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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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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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June 5, 2025

Unpacking ClickFix: Darktrace’s detection of a prolific social engineering tactic

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What is ClickFix and how does it work?

Amid heightened security awareness, threat actors continue to seek stealthy methods to infiltrate target networks, often finding the human end user to be the most vulnerable and easily exploited entry point.

ClickFix baiting is an exploitation of the end user, making use of social engineering techniques masquerading as error messages or routine verification processes, that can result in malicious code execution.

Since March 2024, the simplicity of this technique has drawn attention from a range of threat actors, from individual cybercriminals to Advanced Persistent Threat (APT) groups such as APT28 and MuddyWater, linked to Russia and Iran respectively, introducing security threats on a broader scale [1]. ClickFix campaigns have been observed affecting organizations in across multiple industries, including healthcare, hospitality, automotive and government [2][3].

Actors carrying out these targeted attacks typically utilize similar techniques, tools and procedures (TTPs) to gain initial access. These include spear phishing attacks, drive-by compromises, or exploiting trust in familiar online platforms, such as GitHub, to deliver malicious payloads [2][3]. Often, a hidden link within an email or malvertisements on compromised legitimate websites redirect the end user to a malicious URL [4]. These take the form of ‘Fix It’ or fake CAPTCHA prompts [4].

From there, users are misled into believing they are completing a human verification step, registering a device, or fixing a non-existent issue such as a webpage display error. As a result, they are guided through a three-step process that ultimately enables the execution of malicious PowerShell commands:

  1. Open a Windows Run dialog box [press Windows Key + R]
  2. Automatically or manually copy and paste a malicious PowerShell command into the terminal [press CTRL+V]
  3. And run the prompt [press ‘Enter’] [2]

Once the malicious PowerShell command is executed, threat actors then establish command and control (C2) communication within the targeted environment before moving laterally through the network with the intent of obtaining and stealing sensitive data [4]. Malicious payloads associated with various malware families, such as XWorm, Lumma, and AsyncRAT, are often deployed [2][3].

Attack timeline of ClickFix cyber attack

Based on investigations conducted by Darktrace’s Threat Research team in early 2025, this blog highlights Darktrace’s capability to detect ClickFix baiting activity following initial access.

Darktrace’s coverage of a ClickFix attack chain

Darktrace identified multiple ClickFix attacks across customer environments in both Europe, the Middle East, and Africa (EMEA) and the United States. The following incident details a specific attack on a customer network that occurred on April 9, 2025.

Although the initial access phase of this specific attack occurred outside Darktrace’s visibility, other affected networks showed compromise beginning with phishing emails or fake CAPTCHA prompts that led users to execute malicious PowerShell commands.

Darktrace’s visibility into the compromise began when the threat actor initiated external communication with their C2 infrastructure, with Darktrace / NETWORK detecting the use of a new PowerShell user agent, indicating an attempt at remote code execution.

Darktrace / NETWORK's detection of a device making an HTTP connection with new PowerShell user agent, indicating PowerShell abuse for C2 communications.
Figure 1: Darktrace / NETWORK's detection of a device making an HTTP connection with new PowerShell user agent, indicating PowerShell abuse for C2 communications.

Download of Malicious Files for Lateral Movement

A few minutes later, the compromised device was observed downloading a numerically named file. Numeric files like this are often intentionally nondescript and associated with malware. In this case, the file name adhered to a specific pattern, matching the regular expression: /174(\d){7}/. Further investigation into the file revealed that it contained additional malicious code designed to further exploit remote services and gather device information.

Darktrace / NETWORK's detection of a numeric file, one minute after the new PowerShell User Agent alert.
Figure 2: Darktrace / NETWORK's detection of a numeric file, one minute after the new PowerShell User Agent alert.

The file contained a script that sent system information to a specified IP address using an HTTP POST request, which also processed the response. This process was verified through packet capture (PCAP) analysis conducted by the Darktrace Threat Research team.

By analyzing the body content of the HTTP GET request, it was observed that the command converts the current time to Unix epoch time format (i.e., 9 April 2025 13:26:40 GMT), resulting in an additional numeric file observed in the URI: /1744205200.

PCAP highlighting the HTTP GET request that sends information to the specific IP, 193.36.38[.]237, which then generates another numeric file titled per the current time.
Figure 3: PCAP highlighting the HTTP GET request that sends information to the specific IP, 193.36.38[.]237, which then generates another numeric file titled per the current time.

