A total system audit API that produces 750+ structured signals across 40 categories covering security, performance, reliability, AI/ML, cost, compliance, and everything in between.
Click the button above or visit:
https://render.com/deploy?repo=https://github.com/rajamohan1950/deepAudit
You'll be asked to provide two secret values:
OPENAI_API_KEY— your OpenAI API keyANTHROPIC_API_KEY— your Anthropic API key
Render will automatically provision PostgreSQL, Redis, the API service, and the background worker.
# 1. Copy environment config
cp .env.example .env
# Edit .env with your OpenAI or Anthropic API key
# 2. Start all services
docker compose up -d
# 3. Create database tables and seed categories
docker compose exec api python scripts/seed_categories.py
# 4. API is live at http://localhost:8000
# Docs at http://localhost:8000/docs# Register a tenant
curl -X POST http://localhost:8000/api/v1/tenants \
-H "Content-Type: application/json" \
-d '{"name": "My Org", "email": "admin@myorg.com"}'
# Response includes api_key (shown once)
# Create an audit from a GitHub repo
curl -X POST http://localhost:8000/api/v1/audits \
-H "X-API-Key: da_your_key_here" \
-H "Content-Type: application/json" \
-d '{
"source": {
"type": "github",
"repo_url": "https://github.com/org/repo",
"branch": "main"
},
"system_context": {
"tech_stack": ["Python 3.11", "FastAPI", "PostgreSQL 16"],
"architecture": "Microservices",
"cloud_provider": "AWS",
"databases": ["PostgreSQL 16", "Redis 7"],
"compliance_requirements": ["SOC2", "GDPR"]
}
}'
# Check progress
curl http://localhost:8000/api/v1/audits/{audit_id}/progress \
-H "X-API-Key: da_your_key_here"
# Get P0 critical findings
curl "http://localhost:8000/api/v1/audits/{audit_id}/signals?severity=P0" \
-H "X-API-Key: da_your_key_here"
# Get executive summary
curl http://localhost:8000/api/v1/audits/{audit_id}/reports/executive-summary \
-H "X-API-Key: da_your_key_here"| Part | Categories | Focus |
|---|---|---|
| A | 1-5 | Security & Access Control |
| B | 6-12 | Performance & Resources |
| C | 13-18 | Reliability & Fault Tolerance |
| D | 19-22 | Infrastructure & Cloud |
| E | 23-24 | AI/ML Specific |
| F | 25-28 | Observability & Ops |
| G | 29-34 | Quality & Process |
| H | 35-40 | Compliance, Process & Misc |
- Signal Table — filterable/sortable export of all 750+ signals
- Executive Summary — top 15 findings with impact and cost
- Risk Heatmap — 40 categories x 4 severity levels
- SPOF Map — every single point of failure with blast radius
- Failure Mode Catalog — critical path failures and cascading effects
- Performance Profile — latency, memory, CPU, DB analysis
- AI/ML Risk Register — per-endpoint injection, hallucination, cost risk
- Cost Analysis — optimization opportunities ranked by savings
- Observability Scorecard — maturity rating per subcategory
- Compliance Gap Matrix — regulation to control to gap mapping
- Remediation Roadmap — prioritized timeline (Week 1 P0 through Quarter 2 P3)
- FastAPI — async REST API
- PostgreSQL 16 — persistent storage
- Redis 7 — job queue, rate limiting, progress events
- ARQ — async background workers for audit execution
- OpenAI / Anthropic — LLM-driven analysis engine
- GitPython — repository cloning and git history analysis
# Install dependencies
pip install -r requirements.txt
# Run API locally
uvicorn app.main:app --reload
# Run worker
arq app.workers.audit_worker.WorkerSettings
# Run tests
pytest tests/ -v