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Integration in Focus: Bringing Machine Learning to Third-Party EDR Alerts

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12
Dec 2022
12
Dec 2022
This blog walks through the key benefits of integrating EDR technologies with Darktrace.

This blog demonstrates how we use EDR integration in Darktrace for detection & investigation. We’ll look at four key features, which are summarized with an example below:  

1)    Contextualizing existing Darktrace information – E.g. ‘There was a Microsoft Defender for Endpoint (MDE) alert 5 minutes after Darktrace saw the device beacon to an unusual destination on the internet. Let me pivot back into the Defender UI’
2)    Cross-data detection engineering
‘Darktrace, create an alert or trigger a response if you see a specific MDE alert and a native Darktrace detection on the same entity over a period of time’
3)    Applying unsupervised machine learning to third-party EDR alerts
‘Darktrace, create an alert or trigger a response if there is a specific MDE alert that is unusual for the entity, given the context’
4)    Use third-party EDR alerts to trigger AI Analyst
‘AI Analyst, this low-fidelity MDE alert flagged something on the endpoint. Please take a deep look at that device at the time of the Defender alert, conduct an investigation on Darktrace data and share your conclusions about whether there is more to it or not’ 

MDE is used as an example above, but Darktrace’s EDR integration capabilities extend beyond MDE to other EDRs as well, for example to Sentinel One and CrowdStrike EDR.

Darktrace brings its Self-Learning AI to your data, no matter where it resides. The data can be anywhere – in email environments, cloud, SaaS, OT, endpoints, or the network, for example. Usually, we want to get as close to the raw data as possible to get the maximum context for our machine learning. 

We will explain how we leverage high-value integrations from our technology partners to bring further context to Darktrace, but also how we apply our Self-Learning AI to third-party data. While there are a broad range of integrations and capabilities available, we will primarily look at Microsoft Defender for Endpoint, CrowdStrike, and SentinelOne and focus on detection in this blog post. 

The Nuts and Bolts – Setting up the Integration

Darktrace is an open platform – almost everything it does is API-driven. Our system and machine learning are flexible enough to ingest new types of data & combine it with already existing information.  

The EDR integrations mentioned here are part of our 1-click integrations. All it requires is the right level of API access from the EDR solutions and the ability for Darktrace to communicate with the EDR’s API. This type of integration can be setup within minutes – it currently doesn’t require additional Darktrace licenses.

Figure 1: Set-up of Darktrace Graph Security API integration

As soon as the setup is complete, it enables various additional capabilities. 
Let’s look at some of the key detection & investigation-focussed capabilities step-by-step.

Contextualizing Existing Darktrace Information

The most basic, but still highly-useful integration is enriching existing Darktrace information with EDR alerts. Darktrace shows a chronological history of associated telemetry and machine learning for each entity observed in the entities event log. 

With an EDR integration enabled, we now start to see EDR alerts for the respective entities turn up in the entity’s event log at the correct point in time – with a ton of context and a 1-click pivot back to the native EDR console: 

Figure 2: A pivot from the Darktrace Threat Visualizer to Microsoft Defender

This context is extremely useful to have in a single screen during investigations. Context is king – it reduces time-to-meaning and skill required to understand alerts.

Cross-Data Detection Engineering

When an EDR integration is activated, Darktrace enables an additional set of detections that leverage the new EDR alerts. This comes out of the box and doesn’t require any further detection engineering. It is worth mentioning though that the new EDR information is being made available in the background for bespoke detection engineering, if advanced users want to leverage these as custom metrics.

The trick here is that the added context provided by the additional EDR alerts allows for more refined detections – primarily to detect malicious activity with higher confidence. A network detection showing us beaconing over an unusual protocol or port combination to a rare destination on the internet is great – but seeing within Darktrace that CrowdStrike detected a potentially hostile file or process three minutes prior to the beaconing detection on the same device will greatly help to prioritize the detections and aid a subsequent investigation.

