How does EDR work? Architecture, monitoring, detection and response explained

EDR (endpoint detection and response) works by deploying sensors on protected endpoints to continuously collect selected behavioral telemetry, forwarding that telemetry to a centralized analytics layer, commonly cloud-hosted, that applies detection rules, behavioral analytics, machine learning and threat intelligence, and surfacing prioritized incidents in a console where analysts can investigate and respond. A simplified EDR workflow includes telemetry collection, detection and correlation, investigation, and response. In practice, these activities operate continuously and often overlap.

Traditional antivirus historically relied heavily on signatures and file-based indicators. Modern endpoint protection also uses behavioral analysis, reputation, heuristics, cloud intelligence and machine learning. EDR adds continuous endpoint telemetry, investigation and response capabilities beyond the prevention layer: it provides deeper visibility and investigation when endpoint prevention alone does not provide sufficient context or response capability. OMB Memorandum M-22-01 directed U.S. federal civilian agencies to accelerate EDR adoption to improve continuous endpoint visibility, early incident detection, response and remediation. This guide walks through how each part of an EDR platform works, from the sensor on the endpoint to the response actions an analyst executes from the console.

Most modern EDR platforms include three broad functional layers: endpoint telemetry collection, centralized analytics and an investigation and response interface. The implementation may be cloud-based, on-premises or hybrid and varies substantially by vendor.

Endpoint telemetry collection is usually handled by a dedicated agent installed on protected devices, although some architectures use native operating-system sensors, add local preprocessing or combine endpoint sensors with agentless assessment components. The sensor collects selected behavioral telemetry and often performs filtering, detection or prevention locally before forwarding data upstream.

The centralized analytics layer, commonly cloud-hosted, receives telemetry from the sensors and applies behavioral models, machine learning, threat intelligence and rule-based detection logic. Some products support on-premises or hybrid processing, and vendor data lakes, SIEM integrations and APIs may extend where correlation, investigation and retention take place. Broader correlation and long-term retention normally happen centrally, while some detection and enforcement may occur on the endpoint itself.

The investigation and response interface is where analysts work. It presents prioritized incidents with context, supports investigation workflows, hosts response actions and generates reports. Third-party response orchestration through APIs may extend the actions available from it.

Each layer constrains the others. A sensor with limited telemetry coverage narrows what can be detected at all. A weak analytics layer generates noise. A weak console burns analyst time on workflows that should be automated.

EDR monitoring is continuous rather than scheduled. The EDR sensor continuously collects selected behavioral telemetry, such as process execution, command-line, network, file-system, registry and authentication activity. Vendors filter and normalize this data to balance detection coverage, performance and storage requirements.

That telemetry typically spans five broad categories: process activity (executables launched, their parent processes and command-line arguments), file events (creation, modification, deletion and access patterns), network activity (outbound connections, DNS queries and unusual communication patterns), registry and configuration changes (persistence mechanisms attackers use to survive reboots) and identity activity (logon events, privilege changes and lateral-movement indicators).

No EDR product records every endpoint operation. Endpoints can generate a high volume of raw operating-system activity, so EDR sensors apply local filtering and normalization before forwarding security-relevant telemetry. Microsoft states explicitly that Defender for Endpoint is not intended as an auditing or logging solution that records every operation on a device, and that its sensor throttles high rates of repeated identical events.

Retention varies materially by vendor, licence tier and telemetry type. Buyers should verify how long raw telemetry, alerts, incidents and forensic evidence remain searchable, whether extended retention costs extra and whether data can be exported to a SIEM or security data lake. Microsoft, for example, documents six months of behavioral telemetry for Defender for Endpoint, which is a useful reminder that no single market-wide retention norm should be assumed.

Longer searchable retention can support retrospective investigation when an incident is discovered after the initial compromise. The appropriate retention period depends on investigation, compliance, threat-hunting and cost requirements. According to the IBM Cost of a Data Breach Report 2025, organizations took an average of 241 days to identify and contain a breach, a nine-year low that IBM attributes partly to faster identification and containment supported by security teams, AI and automation. That figure describes the breach lifecycle rather than how long an attacker remained undetected on any individual endpoint, so it should not be read as a retention target.

