RS-2026-094: Cognitive Adversary: Autonomous Attack Chain Synthesis via Local LLM Reasoning and GPU-Accelerated Monte Carlo Tree Search
Year: 2026
Type: article
Abstract: We present FRANKENSTEIN v2.0, a fully autonomous offensive security research platform that synthesises adaptive attack chains against hardened targets without human intervention. The system couples a GPU-accelerated Monte Carlo Tree Search (MCTS) engine - running 10,000 parallel simulations per cycle on an NVIDIA RTX 5090 24GB - with a local reasoning model (DeepSeek R1:14b) that diagnoses defender responses, selects remediation primitives, and rewrites the chain in real time. The primitive registry exposes the complete 312-tool NIGHTFALL arsenal. We evaluate the system against an AppArmor-protected Ollama container: when the initial chain is blocked at the LSM hook, R1 autonomously selects T68 SPECTER KERNEL (eBPF/LSM bypass) and mutates the chain within 15 seconds. All computation is on-device. No cloud inference, no internet connection. We also document the hallucination failure mode and present registry context injection as the mitigation. Report RS-2026-094, Red Specter Security Research Ltd, November 2026.
Author: Barron, Richard
Language: English
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225621238
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