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November 25, 2024

Why Artificial Intelligence is the Future of Cybersecurity

This blog explores the impact of AI on the threat landscape, the benefits of AI in cybersecurity, and the role it plays in enhancing security practices and tools.
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
Brittany Woodsmall
Product Marketing Manager, AI & Attack Surface
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25
Nov 2024

Introduction: AI & Cybersecurity

In the wake of artificial intelligence (AI) becoming more commonplace, it’s no surprise to see that threat actors are also adopting the use of AI in their attacks at an accelerated pace. AI enables augmentation of complex tasks such as spear-phishing, deep fakes, polymorphic malware generation, and advanced persistent threat (APT) campaigns, which significantly enhances the sophistication and scale of their operations. This has put security professionals in a reactive state, struggling to keep pace with the proliferation of threats.

As AI reshapes the future of cyber threats, defenders are also looking to integrate AI technologies into their security stack. Adopting AI-powered solutions in cybersecurity enables security teams to detect and respond to these advanced threats more quickly and accurately as well as automate traditionally manual and routine tasks. According to research done by Darktrace in the 2024 State of AI Cybersecurity Report improving threat detection, identifying exploitable vulnerabilities, and automating low level security tasks were the top three ways practitioners saw AI enhancing their security team’s capabilities [1], underscoring the wide-ranging capabilities of AI in cyber.  

In this blog, we will discuss how AI has impacted the threat landscape, the rise of generative AI and AI adoption in security tools, and the importance of using multiple types of AI in cybersecurity solutions for a holistic and proactive approach to keeping your organization safe.  

The impact of AI on the threat landscape

The integration of AI and cybersecurity has brought about significant advancements across industries. However, it also introduces new security risks that challenge traditional defenses.  Three major concerns with the misuse of AI being leveraged by adversaries are: (1) the increase of novel social engineering attacks that are harder to detect and able to bypass traditional security tools,  (2) the ease of access for less experienced threat actors to now deliver advanced attacks at speed and scale and (3) the attacking of AI itself, to include machine learning models, data corpuses and APIs or interfaces.

In the context of social engineering, AI can be used to create more convincing phishing emails, conduct advanced reconnaissance, and simulate human-like interactions to deceive victims more effectively. Generative AI tools, such as ChatGPT, are already being used by adversaries to craft these sophisticated phishing emails, which can more aptly mimic human semantics without spelling or grammatical error and include personal information pulled from internet sources such as social media profiles. And this can all be done at machine speed and scale. In fact, Darktrace researchers observed a 135% rise in ‘novel social engineering attacks’ across Darktrace / EMAIL customers in 2023, corresponding to the widespread adoption and use of ChatGPT [2].  

Furthermore, these sophisticated social engineering attacks are now able to circumvent traditional security tools. In between December 21, 2023, and July 5, 2024, Darktrace / EMAIL detected 17.8 million phishing emails across the fleet, with 62% of these phishing emails successfully bypassing Domain-based Message Authentication, Reporting, and Conformance (DMARC) verification checks [2].  

And while the proliferation of novel attacks fueled by AI is persisting, AI also lowers the barrier to entry for threat actors. Publicly available AI tools make it easy for adversaries to automate complex tasks that previously required advanced technical skills. Additionally, AI-driven platforms and phishing kits available on the dark web provide ready-made solutions, enabling even novice attackers to execute effective cyber campaigns with minimal effort.

The impact of adversarial use of AI on the ever-evolving threat landscape is important for organizations to understand as it fundamentally changes the way we must approach cybersecurity. However, while the intersection of cybersecurity and AI can have potentially negative implications, it is important to recognize that AI can also be used to help protect us.

A generation of generative AI in cybersecurity

When the topic of AI in cybersecurity comes up, it’s typically in reference to generative AI, which became popularized in 2023. While it does not solely encapsulate what AI cybersecurity is or what AI can do in this space, it’s important to understand what generative AI is and how it can be implemented to help organizations get ahead of today’s threats.  