Across Darktrace’s investigations into other customers' affected by ClickFix campaigns, both internal information discovery events and further execution of malicious code were observed.

Data Exfiltration

By following the HTTP stream in the same PCAP, the Darktrace Threat Research Team assessed the activity as indicative of data exfiltration involving system and device information to the same command-and-control (C2) endpoint, , 193.36.38[.]237. This endpoint was flagged as malicious by multiple open-source intelligence (OSINT) vendors [5].

PCAP highlighting HTTP POST connection with the numeric file per the URI /1744205200 that indicates data exfiltration to 193.36.38[.]237.
Figure 4: PCAP highlighting HTTP POST connection with the numeric file per the URI /1744205200 that indicates data exfiltration to 193.36.38[.]237.

Further analysis of Darktrace’s Advanced Search logs showed that the attacker’s malicious code scanned for internal system information, which was then sent to a C2 server via an HTTP POST request, indicating data exfiltration

Advanced Search further highlights Darktrace's observation of the HTTP POST request, with the second numeric file representing data exfiltration.
Figure 5: Advanced Search further highlights Darktrace's observation of the HTTP POST request, with the second numeric file representing data exfiltration.

Actions on objectives

Around ten minutes after the initial C2 communications, the compromised device was observed connecting to an additional rare endpoint, 188.34.195[.]44. Further analysis of this endpoint confirmed its association with ClickFix campaigns, with several OSINT vendors linking it to previously reported attacks [6].

In the final HTTP POST request made by the device, Darktrace detected a file at the URI /init1234 in the connection logs to the malicious endpoint 188.34.195[.]44, likely depicting the successful completion of the attack’s objective, automated data egress to a ClickFix C2 server.

Darktrace / NETWORK grouped together the observed indicators of compromise (IoCs) on the compromised device and triggered an Enhanced Monitoring model alert, a high-priority detection model designed to identify activity indicative of the early stages of an attack. These models are monitored and triaged 24/7 by Darktrace’s Security Operations Center (SOC) as part of the Managed Threat Detection service, ensuring customers are promptly notified of malicious activity as soon as it emerges.

Darktrace correlated the separate malicious connections that pertained to a single campaign.
Figure 6: Darktrace correlated the separate malicious connections that pertained to a single campaign.

Darktrace Autonomous Response

In the incident outlined above, Darktrace was not configured in Autonomous Response mode. As a result, while actions to block specific connections were suggested, they had to be manually implemented by the customer’s security team. Due to the speed of the attack, this need for manual intervention allowed the threat to escalate without interruption.

However, in a different example, Autonomous Response was fully enabled, allowing Darktrace to immediately block connections to the malicious endpoint (138.199.156[.]22) just one second after the initial connection in which a numerically named file was downloaded [7].

Darktrace Autonomous Response blocked connections to a suspicious endpoint following the observation of the numeric file download.
Figure 7: Darktrace Autonomous Response blocked connections to a suspicious endpoint following the observation of the numeric file download.

This customer was also subscribed to our Managed Detection and Response service, Darktrace’s SOC extended a ‘Quarantine Device’ action that had already been autonomously applied in order to buy their security team additional time for remediation.

Autonomous Response blocked connections to malicious endpoints, including 138.199.156[.]22, 185.250.151[.]155, and rkuagqnmnypetvf[.]top, and also quarantined the affected device. These actions were later manually reinforced by the Darktrace SOC.
Figure 8: Autonomous Response blocked connections to malicious endpoints, including 138.199.156[.]22, 185.250.151[.]155, and rkuagqnmnypetvf[.]top, and also quarantined the affected device. These actions were later manually reinforced by the Darktrace SOC.

Conclusion

ClickFix baiting is a widely used tactic in which threat actors exploit human error to bypass security defenses. By tricking end point users into performing seemingly harmless, everyday actions, attackers gain initial access to systems where they can access and exfiltrate sensitive data.

Darktrace’s anomaly-based approach to threat detection identifies early indicators of targeted attacks without relying on prior knowledge or IoCs. By continuously learning each device’s unique pattern of life, Darktrace detects subtle deviations that may signal a compromise. In this case, Darktrace's Autonomous Response, when operating in a fully autonomous mode, was able to swiftly contain the threat before it could progress further along the attack lifecycle.

