Expand 39 api-reference stubs with real tool docs, expand 15 agent.py boilerplate stubs

2026-07-19 14:09:40 +03:00 · 2026-03-19 13:29:33 +01:00
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 Network traffic baselining establishes normal communication patterns by analyzing historical NetFlow/IPFIX data to create statistical profiles of expected behavior. This skill uses Python pandas to compute hourly and daily traffic distributions, per-host byte/packet counts, protocol ratios, and top-N talker profiles. Anomalies are detected using z-score thresholds and IQR (interquartile range) outlier methods, enabling SOC analysts to identify deviations such as data exfiltration spikes, beaconing patterns, and unusual port usage.

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+## When to Use
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+- When deploying or configuring implementing network traffic baselining capabilities in your environment
+- When establishing security controls aligned to compliance requirements
+- When building or improving security architecture for this domain
+- When conducting security assessments that require this implementation
+
 ## Prerequisites

 - NetFlow v5/v9 or IPFIX flow data exported as CSV or JSON