Endpoint detection and response (EDR) is an integrated endpoint security solution that combines real-time endpoint monitoring and collection of endpoint data with rules-based automated response and analysis capabilities. Adoption of EDR is projected to increase significantly over the next few years. According to Stratistics MRC's Endpoint Detection and Response - Global Market Outlook (2017-2026), sales of EDR solutions—both on-premises and cloud-based—are expected to reach $7.27 million by 2026, with an annual growth rate of nearly 26%.

One of the factors driving the rise in EDR adoption is the rise in the number of endpoints attached to networks. Another major driver is the increased sophistication of cyberattacks, which often focus on endpoints as easier targets for infiltrating a network.

New types of endpoints and endpoint attacks

An average IT department manages thousands of endpoints across its network. These endpoints include not only desktops and servers, but laptops, tablets, smartphones, internet of things (IoT) devices, and even smart watches and digital assistants. The SANS Endpoint Protection and Response Survey reports that 44% of IT teams manage between 5,000 and 500,000 endpoints. Each of these endpoints can become an open door for a cyberattack.

While today's antivirus solutions can identify and block many new types of malware, hackers are constantly creating more. Many types of malware are difficult to detect using standard methods. For example, fileless malware—a recent development—operates in the computer's memory, thus avoiding malware signature scanners.

To bolster security, an IT department may implement a variety of endpoint security solutions, as well as other security applications, over time. However, multiple standalone security tools can complicate the threat detection and prevention process, especially if they overlap and produce similar security alerts. A better approach is an integrated endpoint security solution.

Key components of endpoint detection and response

EDR provides an integrated hub for the collection, correlation, and analysis of endpoint data, as well as for coordinating alerts and responses to immediate threats. Endpoint detection and response applications have three basic components:

Endpoint data collection agents. Software agents conduct endpoint monitoring and collect data—such as processes, connections, volume of activity, and data transfers—into a central database.

Automated response. Pre-configured rules in an EDR solution can recognize when incoming data indicates a known type of security breach and triggers an automatic response, such as to log off the end user or send an alert to a staff member.

Analysis and forensics. An endpoint detection and response system may incorporate both real-time analytics, for rapid diagnosis of threats that do not quite fit the pre-configured rules, and forensics tools for threat hunting or conducting a post-mortem analysis of an attack.

  • A real-time analytics engine uses algorithms to evaluate and correlate large volumes of data, searching for patterns.
  • Forensics tools enable IT security professionals to investigate past breaches to better understand how an exploit works and how it penetrated security. IT security professionals also use forensics tools to hunt for threats in the system, such as malware or other exploits that might lurk undetected on an endpoint.

New EDR capabilities improve threat intelligence

New features and services are expanding EDR solutions' ability to detect and investigate threats.

For example, third-party threat intelligence services, such as McAfee Global Threat Intelligence, increase the effectiveness of endpoint security solutions. Threat intelligence services provide an organization with a global pool of information on current threats and their characteristics. That collective intelligence helps increase an EDR's ability to identify exploits, especially multi-layered and zero-day attacks. Many EDR vendors offer threat intelligence subscriptions as part of their endpoint security solution.

Additionally, new investigative capabilities in some EDR solutions can leverage AI and machine learning to automate the steps in an investigative process. These new capabilities can learn an organization's baseline behaviors and use this information, along with a variety of other threat intelligence sources, to interpret findings.

Another type of threat intelligence is the Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) project underway at MITRE, a nonprofit research group that works with the U.S. government. ATT&CK is a knowledgebase and framework built on the study of millions of real-world cyberattacks.

ATT&CK categorizes cyberthreats by various factors, such as the tactics used to infiltrate an IT system, the type of system vulnerabilities exploited, the malware tools used, and the criminal groups associated with the attack. The focus of the work is on identifying patterns and characteristics that remain unchanged regardless of minor changes to an exploit. Details such as IP addresses, registry keys, and domain numbers can change frequently. But an attacker's methods—or "modus operandi"—usually remain the same. An EDR can use these common behaviors to identify threats that may have been altered in other ways.

As IT security professionals face increasingly complex cyberthreats, as well as a greater diversity in the number and types of endpoints accessing the network, they need more help from the automated analysis and response that endpoint detection and response solutions provide.

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