The 2025 Verizon Data Breach Investigations Report found that stolen credentials were the initial access vector in 22% of breaches. EDR can help identify endpoint activity associated with credential theft or abuse, but attacks occurring primarily in identity, email or SaaS environments may require XDR, identity-protection or cloud-application telemetry.

Modern EDR does not identify threats through a single technique. Detection is better understood as a layered pipeline in which endpoint telemetry, rules and signatures, behavioral analytics, machine-learning models, threat-intelligence and reputation data, event correlation, contextual enrichment and retrospective analysis each contribute. These layers run continuously and often overlap.

EDR and the accompanying endpoint-protection layer can match observed activity against known-bad artifacts and against rules written around documented attacker techniques:

• Malware signatures.
• File hashes and code-signing certificates.
• Malicious IP addresses, URLs and domains.
• Known command-line patterns.
• Registry and persistence rules.
• Detection rules built around known attacker techniques.

Signatures and known indicators remain an efficient way to identify known malicious artifacts, and behavioral detection does not replace them. Acronis explicitly combines signature- and behavior-based engines rather than treating the two as mutually exclusive.

This is the core EDR layer. The platform evaluates relationships among events rather than assessing each event in isolation. For example, a document application unexpectedly launching PowerShell, followed by an external download or persistence activity, may create a high-risk behavioral sequence. The individual events may be legitimate in isolation; correlation and context determine the detection's confidence.

Legitimate automation, macros and administrative workflows can produce similar process chains, which is why MITRE's detection guidance emphasizes correlated behavioral evidence across processes, network activity, memory operations and file changes rather than single events.

Many techniques never produce a conventional malware file. Endpoint prevention, EDR telemetry and behavioral rules together provide visibility into activity such as:

• Suspicious PowerShell or shell execution.
• Command-line obfuscation.
• Process injection.
• Memory manipulation.
• Credential dumping.
• Exploit behavior.
• Living-off-the-land binaries.
• Security-control tampering.

These are not capabilities that antivirus universally lacks. Modern endpoint-prevention engines also use behavior monitoring, heuristics and machine learning; the difference EDR makes is the retained telemetry, correlation and response workflow around them.

EDR platforms may use machine-learning models to classify suspicious activity, score event sequences or identify anomalies. The exact approach varies: some models are centrally trained, while others incorporate environment-specific baselines. Machine learning is applied to several distinct functions:

• Classifying files or processes.
• Scoring suspicious event sequences.
• Identifying anomalous activity.
• Reducing false positives.
• Prioritizing alerts.
• Recognizing similarities to previously observed attacks.

Machine learning can help identify suspicious files or behaviors that do not match an exact known signature. Its effectiveness depends on model quality, telemetry coverage, configuration and the surrounding detection logic, and models can still produce false positives or be evaded. Not every product continuously learns an individualized baseline for every device: Microsoft, for example, documents a combination of local and cloud machine learning, behavioral analysis, heuristics and security intelligence.

Threat intelligence adds context to observed files, domains, IP addresses, certificates, tools and techniques. This layer is intelligence enrichment and indicator correlation rather than an equivalent to behavioral or machine-learning detection. It may help establish that:

• A domain is associated with an active campaign.
• A file hash is known malware.
• A legitimate tool is commonly abused by a threat actor.
• An observed behavior resembles a newly disclosed technique.

Modern EDR should not raise a separate alert for every suspicious event. It can correlate related processes, files, registry changes, scheduled tasks, domains and user identities into a consolidated incident or attack graph. Acronis aggregates related detection results into guided attack interpretations and incident graphs containing process, file, network, registry and identity context.

The stages are worth separating:

• Detection identifies potentially malicious activity.
• Correlation links related activity into an incident.
• Enrichment adds threat intelligence, asset and ATT&CK context.
• Prioritization determines what requires attention first.
• Interpretation helps an analyst understand the attack's progression and scope.