Credit to Keanna Grelicha (Cyber Analyst) and Jennifer Beckett (Cyber Analyst)

Appendices

NETWORK Models

  • Device / New PowerShell User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous Connection / Posting HTTP to IP Without Hostname
  • Anomalous Connection / Powershell to Rare External
  • Device / Suspicious Domain
  • Device / New User Agent and New IP
  • Anomalous File / New User Agent Followed By Numeric File Download (Enhanced Monitoring Model)
  • Device / Initial Attack Chain Activity (Enhanced Monitoring Model)

Autonomous Response Models

  • Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block
  • Antigena / Network::Significant Anomaly::Antigena Enhanced Monitoring from Client Block
  • Antigena / Network::External Threat::Antigena File then New Outbound Block
  • Antigena / Network::External Threat::Antigena Suspicious File Block
  • Antigena / Network::Significant Anomaly::Antigena Alerts Over Time Block
  • Antigena / Network::External Threat::Antigena Suspicious File Block

IoC - Type - Description + Confidence

·       141.193.213[.]11 – IP address – Possible C2 Infrastructure

·       141.193.213[.]10 – IP address – Possible C2 Infrastructure

·       64.94.84[.]217 – IP address – Possible C2 Infrastructure

·       138.199.156[.]22 – IP address – C2 server

·       94.181.229[.]250 – IP address – Possible C2 Infrastructure

·       216.245.184[.]181 – IP address – Possible C2 Infrastructure

·       212.237.217[.]182 – IP address – Possible C2 Infrastructure

·       168.119.96[.]41 – IP address – Possible C2 Infrastructure

·       193.36.38[.]237 – IP address – C2 server

·       188.34.195[.]44 – IP address – C2 server

·       205.196.186[.]70 – IP address – Possible C2 Infrastructure

·       rkuagqnmnypetvf[.]top – Hostname – C2 server

·       shorturl[.]at/UB6E6 – Hostname – Possible C2 Infrastructure

·       tlgrm-redirect[.]icu – Hostname – Possible C2 Infrastructure

·       diagnostics.medgenome[.]com – Hostname – Compromised Website

·       /1741714208 – URI – Possible malicious file

·       /1741718928 – URI – Possible malicious file

·       /1743871488 – URI – Possible malicious file

·       /1741200416 – URI – Possible malicious file

·       /1741356624 – URI – Possible malicious file

·       /ttt – URI – Possible malicious file

·       /1741965536 – URI – Possible malicious file

·       /1.txt – URI – Possible malicious file

·       /1744205184 – URI – Possible malicious file

·       /1744139920 – URI – Possible malicious file

·       /1744134352 – URI – Possible malicious file

·       /1744125600 – URI – Possible malicious file

·       /1[.]php?s=527 – URI – Possible malicious file

·       34ff2f72c191434ce5f20ebc1a7e823794ac69bba9df70721829d66e7196b044 – SHA-256 Hash – Possible malicious file

·       10a5eab3eef36e75bd3139fe3a3c760f54be33e3 – SHA-1 Hash – Possible malicious file

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique  

Spearphishing Link - INITIAL ACCESS - T1566.002 - T1566

Drive-by Compromise - INITIAL ACCESS - T1189

PowerShell - EXECUTION - T1059.001 - T1059

Exploitation of Remote Services - LATERAL MOVEMENT - T1210

Web Protocols - COMMAND AND CONTROL - T1071.001 - T1071

Automated Exfiltration - EXFILTRATION - T1020 - T1020.001

References

[1] https://www.logpoint.com/en/blog/emerging-threats/clickfix-another-deceptive-social-engineering-technique/

[2] https://www.proofpoint.com/us/blog/threat-insight/security-brief-clickfix-social-engineering-technique-floods-threat-landscape

[3] https://cyberresilience.com/threatonomics/understanding-the-clickfix-attack/

[4] https://www.group-ib.com/blog/clickfix-the-social-engineering-technique-hackers-use-to-manipulate-victims/

[5] https://www.virustotal.com/gui/ip-address/193.36.38.237/detection

[6] https://www.virustotal.com/gui/ip-address/188.34.195.44/community

[7] https://www.virustotal.com/gui/ip-address/138.199.156.22/detection

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Keanna Grelicha
Cyber Analyst

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June 4, 2025

Beyond Discovery: Adding Intelligent Vulnerability Validation to Darktrace / Attack Surface Management

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Introducing Exploit Prediction Assessment

Security teams are drowning in vulnerability alerts, but only a fraction of those issues pose a real threat. The new Exploit Prediction Assessment feature in Darktrace / Attack Surface Management helps teams cut through the noise by validating which vulnerabilities on their external attack surface can be actively exploited.