Here is an example of what this looks like in Darktrace:

Figure 3: A combined model breach in the Threat Visualizer

Applying Unsupervised Machine Learning to Third-Party EDR Alerts


Once we start seeing EDR alerts in Darktrace, we can start treating it like any other data – by applying unsupervised machine learning to it. This means we can then understand how unusual a given EDR detection is for each device in question. This is extremely powerful – it allows to reduce noisy alerts without requiring ongoing EDR alert tuning and opens a whole world of new detection capabilities.

As an example – let’s imagine a low-level malware alert keeps appearing from the EDR on a specific device. This might be a false-positive in the EDR, or just not of interest for the security team, but they may not have the resources or knowledge to further tune their EDR and get rid of this noisy alert.

While Darktrace keeps adding this as contextual information in the device’s event log, it could, depending on the context of the device, the EDR alert, and the overall environment, stop alerting on this particular EDR malware alert on this specific device if it stops being unusual. Over time, noise is reduced across the environment – but if that particular EDR alert appears on another device, or on the same device in a different context, it might get flagged again, as it now is unusual in the given context.

Darktrace then goes a step further, taking those unusual EDR alerts and combining them with unusual activity seen in other Darktrace coverage areas, like the network for example. Combining an unusual EDR alert with an unusual lateral movement attempt, for example, allows it to find these combined, high-precision, cross-data set anomalous events that are highly indicative of an active cyber-attack – without having to pre-define the exact nature of what ‘unusual’ looks like.

Figure 4: Combined EDR & network detection using unsupervised machine learning in Darktrace

Use Third-Party EDR Alerts to Trigger AI Analyst

Everything we discussed so far is great for improving precision in initial detections, adding context, and cutting through alert-noise. We don’t stop there though – we can also now use the third-party EDR alerts to trigger our investigation engine, the AI Analyst.

Cyber AI Analyst replicates and automates typical level 1 and level 2 Security Operations Centre (SOC) workflows. It is usually triggered by every native Darktrace detection. This is not a SOAR where playbooks are statically defined – AI Analyst builds hypotheses, gathers data, evaluates the data & reports on its findings based on the context of each individual scenario & investigation. 

Darktrace can use EDR alerts as starting points for its investigation, with every EDR alert ingested now triggering AI Analyst. This is similar to giving a (low-level) EDR alert to a human analyst and telling them: ‘Go and take a look at information in Darktrace and try to conclude whether there is more to this EDR alert or not.’

The AI Analyst subsequently looks at the entity which had triggered the EDR alert and investigates all available Darktrace data on that entity, over a period of time, in light of that EDR alert. It does not pivot outside Darktrace itself for that investigation (e.g. back into the Microsoft console) but looks at all of the context natively available in Darktrace. If concludes that there is more to this EDR alert – e.g. a bigger incident – it will report on that and clearly flag it. The report can of course be directly downloaded as a PDF to be shared with other stakeholders.

This comes in handy for a variety of reasons – primarily to further automate security operations and alleviate pressure from human teams. AI Analyst’s investigative capabilities sit on top of everything we discussed so far (combining EDR detections with detections from other coverage areas, applying unsupervised machine learning to EDR detections, …).

However, it can also come in handy to follow up on low-severity EDR alerts for which you might not have the human resources to do so.

The below screenshot shows an example of a concluded AI Analyst investigation that was triggered by an EDR alert:

Figure 5: An AI Analyst incident trained on third-party data

The Impact of EDR Integrations

The purpose behind all of this is to augment human teams, save them time and drive further security automation.

By ingesting third-party endpoint alerts, combining it with our existing intelligence and applying unsupervised machine learning to it, we achieve that further security automation. 

Analysts don’t have to switch between consoles for investigations. They can leverage our high-fidelity detections that look for unusual endpoint alerts, in combination with our already powerful detections across cloud and email systems, zero trust architecture, IT and OT networks, and more. 

In our experience, this pinpoints the needle in the haystack – it cuts through noise and reduces the mean-time-to-detect and mean-time-to-investigate drastically.

