Threat hunting with Network Detection and Response (NDR) is a proactive security practice that leverages the deep visibility, analytics, and machine learning capabilities of NDR tools to discover hidden threats within your network — before they cause damage.
Network Detection and Response or NDR platforms provide powerful capabilities for proactive threat hunting—the practice of actively searching for hidden threats that may have bypassed traditional defenses.
Here’s how NDR enables and enhances threat hunting:
1. Rich Network Telemetry for Deep Forensics
NDR collects and retains detailed metadata and packet-level data, enabling threat hunters to:
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Analyze historical communication patterns.
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Investigate lateral movement across the network.
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Reconstruct sessions to understand attacker behavior.
Example: Investigating whether a compromised host communicated with other sensitive servers using unusual protocols.
2. AI-Driven Anomaly Detection
Most NDR solutions use machine learning to build baselines of normal behavior and highlight deviations such as:
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Unexpected port usage or protocol mismatches.
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Sudden increases in data transfer volume.
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Devices communicating with known malicious IPs or rare destinations.
These anomalies can trigger hunt leads for deeper manual investigation.
3. Threat Intelligence Integration
NDR integrates with threat intelligence feeds to flag:
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Known bad IPs/domains (C2 servers, malware hosts).
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Traffic matching known attack techniques (e.g., DNS tunneling).
Threat hunters can pivot from IoCs to discover affected systems and uncover broader campaigns.
4. Historical Threat Hunting
Unlike firewalls or traditional SIEMs, NDR platforms typically store metadata for weeks or months, enabling:
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Retrospective analysis after an IoC is discovered elsewhere.
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Long-term pattern analysis across attack campaigns.
5. Custom Query and Search Tools
Threat hunters can run ad hoc queries across the network data to answer questions like:
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“Which internal devices connected to this suspicious domain?”
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“Where else has this command-and-control pattern appeared?”
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“What devices initiated SMB sessions to sensitive servers?”
6. Workflow Integration for Rapid Response
Modern NDR solutions support integration with SOAR, EDR, and ticketing systems to:
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Automate response playbooks (e.g., isolate device, block IP).
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Collaborate across teams during investigations.
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Record hunt findings for audit and continuous improvement.
7. Network Behavior Anomaly Detection (NBAD)
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NDRs continuously baseline normal network activity.
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Threat hunters can identify anomalies such as:
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Unusual lateral movement
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Unexpected data transfers
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Rare or suspicious protocol usage
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8. Rich Metadata & Packet Capture
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NDR tools extract metadata from traffic (e.g., DNS, HTTP headers, TLS SNI, JA3 fingerprints).
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Full PCAP (packet capture) may be available for deep forensic analysis.
9. Historical Data & Retrospection
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NDR platforms store metadata and alerts for extended periods (weeks to months).
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Threat hunters can pivot on IOCs (IP, domain, JA3 hash, etc.) retrospectively.
Common Threat Hunting Use Cases with NDR
| Use Case | Example |
|---|---|
| Command and Control (C2) | Repetitive connections to rare external IPs at odd intervals |
| Credential Theft | Lateral Kerberos brute force or unusual LDAP queries |
| Insider Threats | Abnormal data transfers to cloud or USB |
| Malware Beaconing | Low-and-slow connections with similar intervals |
| DNS Tunneling | Long, encoded subdomains and high-frequency queries |
| Exfiltration | Large outbound transfers after privilege escalation |
Integration-Driven Enrichment
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SIEM: Pivot from network events to endpoint logs.
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EDR: Correlate network alerts with endpoint behavior.
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SOAR: Automate hunting workflows (e.g., query NDR for all DNS traffic to a suspicious domain).
Summary
Network Detection and Response makes threat hunting more efficient and effective by:
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Providing deep visibility across the network.
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Surfacing high-fidelity anomalies.
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Supporting fast, contextual investigation.
