Network Detection & Response (NDR) is a proactive cybersecurity solution. Basically, this system deeply monitors all your internal network traffic. Therefore, NDR easily detects threats moving silently between devices. This solution uses artificial intelligence (AI) and behavioral analytics. As a result, every anomaly and malicious communication is quickly identified. Furthermore, NDR fills critical visibility gaps left by endpoint security (EDR) and logs (SIEM). Thus, cyber threats are stopped in the post-compromise phase before damaging your data.
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Network perimeters are highly vulnerable today. Consequently, hackers move freely inside your system. However, NDR continuously monitors east-west traffic. Thus, lateral movement is blocked instantly.
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Attackers use built-in tools to hide. Because of this, standard antiviruses easily fail. In contrast, NDR machine learning detects the smallest deviations. Therefore, attacks are stopped early.
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Many assets cannot run security agents. For example, IoT devices and industrial machines. Fortunately, NDR monitors all traffic entirely without agents. As a result, blind spots disappear.
The system records all network traffic entirely. Subsequently, analysts can easily replay this historical data. Thus, forensic incident investigations become much more accurate.
The platform builds normal behavior models for every organizational device. After that, the system automatically detects any deviations. As a result, suspicious network anomalies are handled immediately.
Hackers often hide malicious data within encrypted connections. However, our analytics feature reads metadata patterns accurately. Remarkably, this detection process happens without decrypting the original privacy data.
Every threat is automatically mapped to the MITRE ATT&CK framework. Therefore, security analysts receive rich tactical context. Consequently, response strategies can be prioritized very quickly.
NDR does more than just detect a security incident. Moreover, the system instantly isolates compromised devices. As a result, the Mean Time to Respond (MTTR) becomes incredibly short.
Modern IT architectures are very complex and highly distributed. Nevertheless, our virtual sensors monitor cloud environments seamlessly. Therefore, data security across all platforms remains fully guaranteed.
You can easily catch hackers who bypass your internal network. With this feature, malicious activities are stopped before reaching critical databases. In short, financial losses from data theft are completely prevented.
This solution perfectly complements your existing EDR and SIEM systems. Together, these three form a solid SOC Triad defense. As a result, your organization gains multi-layered network protection.
Security analysts can now search for threats proactively. In addition, device communication visualizations greatly speed up the investigation process. Thus, proving cyber attack hypotheses becomes much more efficient.
The system securely stores the entire data traffic history. Therefore, your IT team can trace root causes comprehensively. Ultimately, regulatory reporting and compliance audits become much easier.
Field operational infrastructure often has very weak security systems. However, this service passively monitors devices without extra installations. Consequently, your medical devices and factory machines are always safe.
We continuously align with global cyber threat intelligence in real-time. For instance, the system blocks recognized command-and-control (C2) communications. Thus, your infrastructure is immune to actively known hacker groups.
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These three security solutions perfectly complement each other. First, EDR monitors running processes at the endpoint level. Second, SIEM collects and correlates logs from various servers. Finally, NDR specifically analyzes data traffic movement between devices across the network.
The system uses Encrypted Traffic Analysis (ETA) techniques. With this method, the platform extracts metadata characteristics and TLS handshake patterns. Therefore, hidden malware traffic is identified accurately without decrypting user privacy.
Sensor placement heavily depends on your specific visibility goals. Usually, sensors are installed on core switches to monitor external traffic. Additionally, sensors are placed on the internal network distribution layer to detect lateral movement.
Absolutely, this NDR approach is ideal for hybrid and multi-cloud setups. Because, hackers inside the cloud also frequently perform data exfiltration. Therefore, we use virtual sensors and flow logs to secure your cloud workloads.
The platform needs an initial learning period of about 2 to 4 weeks. During this time, machine learning analytics build a normal behavior foundation. Afterward, the operational anomaly detection accuracy will continuously improve.
