Blog
/
AI
/
November 29, 2022

How to Cut Through Cyber Security Noise

Learn how Cyber AI Analyst tackles alert fatigue by categorizing vast amounts of data into actionable security incidents for your team's review.
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
Dan Fein
VP, Product
Written by
Elliot Stocker
Product SME
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
29
Nov 2022

For cyber security experts, it’s hard enough staying on top of the latest threats and emerging attacks without having to deal with a virtual tsunami of alert noise from systems monitoring email, SaaS environments, and endpoints – in addition to IaaS cloud and on-premises networks. Unfortunately, fatigue from these demands can lead to overworking, burnout, and crucially, high employee turnover. 

The worldwide industry shortage of 3.5 million cyber security professionals only exacerbates the problem. Not only does it add pressure to the current stock of skilled and available security professionals, but it also raises the stakes for CISOs and other security leaders to find a way to cut through the alert noise while staying on ahead of threat actors who never stop innovating and applying novel malware strains and attack techniques.

Working Smarter Not Harder

One way to help with retention is to empower security teams to break away from monotony and to think creatively and leverage their expertise where it can really add value. Working smarter, rather than harder, is often easier said than done, but by employing automation and AI-driven tools to take on the heavy lifting of threat detection, investigation, and response, human teams can be given the breathing room needed to focus on long-term objectives and think more deeply about their security approaches.

It is important for security programs to continuously level up alongside evolving threat landscapes by questioning existing security operations, and this cannot be achieved during times of hand-to-hand alert combat.

When alerts are fewer, higher quality, and context-heavy, the background to each can be easily explored, whether that’s reevaluating a policy or configuration, or simply asking useful questions around the company’s broader security approach. Work done at this level empowers security teams and fosters growth.

Less is More

Business risk– or the potential impact of cyber disruption– should be the number one concern driving a security team, but lack of resources is a near-constant constraint. Reducing the volume of alerts doesn’t just mean bringing the noise floor up. You can think of the noise floor as an alert threshold: if it is too high then there are fewer alerts, but more threats may be missed, whereas if it is too low, there are high volumes of unhelpful false positives. Freeing up time for the team must not equate to ignoring alerts; it should instead mean focusing on the alerts that matter.

Darktrace’s technologies make this possible, with Darktrace DETECT™ and Cyber AI Analyst working together to address alert fatigue and burnout for security teams while strengthening an organizations’ overall security posture. Cyber AI Analyst essentially takes over the busy work from the human analysts and elevates a team’s overall decision making. Teams now operate at higher levels, as they’re not stuck in mundane alert management and humans are brought in only after the machine and AI have done the heavy lifting.

“Before AI Analyst, we were barely treading water with all of the alerts, most of which were false positives, our old systems produced daily. With AI Analyst, we’ve been able to exponentially reduce those alerts, harden our environment, and get strategic.”

Dr. Robert Spangler, the CISO and Assistant Executive Director of the New Jersey State Bar Association.

Figure 1: Billions of individual events are reduced into a critical incident for review


Imagine a scenario in which Darktrace observed around 9.6 billion events over a 28-day period. DETECT and Cyber AI Analyst might distill that huge amount of data down into just, say, 54 critical incidents, or just two per day. Here’s how:

9.6 billion events

When trying to understand the full picture, every single puzzle piece counts. That’s why Darktrace’s Self-Learning AI goes wherever your organization has data, integrating with data sources across the digital estate, including network, email, endpoints, OT, cloud, and SaaS environments. And with an open architecture, Darktrace facilitates quick and easy integrations with everything from SIEMs and SOARs to public clouds and the latest Zero Trust technologies. So, any data can become learnable, whether directly ingested or via integration.

By examining this full and contextualized data set, Self-Learning AI builds a constantly evolving understanding of what ‘normal’ looks like for the entire organization. Every connection, every email, app login, resource accessed, VM spun up, PLC reprogrammed, and more become signals from which Darktrace can learn, evaluate, and improve its understanding.

40,404 model breaches

The billions of events are analyzed by Darktrace DETECT, which uses its extensive knowledge of ‘normal’ to draw out hosts of subtle anomalies or ‘AI model breaches.’ Many of these AI model breaches will be weak indicators of threatening activity, and most will not be sufficient to individually signal a threat. For that reason, no human attention is required at this stage. Darktrace DETECT will continue to draw anomalous behaviors from the ongoing stream of events without the need for intervention. 