Generative AI (e.g., ChatGPT or Microsoft Copilot) is a type of AI that creates new or original content. It has the capability to generate images, videos, or text based on information it learns from large datasets. These systems use advanced algorithms and deep learning techniques to understand patterns and structures within the data they are trained on, enabling them to generate outputs that are coherent, contextually relevant, and often indistinguishable from human-created content.

For security professionals, generative AI offers some valuable applications. Primarily, it’s used to transform complex security data into clear and concise summaries. By analyzing vast amounts of security logs, alerts, and technical data, it can contextualize critical information quickly and present findings in natural, comprehensible language. This makes it easier for security teams to understand critical information quickly and improves communication with non-technical stakeholders. Generative AI can also automate the creation of realistic simulations for training purposes, helping security teams prepare for various cyberattack scenarios and improve their response strategies.  

Despite its advantages, generative AI also has limitations that organizations must consider. One challenge is the potential for generating false positives, where benign activities are mistakenly flagged as threats, which can overwhelm security teams with unnecessary alerts. Moreover, implementing generative AI requires significant computational resources and expertise, which may be a barrier for some organizations. It can also be susceptible to prompt injection attacks and there are risks with intellectual property or sensitive data being leaked when using publicly available generative AI tools.  In fact, according to the MIT AI Risk Registry, there are potentially over 700 risks that need to be mitigated with the use of generative AI.

Generative AI impact on cyber attacks screenshot data sheet

For more information on generative AI's impact on the cyber threat landscape download the Darktrace Data Sheet

Beyond the Generative AI Glass Ceiling

Generative AI has a place in cybersecurity, but security professionals are starting to recognize that it’s not the only AI organizations should be using in their security tool kit. In fact, according to Darktrace’s State of AI Cybersecurity Report, “86% of survey participants believe generative AI alone is NOT enough to stop zero-day threats.” As we look toward the future of AI in cybersecurity, it’s critical to understand that different types of AI have different strengths and use cases and choosing the technologies based on your organization’s specific needs is paramount.

There are a few types of AI used in cybersecurity that serve different functions. These include:

Supervised Machine Learning: Widely used in cybersecurity due to its ability to learn from labeled datasets. These datasets include historical threat intelligence and known attack patterns, allowing the model to recognize and predict similar threats in the future. For example, supervised machine learning can be applied to email filtering systems to identify and block phishing attempts by learning from past phishing emails. This is human-led training facilitating automation based on known information.  

Large Language Models (LLMs): Deep learning models trained on extensive datasets to understand and generate human-like text. LLMs can analyze vast amounts of text data, such as security logs, incident reports, and threat intelligence feeds, to identify patterns and anomalies that may indicate a cyber threat. They can also generate detailed and coherent reports on security incidents, summarizing complex data into understandable formats.

Natural Language Processing (NLP): Involves the application of computational techniques to process and understand human language. In cybersecurity, NLP can be used to analyze and interpret text-based data, such as emails, chat logs, and social media posts, to identify potential threats. For instance, NLP can help detect phishing attempts by analyzing the language used in emails for signs of deception.

Unsupervised Machine Learning: Continuously learns from raw, unstructured data without predefined labels. It is particularly useful in identifying new and unknown threats by detecting anomalies that deviate from normal behavior. In cybersecurity, unsupervised learning can be applied to network traffic analysis to identify unusual patterns that may indicate a cyberattack. It can also be used in endpoint detection and response (EDR) systems to uncover previously unknown malware by recognizing deviations from typical system behavior.

Types of AI in cybersecurity
Figure 1: Types of AI in cybersecurity

Employing multiple types of AI in cybersecurity is essential for creating a layered and adaptive defense strategy. Each type of AI, from supervised and unsupervised machine learning to large language models (LLMs) and natural language processing (NLP), brings distinct capabilities that address different aspects of cyber threats. Supervised learning excels at recognizing known threats, while unsupervised learning uncovers new anomalies. LLMs and NLP enhance the analysis of textual data for threat detection and response and aid in understanding and mitigating social engineering attacks. By integrating these diverse AI technologies, organizations can achieve a more holistic and resilient cybersecurity framework, capable of adapting to the ever-evolving threat landscape.

