Artificial intelligence is moving beyond systems that simply generate text, images, code, or recommendations. Organizations are increasingly deploying AI agents capable of interpreting objectives, making decisions, using tools, accessing data, interacting with applications, and executing multi-step workflows with limited human intervention. This shift creates new opportunities for automation, but it also introduces a new cybersecurity
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Endpoints have become one of the most important attack surfaces in modern organizations. Laptops, desktops, servers, virtual machines, workstations, and other connected devices provide users and applications with access to corporate resources. They also give attackers potential entry points into business environments. A compromised endpoint can become the starting point for credential theft, malware execution,
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Cyberattacks are becoming increasingly difficult to identify using isolated security alerts. Attackers can use legitimate credentials, compromised infrastructure, cloud services, malware, phishing campaigns, and other techniques to avoid traditional security controls. Security teams therefore need more than raw event data. They need context that helps them understand who may be attacking, what techniques are being
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Modern organizations generate enormous amounts of security data from endpoints, servers, applications, cloud environments, network devices, identity systems, and security tools. The challenge is not simply collecting this information. Security teams need to determine which events matter, identify relationships between seemingly unrelated activities, investigate threats, and respond before an incident causes significant damage. SIEM software,
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