Advanced fraud detection and phishing protection SDK for iOS applications. Powered by Adara AI Chat API.
- 🛡️ Real-time phishing detection
- 🔗 URL and domain analysis
- 📱 OTP classification and risk assessment
- 🤖 AI-powered threat intelligence
- 📊 Comprehensive risk scoring
- 🔒 Privacy-focused (on-device + cloud hybrid)
- ⚡ Fast malicious link detection
- iOS 13.0+
- Swift 5.0+
- Xcode 13.0+
Add this to your Podfile:
pod 'FraudLinksDetectionKit'Then run:
pod installAdd the following to your Package.swift:
dependencies: [
.package(url: "https://github.com/Rayatkhan690/FraudLinksDetectionKit.git", from: "1.0.0")
]Or add it via Xcode:
- File > Add Packages
- Enter:
https://github.com/Rayatkhan690/FraudLinksDetectionKit.git
import FraudLinksDetectionKit
// In AppDelegate or SceneDelegate
let config = FraudLinksDetectionKit.Configuration(
apiKey: "your-api-key",
isProduction: true // false for dev environment
)
FraudLinksDetectionKit.shared.configure(with: config)// Analyze SMS or notification text
Task {
do {
let result = try await FraudLinksDetectionKit.shared.analyzeText(messageText)
if result.riskLevel == .high {
print("⚠️ High risk detected!")
print("Risk Score: \(result.riskScore)/100")
print("Indicators: \(result.indicators)")
}
} catch {
print("Analysis error: \(error)")
}
}if let url = URL(string: "https://suspicious-link.com") {
Task {
let analysis = try await FraudLinksDetectionKit.shared.analyzeURL(url)
print("Domain: \(analysis.domain)")
print("Risk Score: \(analysis.riskScore)")
print("Spoofed: \(analysis.isDomainSpoofed)")
}
}let text = "Your bank verification code is 123456"
if let otp = FraudLinksDetectionKit.shared.detectOTP(in: text) {
print("OTP: \(otp.code)")
print("Category: \(otp.category.rawValue)")
}FraudLinksDetectionKit uses Adara AI Chat API:
- Production:
https://mcp.adarasdwan.com - Development:
https://dev-mcp.adarasdwan.com
- Safe (0-30): No significant threats detected
- Suspicious (30-60): Some indicators found, caution advised
- High (60-100): Strong fraud indicators, high risk
FraudLinksDetectionKit respects user privacy:
- Local analysis performed on-device
- Only suspicious URLs sent to API
- No personal data collected
- GDPR compliant
FraudLinksDetectionKit is available under the MIT license. See the LICENSE file for more info.
Rayat Khan, [email protected]
Contributions are welcome! Please feel free to submit pull requests.