A Multi-Layered AI Approach with Darktrace

AI-powered security solutions are emerging as a crucial line of defense against an AI-powered threat landscape. In fact, “Most security stakeholders (71%) are confident that AI-powered security solutions will be better able to block AI-powered threats than traditional tools.” And 96% agree that AI-powered solutions will level up their organization’s defenses.  As organizations look to adopt these tools for cybersecurity, it’s imperative to understand how to evaluate AI vendors to find the right products as well as build trust with these AI-powered solutions.  

Darktrace, a leader in AI cybersecurity since 2013, emphasizes interpretability, explainability, and user control, ensuring that our AI is understandable, customizable and transparent. Darktrace’s approach to cyber defense is rooted in the belief that the right type of AI must be applied to the right use cases. Central to this approach is Self-Learning AI, which is crucial for identifying novel cyber threats that most other tools miss. This is complemented by various AI methods, including LLMs, generative AI, and supervised machine learning, to support the Self-Learning AI.  

Darktrace focuses on where AI can best augment the people in a security team and where it can be used responsibly to have the most positive impact on their work. With a combination of these AI techniques, applied to the right use cases, Darktrace enables organizations to tailor their AI defenses to unique risks, providing extended visibility across their entire digital estates with the Darktrace ActiveAI Security Platform™.

Credit to: Ed Metcalf, Senior Director Product Marketing, AI & Innovations - Nicole Carignan VP of Strategic Cyber AI for their contribution to this blog.

CISOs guide to buying AI white paper cover

To learn more about Darktrace and AI in cybersecurity download the CISO’s Guide to Cyber AI here.

Download the white paper to learn how buyers should approach purchasing AI-based solutions. It includes:

  • Key steps for selecting AI cybersecurity tools
  • Questions to ask and responses to expect from vendors
  • Understand tools available and find the right fit
  • Ensure AI investments align with security goals and needs
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
Brittany Woodsmall
Product Marketing Manager, AI & Attack Surface

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October 20, 2025

Salty Much: Darktrace’s view on a recent Salt Typhoon intrusion

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What is Salt Typhoon?

Salt Typhoon represents one of the most persistent and sophisticated cyber threats targeting global critical infrastructure today. Believed to be linked to state-sponsored actors from the People’s Republic of China (PRC), this advanced persistent threat (APT) group has executed a series of high-impact campaigns against telecommunications providers, energy networks, and government systems—most notably across the United States.

Active since at least 2019, the group—also tracked as Earth Estries, GhostEmperor, and UNC2286—has demonstrated advanced capabilities in exploiting edge devices, maintaining deep persistence, and exfiltrating sensitive data across more than 80 countries. While much of the public reporting has focused on U.S. targets, Salt Typhoon’s operations have extended into Europe, the Middle East, and Africa (EMEA) where it has targeted telecoms, government entities, and technology firms. Its use of custom malware and exploitation of high-impact vulnerabilities (e.g., Ivanti, Fortinet, Cisco) underscores the strategic nature of its campaigns, which blend intelligence collection with geopolitical influence [1].

Leveraging zero-day exploits, obfuscation techniques, and lateral movement strategies, Salt Typhoon has demonstrated an alarming ability to evade detection and maintain long-term access to sensitive environments. The group’s operations have exposed lawful intercept systems, compromised metadata for millions of users, and disrupted essential services, prompting coordinated responses from intelligence agencies and private-sector partners worldwide. As organizations reassess their threat models, Salt Typhoon serves as a stark reminder of the evolving nature of nation-state cyber operations and the urgent need for proactive defense strategies.

