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November 29, 2022

How to Cut Through Cyber Security Noise

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29
Nov 2022
Learn how Cyber AI Analyst tackles alert fatigue by categorizing vast amounts of data into actionable security incidents for your team's review.

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.
Author
Dan Fein
VP, Product

Based in New York, Dan joined Darktrace’s technical team in 2015, helping customers quickly achieve a complete and granular understanding of Darktrace’s product suite. Dan has a particular focus on Darktrace/Email, ensuring that it is effectively deployed in complex digital environments, and works closely with the development, marketing, sales, and technical teams. Dan holds a Bachelor’s degree in Computer Science from New York University.

Elliot Stocker
Product SME

After 2 years in a commercial role helping to deploy Darktrace across a broad range of digital environments, Elliot currently occupies the role of Product Subject Matter Expert, where he helps to articulate the value of Darktrace’s technology to customers around the world. Elliot holds a Masters degree in Data Science and Machine Learning, using this knowledge to communicate concepts around machine learning and AI in an accessible way to different audiences.

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February 18, 2025

Unifying IT & OT With AI-Led Investigations for Industrial Security

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As industrial environments modernize, IT and OT networks are converging to improve efficiency, but this connectivity also creates new attack paths. Previously isolated OT systems are now linked to IT and cloud assets, making them more accessible to attackers.

While organizations have traditionally relied on air gaps, firewalls, data diodes, and access controls to separate IT and OT, these measures alone aren’t enough. Threat actors often infiltrate IT/Enterprise networks first then exploit segmentation, compromising credentials, or shared IT/OT systems to move laterally, escalate privileges, and ultimately enter the OT network.

To defend against these threats, organizations must first ensure they have complete visibility across IT and OT environments.

Visibility: The first piece of the puzzle

Visibility is the foundation of effective industrial cybersecurity, but it’s only the first step. Without visibility across both IT and OT, security teams risk missing key alerts that indicate a threat targeting OT at their earliest stages.

For Attacks targeting OT, early stage exploits often originate in IT environments, adversaries perform internal reconnaissance among other tactics and procedures but then laterally move into OT first affecting IT devices, servers and workstations within the OT network. If visibility is limited, these threats go undetected. To stay ahead of attackers, organizations need full-spectrum visibility that connects IT and OT security, ensuring no early warning signs are missed.

However, visibility alone isn’t enough. More visibility also means more alerts, this doesn’t just make it harder to separate real threats from routine activity, but bogs down analysts who have to investigate all these alerts to determine their criticality.

Investigations: The real bottleneck

While visibility is essential, it also introduces a new challenge: Alert fatigue. Without the right tools, analysts are often occupied investigating alerts with little to no context, forcing them to manually piece together information and determine if an attack is unfolding. This slows response times and increases the risk of missing critical threats.

Figure 1: Example ICS attack scenario

With siloed visibility across IT and OT each of these events shown above would be individually alerted by a detection engine with little to no context nor correlation. Thus, an analyst would have to try to piece together these events manually. Traditional security tools struggle to keep pace with the sophistication of these threats, resulting in an alarming statistic: less than 10% of alerts are thoroughly vetted, leaving organizations vulnerable to undetected breaches. As a result, incidents inevitably follow.

Darktrace’s Cyber AI Analyst uses AI-led investigations to improve workflows for analysts by automatically correlating alerts wherever they occur across both IT and OT. The multi-layered AI engine identifies high-priority incidents, and provides analysts with clear, actionable insights, reducing noise and highlighting meaningful threats. The AI significantly alleviates workloads, enabling teams to respond faster and more effectively before an attack escalates.

Overcoming organizational challenges across IT and OT

Beyond technical challenges like visibility and alert management, organizational dynamics further complicate IT-OT security efforts. Fundamental differences in priorities, workflows, and risk perspectives create challenges that can lead to misalignment between teams:

Non-transferable practices: IT professionals might assume that cybersecurity practices from IT environments can be directly applied to OT environments. This can lead to issues, as OT systems and workflows may not handle IT security processes as expected. It's crucial to recognize and respect the unique requirements and constraints of OT environments.

Segmented responsibilities: IT and OT teams often operate under separate organizational structures, each with distinct priorities, goals, and workflows. While IT focuses on data security, network integrity, and enterprise applications, OT prioritizes uptime, reliability, and physical processes.