When new intelligence or detection logic becomes available, retained telemetry may be searched for earlier evidence of the threat. Analysts, or automated retroactive-detection functions where supported, can search retained telemetry for the new indicator or related behavior. That search may be driven by analyst-led hunting, IoC searches, newly deployed detection rules or automated retroactive detection.

In every case the result depends on whether the relevant telemetry was collected, whether it was retained, whether the indicator type is searchable and whether the licence includes the function. Acronis includes threat-feed review and intelligent searches for emerging indicators on the same basis.

Detection confidence improves with context. Depending on the platform, that context may include:

• Whether the process is signed.
• Parent-child process relationships.
• User privileges.
• Asset criticality.
• Prevalence across the environment.
• Whether the behavior is new for the organization.
• Known vulnerabilities on the endpoint.
• Other detections occurring in the same attack chain.

Not every EDR platform uses every one of these sources, so they are examples rather than universal features.

MITRE ATT&CK mapping helps analysts understand which adversary tactic and technique the observed behavior resembles and provides a common framework for investigation and reporting. It does not, by itself, determine the attacker's intent or predict the next step. Alerts are mapped to ATT&CK tactics and techniques; the framework is a knowledge base of observed adversary behavior, not a detection engine.

The same distinction applies to incident graphs, AI-generated summaries and remediation recommendations. They help analysts interpret and prioritize detections, but they mostly operate after initial detection and correlation: detection engines identify suspicious events, correlation groups them into an incident, ATT&CK mapping classifies the observed behavior, AI-guided interpretation explains the attack chain and recommends response, and technicians then contain, remediate, recover and patch.

For Acronis, the detection layer includes automated behavioral- and signature-based engines, anti-ransomware detection, URL filtering, an emerging-threat intelligence feed, automated event correlation and attack-chain interpretation mapped to MITRE ATT&CK. AI-generated summaries and Acronis Copilot are documented as investigation and guided-remediation capabilities rather than primary detection technologies.

Threat hunting is a proactive, hypothesis-driven search for adversary behavior, anomalies or indicators that automated detection may not have escalated. EDR telemetry can support hunts based on known IoCs, ATT&CK techniques, process patterns or environment-specific hypotheses.

A typical hunt starts with a hypothesis: an analyst reads about a technique published by CISA or a security vendor, then queries retained telemetry to determine whether related behavior appears in the environment. Effective hunting depends on retention that covers the period of interest, telemetry coverage for the behavior in question and a flexible query interface.

The "R" in EDR is what separates it from passive monitoring, but the actions available vary substantially by platform, licence and integration.

Common EDR actions are supported by most platforms:

• Isolate an endpoint from the network.
• Stop a malicious process.
• Quarantine or block a file.
• Collect investigation packages.
• Run scripts or supported response commands.

Platform- or integration-dependent actions should be verified against the specific product and licence:

• Network or domain blocking.
• Identity suspension and password reset.
• Remote shell.
• Attack-specific rollback.
• Backup-based recovery.
• Automated patching.

Credential resets in particular are normally identity, XDR or SOAR actions rather than endpoint-only EDR functions.

Automated response is also not always enabled, because automatic isolation or process termination can disrupt legitimate operations. High-confidence detections can trigger automated response where policy permits. Other incidents may generate recommended actions that require analyst or customer approval. Most platforms support different response modes based on confidence, severity, asset criticality, policy and customer authorization.

Recovery terminology matters as well, and rollback is not a synonym for all recovery. Attack-specific rollback reverses malicious changes to files, registry entries, scheduled tasks or other affected items. Backup-based recovery restores files or an entire workload from a recovery point. Disaster recovery fails over critical workloads where that service is enabled.

Acronis extends standard containment with attack-specific rollback and integrated recovery. Depending on the incident and enabled services, affected items can be restored from local rollback data or backup, while broader workload recovery or disaster recovery can be used when containment and targeted remediation are insufficient.

