What is endpoint detection and response (EDR)?

Why is EDR important?

Endpoint detection and response matters for a simple reason: endpoints create critical cybersecurity vulnerabilities.

Laptops, smartphones, and IoT systems are prime targets for cyber-attackers. Sophisticated advanced threats work around conventional firewalls and malware scanning solutions. Almost 70% of attacks start with compromised endpoints, posing a critical risk to data and system integrity.

Security teams need tools that monitor activity and traffic passing through every endpoint. EDR fills this gap by providing visibility and enabling organizations to monitor weak spots and detect potential cyberattacks.

EDR goes beyond older endpoint protection solutions such as antivirus and anti-malware scanners. These older tools can detect threats by scanning files as they enter the network. However, they are not well-suited to detecting suspicious activities such as data extraction.

Endpoint detection and response also handles advanced threat types that evade traditional security tools. EDR security uses real-time scanning, behavioral analysis, machine learning, and threat intelligence to identify previously unknown threats. This enables rapid triage and mitigation actions.

How does EDR work?

Endpoint detection and response solutions analyze data flows to extract actionable threat intelligence. They handle vast amounts of data in real time, sifting through it for evidence of obvious and hidden threats.

Detection

In the detection phase of EDR, agents installed on endpoints continuously collect and monitor a wide range of telemetry. It includes:

• Failed access requests
• Modifications to files
• Data transfers
• Network connection changes
• Suspicious activities (such as rapid location or IP address changes)
• Registry alterations
• Sudden system events (such as traffic spikes or device shutdowns)

Endpoint agents feed this telemetry from managed devices to centralized consoles and analytics software.

Analysis

The bulk of EDR analysis occurs automatically. Automated artificial intelligence (AI) and machine learning (ML) check user behavior against baselines or other threat indicators. This allows EDR solutions to flag unusual patterns of behavior and identify the data or applications involved.

EDR also correlates threats across multiple endpoints. Attackers may launch DDoS or data breach campaigns via many user accounts. EDR can link registry changes or file transfers, exposing attacks at the earliest possible stage.

AI/ML can also correlate telemetry with historical threat data and global threat intelligence. These techniques help identify advanced threat types before they compromise network assets.

Threat hunting and incident response

EDR tools forward high-risk alerts to security teams for forensic analysis. Centralized consoles then allow analysts to assess alerts and launch incident response procedures.

Analysts can consult a wide range of telemetry to verify the severity of alerts and dive deep into endpoint processes. Activity logs, authentication requests, SIEM logs, application data, and device or geolocation data provide valuable context.

Analysts can construct incident timelines and visualize execution chains. This allows security teams to quarantine network assets and prevent threat escalation. It also helps to detect multi-stage attacks that work around simple defensive measures.

If necessary, security analysts can use endpoint data and threat intelligence services to hunt threats. Threat hunters can dive deep into network registries to uncover persistent threats and counteract known attack techniques.

The role of EDR does not stop after successful threat mitigation. EDR systems store threat data in accessible formats. This facilitates regular audits to enhance future detection processes and aids compliance strategies.

Compliance assistance

EDR solutions safeguard internet-facing devices or applications by monitoring for threats and bring order to chaotic security landscapes by enabling centralized control.

They also help organizations meet compliance standards (for instance, the NIST CSF or ISO 27001) and demonstrate a strong commitment to data security. EDR systems generate audit trails for each incident, documenting mitigation processes. This is a valuable tool for healthcare, financial, or education providers where data privacy is paramount.

Key EDR capabilities

EDR is a sophisticated cybersecurity solution with several core features. The following EDR capabilities are commonly found in high-quality services:

Automated behavioral analytics

Behavioral analysis monitors user activity and endpoint data, comparing actions to normal baselines and intelligence signatures. EDR tools monitor behavior to detect suspicious sequences of events and deliver reliable alerts.

Real-time threat visibility

Endpoint detection and response tools never sleep. Agents deliver a continuous stream of endpoint data, allowing rapid detection of suspicious activities. For example, EDR immediately captures unauthorized data transfers, process creation, or script executions. This minimizes the lag between detection and response.

Remove cybersecurity blind spots

EDR security tools scan for unsecured endpoints and deliver agents to integrate them into monitoring systems. This provides network-wide visibility across on-premises, remote, and cloud environments. EDR also detects new endpoints automatically, reducing the risks related to shadow IT and remote work practices.

Correlation and prioritization

Endpoint detection and response tools assess data to separate false positives from genuine threats. EDR tools grade alerts based on threat severity, allowing security teams to quickly validate incidents and prioritize mitigation actions.

