Automated threat intelligence is a cybersecurity approach that leverages specialized software, machine learning algorithms, and artificial intelligence to autonomously collect, aggregate, and analyze threat data from multiple sources. These sources include open-source intelligence feeds, deep and dark web monitoring, industry threat sharing platforms, and internal security logs. The primary goal is to transform vast amounts of raw data into actionable intelligence, such as indicators of compromise (IoCs), attacker tactics, techniques, and procedures (TTPs), and emerging vulnerability trends.

By automating the threat intelligence process, security operations teams gain real-time visibility into the evolving threat landscape, enabling proactive threat detection, effective risk prioritization, and faster decision-making. This approach significantly reduces manual effort, accelerates response times to potential cyberattacks, and strengthens an organization's overall defensive posture against sophisticated and rapidly changing cyber threats.