The FREE Cybersecurity Glossary by Thor Pedersen!

Attack vector: A path or method used by an attacker to gain access to a computer system or network. It is used in cybersecurity to describe the specific methods and techniques used by attackers to breach the security of a system or network. Examples include exploiting a software vulnerability, using social engineering tactics to trick a user, or using a brute force attack to guess a password.

Attenuation: The reduction in signal strength as it travels through a medium, such as cables or air. In networking, attenuation can degrade data transmission quality as signals are weakened over distance or through obstacles, potentially impacting communication and requiring countermeasures to maintain signal integrity.

Attestation Engagement: A type of assurance engagement where an independent auditor evaluates and reports on specific subject matter or assertions made by an organization, often following an established framework, resulting in a report that stakeholders can use to assess compliance and control effectiveness.

Attribute: A characteristic or quality of an object or entity. It is used in data modeling to describe the properties or characteristics of a data element. Examples include the name, address, and phone number of a customer or the product name, price, and quantity of an order.

Attribute-Based Access Control (ABAC): A model that controls access to resources based on the evaluation of attributes associated with the user, the resource to be accessed, and current environmental conditions. This sophisticated method allows for flexible, fine-grained access control, catering to a wide range of potential scenarios. ABAC is particularly useful in complex environments where role-based access control (RBAC) may be too rigid or insufficient.

Attribute Sampling: A statistical approach where a subset of data is selected from a larger population based on specific characteristics or "attributes." The analysis of this sample can then be used to make inferences about the overall population. This method is often employed in various security contexts, such as network monitoring or transaction reviews, to identify anomalous behavior or potential threats without having to analyze every single data point.