Blog Articles
The Age of Autonomous CTI: How LLMs and Agents Can Build and Maintain Threat Intelligence Pipelines
In an era where data overwhelms human capacity, Cyber Threat Intelligence must evolve beyond manual curation. This article explores how Large Language Models and autonomous agents can build self-learning CTI pipelines that collect, enrich, correlate, and report intelligence at machine speed, while humans provide oversight, ethics, and strategic judgment. By turning static workflows into adaptive ecosystems, autonomous CTI transforms intelligence from information gathering into continuous, self-improving understanding.
The Evolution of Threat Intelligence: From IOC Feeds to Context-Driven Detection
Traditional IoC-based detection is losing relevance due to its static, context-poor nature. Modern threat detection now integrates CTI, behavioral analytics, and AI models (VAEs, TCN-BiGRU, GNNs) to reveal intent and multi-stage attacks. By enriching data with context and automation, SOCs move from reactive noise to proactive, intelligent defense.
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