According to the IBM Cost of a Data Breach Report 2025, the global average cost of a data breach was $4.44 million, and organizations using AI and automation extensively across security operations reduced their breach lifecycle by an average of 80 days and saved nearly $1.9 million.

The scenario below is illustrative rather than a description of what every product will do. What actually happens depends on platform capabilities, configuration, licensing and analyst involvement.

1. An attacker sends a phishing email with a malicious attachment. A user opens it, and the document application launches PowerShell to download a payload.
2. The endpoint sensor records the process execution, parent-child relationship and outbound network connection, forwarding selected telemetry to the analytics layer.
3. Behavioral analytics may flag the document-to-PowerShell sequence, and threat intelligence can correlate the destination domain with a known campaign indicator where such an indicator exists. The platform can consolidate the related events into one prioritized incident mapped to ATT&CK tactics and techniques.
4. If configured, automated response can isolate the endpoint, stop the process and quarantine the payload. Where automation is not enabled or confidence is lower, the platform may instead recommend those actions for analyst or customer approval.
5. The incident surfaces in the console with the collected context. An analyst validates the detection, confirms the scope and searches retained telemetry for related activity on other endpoints. This step often requires additional investigation rather than a single query.
6. Where supported, the analyst rolls back malicious changes or recovers affected data, closes the vulnerability that enabled the intrusion and documents the incident.

Automated detection and initial containment can occur quickly, limiting attacker movement. Complete investigation, eradication and recovery depend on incident complexity, telemetry coverage and operational readiness.

Acronis EDR is integrated into Acronis Cyber Platform (formerly Acronis Cyber Protect Cloud), a multitenant platform purpose-built for MSPs. It correlates endpoint activity into prioritized incidents and uses AI-generated summaries, attack-chain visualization and MITRE ATT&CK mapping to accelerate investigation. Technicians can contain threats by isolating endpoints, stopping malicious processes and quarantining files, then move through attack-specific rollback, workload recovery and patching from the same operational platform. This connects detection and response directly to business continuity rather than ending the workflow at containment.

Purpose-built for MSP operations. The platform is designed around service-provider workflows rather than single-tenant enterprise deployment:

• Multitenant management across client environments.
• Prioritized incident views rather than undifferentiated alert lists.
• AI-guided investigation that supports lower-tier technicians.
• Automated and single-click response.
• Integrated recovery and endpoint management.
• Optional 24/7 Acronis MDR.

Internal IT teams remain a secondary audience, but the commercial design of the platform is MSP-led.

Acronis Cyber Platform (formerly Acronis Cyber Protect Cloud) consolidates endpoint security, endpoint management and data-protection capabilities through a common multitenant platform and console, using a shared Acronis agent for applicable endpoint services. This reduces the operational overhead and compatibility risk associated with deploying and maintaining multiple endpoint agents.

AI-guided summaries, attack-chain interpretation and recommended actions reduce the expertise and time required for initial investigation, enabling lower-tier technicians to resolve more routine incidents and escalate complex cases with stronger context. Complex incidents still require security expertise.

MSPs already using Microsoft Defender Antivirus can add Acronis EDR for centralized multitenant visibility, AI-guided analysis and integrated response, rollback, recovery and patching without replacing Defender as the underlying prevention engine.

EDR provides the technology for detection, investigation and response; people and processes still have to operate it. MSPs can run Acronis EDR themselves or add Acronis MDR when they need 24/7 monitoring, investigation and response delivered by a dedicated SOC. Acronis positions MDR as a 24/7/365 service delivered by the Acronis Threat Research Unit or through other trusted partners.

• EDR continuously collects selected endpoint telemetry to support detection, investigation and response; it does not record every operation.
• Most EDR platforms combine endpoint sensors, centralized analytics and an investigation and response interface, but deployment architectures vary.
• Detection may combine behavioral analytics, machine learning, threat intelligence and rule-based logic.
• MITRE ATT&CK mapping classifies observed adversary behaviors; it does not predict the attacker's next action.
• Common response actions include isolation, process termination and quarantine, while rollback, identity response and recovery are vendor- or integration-specific.
• EDR retention, offline behavior and resource usage vary by vendor and should be validated rather than assumed.
• Acronis differentiates through MSP-first multitenancy, AI-guided incident analysis and an integrated workflow spanning containment, remediation, rollback, recovery and patching.
• MSPs can operate Acronis EDR themselves or add Acronis MDR for continuous SOC coverage.

