The Problem​

AI agents are powerful but introduce unique security challenges:

• Prompt injection attacks — malicious inputs that hijack agent behavior
• Uncontrolled tool access — agents executing dangerous operations without authorization
• Lack of audit trails — no visibility into what agents actually did
• Difficult to enforce policies — security rules scattered across application code

The Solution​

KalGuard provides a zero-trust, fail-closed security layer that sits between your agent and the outside world:

• Prompt Firewall — Detect and sanitize malicious prompts before they reach the LLM
• Tool Mediation — Control exactly which tools agents can execute, with what arguments
• Policy Engine — Declarative, composable security policies with hot-reload support
• Agent Identity — JWT-based authentication and per-agent authorization
• Immutable Audit Logging — Append-only, signed audit trail for every decision

Architecture​

KalGuard runs as a sidecar process — not embedded in your agent. This means:

• Works with any framework (LangChain, AutoGPT, custom agents)
• Simple HTTP API or TypeScript SDK integration
• Deploy alongside your agent in Docker, Kubernetes, or bare metal
• No vendor lock-in — swap it out without changing your agent code

Free & Cloud Options​

KalGuard is fully functional as a free, self-hosted open-source project. For teams that need more, KalGuard Cloud adds managed rate limiting, usage analytics, and extended audit retention through a simple API key.

Get Started​

pnpm add kalguard

Check out the Quick Start Guide to get started, or read the Cloud documentation for managed features.