Cybersecurity solutions are improving and evolving and breakneck speed. What was true last week, may well be different the next, and that rapid pace of change can leave IT leaders – from IT Directors to CIOs and even CISOs – feeling disconnected from their security technology.

Endpoint Detection and Response is one of those increasingly popular and business-critical solutions with impressive but sometimes ambiguous technologies powering it. Sharing features of SIEM, ATP and even Endpoint Lifecycle and Compliance management solutions, it pinning down exactly how EDR works can be convoluted.

Here, we explain the core technologies behind great EDR solutions and the techniques that IT leaders are deploying.

• What are EDR Technologies?
• How Does EDR Help to Improve Overall Security Posture?
• What are the Latest EDR Technologies and Techniques?
• Which EDR Technologies are Most Important for Businesses?
• Machine Learning in EDR
• Behavioural Analytics in EDR
• Real-World Examples of EDR Technology Strengthing Organisational Security Posture
• What’s Next for EDR and its Applications?

What are EDR Technologies?

EDR technologies are used to detect and respond to security incidents on endpoint devices, such as computers, laptops, and mobile devices. EDR solutions monitor the activity on endpoint devices and use various techniques, such as machine learning and behavioural analytics, to identify and alert security teams of potential security threats.

They can also be configured to take automated response actions, such as quarantining or blocking malicious files, to prevent or mitigate security incidents. EDR technologies are an important part of a comprehensive security strategy, as they can help organisations detect and respond to advanced threats that may not be detected by other security controls.

 

 

How Does EDR Help to Improve Overall Security Posture?

As part of a cohesive, zero-trust security strategy, EDR is critical in maintaining operational resiliency, business continuity, and data integrity. Endpoints are a major security breach risk for businesses of all scope and scale (we explain why here). Hence, EDR software is very helpful in improving overall security posture. Here are four examples:

1. Early Detection: EDR continuously monitors and analyses network activity in real-time, alerting security teams to any suspicious or malicious activity. This allows organisations to quickly detect and respond to potential threats before they can cause significant damage.
2. Contextual Information: EDR provides detailed information about detected threats, including their origin, impact, and potential remediation steps. This helps security teams – external or internal – to better understand the threat and take appropriate action.
3. Automated Response: EDR can be configured to automatically take certain actions in response to detected threats, such as blocking access to malicious websites or quarantining infected devices. This helps to reduce the time it takes to respond to threats and minimise the impact of an attack.
4. Continuous Improvement: EDR provides organisations with ongoing visibility into their security posture, allowing analysts and leaders to identify and address any weaknesses or vulnerabilities.

 

 

What are the Latest EDR Technologies and Techniques?

Good cybersecurity is always evolving and EDR is no exception. In fact, there have been a number of recent developments in Endpoint Detection and Response (EDR) technologies and techniques, including:

• Machine Learning: Many EDR solutions now use machine learning (ML) algorithms to analyse endpoint data and identify patterns that may indicate the presence of a cyber threat. These algorithms can be trained to improve their accuracy over time, making them more effective at detecting threats.
• Behavioural analytics: Some EDR solutions use behavioural analytics to detect anomalies in the behaviour of processes or users that may indicate the presence of a cyber threat.
• Cloud-based EDR: Cloud-based EDR solutions allow organisations to monitor and protect their endpoints from anywhere, using cloud servers and storage. This can be more cost-effective and scalable than traditional on-premises solutions.
• Integration with other security solutions: Many EDR solutions now offer integration with other security solutions, such as firewalls, intrusion prevention systems (IPS), and security information and event management (SIEM) systems. This allows organisations to use EDR as part of a comprehensive security strategy, like that delivered by a SOC.
• Automated response: Some EDR solutions now offer automated response capabilities, allowing them to take immediate action to contain, mitigate and minimise threats.

 

Which EDR Technologies are Most Important for Businesses?

EDR has several irreplaceable features but machine learning and behavioural analytics are two of the most powerful. ML and BA are the bedrock of EDR’s real-time response capabilities, such as endpoint isolation and recommended action pathways. Here are four ML and BA functionalities and an explanation of their use in EDR technology.

 

Machine Learning in EDR

Machine learning algorithms are used by some Endpoint Detection and Response (EDR) solutions to analyse endpoint data and identify patterns that may indicate the presence of a cyberthreat.