How does EDR work in simple terms?

EDR works by installing a sensor on protected endpoints that continuously collects selected behavioral telemetry, forwarding it to a centralized analytics layer, commonly cloud-hosted, that looks for suspicious activity and correlates related events into prioritized incidents. Analysts investigate those incidents and respond from a console.

What is an EDR agent?

An EDR agent, or sensor, is a software component installed on protected endpoints that collects selected behavioral telemetry including process execution, command-line, network, file-system, registry and authentication activity. It filters and normalizes that data locally, and may perform some detection or prevention on the device, before forwarding telemetry for centralized analysis. Some platforms use native operating-system sensors alongside or instead of a dedicated agent.

How long does EDR data last?

Retention varies materially by vendor, licence tier and telemetry type. Verify how long raw telemetry, alerts, incidents and forensic evidence remain searchable, whether extended retention costs extra and whether data can be exported to a SIEM or security data lake. Microsoft documents six months of behavioral telemetry for Defender for Endpoint, so a single market-wide norm should not be assumed.

How does EDR detect malware?

EDR detection is a layered pipeline: rules and known indicators, behavioral and sequence-based analytics, machine-learning models, threat-intelligence and reputation enrichment, automated correlation of related events into incidents and retrospective search of retained telemetry. Contextual factors such as process signing, user privileges and asset criticality influence how detections are scored and prioritized.

What is EDR threat hunting?

EDR threat hunting is a proactive, hypothesis-driven search for adversary behavior, anomalies or indicators that automated detection may not have escalated. Hunts can be based on known IoCs, ATT&CK techniques, process patterns or environment-specific hypotheses, and they depend on the relevant telemetry having been collected and retained.

Does EDR work offline?

Offline behavior varies by vendor and operating system. Endpoint sensors may continue local prevention, telemetry collection or queued event storage while disconnected, but cloud-based investigation, policy updates and remote response actions generally require connectivity. Verify the specific vendor's offline capabilities and storage limits.

What operating systems does EDR support?

Supported operating systems and feature depth vary by vendor. Windows normally receives the broadest telemetry and response coverage; macOS and Linux may have different sensor architectures, supported distributions and remediation capabilities. Mobile, container and legacy-system support should be evaluated separately.

How much CPU and memory does an EDR agent use?

Agent performance depends on device specifications, enabled features and workload activity. Evaluate vendor benchmarks and test CPU, memory, disk and network impact under both normal and high-activity conditions.

What is the difference between EDR and EPP?

EPP (endpoint protection platform) focuses primarily on preventing malicious activity through capabilities such as anti-malware, exploit prevention and application control. EDR adds continuous telemetry, investigation and response. Most modern endpoint-security platforms combine prevention and EDR in one product or agent, although licensing and operational workflows may remain separate.

How does EDR work with SIEM and SOAR?

EDR can send alerts, incidents and, where supported, endpoint telemetry into a SIEM for cross-source correlation and retention. SOAR platforms can orchestrate response across EDR, identity, email, network and IT systems. The exact integration depth depends on vendor APIs, data schemas and licensing.

EDR turns endpoint activity into actionable security context, but visibility alone does not create resilience. Acronis EDR helps MSPs move from detection and investigation to containment, remediation and recovery through the same multitenant platform used for endpoint management and data protection. With Acronis MDR available for 24/7 operations, partners can choose whether to operate the technology internally or extend their team with expert SOC coverage.

To see how this works in practice, request a demo of Acronis Cyber Platform (formerly Acronis Cyber Protect Cloud) and walk through sensor deployment, the console workflow and response actions with an Acronis specialist.