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Agent skill

Analyzing Network Flow Data With Netflow

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns.

Apache-2.0Auto-check passedSecurity

Install Analyzing Network Flow Data With Netflow

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-flow-data-with-netflow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-network-flow-data-with-netflow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyzing-network-flow-data-with-netflow .claude/skills/analyzing-network-flow-data-with-netflow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
analyzing-network-flow-data-with-netflow
GitHub stars
34k
Token cost
~543 tokens
SKILL.md length
159 words
Files
4 (incl. scripts, references)
Skills in repo
637
Repo updated
First seen
Licence
Apache-2.0

At a glance

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns.

  • Works in 5 steps: Install dependencies: pip install netflow → Collect NetFlow/IPFIX data from routers… → Parse captured flow data using… → …
  • Tasks that involve Statistics
  • SKILL.md covers When to Use, Prerequisites, Instructions and Examples
  • Runs Python scripts from its folder; calls python and pip

What it does

Analyzing Network Flow Data With Netflow is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. 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.

Its SKILL.md is about 540 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Statistics. It works with Python. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Statistics

Example prompts

  • “/analyzing-network-flow-data-with-netflow”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  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
  5. Generate a prioritized findings report.

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Analyzing Network Flow Data With Netflow loads about 543 tokens when it runs, and up to ~947 if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 159 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~543
With references · SKILL.md plus every file in references/, read only if the agent opens them
~947

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 159 words, ~543 tokens.

Download SKILL.mdSave it as .claude/skills/analyzing-network-flow-data-with-netflow/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
analyzing-network-flow-data-with-netflow
description
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.
domain
cybersecurity
subdomain
network-security
tags
analyzing, network, flow, data
version
1.0
author
mahipal
license
Apache-2.0
nist_csf
PR.IR-01, DE.CM-01, ID.AM-03, PR.DS-02
mitre_attack
T1071, T1048, T1046, T1095

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)

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/analyzing-network-flow-data-with-netflow of mukul975/Anthropic-Cybersecurity-Skills.

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

Open the folder on GitHubat commit 54a7988

Compare with similar skills

Analyzing Network Flow Data With Netflow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Analyzing Network Flow Data With Netflow compared with similar skills
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Analyzing Network Flow Data With Netflow this skillmukul975/Anthropic-Cybersecurity-Skills34k—~543Automated safety check: PassApache-2.0
StatsmodelszLanqing/codex-claude-academic-skills4.6k16 repos~4.9kAutomated safety check: PassBSD-3-Clause
Fla Ascend Performancefla-org/flash-linear-attention5.8k—~6.3kAutomated safety check: PassMIT
Rota Bench Regression Analysisoracle/graalpython1.7k—~1.6kAutomated safety check: PassCustom licence
Querying Indonesian Gov Datasuryast/indonesia-gov-apis172—~997Automated safety check: PassMIT
MatlabzLanqing/codex-claude-academic-skills4.6k9 repos~2.3kAutomated safety check: NotesGPL-3.0

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Works with

Categories

Questions about Analyzing Network Flow Data With Netflow

What does Analyzing Network Flow Data With Netflow do?

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Analyzing Network Flow Data With Netflow is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns.

When should I use Analyzing Network Flow Data With Netflow?

Analyzing Network Flow Data With Netflow fits situations like: tasks that involve Statistics.

How do I install Analyzing Network Flow Data With Netflow in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-flow-data-with-netflow -a claude-code`. Or copy the skill folder (skills/analyzing-network-flow-data-with-netflow in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/analyzing-network-flow-data-with-netflow in your project. Claude Code loads it when a task matches its description.

How do I install Analyzing Network Flow Data With Netflow in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-flow-data-with-netflow -a codex`. Or copy the skill folder (skills/analyzing-network-flow-data-with-netflow in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/analyzing-network-flow-data-with-netflow in your project. Codex loads it when a task matches its description.

Can I use Analyzing Network Flow Data With Netflow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-flow-data-with-netflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyzing-network-flow-data-with-netflow, .gemini/skills/analyzing-network-flow-data-with-netflow, .github/skills/analyzing-network-flow-data-with-netflow and .opencode/skills/analyzing-network-flow-data-with-netflow in your project.

What does Analyzing Network Flow Data With Netflow need to run?

Going by SKILL.md and its folder, Analyzing Network Flow Data With Netflow needs Python for the scripts in its folder and the command-line tools its instructions call (python and pip). Our summary lists: Python 3.

Does Analyzing Network Flow Data With Netflow access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Analyzing Network Flow Data With Netflow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Analyzing Network Flow Data With Netflow use?

Analyzing Network Flow Data With Netflow is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Analyzing Network Flow Data With Netflow use?

About 543 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 404 tokens, read only when the agent opens those files.

What are the alternatives to Analyzing Network Flow Data With Netflow?

Skills that share tags, products or a category with Analyzing Network Flow Data With Netflow: Statsmodels (zLanqing/codex-claude-academic-skills, 4.6k stars), Fla Ascend Performance (fla-org/flash-linear-attention, 5.8k stars), Rota Bench Regression Analysis (oracle/graalpython, 1.7k stars) and Querying Indonesian Gov Data (suryast/indonesia-gov-apis, 172 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyzing Network Flow Data With Netflow?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,922 GitHub stars. The repository holds 637 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.