Because ML can process large volumes of data and identify patterns that may be missed by traditional security solutions, its application is ideal for endpoint security which commonly deals with zero day and never-before-seen threats. Here’s how it works:

1. Training: The ML algorithm is “trained” using a large dataset of labelled examples (e.g., examples of normal endpoint activity and malicious activity). The algorithm uses this training data to learn how to identify patterns that are indicative of malicious activity.
2. Testing: Algorithms are then tested using a separate dataset of labelled examples to see how accurately it can identify patterns indicative of malicious activity. If the algorithm performs well during testing, it is considered “trained” and ready for use.
3. Deployment: The trained ML algorithm is deployed on endpoint devices, where it continuously analyses endpoint data and looks for anomalies or patterns suggestive of incoming or active threats. If the algorithm identifies a pattern consistent with malicious activity, it will alert the security team or deploy a range of automated responses.
4. Continuous learning: ML continues to learn and improve over time as it processes more data and is exposed to new threats. This allows it to become more accurate and effective at detecting threats.

 

Behavioural Analytics in EDR

Behavioural analytics is a technique some EDR solutions use to detect anomalies in the behaviour of processes or users that may signal a lurking threat. BA helps EDR separate normal behaviour from deviations and concentrate efforts on the most likely signs of risk. It works like this:

1. Baseline behaviour: The EDR solution establishes a baseline of normal behaviour for each endpoint device, user, and process. This baseline is used to identify deviations from normal behaviour that may indicate a cyber threat.
2. Continuous monitoring: EDR software clients continuously monitor the behaviour of endpoint devices, users, and processes and compare it to the established baseline. If it detects a deviation from normal behaviour, it will flag it as a potential anomaly.
3. Anomaly analysis: EDR software analyses the flagged anomalies to determine whether they indicate a cyberthreat. This may involve comparing the anomalies to known patterns of malicious activity or consulting with security experts to determine their significance. The latter is a key feature of a SOC.
4. Response: If the EDR solution determines that suspicious activity is likely an active threat, it will take appropriate action to contain and mitigate the threat, such as quarantining infected devices or blocking malicious traffic.

 

 

Four Real-World Examples of How EDR Technology Strengthens Organisational Security Posture

A healthcare organisation was able to quickly detect and remediate a ransomware attack thanks to EDR. The software client alerted security teams to malicious activity and provided detailed information about the attack, allowing the organisation to quickly isolate affected systems and prevent further damage.

A financial institution prevented a data breach by detecting and blocking an attempted phishing attack. EDR alerted flagged the presence of suspicious activity , which was then traced back to an attempted spoofed domain with a virus-injected attachment.  The attack was subsequently cut off in its tracks.

A government agency was able to mitigate a network intrusion thanks to their EDR solution. The solution pinpointed anomalous network traffic alongside an unusual amount of failed VPN login attempts. The threat was tracked back to an endpoint connected to unsecured WiFi. Security teams immediately isolated the device and blocked the router to prevent further damage.

A retail company was able to prevent a data breach by detecting the misuse of data on a company endpoint. EDR alerted security analysts of attempts to upload data , downloaded from the corporate server, to a personal public cloud location. The organisation prevented the insider from succeeding and protected customer information.

 

What’s Next for EDR and its Applications?

New technologies and techniques may shape how organisations protect themselves against cyber threats. The future of EDR will likely involve continued evolution and innovation in the technologies and approaches used to detect and respond to security threats on endpoint devices. Some specific trends you may see emerging in the not-so-far future are:

• Increased automation of attack neutralisation functions
• Greater use of machine learning and artificial intelligence
• Expanded coverage, perhaps even integrated with third parties
• More focus on cloud capabilities

 

Sentis Managed Solutions Provides EDR Solutions

Are you considering adding EDR to your security stack or want to confirm your current threat detection and response is working to best effect?

Sentis Managed Solutions would love to hear from you. We’re a Managed Security Services Provider (MSSP) delivering a complete range of specialist threat detection and response solutions, EDR included. We also offer a free, no-obligation security audit – so you can confirm what’s working well and what needs reinforcement before committing.

Learn more about our audits here or browse our threat detection solutions here.