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An Introduction to Proactive Cybersecurity Tools for Business

As a business owner, you understand the importance of effective cybersecurity. You have a high-quality, next-gen firewall in place and use reputable antivirus software. Unfortunately, these efforts may not be enough to protect you against sophisticated cyberattacks. 

Cybersecurity experts use a variety of tools to help recognize and block evolving attacks on businesses. This guide describes the most common tools cybersecurity professionals use to proactively detect and respond to cybersecurity threats.

Why Modern Cybersecurity Requires a Proactive Approach

Firewalls and antivirus software are perimeter solutions designed to keep threats out of your network. While this is a worthy pursuit, it’s not always possible to achieve in the modern threat landscape. Perimeter solutions recognize and block known threats. That means vulnerabilities and attacks that haven’t already been discovered (also known as zero-day threats) can’t be detected by these tools. 

Perimeter tools also fail to address human error. Research from Stanford University revealed that employee mistakes cause approximately 88% of data breaches. When an authorized user chooses to click a link or download an attachment, they allow the threat to surpass external security perimeter tools. To address these threats, businesses need tools that identify and eliminate threats within the network. 

4 Types of Cybersecurity Tools that Detect and Respond to Threats


Security information and event management, better known by the acronym SIEM, is a system that collects data from the activities that occur on the devices across your network. The data collected from a SIEM system is used in two ways. It is categorized and stored to be easily accessible for investigation. During the collection process, the data is analyzed and categorized in real time. When the system recognizes a threat, it alerts assigned personnel to prompt immediate action.  

Most modern SIEM systems provide visibility into the activities that occur across a company’s network using dashboards. The system also detects and alerts to threats in real time. Some SIEM systems are connected to incident response tools to provide automated responses like quarantining compromised devices.  

Endpoint Detection and Response (EDR)

Endpoint protection is becoming more widely recognized as a necessity as businesses depend more on various remote devices that remotely connect to an organizational network. Endpoints like remote devices and IoT devices often have weaker security measures in place. This makes them an attractive target for hackers. Endpoint detection and response (EDR) is a system that continuously monitors activity across endpoints. Like SIEM, it detects and alerts to threats. Many modern EDR systems also provide automated responses to these attacks. 

EDR is typically used as an added layer of protection for businesses that have an established SIEM system or other protection in place for network devices. When endpoints are added that aren’t protected by the network solution, they need to be protected by EDR. Modern SIEM systems (defined as Next-Gen SIEM) often provide protection for endpoints and network assets, eliminating the need for additional endpoint protection. 


Security orchestration, automation, and response (SOAR) is a system that automatically responds to threats. Multiple security tools within a network environment can generate different alerts about the same event. SOAR integrates tools like SIEM, firewalls, and EDR to streamline response actions. The system can be optimized to guide personnel through responses and to provide automated responses to specific threats. SOAR can work as an extension of a SIEM system that doesn’t have response capabilities. 

User and Entity Behavior Analytics (UEBA)

Different types of artificial intelligence (AI) and machine learning (ML) tools are used to detect suspicious behavior within a network. In order to do this, they need a baseline for normal behavior. User and entity behavior analytics (UEBA) is an AI system that learns the behavior of devices and users in a network. It works by collecting data from the normal activities of established users and devices to define normal behavior. When activities occur outside of this baseline of established behavior, the system generates an alert. Since UEBA alerts to unusual behavior by authorized users and devices, it is particularly useful in recognizing attacks that exploit stolen credentials.

Cyberattacks are increasing in frequency and sophistication. Attackers use AI, automated systems, and as-a-service options to conduct many attacks in a short period of time. To keep up with modern attacks, businesses need systems that automate security actions and eliminate manual tasks for analysts and other cybersecurity professionals. By learning more about these tools, you can improve your overall cybersecurity posture to better protect your network.

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