VANGUARD: A Cognitive Purple Agent Framework for Autonomous Adversarial Simulation and Real-Time SIEM Validation

The rapid evolution of cyber threats demands continuous, high-fidelity validation of enterprise defensive postures. Conventional Breach and Attack Simulation (BAS) methodologies rely on static playbooks that fail to emulate the adaptive reasoning of modern Advanced Persistent Threats (APTs). In this paper, we present VANGUARD, a novel "Cognitive Purple Agent" framework. VANGUARD fuses an interactive, Large Language Model (LLM)-driven Red Team agent, built on a Reason-and-Act (ReAct) cognitive architecture, with a real-time Blue Team telemetry validation pipeline via the Elasticsearch (ELK) stack. Unlike black-box offensive AIs, VANGUARD mathematically quantifies its own Time-to-Detect (TTD) and subsequently acts as a DefSecOps engineer by autonomously synthesizing and deploying bespoke SOC Heuristics to close the gaps. We address the critical "Agentic Alignment" problem in offensive AI by implementing a mathematically strict FATAL_OS_BLOCKLIST, granting the agent total operational autonomy while safely preventing host destruction. Our results demonstrate that VANGUARD successfully exploits multiple vulnerability classes across diverse enterprise targets (Generic Web, Cloud Storage, Legacy ERP) autonomously, while identifying catastrophic 0.0% SOC alert rates and immediately repairing the target's Elasticsearch SIEM with functional defensive rules.