OctoArch v5.0: Zero-Trust B2B Runtime with JSON-Based AI Personas

OctoArch v5.0 is an open-source zero-trust B2B cognitive runtime designed for enterprise applications requiring strict security and mathematical control over AI hallucinations. Built by a developer inspired by the OpenClaw ecosystem, it targets production use cases like fiscal and invoice extraction where standard text-based prompting falls short.

Core Architecture Features

The system implements three key architectural innovations:

• AIEOS (Digital DNA): Instead of standard text roles, OctoArch uses strict JSON files to define AI personas. These JSON files contain parameters like logic_weight: 0.95, creativity_weight: 0.05, and risk_tolerance: 0.0. The core runtime reads these files and dynamically injects the exact API temperature and PBAC constraints in real-time, physically altering the LLM's state based on the active role.
• The Titanium Cage (Zero-Trust): OctoArch eliminates default "God Mode" access. It implements strict path jailing through a validatePath function and segment filtering to prevent the AI from executing Path Traversal attacks (like ../) on the host server. The default state is a restricted sandbox.
• Swarm Hot-Swapping: The system can write its own tools at runtime. It spawns a Sub-Agent in an isolated sandbox, writes the code, runs npx tsc --noEmit to validate TypeScript syntax, and promotes the validated code to production without restarting the server.

Technical Implementation

The developer built OctoArch specifically for B2B scenarios where mathematical control over hallucinations and strict sandbox security were not achievable with standard approaches. The project is open-sourced under the Apache 2.0 license, with the core engine available on GitHub.

The architecture represents a departure from text-based prompting systems, instead treating AI personas as JSON-defined objects with precise numerical weights that directly influence LLM behavior and security constraints.