Multi-agent adversarial evaluation platform for LLM-powered applications. First target: OpenEMR Clinical Co-Pilot.
Live Deployments:
- Target (OpenEMR Co-Pilot): https://openemr-production-f23e.up.railway.app/
- RedTeam Forge Platform: https://redteam-forge-production.up.railway.app/
# Install dependencies
pip install -e ".[dev]"
# Start PostgreSQL
docker compose up -d
# Copy and configure environment
cp .env.example .env
# Edit .env with your OpenEMR credentials, patient PID, and RunPod API key
# Run a campaign against the live target (authenticated path)
python scripts/run_campaign.py \
--target-url https://openemr-production-f23e.up.railway.app \
--username admin \
--password pass \
--patient-pid 100The campaign authenticates to OpenEMR as a clinician user, sets the active
patient, and sends adversarial prompts through /api/copilot/chat — the same
endpoint real users hit. This tests the full defense stack: refusal classifiers,
intent routing, tool-use ACLs, LLM guardrails, verification, and the sidecar
RAG layer.
See ARCHITECTURE.md for the full multi-agent design.
See THREAT_MODEL.md for the attack surface analysis.