Darktrace’s coverage

In this case, Darktrace observed activity in a European telecommunications organisation consistent with Salt Typhoon’s known tactics, techniques and procedures (TTPs), including dynamic-link library (DLL) sideloading and abuse of legitimate software for stealth and execution.

Initial access

The intrusion likely began with exploitation of a Citrix NetScaler Gateway appliance in the first week of July 2025. From there, the actor pivoted to Citrix Virtual Delivery Agent (VDA) hosts in the client’s Machine Creation Services (MCS) subnet. Initial access activities in the intrusion originated from an endpoint potentially associated with the SoftEther VPN service, suggesting infrastructure obfuscation from the outset.

Tooling

Darktrace subsequently observed the threat actor delivering a backdoor assessed with high confidence to be SNAPPYBEE (also known as Deed RAT) [2][3] to multiple Citrix VDA hosts. The backdoor was delivered to these internal endpoints as a DLL alongside legitimate executable files for antivirus software such as Norton Antivirus, Bkav Antivirus, and IObit Malware Fighter. This pattern of activity indicates that the attacker relied on DLL side-loading via legitimate antivirus software to execute their payloads. Salt Typhoon and similar groups have a history of employing this technique [4][5], enabling them to execute payloads under the guise of trusted software and bypassing traditional security controls.

Command-and-Control (C2)

The backdoor delivered by the threat actor leveraged LightNode VPS endpoints for C2, communicating over both HTTP and an unidentified TCP-based protocol. This dual-channel setup is consistent with Salt Typhoon’s known use of non-standard and layered protocols to evade detection. The HTTP communications displayed by the backdoor included POST requests with an Internet Explorer User-Agent header and Target URI patterns such as “/17ABE7F017ABE7F0”. One of the C2 hosts contacted by compromised endpoints was aar.gandhibludtric[.]com (38.54.63[.]75), a domain recently linked to Salt Typhoon [6].

Detection timeline

Darktrace produced high confidence detections in response to the early stages of the intrusion, with both the initial tooling and C2 activities being strongly covered by both investigations by Darktrace Cyber AI AnalystTM investigations and Darktrace models. Despite the sophistication of the threat actor, the intrusion activity identified and remediated before escalating beyond these early stages of the attack, with Darktrace’s timely high-confidence detections likely playing a key role in neutralizing the threat.

Cyber AI Analyst observations

Darktrace’s Cyber AI Analyst autonomously investigated the model alerts generated by Darktrace during the early stages of the intrusion. Through its investigations, Cyber AI Analyst discovered the initial tooling and C2 events and pieced them together into unified incidents representing the attacker’s progression.

Cyber AI Analyst weaved together separate events from the intrusion into broader incidents summarizing the attacker’s progression.
Figure 1: Cyber AI Analyst weaved together separate events from the intrusion into broader incidents summarizing the attacker’s progression.

Conclusion

Based on overlaps in TTPs, staging patterns, infrastructure, and malware, Darktrace assesses with moderate confidence that the observed activity was consistent with Salt Typhoon/Earth Estries (ALA GhostEmperor/UNC2286). Salt Typhoon continues to challenge defenders with its stealth, persistence, and abuse of legitimate tools. As attackers increasingly blend into normal operations, detecting behavioral anomalies becomes essential for identifying subtle deviations and correlating disparate signals. The evolving nature of Salt Typhoon’s tradecraft, and its ability to repurpose trusted software and infrastructure, ensures it will remain difficult to detect using conventional methods alone. This intrusion highlights the importance of proactive defense, where anomaly-based detections, not just signature matching, play a critical role in surfacing early-stage activity.