200 incidents

The Cyber AI Analyst takes the total list of model breaches collated by DETECT and performs the truly sophisticated work of determining distinct threat incidents. By piecing together anomalies which may, in themselves, appear harmless, the AI Analyst draws out subtle and often wide-ranging attacks, tracking their route from the initial compromise to the present moment. This creates a much shorter list of genuine threat incidents, but there is still no need for human attention at this stage.

54 critical incidents

Once it has discovered the threat incidents facing an organization, the Cyber AI Analyst begins the crucial processes of triage to determine which incidents need to be surfaced to the security team, and in what order of priority. This supplies the human team with a highly focused briefing of the most pressing threats, massively reducing their overall workload and minimizing or potentially eradicating alert fatigue. In the above example of a month with over 9.6 billion distinct events, the team are left with just two incidents to address per day. These two incidents are clearly presented with natural language-processing and all the most relevant info, including details, devices, and dates. 

“When we had other, noisier systems, we didn’t have the time to have truly in-depth discussions or conduct deep investigations, so there were fewer teachable moments for junior team members and fewer opportunities to inform our cybersecurity strategy as a whole,” Spangler said. “Now, we’re not just a better team, we’re more efficient, responsive, and informed than we’ve ever been. We’re all better cyber security professionals as a result.”

In the event of a breach, CISOs and security leaders want the full incident report, and they want it yesterday. The promise of AI is to handle specific tasks at a speed and scale that humans can’t. Going from 9.6 billion events to 54 incidents demonstrates the scale, but it’s important to consider the impact of speed here as well, as the Cyber AI Analyst works in real time, meaning all relevant events are presented in an easy to consume downloadable report available immediately upon investigation.

This isn’t a black box either; every step of the AI Analyst’s investigation process is visible to the human team. Not only can they see the relevant events and breaches that led to the incident, but if required, they can pivot into them easily with a click. If the investigation requires going all the way down to the metadata level to easily peruse the filtered events of the 9.6 billion overall signals or even to PCAP data, those are available and easy to find too.

Since DETECT and Cyber AI Analyst not only reduce alert fatigue but also simplify incident investigations, security teams feel empowered and experience less burnout. 

“We’ve been stable and have had minimal turnover since we started using AI Analyst,” Spangler said. “We’re not scrambling to keep up with noisy and time-consuming false positives, making the investigations that we undertake stimulating and– I say this cautiously– fun! Put simply, the thing we all love about this career, the virtual chess game we play with attackers, is a lot more fun when you know you’re going to win.”

Autonomous Response

Organizations that deploy Darktrace RESPOND™ can address the incidents raised by DETECT and the Cyber AI Analyst autonomously, and in mere seconds. Using the full context of the organization built up by Self-Learning AI, RESPOND takes the least disruptive measures necessary to disarm threats at machine speed. By the time the security team learns about the attack, it is already contained, continuing to save them from the hand-to-hand combat of threat fighting.

With day-to-day threat detection, response, and analysis taken care of, security teams are free to give full and sustained attention to their overall security posture. Neutralized threats may yet reveal broader security gaps and potential improvements which the team now has the time and headspace to pursue.

For example, discovering a trend that users are uploading potentially sensitive data via third-party file-sharing services might lead to a discussion about whether it should be company policy to block access to this service, reducing to zero the number of future alerts that would have been triggered by this behavior. Importantly, this wouldn’t be altering the aforementioned noise floor, but instead fundamentally altering security policies to align with the needs of the business, which could indirectly affect future alerting, as activities may subside.

As a result, practitioners find more value in their work, security teams efforts are optimized, and organizations are strengthened overall.

“We’re now focused on the items that AI Analyst alerts us to, which are always worth looking into because they either identify an activity that we need to get eyes on and/or provide us with insight into ways we can harden our network,” Spangler said. “The hardening that we’ve done has been incalculably beneficial– it’s one of the reasons we get fewer alerts, and it’s also protected us against a wide variety of threats.”

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
Dan Fein
VP, Product
Written by
Elliot Stocker
Product SME

More in this series

No items found.

Blog

/

Network

/

June 5, 2025

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

Woman on laptop in office buildingDefault blog imageDefault blog image

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

Continue reading
About the author
Keanna Grelicha
Cyber Analyst

Blog

/

Proactive Security

/

June 4, 2025

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

Man on computer doing workDefault blog imageDefault blog image

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.

[related-resource]

Continue reading
About the author
Kelland Goodin
Product Marketing Specialist
Your data. Our AI.
Elevate your network security with Darktrace AI
OSZAR »