DIGEST): Using graph neural networks, this model analyzes how attacks progress to predict which threats are likely to escalate — giving your team earlier warnings and sharper prioritization.  This means earlier warnings, better prioritization, and fewer surprises during active threats.
  • Darktrace Embedding Model for Investigation of Security Threats - Version 2 (DEMIST-2): This new language model is purpose-built for cybersecurity. With deep contextual understanding, it automates critical human-like analysis— like assessing hostnames, file sensitivity, and tracking users across environments. Unlike large general-purpose models, it delivers superior performance with a smaller footprint. Working across all our deployment types, including on-prem and cloud, it can run without internet access, keeping inference local.

Unlike the foundational LLMs that power many generative and agentic systems, these models are purpose-built for cybersecurity, supported by insights of over 200 security analysts and is capable of mimicking how an analyst thinks, to bring AI-based precision and depth of analysis into the SOC. By understanding how attacks evolve and predicting which threats are most likely to escalate, these machine learning models enable Cyber AI AnalystTM to provide earlier detection, sharper prioritization, and faster, more confident decision-making.

Conclusion

Darktrace Cyber AI AnalystTM redefines security operations with proven agentic AI — delivering autonomous investigations and faster response times, while significantly reducing false positives. With powerful new models like DIGEST and DEMIST-2, it empowers security teams to prioritize what matters, cut through noise, and stay ahead of evolving threats — all without additional headcount. As cyber risk grows, Cyber AI Analyst stands out as a force multiplier, driving efficiency, resilience, and confidence in every SOC.

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Additional resources

Learn more about Cyber AI Analyst

Explore the solution brief, learn how Cyber AI Analyst combines advanced AI techniques to deliver faster, more effective security outcomes

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
Ed Metcalf
Senior Director of Product Marketing, AI & Innovation Products

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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].

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

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

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

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

Autonomous Response’s intervention against the suspicious connectivity observed.
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.

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