Integration with threat intelligence services

Advanced EDR solutions draw on external threat intelligence platforms. Intelligence provides invaluable context when evaluating adversaries. Security teams can establish the identity and aims of attackers, estimate the scope of cyber-attacks, and put in place suitable remediation measures.

Proactive threat hunting

EDR allows security analysts to adopt a proactive approach to threat hunting. Analysts can leverage behavioral data to gain early warning of insider threats or network infiltration. Threat hunters can investigate threats with forensic detail to establish the root cause of incidents and block threat actors.

For example, AI analytics may identify a suspicious sequence of authentication requests and file changes. Security teams can correlate this information with indicators of compromise and known tactics, techniques, and procedures (TTPs).

Protection against advanced threat types

Advanced persistent threats (APTs) pose a critical threat to modern networks. They evade detection and embed themselves deep within targeted systems before extracting data.

Conventional scanning tools and firewalls struggle to detect APTs. However, an endpoint security solution detects many advanced threats via granular monitoring and intelligence integration.

More efficient incident response

Above all else, an endpoint security solution should make it easier to respond to threats and reduce the time between detection and mitigation.

Automation reduces lag to an absolute minimum. EDR can handle many simple threats instantly, without the need for human intervention. If action is needed, endpoint data enables smart responses that understand the scope of attacks and their potential effects.

What are the differences between EDR, XDR, and MDR?

Endpoint detection and response is one of several cybersecurity solutions, and may not be the best fit for every organization.

Companies can also employ extended detection and response (XDR) or managed detection and response (MDR) to secure network assets. Both alternatives extend core EDR capabilities, potentially making them more effective options.

EDR, XDR, and MDR solutions have several features in common. All employ AI and ML to automatically analyze behavior and traffic. All draw on threat intelligence to add context and reduce the incidence of false positives. The main differences lie in the scope of XDR and MDR.

XDR does more than gather endpoint data. XDR covers cloud deployments, emails, and internal network traffic. This makes it an ideal solution for hybrid networks mixing on-premises and cloud assets. XDR can also integrate existing EDR solutions (alongside SIEM tools, next-generation firewalls and threat protection software).

MDR involves outsourcing cybersecurity activities to external vendors. MDR services monitor network traffic continuously, often using XDR solutions that cover hybrid environments. Vendor security teams usually include analytics specialists who triage alerts and detect advanced threats that internal teams miss.

MDR is ideal for companies that require advanced cybersecurity protection but lack resources or skills. External vendors provide effective detection and response services via affordable subscription models.

Best practices to follow when implementing EDR

EDR tools alone do not guarantee robust cybersecurity. Following the best practices below will help organizations implement an endpoint security solution that covers every weakness and detects advanced threats.

• Understand normal activity baselines: EDR compares user behavior and traffic patterns to normal (and safe) baselines. Take care to assess and establish baselines for EDR solutions, including all network users and standard network activities. Be comprehensive at this stage. More detailed assessments of normal behavior ensure accurate correlations when threats emerge.
• Use threat intelligence to strengthen EDR outputs: Context-rich intelligence feeds complement endpoint data outputs, adding information about global threat actors and attack signatures. Couple local network data with indicators of compromise to assess risks and understand which alerts require urgent action.
• Apply risk analysis to triage alerts: EDR solutions can generate a lot of alerts (depending on their configuration). Use AI to implement risk scoring based on organizational needs. Automated tools prioritize risks related to data integrity and compliance goals, allowing security teams to act quickly and effectively.
• Save time by automating repetitive tasks: EDR solutions can automate many tasks that normally require manual input. For example, users can automate basic threat analysis and device isolation. Use automation strategically to save time and devote attention to the most urgent risks.
• Audit EDR systems to ensure consistent coverage: Endpoints constantly change, especially in complex corporate networks. Auditing EDR systems is essential to verify that they function as designed. Regularly scan for undetected endpoints and investigate concerning metrics like rising false positives or detection to response times.
• Integrate threat detection with incident response: EDR solutions should connect seamlessly with response processes. Workshop on common attacks from detection through analysis and response. Ensure your security team has a reliable playbook to turn EDR insights into threat mitigation.
• Train staff to use EDR solutions: Security teams must know how to calibrate EDR tools to ensure accurate correlation and risk assessment. Consider funding CySA+ certification for security team members. This will give them the skills needed to analyze data and take a proactive approach to threat hunting.

Protect the network edge with endpoint detection and response

EDR security tools scan user activity and network traffic where internal systems meet the wider internet. Advanced EDR solutions use AI and exploit threat intelligence feeds to detect advanced threats—an area where older cybersecurity solutions struggle.

XDR and MDR-based cybersecurity services provide alternatives, particularly for businesses with hybrid network architectures. However, EDR solutions may be the best option for securing networks against today's most dangerous cyber threats.