Smart automation in ASM refers to the application of intelligent and adaptive technologies and tools to automate the attack surface management process. By leveraging machine learning algorithms and artificial intelligence technologies, enterprises can automate discovery and threat exposure, drastically reducing the time and resources required for the process. They can also minimize false positives and false negatives.

In the digital era, managing your attack surface – the sum total of all potential attack vectors in your systems – is a critical part of your cybersecurity strategy. Attack Surface Management (ASM) provides the insights and tools necessary to understand, assess, prioritize and remediate risks faster and more effectively. In this post, we’re going to explore eight key ASM advantages for security teams, and the key product capabilities needed to achieve them.

As security teams witness that their organization’s digital footprint keeps growing in size and complexity, the urgent need for attack surface discovery becomes clear. But what exactly does attack surface discovery entail, and why is it so crucial in today’s digital landscape? This blog post aims to demystify attack surface discovery and provide insights into its importance for security operations teams.

CVE-2023-34362 is an SQL injection (SQLi) vulnerability that has been found in the MOVEit Transfer web application that could allow an unauthenticated attacker to gain unauthorized access to MOVEit Transfer’s database. SQL Injection (SQLi) poses significant risks as it allows attackers to potentially steal, manipulate, or delete sensitive data from databases.