Most engineers think…
Most people picture a SIEM as 'something that collects syslog'. That is true but only half the picture for QRadar.
IBM QRadar treats network flows as a first-class data type alongside events. A flow record captures a full conversation — source IP, destination IP, ports, protocol, byte and packet counts — so the SIEM can answer 'who talked to whom, for how long and how much data moved?' without ever seeing a log. Add QRadar Network Insights (QNI) and you also get application-layer visibility: URLs, DNS names, TLS certificates, file hashes and HTTP headers extracted from live traffic. Understanding the flow pipeline — QFlow collector → normalisation → superflows → QNI content flows → asset enrichment — is what separates a junior SOC analyst from one who can actually hunt on network data.
① Flows vs events — two data types, one SIEM
A log event is a message a device sends to tell you something happened: a login attempt, a firewall rule hit, a VPN session start. An event has a timestamp, a source and a message. A flow record is different — it describes a network conversation between two endpoints: source IP, destination IP, source port, destination port, protocol (the five-tuple) plus byte count, packet count and duration. The device does not send a flow voluntarily; QRadar's QFlow collector or an external flow exporter (NetFlow, IPFIX, sFlow) produces it.
The practical difference matters for investigation. Events tell you what happened on a device. Flows tell you what moved across the network. A malware beacon may never generate a log event on a misconfigured firewall, but it always generates a flow — same destination IP, same small byte count, same interval, every hour. QRadar correlates both in the same offense, so you need to read both tabs: Log Activity (events) and Network Activity (flows).
In an investigation, never look only at Log Activity. Open Network Activity too — flows often reveal lateral movement, data exfiltration or beaconing that generates zero log events, especially when firewalls only log denied traffic.
A firewall is misconfigured and generates no log events for outbound connections. Which QRadar data source can still detect a malware beacon to an external IP?
② The QFlow collector — from raw packets to flow records
The QFlow collector is the component that sits on a network tap or SPAN port, captures packets, assembles them into conversations and emits a normalised flow record to QRadar. It understands many flow export formats — NetFlow v5/v9, IPFIX, sFlow, J-Flow — so you can also point external routers and switches at it instead of needing a packet tap everywhere.
Superflows — handling high-volume traffic
In busy environments a single conversation can produce thousands of individual flow records per second. To keep storage manageable, QRadar creates superflows: aggregated bundles that roll up many similar flows into one record, preserving the key metrics (total bytes, packets, duration, ports) but not storing each conversation individually. You will see a superflow flag in the Network Activity tab. Superflows are normal — they mean the collector is healthy and managing volume correctly. The QFlow process also uses multi-threaded processing so it can keep up with high-throughput links.
Captures packets from a SPAN port or tap (or accepts NetFlow/IPFIX/sFlow) and emits normalised five-tuple flow records with byte and packet counts into QRadar.
A DPI appliance or VM that produces content flows with application-layer artifacts — TLS certs, DNS names, JA4 fingerprints, file hashes — in addition to standard flow metadata.
An aggregated flow record created by QRadar to bundle many similar conversations in high-volume traffic into one record, preserving key metrics without storing every individual flow.
The process by which QRadar uses incoming flow and event data to passively build a behaviour profile for each IP — open ports, applications, users, typical volume — without active scanning.
What is a QRadar superflow?
③ QRadar Network Insights (QNI) — application-layer visibility
QRadar Network Insights (QNI) is a dedicated appliance or virtual machine that performs deep packet inspection (DPI) and sends enriched content flows to QRadar alongside the standard flow records. Where a plain flow record only tells you '10.1.1.5 talked to 52.23.4.1 on port 443 for 30 seconds and sent 120 KB', a QNI content flow also extracts: the TLS certificate subject and issuer, the JA4 TLS fingerprint (supported in QRadar 7.5+), HTTP Host headers, DNS query names, User-Agent strings, and file hashes from transferred files.
QNI operates at two inspection levels. At Enriched level it adds metadata fields to flows. At Advanced level it also produces full content flows with extracted artifacts stored as QNI content flow records visible in the Network Activity tab. You enable the QNI flow source from the QRadar console; it is disabled by default. QNI also supports decoding ERSPAN-encapsulated traffic (from remote or cloud-based taps), extending visibility into hybrid environments.
The interview-critical point: QNI does not replace the correlation engine. It produces richer flow data that the Sense Analytics engine and your custom rules can act on — detecting beaconing, DNS tunnelling, certificate anomalies and data exfiltration that pure log analysis would miss.
QNI ships with its flow source disabled. If you deploy a QNI appliance and see no content flows in Network Activity, do not assume QNI is broken — check Admin ▸ Data Sources ▸ Flow Sources first and enable the source.
▶ Watch a suspicious beacon get caught by QNI
A compromised workstation calls home every hour. Press Play for the detection path, then Break it to see the classic gap.
An analyst suspects DNS tunnelling but sees only normal-looking DNS query events in Log Activity. Which QNI artifact should they pivot to?
