analyzing-network-packets-with-scapy

Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and traffic anomaly detection in authorized security testing

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Install Skill

Run in your terminal

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/analyzing-network-packets-with-scapy

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Installation Guide

How to use analyzing-network-packets-with-scapy on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add analyzing-network-packets-with-scapy
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/analyzing-network-packets-with-scapy

Fetches analyzing-network-packets-with-scapy from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/analyzing-network-packets-with-scapy

Restart Cursor to activate analyzing-network-packets-with-scapy. Access via /analyzing-network-packets-with-scapy in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

name
analyzing-network-packets-with-scapy
description
Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and traffic anomaly detection in authorized security testing
domain
cybersecurity
subdomain
network-security
tags
- scapy - packet-analysis - network-forensics - protocol-dissection - pcap - traffic-analysis
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- PR.IR-01 - DE.CM-01 - ID.AM-03 - PR.DS-02

Analyzing Network Packets with Scapy

Overview

Scapy is a Python packet manipulation library that enables crafting, sending, sniffing, and dissecting network packets at granular protocol layers. This skill covers using Scapy for security-relevant tasks including TCP/UDP/ICMP packet crafting, pcap file analysis, protocol field extraction, SYN scan implementation, DNS query analysis, and detecting anomalous traffic patterns such as unusually fragmented packets or malformed headers.

When to Use

  • When investigating security incidents that require analyzing network packets with scapy
  • 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

  • Python 3.8+ with scapy library installed (pip install scapy)
  • Root/administrator privileges for raw socket operations (sniffing, sending)
  • Npcap (Windows) or libpcap (Linux) for packet capture
  • Authorization to perform packet operations on target network

Steps

  1. Read and parse pcap/pcapng files with rdpcap() for offline analysis
  2. Extract protocol layers (IP, TCP, UDP, DNS, HTTP) and field values
  3. Compute traffic statistics: top talkers, protocol distribution, port frequency
  4. Detect SYN flood patterns by analyzing TCP flag ratios
  5. Identify DNS exfiltration indicators via query length and entropy analysis
  6. Craft custom probe packets for authorized network testing
  7. Export findings as structured JSON report

Expected Output

JSON report containing packet statistics, protocol distribution, top source/destination IPs, detected anomalies (SYN floods, DNS tunneling indicators, fragmentation attacks), and per-flow summaries.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Steps

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 5Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use when

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid when

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.471 reviews
  • A
    Anika ReddyDec 24, 2024

    I recommend analyzing-network-packets-with-scapy for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • S
    Shikha MishraDec 16, 2024

    Keeps context tight: analyzing-network-packets-with-scapy is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • H
    Harper AndersonDec 16, 2024

    Keeps context tight: analyzing-network-packets-with-scapy is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • B
    Benjamin JacksonDec 12, 2024

    analyzing-network-packets-with-scapy is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • C
    Chinedu JacksonDec 8, 2024

    Keeps context tight: analyzing-network-packets-with-scapy is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • M
    Maya ParkNov 27, 2024

    analyzing-network-packets-with-scapy has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • A
    Anaya KhanNov 15, 2024

    analyzing-network-packets-with-scapy reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • R
    Rahul SantraNov 7, 2024

    analyzing-network-packets-with-scapy has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • C
    Chinedu JainNov 7, 2024

    analyzing-network-packets-with-scapy has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • A
    Advait ThompsonNov 3, 2024

    Solid pick for teams standardizing on skills: analyzing-network-packets-with-scapy is focused, and the summary matches what you get after install.

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