All of this is done out of the box in Darktrace once the endpoint integrations are enabled. It does not need a data scientist to make the machine learning work. Nor does it need a detection engineer or threat hunter to create bespoke, meaningful detections. We want to reduce the barrier to entry for using detection and investigation solutions – in terms of skill and experience required. The system is still flexible, transparent, and open, meaning that advanced users can create their own combined detections, leveraging unsupervised machine learning across different data sets with a few clicks.

There are of course more endpoint integration capabilities available than what we covered here, and we will explore these in future blog posts.

EINBLICKE IN DAS SOC-Team
Darktrace Cyber-Analysten sind erstklassige Experten für Threat Intelligence, Threat Hunting und Incident Response. Sie bieten Tausenden von Darktrace Kunden auf der ganzen Welt rund um die Uhr SOC-Support. Einblicke in das SOC-Team wird ausschließlich von diesen Experten verfasst und bietet Analysen von Cyber-Vorfällen und Bedrohungstrends, die auf praktischen Erfahrungen in diesem Bereich basieren.
AUTOR
ÜBER DEN AUTOR
Max Heinemeyer
Leiter der Produktabteilung

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

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Looking Beyond Secure Email Gateways with the Latest Innovations to Darktrace/Email

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09
Apr 2024

Organizations Should Demand More from their Email Security

In response to a more intricate threat landscape, organizations should view email security as a critical component of their defense-in-depth strategy, rather than defending the inbox alone with a traditional Secure Email Gateway (SEG). Organizations need more than a traditional gateway – that doubles, instead of replaces, the capabilities provided by native security vendor – and require an equally granular degree of analysis across all messaging, including inbound, outbound, and lateral mail, plus Teams messages.  

Darktrace/Email is the industry’s most advanced cloud email security, powered by Self-Learning AI. It combines AI techniques to exceed the accuracy and efficiency of leading security solutions, and is the only security built to elevate, not duplicate, native email security.  

With its largest update ever, Darktrace/Email introduces the following innovations, finally allowing security teams to look beyond secure email gateways with autonomous AI:

  • AI-augmented data loss prevention to stop the entire spectrum of outbound mail threats
  • an easy way to deploy DMARC quickly with AI
  • major enhancements to streamline SOC workflows and increase the detection of sophisticated phishing links
  • expansion of Darktrace’s leading AI prevention to lateral mail, account compromise and Microsoft Teams

What’s New with Darktrace/Email  

Data Loss Prevention  

Block the entire spectrum of outbound mail threats with advanced data loss prevention that builds on tags in native email to stop unknown, accidental, and malicious data loss

Darktrace understands normal at individual user, group and organization level with a proven AI that detects abnormal user behavior and dynamic content changes. Using this understanding, Darktrace/Email actions outbound emails to stop unknown, accidental and malicious data loss.  

Traditional DLP solutions only take into account classified data, which relies on the manual input of labelling each data piece, or creating rules to catch pattern matches that try to stop data of certain types leaving the organization. But in today’s world of constantly changing data, regular expression and fingerprinting detection are no longer enough.

  • Human error – Because it understands normal for every user, Darktrace/Email can recognize cases of misdirected emails. Even if the data is correctly labelled or insensitive, Darktrace recognizes when the context in which it is being sent could be a case of data loss and warns the user.  
  • Unclassified data – Whereas traditional DLP solutions can only take action on classified data, Darktrace analyzes the range of data that is either pending labels or can’t be labeled with typical capabilities due to its understanding of the content and context of every email.  
  • Insider threat – If a malicious actor has compromised an account, data exfiltration may still be attempted on encrypted, intellectual property, or other forms of unlabelled data to avoid detection. Darktrace analyses user behaviour to catch cases of unusual data exfiltration from individual accounts.

And classification efforts already in place aren’t wasted – Darktrace/Email extends Microsoft Purview policies and sensitivity labels to avoid duplicate workflows for the security team, combining the best of both approaches to ensure organizations maintain control and visibility over their data.

