How RakshaAI Detects Scams
Our Trust Score (0–100) combines seven detection factors to give you an instant, accurate verdict on any website, UPI ID, or phone number.
Understanding Your Trust Score
No significant risk signals detected. No active blacklist matches. Domain and SSL look legitimate. Proceed with normal caution.
Some risk signals present — new domain, unusual WHOIS data, or minor community reports. Verify the entity independently before transacting.
Multiple risk signals or active blacklist match. Likely a scam or phishing site. Do not click links, enter credentials, or make payments.
The Seven Detection Factors
Every RakshaAI check analyses these seven signals simultaneously.
Domain Age & History
High WeightRecently registered domains (under 30 days) are a strong phishing indicator. We check registration date, previous ownership history, and expiration patterns.
Over 80% of phishing domains are less than 30 days old at time of attack.
SSL Certificate Analysis
High WeightWe verify the SSL certificate's validity, issuer reputation, expiration date, and grade (A+ to F). Mismatched or self-signed certificates on financial sites are red flags.
All legitimate banking and payment sites require valid SSL; absence is a definitive risk signal.
Blacklist Cross-Reference
Critical WeightWe query Google Safe Browsing, PhishTank, VirusTotal, CERT-In advisories, and India-specific threat feeds in real time. A blacklist match triggers immediate high-risk classification.
Databases updated every 15 minutes with new threat intelligence.
WHOIS Data Analysis
Medium WeightWe analyse registrar reputation, WHOIS privacy masking patterns, and registrant country. Domains registered through known bulk-registration services popular with scammers are flagged.
Privacy masking on financial domains combined with new registration is a compound risk signal.
Community Scam Reports
High WeightUser-submitted reports from Indian users, moderated by AI and human reviewers. Community reports carry significant weight for phone numbers and UPI IDs.
Community data is especially valuable for detecting new scams not yet in threat databases.
AI Behavioral Pattern Analysis
High WeightOur AI models are trained on India-specific scam patterns: fake government portals, cloned banking sites, investment fraud templates, and digital arrest impersonation pages.
Pattern matching catches novel variants of known scam types before they reach threat feeds.
Business Verification Status
Medium WeightEntities with a RakshaAI Trust Badge have passed GST, PAN, MCA, and Aadhaar verification — contributing positively to their Trust Score.
Verified businesses receive a minimum baseline score reflecting their confirmed legitimacy.
How to Check a Website in 5 Steps
Takes under 60 seconds. No account needed.
- 1Copy the suspicious URL
Copy the full website address (starting with http:// or https://) that you want to verify.
- 2Paste it into RakshaAI
Go to rakshaai.co/check and paste it into the search box. No login required.
- 3Review your Trust Score
Results appear in under 5 seconds with a colour-coded verdict: green (safe), yellow (caution), red (high risk).
- 4Read the risk breakdown
See exactly which signals triggered the score — domain age, SSL, blacklists, community reports — in plain language.
- 5Report confirmed scams
If it is a scam, use the Report button to protect other Indian users from the same threat.
Threat Intelligence Sources
Public threat databases are queried in real time. Community reports are processed and moderated before use. Full data source details →
Why Trust RakshaAI
Built specifically for Indian scam patterns — UPI fraud, digital arrest, IRCTC phishing, job offer scams — not adapted from Western models.
All detection tools are completely free with no registration, no trial limits, and no premium tier required for safety features.
Indian users submit fraud reports for websites, UPI IDs, and phone numbers — contributing to a community database that improves detection of newly emerging scams.
We publish exactly how Trust Scores are calculated. No black box — you can see which factors triggered every score.
Our guidance aligns with CERT-In advisories, MeitY cybersecurity guidelines, and the 1930 national helpline framework.
RakshaAI is a registered Indian company operating under Indian IT law, data protection requirements, and RBI cybersecurity guidance.
Methodology FAQs
How is the Trust Score calculated?▾
The RakshaAI Trust Score (0–100) is a weighted composite of seven factors: domain age and history, SSL certificate quality, blacklist database matches, WHOIS data patterns, community scam reports, AI behavioral pattern analysis, and business verification status. Each factor is weighted by its predictive power for scam detection in the Indian context.
How accurate is the Trust Score?▾
RakshaAI is effective at detecting known threats via public blacklists and community reports. No automated system is 100% accurate — we recommend additional personal verification for high-value financial transactions.
How quickly are new scam websites detected?▾
Our threat intelligence databases update every 15 minutes. Community reports are processed within minutes of submission. New AI pattern detections are deployed continuously. Most active phishing campaigns are flagged within hours of launch.
Can a legitimate website get a low score?▾
Yes — legitimate new websites (launched within the past 30 days) may receive lower initial scores because domain age is a strong scam signal. If you believe your legitimate site has an incorrect score, contact support@rakshaai.co for a manual review.
What data sources does RakshaAI use?▾
We use Google Safe Browsing, PhishTank, VirusTotal, CERT-In advisories, India-specific threat feeds, WHOIS databases, SSL certificate authorities, and our community report database of user-submitted scam reports. See our data sources page for full details.
Is my check query stored or tracked?▾
We do not associate check queries with individual users or IP addresses. Only anonymised aggregate statistics are retained for improving our detection models. We do not sell, share, or monetise query data.
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