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analyzing-network-flow-data-with-netflow

analyzing-network-flow-data-with-netflow

github.com/mukul975Security35.2k374 installsUpdated 8w ago
Repository

About analyzing-network-flow-data-with-netflow

A NetFlow analysis skill guide for SOC analysts. It describes collecting and parsing flow data to look for scanning, exfiltration, C2 beaconing, and traffic anomalies.

Key features

  1. 01Collect NetFlow/IPFIX data
  2. 02Parse NetFlow packets
  3. 03Detect port-scanning patterns
  4. 04Look for exfiltration and C2 beaconing
  5. 05Generate prioritized analysis reports

Use cases

  1. 01Investigate network security incidents
  2. 02Hunt for suspicious traffic patterns
  3. 03Validate security monitoring coverage

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-network-flow-data-with-netflow

After installing, type/analyzing-network-flow-data-with-netflowin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

LICENSE
references/
api-reference.md
scripts/
agent.py

Details

From the project README

Analyzing Network Flow Data with Netflow

When to Use

  • When investigating security incidents that require analyzing network flow data with netflow
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • Familiarity with network security concepts and tools
  • Access to a test or lab environment for safe execution
  • Python 3.8+ with required dependencies installed
  • Appropriate authorization for any testing activities

Instructions

  1. Install dependencies: pip install netflow
  2. Collect NetFlow/IPFIX data from routers or use the built-in collector: python -m netflow.collector -p 9995
  3. Parse captured flow data using netflow.parse_packet().
  4. Analyze flows for:
    • Port scanning: single source to many destinations on same port
    • Data exfiltration: high byte-count outbound flows to unusual destinations
    • C2 beaconing: periodic connections with consistent intervals
    • Volumetric anomalies: traffic spikes beyond baseline thresholds
  5. Generate a prioritized findings report.
python scripts/agent.py --flow-file captured_flows.json --output netflow_report.json

Examples

Parse NetFlow v9 Packet
import netflow
data, _ = netflow.parse_packet(raw_bytes, templates={})
for flow in data.flows:
    print(flow.IPV4_SRC_ADDR, flow.IPV4_DST_ADDR, flow.IN_BYTES)

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