AI Malware and LLM Abuse: The Next Wave of Cyber Threats

This report forecasts the rapid emergence of AI-native cyber threats, including malware with embedded models capable of adaptive evasion, and argues that traditional SIEM processes cannot scale to meet the required detection coverage and speed. It outlines an AI-assisted detection lifecycle (rule generation, enrichment, prioritization), calls for LLM firewalls to mitigate malicious model usage, and promotes a shift-left architecture where real-time detection runs in streaming platforms before the SIEM. The piece concludes that by 2026, AI-native detection intelligence and streaming-first operations will become baseline expectations for enterprise security.