# How to Install AI-Infra-Guard: Three Methods for Deploying the Hybrid Go/Python Platform

> Learn how to install AI-Infra-Guard. Explore three deployment methods: Docker Compose, a one-click script, or building from source for your hybrid Go/Python platform.

- Repository: [Tencent/AI-Infra-Guard](https://github.com/tencent/AI-Infra-Guard)
- Tags: getting-started
- Published: 2026-08-22

---

**AI-Infra-Guard can be installed via Docker Compose with pre-built images, a one-click shell script that automates the setup, or built from source by compiling the Go binary and Python agents.**

AI-Infra-Guard (A.I.G) is an open-source AI red-team platform developed by Tencent that combines Go-based infrastructure scanning with Python-powered security agents. Whether you need a production-ready deployment or a development environment for customizing detection rules, installing AI-Infra-Guard requires only Docker and Git. This guide covers every installation method supported by the Tencent/AI-Infra-Guard repository, from one-line commands to full source compilation.

## Prerequisites

Before installing AI-Infra-Guard, ensure your system meets these requirements:

- Docker (≥ 20.10) with Compose V2 support
- Git for cloning the repository
- (Optional) Python 3.9+ and pip if running Python agents manually outside Docker

The platform exposes the web interface on port 8088 by default, so ensure this port is available or modify the [`docker-compose.images.yml`](https://github.com/Tencent/AI-Infra-Guard/blob/main/docker-compose.images.yml) configuration accordingly.

## Method 1: Docker Compose with Pre-Built Images (Recommended)

The fastest way to install AI-Infra-Guard uses pre-built images from Docker Hub. This method deploys the complete stack—including the web UI, REST API, and all three scan engines—without compiling any code.

First, clone the repository:

```bash
git clone https://github.com/Tencent/AI-Infra-Guard.git
cd AI-Infra-Guard

```

Then start the services using the pre-built image configuration:

```bash
docker-compose -f docker-compose.images.yml up -d

```

For Docker Compose V2+, use `docker compose` instead of `docker-compose`.

Once containers start, access the web UI at `http://localhost:8088`. The API documentation is available at [`/docs/index.html`](https://github.com/Tencent/AI-Infra-Guard/blob/main//docs/index.html), and all scan modules are immediately operational.

## Method 2: One-Click Install Script

For fresh machines or CI environments, the [`docker.sh`](https://github.com/Tencent/AI-Infra-Guard/blob/main/docker.sh) script automates the entire installation process. It checks for Docker (installing it if missing), clones the repository, and executes the Docker Compose command.

Run the installer with:

```bash
curl https://raw.githubusercontent.com/Tencent/AI-Infra-Guard/refs/heads/main/docker.sh | bash

```

This script performs the same operations as Method 1, making it ideal for unattended deployments or quick evaluations on new virtual machines.

## Method 3: Build from Source

Developers contributing to Tencent/AI-Infra-Guard or requiring custom modifications should build from source. This approach compiles the Go binary located in [`cmd/cli/main.go`](https://github.com/Tencent/AI-Infra-Guard/blob/main/cmd/cli/main.go) and prepares the Python agents manually.

Clone the repository and build the Go service:

```bash
git clone https://github.com/Tencent/AI-Infra-Guard.git
cd AI-Infra-Guard
go build -o ai-infra-guard ./cmd/cli/main.go

```

Install dependencies for the Python scanning agents:

```bash
pip install -r mcp-scan/requirements.txt
pip install -r agent-scan/requirements.txt
pip install -r AIG-PromptSecurity/requirements.txt

```

Launch the web server directly:

```bash
./ai-infra-guard webserver --server 127.0.0.1:8088

```

Alternatively, use the local Docker Compose file to containerize your custom build:

```bash
docker-compose up -d

```

Building from source gives you full control over the detection rules stored in `data/fingerprints/` and `data/vuln/`, allowing updates without rebuilding binaries.

