OnSefy Laravel SDK – Validate Users & Detect Fraud

Official Laravel SDK for OnSefy – Validate new users, detect fraud, and score risk automatically to stop fake signups.

🚀 Features

• AI Based Quick Intelligent Assessment in microseconds
• Easy integration with Laravel apps
• Validate users with email, phone, IP, and user-agent
• Get detailed fraud risk scoring and patterns
• Detect suspicious users
• Free and paid plan support

📦 Installation

Install the package via Composer:

composer require onsefy/validate-user-laravel

Laravel 11+ will auto-discover the service provider and facade. If not, add manually to config/app.php:

'providers' => [
// ...
OnSefy\Laravel\OnSefyProvider::class,
],

'aliases' => [
// ...
'OnSefy' => OnSefy\Laravel\Facades\OnSefy::class,
],

⚙️ Configuration

Publish the config file:

php artisan vendor:publish --tag=onsefy-config

This will create a config file at config/onsefy. Add your credentials to .env:

ONSEFY_PLAN_TYPE=free
ONSEFY_API_KEY=your-api-key-here
ONSEFY_SERVICE_ID=your-service-id-here

🧠 Usage Example

use OnSefy;

$response = OnSefy::validateUser([
'email' => 'user@example.com',
'phone' => '+13434128780',
'ip' => '103.209.253.36',
'name' => 'John Doe',
'user_agent' => 'mozilla/5.0 (macintosh; intel mac os x 10.15; rv:136.0) gecko/20100101 firefox/136.0',
]);

if ($response['status']) {
// Take action based on risk score or level
$risk = $response['summary']['risk_score'];
$risk_level = $response['summary']['risk_level'];

}

✅ Recommended Validation Flow

To effectively prevent fake signups and reduce fraud risk, follow this validation strategy:

1. Pre-validate user data
   Call OnSefy::validateUser($userData) before creating or storing a new user record.

2. Evaluate the response
   Inspect key indicators from the response:

   • risk_score — numerical fraud risk (0 to 10)
   • verify_level — 0,1,2 level classification (e.g.,"0 Legit","1 Suspicious", "2 Fraud" )
   • risk_patterns — matched signals or warnings (e.g., "x pattern", "y pattern")

3. Take action based on risk score

   • Strict filtering: Block or flag users with risk_score > 1
   • Loose filtering: Allow up to risk_score <= 2, review or throttle above that

This ensures your platform stays protected while balancing user experience.

🛡️ Risk Score Reference

📝 License

The MIT License (MIT). See LICENSE for details.

💬 Support

• Docs
• Website
• Submit Ticket at HelpDesk

👥 Author

OnSefy Stop fake signups. Detect fraud before it costs you. https://onsefy.com