Different risk perspectives: While IT teams focus on preventing cyber threats and regulatory violations, OT teams prioritize uptime and operational reliability making them drawn towards asset inventory tools that provide no threat detection capability.

Result: A combination of disparate and ineffective tools and misaligned teams can make any progress toward risk reduction at an organization seem impossible. The right tools should be able to both free up time for collaboration and prompt better communication between IT and OT teams where it is needed. However, different size operations structure their IT and OT teams differently which impacts the priorities for each team.

In real-world scenarios, small IT teams struggle to manage security across both IT and OT, while larger organizations with OT security teams face alert fatigue and numerous false positives slowing down investigations and hindering effective communication with the IT security teams.

By unifying visibility and investigations, Darktrace / OT helps organizations of all sizes detect threats earlier, streamline workflows, and enhance security across both IT and OT environments. The following examples illustrate how AI-driven investigations can transform security operations, improving detection, investigation, and response.

Before and after AI-led investigation

Before: Small manufacturing company

At a small manufacturing company, a 1-3 person IT team juggles everything from email security to network troubleshooting. An analyst might see unusual traffic through the firewall:

  • Unusual repeated outbound traffic from an IP within their OT network destined to an unidentifiable external IP.

With no dedicated OT security tools and limited visibility into the industrial network, they don’t know what the internal device in question is, if it is beaconing to a malicious external IP, and what it may be doing to other devices within the OT network. Without a centralized dashboard, they must manually check logs, ask operators about changes, and hunt for anomalies across different systems.

After a day of investigation, they concluded the traffic was not to be expected activity. They stop production within their smaller OT network, update their firewall rules and factory reset all OT devices and systems within the blast radius of the IP device in question.

After: Faster, automated response with Cyber AI Analyst

With Darktrace / OT and Cyber AI Analyst, the IT team moves from reactive, manual investigations to proactive, automated threat detection:

  • Cyber AI Analyst connects alerts across their IT and OT infrastructure temporally mapping them to attack frameworks and provides contextual analysis of how alerts are linked, revealing in real time attackers attempting lateral movement from IT to OT.
  • A human-readable incident report explains the full scope of the incident, eliminating hours of manual investigation.
  • The team is faster to triage as they are led directly to prioritized high criticality alerts, now capable of responding immediately instead of wasting valuable time hunting for answers.

By reducing noise, providing context, and automating investigations, Cyber AI Analyst transforms OT security, enabling small IT teams to detect, understand, and respond to threats—without deep OT cybersecurity expertise.

Before: Large critical infrastructure organization

In large critical infrastructure operations, OT and IT teams work in separate silos. The OT security team needs to quickly assess and prioritize alerts, but their system floods them with notifications:

  • Multiple new device connected to the ICS network alerts
  • Multiple failed logins to HMI detected
  • Multiple Unusual Modbus/TCP commands detected
  • Repeated outbound OT traffic to IT destinations

At first glance, these alerts seem important, but without context, it’s unclear whether they indicate a routine error, a misconfiguration, or an active cyber-attack. They might ask:

  • Are the failed logins just a mistake, or a brute-force attempt?
  • Is the outbound traffic part of a scheduled update, or data exfiltration?

Without correlation across events, the engineer must manually investigate each one—checking logs, cross-referencing network activity, and contacting operators—wasting valuable time. Meanwhile, if it’s a coordinated attack, the adversary may already be disrupting operations.

After: A new workflow with Cyber AI Analyst

With Cyber AI Analyst, the OT security team gets clear, automated correlation of security events, making investigations faster and more efficient:

  • Automated correlation of OT threats: Instead of isolated alerts, Cyber AI Analyst stitches together related events, providing a single, high-confidence incident report that highlights key details.
  • Faster time to meaning: The system connects anomalous behaviors (e.g., failed logins, unusual traffic from an HMI, and unauthorized PLC modifications) into a cohesive narrative, eliminating hours of manual log analysis.
  • Prioritized and actionable alerts: OT security receives clear, ranked incidents, immediately highlighting what matters most.
  • Rapid threat understanding: Security teams know within minutes whether an event is a misconfiguration or a cyber-attack, allowing for faster containment.

With Cyber AI Analyst, large organizations cut through alert noise, accelerate investigations, and detect threats faster—without disrupting OT operations.