Instead of relying solely on CVSS scores or waiting for patch cycles, Exploit Prediction Assessment uses safe, targeted simulations to test whether exposed systems can be compromised, delivering fast, evidence-based results in under 72 hours.

This capability augments traditional pen testing and complements existing ASM workflows by transforming passive discovery into actionable insight. With EPA, security teams move from reacting to long lists of potential vulnerabilities to making confident, risk-based decisions on what actually matters.

Key highlights of Exploit Prediction Assessment

Simulated attacks to validate real risk

Exploit Prediction Assessment conducts safe, simulated attacks on assets with potential security vulnerabilities that have been identified by Darktrace / Attack Surface Management. This real-time testing validates your systems' susceptibility to compromise by confirming which vulnerabilities are present and exploitable on your attack surface.

Prioritize what matters most

Confirmed security risks can be prioritized for mitigation, ensuring that the most critical threats are promptly addressed. This takes the existing letter ranking system and brings it a step further by drilling down to yet another level. Even in the most overwhelming situations, teams will be able to act on a pragmatic, clear-cut plan.

Fast results, tailored to your environment

Customers set the scope of the Exploit Prediction Assessment within Darktrace / Attack Surface Management and receive the results of the surgical vulnerability testing within 72 hours. Users will see 1 of 2 shields:

1. A green shield with a check mark: Meaning no vulnerabilities were found on scanned CVEs for the asset.

2. A red shield with a red x: Meaning at least one vulnerability was found on scanned CVEs for the asset.

Why it's a game changer

Traditionally, attack surface management tools have focused on identifying exposed assets and vulnerabilities but lacked the context to determine which issues posed the greatest risk. Without context on what’s exploitable, security teams are left triaging long lists of potential risks, operating in isolation from broader business objectives. This misalignment ultimately leads to both weakened risk posture and cross team communication and execution.

This is where Continuous Threat Exposure Management (CTEM) becomes essential. Introduced by Gartner, CTEM is a framework that helps organizations continuously assess, validate, and improve their exposure to real-world threats. The goal isn’t just visibility, it’s to understand how an attacker could move through your environment today, and what to fix first to stop them.

Exploit Prediction Assessment brings this philosophy to life within Darktrace / Attack Surface Management. By safely simulating exploit attempts against identified vulnerabilities, it validates which exposures are truly at risk—transforming ASM from a discovery tool into a risk-based decision engine.

This capability directly supports the validation and prioritization phases of CTEM, helping teams focus on exploitable vulnerabilities rather than theoretical ones.  This shift from visibility to action reduces the risk of critical vulnerabilities in the technology stack being overlooked, turning overwhelming vulnerability data into focused, clear actionable insights.

As attack surfaces continue to grow and change, organizations need more than static scans they need continuous, contextual insight. Exploit Prediction Assessment ensures your ASM efforts evolve with the threat landscape, making CTEM a practical reality, not just a strategy.

Exploit Prediction Assessment in action

With Darktrace / Attack Surface Management organizations can get Exploit Prediction Assessment, and the cyber risk team no longer guesses which vulnerabilities matter most. Instead, they identify several externally exposed areas of their attack surface, then use the feature to surgically test for exploitability across these exposed endpoints. Within 72 hours, they receive a report:  

Positive outcome: Based on information in the html or the headers it seems that a vulnerable software version is running on an externally exposed infrastructure. By running a targeted attack on this infrastructure, we can confirm that it cannot be abused.

Negative outcome: Based on information in the html or the headers it seems that a vulnerable software version is running on an externally exposed infrastructure. By running a targeted attack on this infrastructure, we can confirm that it can be exploited, so we can predict it being exploited.

This second outcome changes everything. The team immediately prioritizes the exploitable asset for patching and takes the necessary adjustments to mitigate exposure until the fix is deployed.

Instead of spreading their resources thin across dozens of alerts, they focus on what poses a real threat, saving time, reducing risk, and demonstrating actionable results to stakeholders.

Conclusion

Exploit Predication Assessment bolsters Darktrace’s commitment to proactive cybersecurity. It supports intelligent prioritization of vulnerabilities, keeping organizations ahead of emerging threats. With this new addition to / Attack Surface Management, teams have another tool to empower a more efficient approach to addressing security gaps in real-time.

Stay tuned for more updates and insights on how Darktrace continues to develop a culture of proactive security across the entire ActiveAI Security Platform.

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Kelland Goodin
Product Marketing Specialist
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