Credit to Nathaniel Jones (VP, Security & AI Strategy, FCISO), Sam Lister (Specialist Security Researcher), Emma Foulger (Global Threat Research Operations Lead), Adam Potter (Senior Cyber Analyst)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Indicators of Compromise (IoCs)

IoC-Type-Description + Confidence

89.31.121[.]101 – IP Address – Possible C2 server

hxxp://89.31.121[.]101:443/WINMM.dll - URI – Likely SNAPPYBEE download

b5367820cd32640a2d5e4c3a3c1ceedbbb715be2 - SHA1 – Likely SNAPPYBEE download

hxxp://89.31.121[.]101:443/NortonLog.txt - URI - Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/123.txt - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/123.tar - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/pdc.exe - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443//Dialog.dat - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/fltLib.dll - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/DisplayDialog.exe - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/DgApi.dll - URI - Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/dbindex.dat - URI - Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/1.txt - URI - Possible DLL side-loading activity

hxxp://89.31.121[.]101:443/imfsbDll.dll – Likely DLL side-loading activity

hxxp://89.31.121[.]101:443/imfsbSvc.exe - URI – Likely DLL side-loading activity

aar.gandhibludtric[.]com – Hostname – Likely C2 server

38.54.63[.]75 – IP – Likely C2 server

156.244.28[.]153 – IP – Possible C2 server

hxxp://156.244.28[.]153/17ABE7F017ABE7F0 - URI – Possible C2 activity

MITRE TTPs

Technique | Description

T1190 | Exploit Public-Facing Application - Citrix NetScaler Gateway compromise

T1105 | Ingress Tool Transfer – Delivery of backdoor to internal hosts

T1665 | Hide Infrastructure – Use of SoftEther VPN for C2

T1574.001 | Hijack Execution Flow: DLL – Execution of backdoor through DLL side-loading

T1095 | Non-Application Layer Protocol – Unidentified application-layer protocol for C2 traffic

T1071.001| Web Protocols – HTTP-based C2 traffic

T1571| Non-Standard Port – Port 443 for unencrypted HTTP traffic

Darktrace Model Alerts during intrusion

Anomalous File::Internal::Script from Rare Internal Location

Anomalous File::EXE from Rare External Location

Anomalous File::Multiple EXE from Rare External Locations

Anomalous Connection::Possible Callback URL

Antigena::Network::External Threat::Antigena Suspicious File Block

Antigena::Network::Significant Anomaly::Antigena Significant Server Anomaly Block

Antigena::Network::Significant Anomaly::Antigena Controlled and Model Alert

Antigena::Network::Significant Anomaly::Antigena Alerts Over Time Block

Antigena::Network::External Threat::Antigena File then New Outbound Block  

References

[1] https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-239a

[2] https://www.trendmicro.com/en_gb/research/24/k/earth-estries.html

[3] https://www.trendmicro.com/content/dam/trendmicro/global/en/research/24/k/earth-estries/IOC_list-EarthEstries.txt

[4] https://www.trendmicro.com/en_gb/research/24/k/breaking-down-earth-estries-persistent-ttps-in-prolonged-cyber-o.html

[5] https://lab52.io/blog/deedrat-backdoor-enhanced-by-chinese-apts-with-advanced-capabilities/

[6] https://www.silentpush.com/blog/salt-typhoon-2025/

The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.

Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein. Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.

Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.

The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content.

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Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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October 15, 2025

How a Major Civil Engineering Company Reduced MTTR across Network, Email and the Cloud with Darktrace

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Asking more of the information security team

“What more can we be doing to secure the company?” is a great question for any cyber professional to hear from their Board of Directors. After successfully defeating a series of attacks and seeing the potential for AI tools to supercharge incoming threats, a UK-based civil engineering company’s security team had the answer: Darktrace.

“When things are coming at you at machine speed, you need machine speed to fight it off – it’s as simple as that,” said their Information Security Manager. “There were incidents where it took us a few hours to get to the bottom of what was going on. Darktrace changed that.”

Prevention was also the best cure. A peer organization in the same sector was still in business continuity measures 18 months after an attack, and the security team did not want to risk that level of business disruption.

Legacy tools were not meeting the team’s desired speed or accuracy

The company’s native SaaS email platform took between two and 14 days to alert on suspicious emails, with another email security tool flagging malicious emails after up to 24 days. After receiving an alert, responses often took a couple of days to coordinate. The team was losing precious time.