An AI-led approach to industrial cybersecurity

Security vendors with a primary focus on IT may lack insight into OT threats. Even OT-focused vendors have limited visibility into IT device exploitation within OT networks, leading to failed ability to detect early indicators of compromise. A comprehensive solution must account for the unique characteristics of various OT environments.

In a world where industrial security is no longer just about protecting OT but securing the entire digital-physical ecosystem as it interacts with the OT network, Darktrace / OT is an AI-driven solution that unifies visibility across IT, IoT and OT, Cloud into one cohesive defense strategy.

Whether an attack originates from an external breach, an insider threat, a supply chain compromise, in the Cloud, OT, or IT domains Cyber AI Analyst ensures that security teams see the full picture - before disruption occurs.

Learn more about Darktrace / OT 

  • Unify IT and OT security under a single platform, ensuring seamless communication and protection for all interconnected devices.
  • Maintain uptime with AI-driven threat containment, stopping attacks without disrupting production.
  • Mitigate risks with or without patches, leveraging MITRE mitigations to reduce attack opportunities.

Download the solution brief to see how Darktrace secures critical infrastructure.

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About the author
Daniel Simonds
Director of Operational Technology

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Email

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February 13, 2025

Why Darktrace / EMAIL excels against APTs

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What are APTs?

An Advanced Persistent Threat (APT) describes an adversary with sophisticated levels of expertise and significant resources, with the ability to carry out targeted cyber campaigns. These campaigns may penetrate an organization and remain undetected for long periods, allowing attackers to gather intelligence or cause damage over time.

Over the last few decades, the term APT has evolved from being almost exclusively associated with nation-state actors to a broader definition that includes highly skilled, well-resourced threat groups. While still distinct from mass, opportunistic cybercrime or "spray and pray" attacks, APT now refers to the elite tier of adversaries, whether state-sponsored or not, who demonstrate advanced capabilities, persistence, and a clear strategic focus. This shift reflects the growing sophistication of cyber threats, where non-state actors can now rival nation-states in executing covert, methodical intrusions to achieve long-term objectives.

These attacks are resource-intensive for threat actors to execute, but the potential rewards—ranging from financial gain to sensitive data theft—can be significant. In 2020, Business Email Compromise (BEC) attacks netted cybercriminals over $1.8 billion.1

And recently, the advent of AI has helped to automate launching these attacks, lowering the barriers to entry and making it more efficient to orchestrate the kind of attack that might previously have taken weeks to create. Research shows that AI can do 90% of a threat actor’s work2 – reducing time-to-target by automating tasks rapidly and avoiding errors in phishing communications. Email remains the most popular vector for initiating these sophisticated attacks, making it a critical battleground for cyber defense.

What makes APTs so successful?

The success of Advanced Persistent Threats (APTs) lies in their precision, persistence, and ability to exploit human and technical vulnerabilities. These attacks are carefully tailored to specific targets, using techniques like social engineering and spear phishing to gain initial access.

Once inside, attackers move laterally through networks, often remaining undetected for months or even years, silently gathering intelligence or preparing for a decisive strike. Alternatively, they might linger inside an account within the M365 environment, which could be even more valuable in terms of gathering information – in 2023 the average time to identify a breach in 2023 was 204 days.3

The subtle and long-term outlook nature of APTs makes them highly effective, as traditional security measures often fail to identify the subtle signs of compromise.

How Darktrace’s approach is designed to catch the most advanced threats

Luckily for our customers, Darktrace’s AI approach is uniquely equipped to detect and neutralize APTs. Unlike the majority of email security solutions that rely on static rules and signatures, or that train their AI on previous known-bad attack patterns, Darktrace leverages Self-Learning AI that baselines normal patterns of behavior within an organization, to immediately detect unusual activity that may signal an APT in progress.  

But in the modern era of email threats, no email security solution can guarantee 100% effectiveness. Because attackers operate with great sophistication, carefully adapting their tactics to evade detection – whether by altering attachments, leveraging compromised accounts, or moving laterally across an organization – a siloed security approach risks missing these subtle, multi-domain threats. That’s why a robust defense-in-depth strategy is essential to mitigate APTs.