## Verifying Your Installation

Confirm your AI-Infra-Guard installation is functioning correctly:

1. Open `http://localhost:8088` and verify the dashboard loads without errors.
2. Visit `http://localhost:8088/api-checker/docs` to confirm the Swagger API documentation is accessible.
3. Execute a test scan against a local target using the CLI:

```bash
./ai-infra-guard scan -t http://127.0.0.1:8000

```

For manual Python agent testing, run the MCP scanner directly:

```bash
python mcp-scan/main.py --repo /path/to/mcp/server

```

## Architecture Overview

Understanding the platform architecture helps troubleshoot installation issues. AI-Infra-Guard v3.6.0+ consists of three independent scan engines orchestrated by a Go-based entry point in [`cmd/cli/main.go`](https://github.com/Tencent/AI-Infra-Guard/blob/main/cmd/cli/main.go):

- **AI Infra Scan** (Go): Fingerprinting engine for AI services and CVE matching
- **MCP Scan** (Python): Static analysis and LLM verification for Model-Context-Protocol servers
- **Agent Scan** (Go): Multi-agent workflow security testing

Detection rules reside externally in the `data/` directory, enabling rule updates without service restarts or rebuilds.

## Summary

- **Docker Compose with pre-built images** is the recommended installation method for most users, requiring only `docker-compose -f docker-compose.images.yml up -d` to run the complete platform.
- The **one-click script** at [`docker.sh`](https://github.com/Tencent/AI-Infra-Guard/blob/main/docker.sh) automates Docker installation and deployment for fresh environments.
- **Building from source** requires compiling [`cmd/cli/main.go`](https://github.com/Tencent/AI-Infra-Guard/blob/main/cmd/cli/main.go) and installing Python dependencies for developers needing custom builds.
- All methods expose the web UI on port 8088 and include the complete rule sets located in `data/fingerprints/` and `data/vuln/`.

## Frequently Asked Questions

### What are the minimum system requirements for AI-Infra-Guard?

AI-Infra-Guard requires Docker 20.10 or later with Compose V2 support. The platform runs on any Linux, macOS, or Windows host capable of running Docker containers. For source builds, Go 1.20+ and Python 3.9+ are necessary to compile [`cmd/cli/main.go`](https://github.com/Tencent/AI-Infra-Guard/blob/main/cmd/cli/main.go) and run the Python agents in `mcp-scan/` and `AIG-PromptSecurity/`.

### Can I run AI-Infra-Guard without Docker?

Yes, though it requires manual setup. Build the Go binary with `go build -o ai-infra-guard ./cmd/cli/main.go`, install Python dependencies from the various [`requirements.txt`](https://github.com/Tencent/AI-Infra-Guard/blob/main/requirements.txt) files, then execute `./ai-infra-guard webserver --server 127.0.0.1:8088`. However, Docker is recommended for production deployments to ensure consistent dependency management across the hybrid Go/Python architecture.

### How do I update AI-Infra-Guard to the latest version?

For Docker Compose installations, run `docker-compose -f docker-compose.images.yml pull` followed by `up -d` to fetch the latest images. Because detection rules are stored externally in the `data/` directory and mounted as volumes, rule updates only require pulling the latest Git repository changes without rebuilding containers. Source installations require `git pull` and recompiling [`cmd/cli/main.go`](https://github.com/Tencent/AI-Infra-Guard/blob/main/cmd/cli/main.go).

### Which installation method should I choose for production environments?

Use the **Docker Compose with pre-built images** method for production. This approach uses the official [`docker-compose.images.yml`](https://github.com/Tencent/AI-Infra-Guard/blob/main/docker-compose.images.yml) configuration, which pulls tested images from Docker Hub and ensures all three scan engines (AI Infra, MCP, and Agent) start with correct inter-service networking. The one-click script is suitable for testing but review [`docker.sh`](https://github.com/Tencent/AI-Infra-Guard/blob/main/docker.sh) before executing in production environments.