Detect Attackers Hiding on Your Network
Threat Eye NV creates unprecedented visibility into encrypted traffic, threats, and network anomalies.
Threat Detection Faces a Crisis
Cyber defenders are struggling to detect advanced threats on the network, and the problem is getting worse. Record encryption levels are colliding with outdated tools, and traditional rules-based approaches that are blinded by encryption. Attackers are going undetected and teams are burning out.
The Power of Network Detection and Response
Reduce organizational risk and prevent downtime from successful cyberattacks by stopping them before completion.
LiveAction NDR works regardless of encryption.
Streaming Machine Learning Accelerates Threat Detection
Encrypted Traffic Analysis Reveals Attackers Hiding Within Encryption
Enriched Alerts Save Resources & Help Network Defenders Prioritize Response
How Network Detection and Response Reveals Attacks
Disrupt attacks in progress
Network Detection and Response (NDR) utilizes new levels of computational power. This includes next-generation data collection, advanced behavioral analysis, and streaming machine learning. NDR reveals new or unusual activity and ties events together to determine what is malicious.
Agencies [and organizations] should strive to employ heuristics rooted in machine learning to categorize the data they gather, and to deploy processes that offer early warning or detection of anomalous behavior is as close to real time as possible throughout the enterprise. “
ThreatEye, the Most Powerful NDR Platform
Detect Threats Inside Encryption
In Q2 2021, 91.5% of malware arrived through encryption. The Live Action NDR platform solves this challenge by detecting threats through Encrypted Traffic Analysis (ETA). By analyzing behavior, ETA never requires payload inspection or costly and complex decryption techniques.
Uncover Attacks with Fewer Resources
ThreatEye detects lateral movement, data staging, exfiltration, advanced phishing attacks, insider threats and much more.
Industry-leading, real-time machine learning detection, processes millions of events per second, fueled by analyzers – or models – to analyze network traffic with a single pass over the data stream.
ThreatEye – Advantage – ThreatEye’s analysis of Deep Packet Dynamics, characteristics of network traffic can uncover activity relating to a user browsing a phishing website or clicking on a malicious link in an email that prompts a network-based malware call-back.
ThreatEye – Advantage – ThreatEye uses behavioral baselines to track expected network behavior, identifying resources regularly accessed, such as RDP, VPN, and SSH, maintaining an inventory of communications, used to identify anomalies that could be associated with threat actor initial access
ThreatEye – Advantage – ThreatEye can detect anomalies of host behavior associated to scanning activity, tracking communications to destinations, services, and ports often associated to threat actor discovery.
ThreatEye – Advantage – ThreatEye incorporates change-point detection in its modeling approach to identify outlier anomalies from end-systems normal active social network (clique expansion) and synchronization between new communicating parties, such as unexpected/unauthorized RDP, PowerShell Remoting, unexpected encryption tunnels
ThreatEye – Advantage – ThreatEye can detect a host within your network that has consumed an irregularly large asymmetric volume of traffic, resulting in a significant change in the behavior of that host, often associated with threat actor activity collection and staging data before exfiltration.
ThreatEye – Advantage – Deep packet dynamics help identify encrypted C2 traffic by analyzing SPLT and distinctive traffic patterns. Command and control traffic regularly displays detectable traffic characteristics between the client and server and vice versa. Encrypted Traffic Analysis detects C2 traffic by analyzing packet dynamics such as the packet payload length and the total number of bytes observed in the traffic flow.
ThreatEye Advantage – With command and control and hands on keyboard access, attackers can transfer data from an organization’s systems and devices. Data is often exfiltrated over encrypted channels such as SSL/TLS, SSH, and other encrypted protocols. While some data is exfiltrated in large quantities, attackers often use stealthy techniques such as timing channels to send small amounts of data at a time to avoid detection. The combination of deep packet dynamics features with machine learning is used to detect data exfiltration by understanding application “fingerprints” and analyzing producer consumer ratios (PCR). Examining deep packet dynamics data can identify data exfiltration as anomalous activity.
Detection Powers Response
ThreatEye features convenient integration with existing security tools like SIEMs, SOAR, and Threat Intelligence. Workflow automation with leading products helps teams take immediate action on security threats.
Reduce analyst burnout
Alert fatigue is adding to the problem of analyst burnout but you can change this. ThreatEye creates enriched alerts that are risk scored and MITRE ATT&CK labeled. With a click, analysts can even dive down to the packet level if needed. Alerts inform your response and reduce frustration.
Made for the Modern Network
Utilizing a sensor-based SaaS approach, ThreatEye is deployed on premises, in a private or public cloud, or a mixture of both.
The platform provides true end-to-end security: from core, to edge, to cloud. Protect your network and your organization with LiveAction ThreatEye.