Modern attackers no longer rely on single exploits. They execute coordinated, multi-stage kill-chains that combine reconnaissance, initial access, lateral movement, persistence, and exfiltration.
However, most offensive security tools remain fragmented, forcing red teams to manually connect scanners, scripts, and execution frameworks.
This session introduces Red Hunter, a custom-built automated offensive framework developed in-house alongside Blue Hunter, an AI-driven attack surface management system.
Red Hunter supports both agent-based execution and agentless operations, enabling dynamically generated, scenario-driven attacks modeled after real-world threat actor behaviors. By bridging AI-driven attack surface analysis (Blue Hunter) with automated execution (Red Hunter), the framework enables end-to-end offensive operations with minimal human intervention.
The system analyzes OSINT data, generates context-aware and dynamically created attack scenarios derived from known threat actor tradecraft, maps those scenarios to MITRE ATT&CK techniques, and automatically executes validated Atomic Red Team tests through a fully offline, air-gapped architecture.
Attendees will see how AI can move beyond text generation into strategic kill-chain planning, and how these plans can be executed, measured, and reproduced in real-world red team and purple team environments.
I. Introduction
II. Phase 1: Blue Hunter – AI Strategic Reasoning