The problem
Classical zero-days evade traditional SOCs because they rely on signatures. The GS Cyber autonomous SOC uses LLM models to analyse unstructured log behaviour and identify semantic anomalies.
Our methodology
- Continuous log ingestion with vector embedding
- Detection based on cosine distance + clustering
- Automated triage and playbook generation
Results
In the first 12 months we reduced MTTR by 92% versus the Gartner benchmark.