Real-world threat finds: Darktrace / EMAIL in action

Let’s take a look at some real-world scenarios where Darktrace / EMAIL stopped tactics associated with APT campaigns in their tracks – from adversary-in-the-middle attacks to suspicious lateral movement.

1: How Darktrace disrupted an adversary-in-the-middle attack by identifying abnormal login redirects and blocking credential exfiltration

In October 2024, Darktrace detected an adversary-in-the-middle (AiTM) attack targeting a Darktrace customer. The attack began with a phishing email from a seemingly legitimate Dropbox address, which contained multiple link payloads inviting the recipient to access a file. Other solutions would have struggled to catch this attack, as the initial AitM attack was launched through delivering a malicious URL through a trusted vendor or service. Once compromised, the threat actor could have laid low on the target account, gathering reconnaissance, without detection from the email security solution.  

Darktrace / EMAIL identified the abnormal login redirects and flagged the suspicious activity. Darktrace / IDENTITY then detected unusual login patterns and blocked credential exfiltration attempts, effectively disrupting the attack and preventing the adversary from gaining unauthorized access. Read more.

Figure 1: Overview of the malicious email in the Darktrace / EMAIL console, highlighting Dropbox associated content/link payloads

2: How Darktrace stopped lateral movement to block NTLM hash theft

In early 2024, Darktrace detected an attack by the TA577 threat group, which aimed to steal NTLM hashes to gain unauthorized access to systems. The attack began with phishing emails containing ZIP files that connected to malicious infrastructure.  

A traditional email security solution would have likely missed this attack by focusing too heavily on analyzing the zip file payloads or relying on reputation analysis to understand whether the infrastructure was registered as bad before this activity was a recognized IoC.

Because it correlates activity across domains, Darktrace identified unusual lateral movement within the network and promptly blocked the attempts to steal NTLM hashes, effectively preventing the attackers from accessing sensitive credentials and securing the network. Read more.

Figure 2: A summary of anomaly indicators seen for a campaign email sent by TA577, as detected by Darktrace / EMAIL

3: How Darktrace prevented the WarmCookie backdoor deployment embedded in phishing emails

In mid-2024, Darktrace identified a phishing campaign targeting organizations with emails impersonating recruitment firms. These emails contained malicious links that, when clicked, deployed the WarmCookie backdoor.  

These emails are difficult to detect, as they use social engineering tactics to manipulate users into engaging with emails and following the embedded malicious links – but if a security solution is not analysing content and context, these could be allowed through.

In several observed cases across customer environments, Darktrace detected and blocked the suspicious behavior associated with WarmCookie that had already managed to evade customers’ native email security. By using behavioral analysis to correlate anomalous activity across the digital estate, Darktrace was able to identify the backdoor malware strain and notify customers. Read more.

Conclusion

These threat examples highlight a key principle of the Darktrace approach – that a backwards-facing approach grounded in threat intelligence will always be one step behind.

Most threat actors operate in campaigns, carefully crafting attacks and testing them across multiple targets. Once a campaign is identified, good defenders and traditional security solutions quickly update their defenses with new threat intelligence, rules, and signatures. However, APTs have the resources to rapidly adapt – spinning up new infrastructure, modifying payloads and altering their attack footprint to evade detection.

This is where Darktrace / EMAIL excels. Only by analyzing each user, message and interaction can an email security solution hope to catch the types of highly-sophisticated attacks that have the potential to cause major reputational and financial damage. Darktrace / EMAIL ensures that even the most subtle threats are detected and blocked with autonomous response, before causing impact – helping organizations remain one step ahead of increasingly adaptive threat actors.

Download the Darktrace / EMAIL Solution Brief

Discover the most advanced cloud-native AI email security solution to protect your domain and brand while preventing phishing, novel social engineering, business email compromise, account takeover, and data loss.

  • Gain up to 13 days of earlier threat detection and maximize ROI on your current email security
  • Experience 20-25% more threat blocking power with Darktrace / EMAIL
  • Stop the 58% of threats bypassing traditional email security

References

[1] FBI Internet Crime Report 2020

[2] https://www.optiv.com/insights/discover/blog/future-security-automation-how-ai-machine-learning-and-automation-are

[3] IBM Cost of a Data Breach Report 2023

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About the author
Carlos Gray
Product Manager
Your data. Our AI.
Elevate your network security with Darktrace AI