End User and Security Workflows

Achieve more than 60% improvement in the quality of end-user phishing reports and detection of sophisticated malicious weblinks1

Darktrace/Email improves end-user reporting from the ground up to save security team resource. Employees will always be on the front line of email security – while other solutions assume that end-user reporting is automatically of poor quality, Darktrace prioritizes improving users’ security awareness to increase the quality of end-user reporting from day one.  

Users are empowered to assess and report suspicious activity with contextual banners and Cyber AI Analyst generated narratives for potentially suspicious emails, resulting in 60% fewer benign emails reported.  

Out of the higher-quality emails that end up being reported, the next step is to reduce the amount of emails that reach the SOC. Darktrace/Email’s Mailbox Security Assistant automates their triage with secondary analysis combining additional behavioral signals – using x20 more metrics than previously – with advanced link analysis to detect 70% more sophisticated malicious phishing links.2 This directly alleviates the burden of manual triage for security analysts.

For the emails that are received by the SOC, Darktrace/Email uses automation to reduce time spent investigating per incident. With live inbox view, security teams gain access to a centralized platform that combines intuitive search capabilities, Cyber AI Analyst reports, and mobile application access. Analysts can take remediation actions from within Darktrace/Email, eliminating console hopping and accelerating incident response.

Darktrace takes a user-focused and business-centric approach to email security, in contrast to the attack-centric rules and signatures approach of secure email gateways

Microsoft Teams

Detect threats within your Teams environment such as account compromise, phishing, malware and data loss

Around 83% of Fortune 500 companies rely on Microsoft Office products and services, particularly Teams and SharePoint.3

Darktrace now leverages the same behavioral AI techniques for Microsoft customers across 365 and Teams, allowing organizations to detect threats and signals of account compromise within their Teams environment including social engineering, malware and data loss.  

The primary use case for Microsoft Teams protection is as a potential entry vector. While messaging has traditionally been internal only, as organizations open up it is becoming an entry vector which needs to be treated with the same level of caution as email. That’s why we’re bringing our proven AI approach to Microsoft Teams, that understands the user behind the message.  

Anomalous messaging behavior is also a highly relevant indicator of whether a user has been compromised. Unlike other solutions that analyze Microsoft Teams content which focus on payloads, Darktrace goes beyond basic link and sandbox analysis and looks at actual user behavior from both a content and context perspective. This linguistic understanding isn’t bound by the requirement to match a signature to a malicious payload, rather it looks at the context in which the message has been delivered. From this analysis, Darktrace can spot the early symptoms of account compromise such as early-stage social engineering before a payload is delivered.

Lateral Mail Analysis

Detect and respond to internal mailflow with multi-layered AI to prevent account takeover, lateral phishing and data leaks

The industry’s most robust account takeover protection now prevents lateral mail account compromise. Darktrace has always looked at internal mail to inform inbound and outbound decisions, but will now elevate suspicious lateral mail behaviour using the same AI techniques for inbound, outbound and Teams analysis.

Darktrace integrates signals from across the entire mailflow and communication patterns to determine symptoms of account compromise, now including lateral mailflow

Unlike other solutions which only analyze payloads, Darktrace analyzes a whole range of signals to catch lateral movement before a payload is delivered. Contributing yet another layer to the AI behavioral profile for each user, security teams can now use signals from lateral mail to spot the early symptoms of account takeover and take autonomous actions to prevent further compromise.

DMARC

Gain in-depth visibility and control of 3rd parties using your domain with an industry-first AI-assisted DMARC

Darktrace has created the easiest path to brand protection and compliance with the new Darktrace/DMARC. This new capability continuously stops spoofing and phishing from the enterprise domain, while automatically enhancing email security and reducing the attack surface.

Darktrace/DMARC helps to upskill businesses by providing step by step guidance and automated record suggestions provide a clear, efficient road to enforcement. It allows organizations to quickly achieve compliance with requirements from Google, Yahoo, and others, to ensure that their emails are reaching mailboxes.  

Meanwhile, Darktrace/DMARC helps to reduce the overall attack surface by providing visibility over shadow-IT and third-party vendors sending on behalf of an organization’s brand, while informing recipients when emails from their domains are sent from un-authenticated DMARC source.