Beyond long detection and response times, the old email security platform was no longer performing: 19% of incoming spam was missed. Of even more concern: 6% of phishing emails reached users’ inboxes, and malware and ransomware email was also still getting through, with 0.3% of such email-borne payloads reaching user inboxes.

Choosing Darktrace

“When evaluating tools in 2023, only Darktrace had what I was looking for: an existing, mature, AI-based cybersecurity solution. ChatGPT had just come out and a lot of companies were saying ‘AI this’ and ‘AI that’. Then you’d take a look, and it was all rules- and cases-based, not AI at all,” their Information Security Manager.

The team knew that, with AI-enabled attacks on the horizon, a cybersecurity company that had already built, fielded, and matured an AI-powered cyber defense would give the security team the ability to fend off machine-speed attacks at the same pace as the attackers.

Darktrace accomplishes this with multi-layered AI that learns each organization’s normal business operations. With this detailed level of understanding, Darktrace’s Self-Learning AI can recognize unusual activity that may indicate a cyber-attack, and works to neutralize the threat with precise response actions. And it does this all at machine speed and with minimal disruption.

On the morning the team was due to present its findings, the session was cancelled – for a good reason. The Board didn’t feel further discussion was necessary because the case for Darktrace was so conclusive. The CEO described the Darktrace option as ‘an insurance policy we can’t do without’.

Saving time with Darktrace / EMAIL

Darktrace / EMAIL reduced the discovery, alert, and response process from days or weeks to seconds .

Darktrace / EMAIL automates what was originally a time-consuming and repetitive process. The team has recovered between eight and 10 working hours a week by automating much of this process using / EMAIL.

Today, Darktrace / EMAIL prevents phishing emails from reaching employees’ inboxes. The volume of hostile and unsolicited email fell to a third of its original level after Darktrace / EMAIL was set up.

Further savings with Darktrace / NETWORK and Darktrace / IDENTITY

Since its success with Darktrace / EMAIL, the company adopted two more products from the Darktrace ActiveAI Security Platform – Darktrace / NETWORK and Darktrace / IDENTITY.

These have further contributed to cost savings. An initial plan to build a 24/7 SOC would have required hiring and retaining six additional analysts, rather than the two that currently use Darktrace, costing an additional £220,000 per year in salary. With Darktrace, the existing analysts have the tools needed to become more effective and impactful.

An additional benefit: Darktrace adoption has lowered the company’s cyber insurance premiums. The security team can reallocate this budget to proactive projects.

Detection of novel threats provides reassurance

Darktrace’s unique approach to cybersecurity added a key benefit. The team’s previous tool took a rules-based approach – which was only good if the next attack featured the same characteristics as the ones on which the tool was trained.

“Darktrace looks for anomalous behavior, and we needed something that detected and responded based on use cases, not rules that might be out of date or too prescriptive,” their Information Security Manager. “Our existing provider could take a couple of days to update rules and signatures, and in this game, speed is of the essence. Darktrace just does everything we need - without delay.”

Where rules-based tools must wait for a threat to emerge before beginning to detect and respond to it, Darktrace identifies and protects against unknown and novel threats, speeding identification, response, and recovery, minimizing business disruption as a result.

Looking to the future

With Darktrace in place, the UK-based civil engineering company team has reallocated time and resources usually spent on detection and alerting to now tackle more sophisticated, strategic challenges. Darktrace has also equipped the team with far better and more regularly updated visibility into potential vulnerabilities.

“One thing that frustrates me a little is penetration testing; our ISO accreditation mandates a penetration test at least once a year, but the results could be out of date the next day,” their Information Security Manager. “Darktrace / Proactive Exposure Management will give me that view in real time – we can run it daily if needed - and that’s going to be a really effective workbench for my team.”

As the company looks to further develop its security posture, Darktrace remains poised to evolve alongside its partner.

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