Glossary

Welcome to the Glossary! Whether you're already familiar with some of these terms or you're just becoming acquainted, our top-level glossary is a great resource for learning all of the relevant goods. Scroll through the full list below, search by term, or select by individual letter.
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value-added reseller (VAR)

An organization that is part of a sales channel for an original equipment manufacturer (OEM). VARs sell products on behalf of the OEM.

virtual machine (VM)

A software implementation of a hardware-like architecture, which executes predefined instructions in a fashion similar to a physical central processing unit (CPU). VMs are partitions of servers so different applications can run separately.

virtual private network (VPN)

A VPN extends a private network across a public network. It enables users to send and receive data across shared or public networks as if their computing devices were directly connected to a private network.

vishing, voice phishing

The use of manipulative, phone-based tactics to get victims to reveal private information that can be used for digital theft.

voice of customer (VOC)

Getting feedback directly from customers to inform strategy.

vulnerability assessment (VA)

A rapid automated review of network devices, servers and systems to identify key vulnerabilities and configuration issues that an attacker may be able to take advantage of.

vulnerability assessment and penetration test (VAPT)

A security testing to identify security vulnerabilities in an application, network, endpoint, and cloud. Vulnerability Assessment scans the digital assets and notifies organizations about pre-existing flaws. Penetration test exploits the vulnerabilities in the system & determines the security gaps.

Vulnerability Management (VM)

The process of identifying, evaluating, treating, and reporting on security vulnerabilities in systems and the software that runs on them.

vulnerability research (VR)

The term means actually going through publicly disclosed vulnerabilities to determine if they are legitimate issues, aggregating that data, and then normalizing it for consumption.