Darktrace/DMARC integrates with the wider Darktrace product platform, sharing insights to help further secure your business across Email Attack Path and Attack Surface management.

Schlussfolgerung

To learn more about the new innovations to Darktrace/Email download the solution brief here.

All of the new updates to Darktrace/Email sit within the new Darktrace ActiveAI Security Platform, creating a feedback loop between email security and the rest of the digital estate for better protection. Click to read more about the Darktrace ActiveAI Security Platform or to hear about the latest innovations to Darktrace/OT, the most comprehensive prevention, detection, and response solution purpose built for critical infrastructures.  

Learn about the intersection of cyber and AI by downloading the State of AI Cyber Security 2024 report to discover global findings that may surprise you, insights from security leaders, and recommendations for addressing today’s top challenges that you may face, too.

References

[1] Internal Darktrace Research

[2] Internal Darktrace Research

[3] Essential Microsoft Office Statistics in 2024

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Carlos Gray
Product Manager

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Managing Risk Beyond CVE Scores With the Latest Innovations to Darktrace/OT

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09
Apr 2024

Identifying Cyber Risk in Industrial Organizations

Compromised OT devices in ICS and SCADA environments pose significant physical risks, even endangering lives. However, identifying CVEs in the multitude of complex OT devices is labor-intensive and time-consuming, draining valuable resources.

Even after identifying a vulnerability, implementing a patch presents its own challenges limited maintenance windows and the need for uninterrupted operations strain IT and OT teams often leading organizations to prioritize availability over security leading vulnerabilities remaining unresolved for over 5 years on average. (1)

Darktrace’s New Innovation

Darktrace is an industry leader in cybersecurity with 10+ years of experience securing OT environments where we take a fundamentally different approach using Self-Learning AI to enhance threat detection and response.

Continuing to combat the expanding threat landscape, Darktrace is excited to announce new capabilities that enable a contextualized and proactive approach to managing cyber risk at industrial organizations.

Today we launch an innovation to our OT Cybersecurity solution, Darktrace/OT, that will add a layer of proactivity, enabling a comprehensive approach to risk management. This industry leading innovation for Darktrace/OT moves beyond CVE scores to redefine vulnerability management for critical infrastructure, tackling the full breadth of risks not limited by traditional controls.  

Darktrace/OT is the only OT security solution with comprehensive Risk Management which includes:

  • Contextualized risk analysis unique to your organization
  • The most realistic evaluation and prioritization of OT risk
  • Effectively mitigate risk across your OT infrastructure, with and without patching.
  • The only OT security solution that evaluates your defenses against Advanced Persistent Threat (APT) Groups.

The most comprehensive prevention, detection, and response solution purpose built for Critical Infrastructures

Darktrace’s Self-Learning AI technology is a cutting-edge innovation that implements real time prevention, detection, response, and recovery for operational technologies and enables a fundamental shift from the traditional approach to cyber defense by learning a ‘pattern of life’ for every network, device, and user.  

Rather than relying on knowledge of past attacks, AI technology learns what is ‘normal’ for its environment, discovering previously unknown threats by detecting subtle shifts in behavior. Through identifying these unexpected anomalies, security teams can investigate novel attacks, discover blind spots, have live time visibility across all their physical and digital assets, and reduce time to detect, respond to, and triage security events.  

  • Achieve greater visibility of OT and IT devices across all levels of the Purdue Model.
  • The industry's only OT security to scale threat detection and response, with a 92% time saving from triage to recovery.  
  • The only OT focused security solution to provide bespoke Risk Management.

To learn more about how Darktrace/OT approaches unique use cases for industrial organizations visit the Darktrace/OT Webpage or join us LIVE at a city near you.

Read more below to discover how new innovations to Darktrace/OT are bringing a new, contextualized approach to Risk Management for Industrial organizations.

For more information on the entire Darktrace/OT Solution read our solution brief here.

