Project Overview

Concept

LLM Harness provides a secure runtime environment for LLM-integrated tooling, allowing users to:

• Execute AI-generated code safely
• Integrate LLM capabilities into workflows
• Maintain audit trails of all operations
• Control permissions at granular levels

Inspiration

Existing AI agent tools demonstrate the power of LLM-driven automation but often with insufficient security controls. LLM Harness aims to:

• Preserve the utility of LLM-powered tooling
• Add layers of security and safety
• Provide transparency through open source
• Enable enterprise and individual use with confidence

Target Use Cases

1. Development automation - Safe code generation, testing, and refactoring
2. Workflow orchestration - LLM-driven task automation with guardrails
3. Research environments - Sandboxed LLM experimentation
4. Enterprise integration - Secure LLM tooling in regulated environments

Core Principles

• Security first - Every feature evaluated against security impact
• Zero trust - Assume compromise, minimize blast radius
• Composability - Modular design for flexibility
• Performance - Rust’s safety without sacrificing speed