Voice Fraud Evolves Faster Than Static Controls
Fraudsters continuously change calling patterns, routes, identities, and techniques to evade conventional rules and signature-based detection.
Stop Voice Fraud Before It Impacts Revenue and Trust
We protect voice networks from robocalling, CLI spoofing, Wangiri, toll fraud, unauthorized PBX access, and VoIP threats using AI-powered behavioral intelligence and real-time traffic controls.
Challenges
Industry Challenges
Spoofed and Unwanted Calls Erode Subscriber Trust
CLI spoofing and robocalling expose subscribers to deceptive communications while undermining confidence in operator voice services.
Voice Fraud Creates Immediate Revenue Exposure
Wangiri, toll fraud, and unauthorized PBX access can generate significant financial losses before conventional monitoring identifies abnormal activity.
Legitimate and Fraudulent Calls Can Look Similar
Effective detection requires deeper analysis of call behavior, signaling patterns, codec characteristics, and traffic context to distinguish sophisticated fraud.
Product Overview
AI-Powered Protection for Voice Networks
Our Voice Firewall provides a dedicated security layer for detecting and preventing voice-specific threats across telecom networks. AI/ML models analyze call signaling patterns, codec signatures, call-duration distributions, and behavioral anomalies in real time to identify fraudulent traffic with high accuracy.
DPI-based voice traffic inspection adds deeper visibility into VoIP traffic and SIP protocol exploits, while adaptive AI continuously learns from confirmed threat data to recognize evolving fraud techniques.
The Outcomes Are Clear
01
Less voice fraud
02
Lower revenue exposure
03
Greater subscriber trust
Capabilities
Product Capabilities
Multi-Layer Voice Threat Protection
Detect and prevent robocalling, CLI spoofing, Wangiri, toll fraud, unauthorized PBX access, and other voice-specific threats.
AI/ML-Powered Fraud Detection
Analyze call behavior and signaling patterns in real time to identify fraudulent activity with high accuracy.
Behavioral Call Intelligence
Evaluate call-duration distributions, destinations, frequency, signaling patterns, and behavioral anomalies to distinguish suspicious activity from legitimate traffic.
CLI Spoofing Detection
Identify calling-line identity inconsistencies and suspicious behavior associated with spoofed or manipulated caller identities.
DPI-Based VoIP Threat Detection
Inspect voice traffic at deeper layers to identify suspicious VoIP behavior and SIP protocol exploits.
Codec Signature Analysis
Analyze codec characteristics alongside call and signaling behavior to strengthen the identification of suspicious traffic and fraud patterns.
Real-Time Voice Fraud Controls
Apply configured security actions to detected threats in real time to prevent fraudulent traffic from escalating.
Adaptive AI Threat Intelligence
Continuously learn from confirmed threat data to improve detection as voice fraud techniques and attack patterns evolve.
Process
How It Works
01
Monitor Voice Activity
We continuously analyze call signaling, traffic behavior, codec characteristics, and relevant voice indicators across protected environments.
02
Build Behavioral Context
AI/ML models evaluate call duration, frequency, destinations, signaling patterns, and historical behavior to establish context around each call.
03
Detect Voice-Specific Threats
Behavioral intelligence and DPI inspection identify patterns associated with robocalling, CLI spoofing, Wangiri, toll fraud, PBX abuse, and VoIP threats.
04
Classify Fraud Risk
Multiple voice, signaling, codec, and behavioral indicators are evaluated to distinguish suspicious traffic from legitimate calling behavior.
05
Control and Continuously Learn
Real-time security controls prevent identified threats, while confirmed fraud data strengthens adaptive AI models for future detection.
Results
Key Outcomes
Reduced Voice Fraud
Detect and prevent fraudulent voice activity before it develops into wider financial or operational impact.
Lower Revenue Exposure
Control toll fraud, Wangiri, PBX abuse, and other voice threats that can generate direct financial losses.
Faster Detection of Evolving Fraud
Identify changing attack patterns through adaptive AI and real-time behavioral intelligence.
Stronger Subscriber Protection
Reduce exposure to robocalling, spoofed calls, and other deceptive or unwanted voice activity.
Higher Detection Accuracy
Combine behavioral, signaling, codec, and DPI-derived intelligence to distinguish sophisticated fraud from legitimate voice traffic.
Greater Voice Security Control
Protect voice services with dedicated detection and real-time controls designed specifically for telecom calling environments.