The article outlines strategies for operationalizing threat intelligence by integrating it into existing security stacks. It highlights four essential workflows—IOC enrichment, vulnerability prioritization, autonomous threat operations, and watch list automation—to elevate cybersecurity maturity from reactive to autonomous.
Security Operations
3 posts
4 Essential Integration Workflows for Operationalizing Threat Intelligence Machine Learning Operations: Yesterday, Today, and Tomorrow Akamai details its internal Machine Learning Operations (MLOps) platform, highlighting the transition from manual model management to a standardized, Kubeflow-based infrastructure. The platform enhances real-time security detections by streamlining model evaluation, tuning, and deployment, and is currently evolving to support LLMOps and AgentOps for generative AI applications.
Get started with Elastic Security from your AI agent Elastic has introduced open-source Agent Skills that enable AI coding agents to natively interact with Elastic Security. These skills allow security teams to rapidly provision cloud environments, generate realistic sample attack data, and manage alerts and detection rules directly from their IDEs.