Darktrace/OT and New Risk Management

Risk Identification

Leveraging the visibility of Darktrace/OT which identifies individual systems throughout the Purdue Model and the relationship between them, Darktrace/OT identifies high-risk CVEs and presents potential attack routes that go beyond techniques requiring a known exploit, such as misuse of legitimate services. Each attack path will have a mathematical evaluation of difficulty and impact from initial access to the high value objectives.  

Together this gives comprehensive coverage over your real and potential risks from both an attacker and known vulnerability perspectives. OT attack paths as seen here even leverage insights between the industrial and corporate communications to reveal ways threat actors may take advantage of IT-OT convergence. This revelation of imperceptible risks fills gaps in traditional risk analysis like remote access and insider threats.

Figure 1: Darktrace/OT visualizing the most critical attack paths at an organization
Figure 1: Darktrace/OT visualizing the most critical attack paths at an organization
Figure 2: A specific Attack Path identified by Darktrace/OT

Risk Prioritization

Darktrace/OT prioritizes remediations and mitigations based on difficulty and damage to your unique organization, using the established Attack Paths.

We ascertain the priorities that apply to your organization beyond pure theoretical damage answering questions like:

  • How difficult is a particular vulnerability to exploit considering the steps an attacker would require to reach it?
  • And, how significant would the impact be if it was exploited within this particular network?

This expanded approach to risk prioritization has a much more comprehensive evaluation of your organization's unique risk than has ever been possible before. Traditional approaches of ranking only known vulnerabilities with isolated scores using CVSS and exploitability metrics, often leaves gaps in IT-OT risks and is blind to legitimate service exploitation.

Figure 3: Darktrace/OT leverages its contextual understand of the organization’s network to prioritize remediation that will have the positive impact on the risk score

Darktrace provides mitigation strategies associated with each identified risk and the relevant impact it has on your overall risk posture, across all MITRE ATT&CK techniques.

What sets Darktrace apart is our ability to contextualize these mitigations within the broader business. When patching vulnerabilities directly isn’t possible, Darktrace identifies alternative actions that harden attack paths leading to critical assets. Hardening the surrounding attack path increases the difficulty and therefore reduces the likelihood and impact of a breach.

That means unpatched vulnerabilities and vulnerable devices aren’t left unprotected. This also has an added bonus, those hardening techniques work for all devices in that network segment, so apply one change, secure many.

Figure 4: Darktrace prioritizes mitigation reducing accessibility of vulnerability and the overall risk score when patches aren’t available

Communicate Board Level Risk with APT Threat Mapping

Darktrace/OT bridges theory and practice as the only security solution that maps MITRE techniques, frequently used by APT Groups, onto AI-assessed critical Attack Paths. This unique solution provides unparalleled insights including sector and location intelligence, possible operating platforms, common techniques, exploited CVEs, and the number of potential devices affected in your environment, supporting holistic risk assessment and proactive defense measures.

Ultimately, this becomes a power dashboard to communicate board level risk, using both metric based evidence and industry standard threat mapping.

Schlussfolgerung

Darktrace/OT is part of the Darktrace ActiveAI Security Platform a native, holistic, AI-driven platform built on over ten years of AI research. It helps security teams shift to more a productive mode, finding the known and the unknown attacks and transforming the SOC with the various Darktrace products to drive efficiency gains. It does this across the whole incident lifecycle to lower risk, reduce time spent on active incidents, and drive return on investment.

Discover more about Darktrace's ever-strengthening platform with the upcoming changes coming to our Darktrace/Email product and other launch day blogs.

Join Darktrace LIVE half-day event to understand the reality versus the hype surrounding AI and how to achieve cyber resilience.

Learn about the intersection of cyber and AI by downloading the State of AI Cyber Security 2024 report to discover global findings that may surprise you, insights from security leaders, and recommendations for addressing today’s top challenges that you may face, too.  

References

1. https://research-information.bris.ac.uk/ws/portalfiles/portal/313646831/Catch_Me_if_You_Can.pdf

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About the author
Mitchell Bezzina
VP, Product and Solutions Marketing
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