Trust CLI

Ship AI agents with confidence

One CLI to analyze agent code and runtime behavior, any framework.

Why Switch Trust?

• AI-powered analysis — Contextual code understanding, not just pattern matching
• OWASP ASI mapped — Findings aligned to Top 10 for Agentic Applications
• 100% free — First results in minutes

Try it now - 5 minute Quickstart

Requirements

• Python 3.11 or later
• OpenGrep (required for Switch Trust Scan)
• A running agent accessible via HTTP (required for Switch Trust Eval)

Supported frameworks: Google ADK, Google GenAI, Anthropic, OpenAI, OpenAI Agents SDK, LangGraph, CrewAI, AutoGen, HuggingFace Transformers, HuggingFace smolagents

Step 1: Install Switch Trust

Using a virtual environment is recommended to avoid dependency conflicts:

python3 -m venv .venv
source .venv/bin/activate

Install Switch Trust CLI:

pip install switch-trust-cli

pip install "switch-trust-cli[full]"

Step 2: Configure your LLM provider

Switch Trust uses AI to analyze agent code and score reliability. Run the interactive setup:

switch-trust init

You'll be prompted to select a provider (Gemini, OpenAI, Anthropic, or LiteLLM), choose a model, and enter your API key.

Run into issues? See installation troubleshooting

Step 3: Try the example agents

To demonstrate the CLIs capabilities, we've shipped this tool with two example agents. You can get them here.

Both agents work with both switch-trust scan and switch-trust eval:

The included examples/config.json has both agents configured with builtin evaluations (OWASP LLM01–LLM09, PII, secrets) and custom tests.

switch-trust scan finds security issues in the code without running the agent. We'll scan the bookstore agent to see what issues Switch Trust can find:

switch-trust scan examples/bookstore_agent/

Example: Scan found 2 security issues - High severity missing authentication and Medium severity unbounded execution loop

switch-trust eval tests runtime behavior, so the agent needs to be running. Start the bookstore agent:

# Start the bookstore agent (serves on http://localhost:8010)
uvx --with openai-agents,fastapi --from uvicorn uvicorn examples.bookstore_agent.agent:app --port 8010 --host 0.0.0.0

In a new terminal, run evaluations:

switch-trust eval run --model model-bookstore-agent --config examples/config.json

Step 4: Test your own agents

See our documentation to configure, scan and evaluate your agents:

• switch-trust scan
  • Scan your own agent — Apply Switch Trust Scan to your codebase
  • Understand scan results — Interpret findings and severity scores
• switch-trust eval
  • Evaluate your own agent — Configure and test your agent's behavior
  • Configuration — In-depth documentation of our configuration
  • Understand eval results — What the scores means and how to improve

Ship with confidence. Validate behavior, catch risks, prove readiness.

Commands

init

Setup wizard that configures Switch Trust for first use. Creates the ~/.switch-trust directory with a .env file (LLM provider, API key, runtime settings) and a config.json skeleton.

Runs automatically on first use in non-CI environments. You can re-run it at any time to reconfigure.

switch-trust init

scan

AI-powered security analysis of agent source code. Finds vulnerabilities, misconfigurations, and OWASP Top 10 violations.

# Scan a directory
switch-trust scan /path/to/agent/code

# Scan a single file
switch-trust scan agent.py

# Specify output file
switch-trust scan /path/to/code --output results.json

Full scan guide

eval

Test agent behavior at runtime. Get a evaluation score proving production-readiness.

# List all available configuration
switch-trust eval evaluations list

# List your agents and models
switch-trust eval models list

# Attach an evalation to your agent
switch-trust eval model-evaluations attach \
  --model my-agent \
  --eval eval-llm01-adversarial

# Run all evaluations for an agent
switch-trust eval run --model my-agent

The switch-trust eval command requires configuration. See Configuration to:

1. Define your models (agents to test)
2. View available evaluations
3. Attach evaluations to models

Full eval guide

Documentation

Complete guides and reference:

• Getting started
• Command reference
• Configuration
• Environment variables
• Built-in evaluations
• Data privacy
• FAQ

Data privacy

Switch Trust runs on your machine, but several features can call external LLM providers. This can be configured via GENERATOR_MODEL (located in ~/.switch-trust/.env, created by switch-trust init). You can set this to a remote managed LLM (i.e. gemini, openai, anthropic) or a locally hosted LLM (i.e. litellm or ollama).

Read more.

Telemetry

Switch Trust CLI collects anonymous usage analytics to help us understand how the tool is used and improve it. Telemetry is opt-in — you are asked for consent during switch-trust init, and no data is sent without your explicit agreement.

What we collect:

What we never collect: source code, file paths, prompts, API keys, model outputs, usernames, hostnames, IP addresses, or any personally identifiable information.

Opting out: Set SWITCH_TRUST_TELEMETRY_CONSENT=false in ~/.switch-trust/.env, or select "N" when prompted during switch-trust init. You can change this at any time.

Contributing

See CONTRIBUTING.md for details.

License

Free to use - full license.

Contact

• Website: https://switchagents.ai
• Email: info@switchagents.ai