With almost 80% of cyber threats mimic legitimate user behavior, how do top SOCs decide legitimate traffic and potentially dangerous?
If firewall and endpoint detection and response (EDR) is lacking in detection of the most important threats for your organization, where are you heading? Violations on Edge devices and VPN gateways have risen from 3% to 22%, according to Verizon’s latest data breach investigation report. EDR solutions struggle to catch zero-day exploits, land creature techniques, and malware-free attacks. Almost 80% of detected threats use malware-free techniques that mimic normal user behavior, as highlighted in CrowdStrike’s 2025 global threat report. The harsh reality is that traditional detection methods are no longer sufficient as threat actors adapt their strategies.
In response, the Security Operations Center (SOC) is turning to a multi-layered detection approach that cannot use network data to hide enemy activities.
Technologies such as Network Discovery and Response (NDR) are employed to provide complementary visibility to EDR by exposing behaviors that are likely to be missed in endpoint-based solutions. Unlike EDR, NDR works without agent deployment, effectively identifies threats that maliciously use common techniques and legal tools. The bottom row is an evasive technique that works for Edge devices and EDRs when the NDR is on the observation deck.
Layer Up: Faster Threat Detection Strategy
Just like layers of unpredictable weather, elite SOCs increase resilience through multi-layer detection strategies centered around network insights. NDR streamlines management by consolidating detection into a single system, allowing teams to focus on high-priority risks and use cases.
Teams can quickly adapt to evolving attack conditions, detect threats faster and minimize damage. Now let’s adjust the layers that make up this dynamic stack and take a closer look at the following:
Basic layer
To be lightweight and fast applied, these easily capture known threats to form the basis of defense.
Signature-based network detection serves as the first layer of protection due to its light weight and quick response time. Industry-leading signatures like Proofpoint Et Pro running on the Suricata engine can quickly identify known threats and attack patterns. Threat intelligence, which often consists of compromise metrics (IOCs), looks for known network entities (eg, IP addresses, domain names, hashes) that are observed in real attacks. Like signatures, IOCs are easy to share, lightweight, deploy quickly, and provide faster detection.
Malware Layer
Malware detection is considered a waterproof barrier and protects against “drops” of malware payloads by identifying malware families. Detections such as Yara rules, the standard for static file analysis in the malware analysis community, can identify malware families that share common code structures. It is important to detect polymorphic malware that retains core behavioral properties while changing its signature.
Adaptive Layer
The most sophisticated layers built to varying conditions use behavioral detection and machine learning algorithms that identify known, unknown, and avoidance threats.
Behavior detection identifies dangerous activities such as domain generation algorithms (DGAs), command and control communications, and anomalous data extraction patterns. It remains effective even if an attacker changes the IOC (or even the components of the attack), as the underlying behavior remains unchanged and unknown threats can be detected more quickly. Supervised and unsurveillanced ML models can detect both known attack patterns and anomalous behaviors that may indicate new threats. They can target attacks that span more time and complexity than behavioral detection. Anomaly detection uses unsupervised machine learning to find deviations from the behavior of the baseline network. This will alert the SOC of anomalies such as unexpected services, unusual client software, suspicious logins, malicious management traffic, and more. Organizations can help uncover threats hidden in normal network activity and minimize attacker dwell time.
Query Layer
Finally, in some circumstances there is no faster way to generate alerts than querying existing network data. Search-Based Discovery – Log search queries that generate alerts and detections – act like a snap-on layer ready for quick responses in the short term.
Integrated Threat Detection Layer Using NDR
The true strength of multilayer detection is how they work together. Top SOC deploys Network Discovery and Response (NDR) to provide a unified view of threats across the network. NDR correlates detections of multiple engines to provide a context that enhances full threat views, centralized network visibility, and real-time incident response.
Beyond layered detection, Advanced NDR solutions can also offer several important benefits that enhance your overall threat response capabilities.
Detection of new attack vectors and new technologies that are not yet built into traditional EDR signature-based detection systems. Reducing incident response times with AI-driven triage and automated workflows by ~25%, according to the 2022 FIREEYE report
The advancement of modern SOC
The combination of increasingly sophisticated attacks, broadening of attack surfaces and additional resource constraints requires a shift towards multi-tier detection strategies. In an environment where attacks are successful in seconds, the window to maintain effective cybersecurity without an NDR solution is rapidly closing. The elite SOC team has got it and has already stacked it. The question is not whether or not to implement multi-layer detection, but whether or not your organization can make this transition faster.
Corelight Network Discovery and Response
CoreLight’s integrated open NDR platform combines all of the seven network detection types above and is built on the foundations of open source software such as Zeek®, allowing you to harness the power of community-driven detection intelligence. For more information, see CoreLight.
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