Enterprise Threat Detection and Encrypted Traffic Analysis
Secure Your Entire Network – From Core to Edge to Cloud
Threat actors no longer break in, they simply log in. They operate inside encrypted traffic, navigating across your network undetected. Conventional security solutions aren’t cutting it, it’s time for a new approach. The ThreatEye NV network detection and response platform is purpose-built for network security, combining next-generation data collection, advanced behavioral analysis, and streaming machine learning for threat detection and security compliance.
AI-Driven Encrypted Traffic Analysis
Deep Packet Dynamics
150+ Packet Traits & Behaviors across multi-vendor, multi-domain, and multi-cloud networked environments
Agnostic to Packet Contents
Scalable Real-Time Analysis of Deep Packet Dynamics.
Purpose-built for enterprise network security
Encrypted Traffic Analysis
Detect what others miss
Eliminate Encryption Blindness
Validate end-to-end encryption compliance
Encrypted Traffic Visibility is the Key to Security
Increased adoption of encrypted network protocols is causing the erosion of network visibility for security teams. Legacy tools are losing visibility. Encrypted Traffic Analysis, the application of machine learning applied to deep packet dynamics, is the perfect solution for analyzing encrypted traffic without the need for decryption.
Save downtime with faster detection through industry leading real-time detection analysis. Designed to process millions of events per second, ThreatEye NV’s multi-stage analysis pipeline is fueled by analyzers – or models – engineered to analyze network traffic without multiple passes over the data stream. Analyzers are architected specifically for network security and scale via parallel processing.
Detect Threats that Others Miss
ThreatEye’s Deep Packet Dynamics (DPD) is agnostic to packet contents and is used to create a historical inventory of traits and behaviors for profiling and fingerprinting, a technique that works equally well with both encrypted and unencrypted traffic. Machine Learning models are applied to identify advanced behavioral threat actor anomalies including phishing, unauthorized remote access (RDP/VPN), reconnaissance, lateral movement, C2, tunnelling, hands-on-keyboard, and data exfiltration.
Decrease Time to Investigate - SOC Enabled
Enable the effectiveness of the SOC by increasing the speed of response. ThreatEye NV’s multi-stage analysis pipeline correlates and enriches traffic with findings detail, risk scores, and MITRE ATT&CK labeling. Using ThreatEye NV, you can respond in real-time and accelerate triage with integrated packet analysis.
Customizable Dashboards and Advanced Reporting
ThreatEye NV provides multiple workflows to help the professional analyst build a profile of their network supporting out-of-the-box dashboards and customizable reporting, highlighting and prioritizing concerns that need immediate attention. The longer it takes to identify threat actor activity, the more successful their attack will be.
Ensure Platforms Conform to Security Standards
ThreatEye NV provides encryption-policy specific alerting and reporting for security compliance. The increased adoption of encryption to secure applications calls for a greater need to ensure all platforms conform to the encryption standards of the enterprise.