Deepfakes now span voice, video, and digital identity impersonations. netarx’s platform was built as a comprehensive platform to combine signals to form the first all-media defense platform against AI-enhanced fraud.
netarx protects against deepfake video attacks in real time by analyzing over 50 metadata signals surrounding each interaction. Instead of relying on surface-level pixels, our models detect anomalies in context — location mismatches, device fingerprints, and behavioral inconsistencies. Netarx uses:
Frame-Level Forensics – Analyzing individual frames for inconsistencies in lighting, facial features, or micro-expressions.
Temporal Inconsistencies – Detecting unnatural transitions between frames (blinking frequency, jitter, head movement).
Audio-Visual Correlation – Comparing lip movement against voice signals to catch mismatches.
Biometric & Behavioral Cues – Identifying anomalies in eye gaze, pulse detection from skin micro-texture, or breathing patterns.
Metadata & Source Verification – Checking device origin, compression signatures, and blockchain-anchored originals.
AI-Powered Detection Models – Training classifiers to spot GAN-specific fingerprints and adversarial artifacts across multiple inference layers.
Whether in Zoom, Teams, WebEx or recorded video, netarx ensures that what you see is validated against reality.
Voice cloning, vishing attacks, impersonations via messaging, and smishing are among the fastest-growing fraud vectors. Netarx delivers a unified voice and messaging solution engineered to detect deefakes and other AI-generated threats .
netarx detects synthetic audio and impersonations by combining metadata, voice pattern analysis, and federated validators. This shared awareness exposes fake voices, impersonations across calls and meassaging, and prevents attackers from exploiting trust in phone calls, voicemails, messaging, or collaboration platforms.
Phishing is more dangerous than ever because they often set the stage for cross-channel deepfake attacks. netarx integrates with email platforms to detect fakes. Netarx monitors metadata, detects anomalies, and flag inconsistencies across senders, devices, and geographies. Netarx leverages numerous features such as:
Metadata Analysis – Checking inconsistencies in EXIF data, editing history, or image compression patterns.
Contextual Validation – Comparing suspected images against known databases, blockchain-anchored originals, or trusted sources.
Multi-Signal Approaches – Correlating metadata, device origin, behavioral data, and cross-platform checks for higher accuracy.
And, by correlating signals across communication channels, netarx closes the gap point solutions miss and stops fraud before it spreads.
Check for AI-Altered Items
Our manual upload functionality provides a direct and efficient method for ingesting critical file types, including images, text documents, and other file formats, for security analysis. This feature is designed for maximum ease of use, allowing security professionals to drag and drop files or select them from local storage for immediate processing. The streamlined interface ensures that submitting content for threat assessment is a straightforward process, minimizing operational friction and enabling teams to quickly analyze suspicious artifacts or validate content integrity without complex configurations.
Metadata Analysis – Checking inconsistencies in EXIF data, editing history, or image compression patterns.
Pixel & Artifact Inspection – Spotting irregularities in shadows, reflections, or noise distribution that reveal AI-generated anomalies.
AI-Based Forensics – Using trained neural networks to identify patterns invisible to the human eye, such as GAN fingerprints or irregular pixel correlations.
Contextual Validation – Comparing suspected images against known databases, blockchain-anchored originals, or trusted sources.
Multi-Signal Approaches – Correlating metadata, device origin, behavioral data, and cross-platform checks for higher accuracy.
This versatile tool supports a wide range of use cases, from forensic investigation of individual files to rapid validation checks in real time. It serves as a foundational component for any security protocol requiring granular analysis of specific files, offering a reliable and secure method to introduce content into your security ecosystem for comprehensive threat detection and response.
What’s included
What’s included
What’s included
Deepfake actors don’t just target one form of communications. Organizations need deepfake detection for all media that is accurate and dependable yet easy-to-use within standard everyday workflows.
Stop attacks as they happen with sub-second inference speeds. No lag. No retrospective alerts. Just the right information to know when it’s real or fake.
Uses over 50 meta data across all media to train the LLM’s via supervised and unsupervised learning - optimal for combining accuracy with predictability at scale.
We use the best-in-class inference models plus netarx’s proprietary technology to minimize false positive and reduce likelihood of being fooled to evade a specific model.
We cover all media within a single platform since real-world threats target multiple communication channels at once. Point solutions miss the critical cross-media signals.
We use blockchain encryption to validate authenticity and prevent tampering...even against with the most sophisticated quantum computing technologies.
We use simple easy-to-understand traffic light style visual confidence indicators embedded into everyday workflows.
Easy to deploy via standard IT provisioning or via simple app marketplaces. Ready-to-go SaaS solution for your organization.