Automated scam detection for Indian consumers -- SMS, WhatsApp, UPI, deepfakes, voice clones -- across 12 Indian languages.
Chetana is a check-before-you-act tool that turns suspicious digital content into a clear next step. Paste a message, upload a screenshot, or submit a UPI ID -- Chetana returns a verdict, an explanation, and a recommended action. It does not guess when evidence is weak: unclear inputs receive an unclear verdict, not a false confidence score.
Live at chetana.activemirror.ai.
+------------------+ +------------------+ +------------------+
| User Input | | Verdict Engine | | Response |
| | ----> | | ----> | |
| Text, image, | | Deterministic | | Verdict + type |
| QR code, UPI ID | | classification | | + reasons + |
| | | + evidence log | | next action |
+------------------+ +------------------+ +------------------+
|
v
+------------------+
| Evidence Pack |
| (optional) |
| Shareable proof |
+------------------+
Supported input types:
- Suspicious text from WhatsApp, SMS, email, Telegram, or social media
- Screenshots of suspicious messages
- QR codes and UPI payment requests
- Payment confirmation screenshots (fake receipt detection)
Output for every scan:
- Verdict:
safe,risky, orunclear-- three states only, no ambiguity - Scam type classification
- Plain-language reasoning
- Confidence band
- Recommended next action
- Optional share shield and evidence pack
Chetana exposes a public v0 API for programmatic scam checks.
# Scan a suspicious message
curl -X POST https://chetana.activemirror.ai/api/v0/scan \
-H "Content-Type: application/json" \
-d '{
"input_type": "text",
"text": "Urgent: your bank account will be blocked today. Pay Rs 500 now.",
"language_hint": "en",
"session_id": "example-session"
}'| Endpoint | Purpose |
|---|---|
POST /api/v0/scan |
Submit content for scam analysis |
POST /api/v0/evidence |
Retrieve evidence pack for a scan |
POST /api/v0/events |
Event logging |
| Layer | Technology |
|---|---|
| Frontend | Vite 5, React 18, TypeScript, Tailwind CSS, Framer Motion |
| Backend | FastAPI, Python 3.11, Pydantic |
| OCR | Tesseract.js (client-side image text extraction) |
| On-device ML | Hugging Face Transformers (browser inference) |
| Deployment | FastAPI serves the built frontend as a single-origin application |
git clone https://github.com/MirrorDNA-Reflection-Protocol/chetana-site.git
cd chetana-site
# Frontend
cd frontend
npm install
npm run dev
# Backend (separate terminal)
cd backend
pip install -r requirements.txt
uvicorn app.main:app --port 8093- Three verdicts only.
safe,risky, orunclear. No numeric risk scores that imply false precision. - Default to unclear. When evidence is weak, the system says so rather than guessing.
- Show reasoning. Every verdict includes the factors that produced it.
- Surface recovery rails. Official reporting channels are always visible, never buried.
- No government affiliation. Chetana is an advisory tool. Verdicts are automated assessments, not legal determinations.
If you have been scammed:
- National Cybercrime Helpline: 1930
- File a report: cybercrime.gov.in
- Women helpline: 181
Act within the first hour for the best chance of recovery.
Chetana is built within the Active Mirror governed AI framework. See COMPLIANCE.md for control mappings against the EU AI Act, India DPDP Act 2023, SOC 2 Type II, and ISO 27001:2022.
To report a vulnerability, see SECURITY.md. Do not use public GitHub issues for security reports.
Not affiliated with the Government of India, RBI, UIDAI, CERT-IN, or any law enforcement agency.
Built by Active Mirror -- governed AI for institutional work.