④ Asset enrichment — how flows build the IP profile
Every flow that QRadar processes is also used to update the asset database. When QRadar sees a new source IP, it creates an asset record. As flows arrive, the asset accumulates: which ports it listens on, which protocols it uses, what applications it runs (from QNI DPI), which users are associated with it (from event correlation) and its typical traffic volume. This is passive asset discovery — no active scanning needed.
The enriched asset profile is what makes QRadar rules more precise. A rule like 'outbound connection to a known bad IP from an internal host' is much stronger when the asset profile confirms that host is a developer workstation (high risk) rather than an automated build server (expected external calls). QNI artifacts — certificate subjects, DNS names, observed applications — flow directly into the asset profile so analysts see the full picture without pivoting between tools.
Deploy and tune
Enable QNI flow sources from Admin ▸ Data Sources ▸ Flow Sources, set inspection level to Enriched or Advanced, and confirm the flow source appears in Network Activity. For large environments, scale QNI capacity with additional appliances (QNI 6500 or virtual equivalents). If flows are not appearing after adding a new QNI, check that the flow source is enabled — it ships disabled by default.
Arjun at a Mumbai fintech firm faces this
Arjun's SOC detects unusual data transfer volumes to an external IP late at night, but the perimeter firewall shows no blocked events and the SIEM offense queue is empty.
The firewall is logging only denied connections; allowed outbound traffic generates no log events. There are no flow-based correlation rules enabled on QRadar.
Open Network Activity tab, filter by the suspicious external IP and time range — large outbound byte counts appear in flow records even though Log Activity is silent. The asset profile for the internal host shows this behaviour is new.
QRadar console ▸ Network Activity ▸ filter dst IP + time window ▸ asset profile of src IPEnable flow-based correlation rules (e.g. 'Excessive outbound data transfer') and confirm the QNI flow source is set to Enriched inspection so application context is captured. Add a building block that flags first-seen external IPs for an asset.
Re-test with a simulated large upload: a flow offense fires within minutes and the QNI content flow shows the destination domain and transferred volume, giving Arjun the evidence to escalate.
After enabling QNI, open an asset profile for an active internal IP (Assets ▸ select host). If QNI is feeding data correctly, you will see observed services, application names and, at Advanced inspection level, DNS names and TLS certificate subjects populated automatically — no active scan required.
After enabling QNI on QRadar, flows are not appearing in the Network Activity tab. What is the most likely first thing to check?
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📖 Glossary
- Flow record
- A network conversation record: five-tuple (src/dst IP, src/dst port, protocol) plus byte count, packet count, start and end time. Produced by the QFlow collector from raw packets or NetFlow/IPFIX exports.
- QFlow collector
- The QRadar component that captures packets from a SPAN port or tap (or accepts NetFlow/IPFIX/sFlow) and emits normalised flow records to QRadar.
- Superflow
- An aggregated flow record that bundles many similar conversations in high-volume traffic into one record, preserving total byte/packet counts. Normal and expected in busy environments.
- QRadar Network Insights (QNI)
- A DPI appliance or VM that produces content flows enriched with application-layer artifacts: JA4 TLS fingerprints, DNS query names, certificate subjects, file hashes and HTTP headers.
- Content flow
- A QNI-enriched flow record containing application-layer artifacts extracted from deep packet inspection, visible in the Network Activity tab at Enriched or Advanced inspection level.
- JA4 fingerprint
- A TLS client fingerprint (based on ClientHello fields) supported in QRadar 7.5+ that identifies TLS clients — including known malware families — even when IPs and domains change.
- Passive asset discovery
- The process by which QRadar automatically builds and updates asset profiles (open ports, applications, users, traffic patterns) from incoming flow and event data without active scanning.
- Five-tuple
- The identifying key of a network flow: source IP, destination IP, source port, destination port and protocol (e.g. TCP/UDP).
📚 Sources
- IBM — QRadar Network Insights overview (QRadar 7.5.0). ibm.com/docs/en/qsip/7.5.0?topic=insights-qradar-network-overview
- IBM Support — Flows and QRadar Network Insights: enhancing visibility into network traffic (Open Mic). ibm.com/support/pages/lets-talk-about-how-flows-and-qradar-network-insights-can-enhance-visibility-your-network-traffic-open-mic
- IBM — What's new in QRadar 7.5.0 — JA4 TLS fingerprinting, multi-threaded QFlow, ERSPAN support. ibm.com/docs/en/qsip/7.5.0?topic=users-whats-new-in-qradar-750
- IBM Support — QRadar Network Insights: how to view QNI content flows from the Network Activity tab. ibm.com/support/pages/qradar-network-insights-how-view-qni-content-flows-network-activity-tab
- IBM Support — QRadar QNI — NPCAP — QIForensics deployment explanation. ibm.com/support/pages/qradar-qni-npcap-qiforensics-deployment-explanation
- IBM — IBM QRadar Fundamentals of Flows (Open Mic presentation). ibm.com/support/pages/sites/default/files/inline-files/$FILE/Open%20Mic%20-%20QRadar%20Fundamentals%20of%20Flows.pdf
What's next?
Understand flows? Next, go deep on QRadar offenses — how the correlation engine assembles events, flows and anomalies into a single scored offense and what makes a good offense-closing workflow.