Abstract innovates in SIEM with 'composable' architecture

"We had already heard of 'next-gen SIEM'. This is a system that replaces traditional rule-based logging with automatic recognition of complex threats. It was designed to reduce noise on the line for SecOps personnel by reducing the number of false positives. However, according to Abstract CEO and co-founder Colby DeRodeff, this was only the beginning. He believes that a real 'reset' is needed, in the form of an 'AI-Gen Composable SIEM'."

"Unlike monolithic SIEM systems, Abstract is building a modular solution in which the various SIEM components represent a system of systems. Think of data ingestion, pipelines, storage, detection, AI-based triage, and response. Firstly, the functionality is distributed, which Abstract claims reduces vendor lock-in compared to legacy SIEM tooling. Data can also be intelligently navigated to the desired location, resulting in lower storage costs. Scaling up is also easier because only the necessary components grow as needed,"

"Abstract also focuses on the real-time processing of security data. Detections run in-stream for an immediate threat response. AI is further embedded in workflows for triage, investigation, and response. The system scales elastically across multi-cloud and hybrid environments. Abstract notes that the volume of security data continues to grow, making the modular solution of an AI-Gen Composable SIEM more attractive. According to the company, the amount of data is growing by 25 to 30 percent annually, driven by AI expansion and multi-cloud complexity."

Abstract launches a platform that combines modular building blocks to create an AI-Gen Composable SIEM, a system-of-systems for AI-native security operations. The design separates data ingestion, pipelines, storage, detection, AI-based triage, and response into distinct components, enabling distributed functionality and reduced vendor lock-in. Intelligent data navigation lowers storage costs and allows scaling of only required components. A streaming-first architecture runs detections in-stream for immediate response and embeds AI in triage, investigation, and automated response workflows. The platform scales elastically across multi-cloud and hybrid environments to address an annual security data growth of 25–30 percent driven by AI expansion and cloud complexity.

Read at Techzine Global