How do I install the Analyzing Network Flow Data With Netflow skill?

Run npx skillmds add thedixitjain/analyzing-network-flow-data-with-netflow in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Analyzing Network Flow Data With Netflow safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Analyzing Network Flow Data With Netflow?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Analyzing Network Flow Data With Netflow free to use?

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Who published Analyzing Network Flow Data With Netflow?

thedixitjain (@thedixitjain) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Analyzing Network Flow Data With Netflow by thedixitjain

Name: Analyzing Network Flow Data With Netflow
Rating: 4.2 (5 reviews)
Author: thedixitjain

Analyzing Network Flow Data With Netflow

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

thedixitjain a746280 4 files · 22.4 KB Updated Sep 9, 2026 2 repo stars

File contents

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

Install dependencies: pip install netflow
Collect NetFlow/IPFIX data from routers or use the built-in collector: python -m netflow.collector -p 9995
Parse captured flow data using netflow.parse_packet().
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
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)

Source: mukul975/Anthropic-Cybersecurity-Skills → skills/analyzing-network-flow-data-with-netflow/SKILL.md

---name: analyzing-network-flow-data-with-netflowdescription: Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.--- # 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. ```bash python scripts/agent.py --flow-file captured_flows.json --output netflow_report.json ``` ## Examples ### Parse NetFlow v9 Packet ```python 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) ``` --- **Source:** [`mukul975/Anthropic-Cybersecurity-Skills`](https://github.com/mukul975/Anthropic-Cybersecurity-Skills) → `skills/analyzing-network-flow-data-with-netflow/SKILL.md`

Frequently asked questions