Beta
Message Trust
Evaluate messages for social engineering, impersonation, urgency tactics, malicious links, and fraud-oriented language.
Example signal
KYC expiry message with urgent link
Trust score
22/100
Likely scam
- Urgency language
- Brand impersonation
- Unverified destination
Problem
Modern fraud mixes social engineering with links, payment requests, and impersonation. Link scanning alone cannot see the persuasive context around the attack.
Solution
Message Trust classifies message intent, extracts entities, identifies manipulation patterns, and combines those signals with URL and payment intelligence.
How it works
01
Ingest message
02
Extract entities
03
Detect scam intent
04
Correlate links
05
Generate guidance
Live analyzer
Try Message Trust
Submit a sample input to the live TrustShield backend and review the returned Trust Score, Risk Score, recommendation, signals, and technical Security Report.
Message Trust
Analyze a suspicious message
Evaluate SMS, WhatsApp, Telegram, or chat content for impersonation, urgency cues, malicious links, and social engineering signals.
Awaiting analysis
Submit the form to receive a live TrustShield backend Security Report.
Architecture
Benefits
Example API result
curl $NEXT_PUBLIC_API_BASE_URL/api/public/analyze/url \
-H "Authorization: Bearer $TRUSTSHIELD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"url":"https://example.com/login"}'{
"trustScore": 86,
"verdict": "trusted",
"recommendation": "allow",
"signals": [
"valid_tls",
"no_suspicious_redirects",
"domain_reputation_positive"
],
"explanation": "No high-risk indicators were detected."
}FAQ
Will message content be stored?
The architecture is prepared for privacy-first processing with configurable retention and enterprise controls.
Will it support regional languages?
The module is designed to expand multilingual fraud detection as adoption grows.
Use TrustShield on Android
Install the official Android app for URL Trust and QR Trust workflows on mobile.