Skip to content
All Skills

Performing Network Traffic Analysis With Tshark

Automate network traffic analysis using tshark and pyshark for protocol statistics, suspicious flow detection, DNS anomaly identification, and IOC extraction from PCAP files

Security & Compliance|v1|Updated 7/14/2026|GitHub source
MCP get_skill({ skillId: "performing-network-traffic-analysis-with-tshark-a2e07a60" })

Use this skill with your agent

Create a free account and connect via MCP

Get Started Free
# Performing Network Traffic Analysis with TShark

## Overview

This skill automates packet capture analysis using tshark (Wireshark CLI) and pyshark (Python wrapper). It extracts protocol distribution statistics, identifies suspicious network flows (port scans, beaconing, data exfiltration), extracts IOCs (IPs, domains, URLs), and detects DNS tunneling patterns from PCAP files.


## When to Use

- When conducting security assessments that involve performing network traffic analysis with tshark
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing

## Prerequisites

- tshark (Wireshark CLI) installed and in PATH
- Python 3.8+ with pyshark library
- PCAP or PCAPNG capture file for analysis

## Steps

1. **Extract Protocol Statistics** — Generate protocol hierarchy and conversation statistics from the capture
2. **Identify Top Talkers** — Rank source/destination IPs by volume and connection count
3. **Detect Suspicious Flows** — Flag port scanning patterns, unusual port usage, and high-frequency connections
4. **Extract Network IOCs** — Pull unique IPs, domains from DNS queries, and URLs from HTTP traffic
5. **Analyze DNS Traffic** — Detect DNS tunneling via high-entropy subdomain queries and excessive TXT records
6. **Generate Analysis Report** — Produce structured report with flow summaries and threat indicators

## Expected Output

- JSON report with protocol statistics and top talkers
- Suspicious flow detections with severity ratings
- Extracted IOCs (IPs, domains, URLs)
- DNS anomaly analysis results
#mukul-cybersecurity-skills#security#cybersecurity#networkpythontsharkpyshark

Related Skills

More skills in Security & Compliance

1password

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.

#broad-capability#developmentMIT

1password

Set up and use 1Password CLI for sign-in, desktop integration, and reading or injecting secrets.

#identity#accessMIT

Accessibility Lead

Accessibility team lead and orchestrator. Use proactively on EVERY task that involves web UI code, HTML, JSX, CSS, React components, web pages, server-side templates (.leaf, .ejs, .erb, .hbs), or any user-facing web content. This agent coordinates the accessibility specialist team and ensures no accessibility requirement is missed. Runs the final review before any UI code is considered complete. Applies to any web framework, server-side templating framework (Vapor/Leaf, Rails/ERB, Django/Jinja, Express/EJS), or vanilla HTML/CSS/JS. Works alongside other team leads (e.g., swift-lead) in multi-language projects.

#broad-capability#accessibilityMIT

Accessibility Regression Detector

Detects accessibility regressions by comparing audit results across commits/branches. Tracks score trends, identifies new issues, and validates previous fixes remain in place.

#broad-capability#accessibilityMIT

Accessibility Statement

Generates conformance/accessibility statements following W3C or EU model templates. Takes audit results as input, maps to conformance claims, identifies known limitations, and outputs a deployable HTML page or markdown document.

#broad-capability#accessibilityMIT

Accessibility Tool Builder

Expert in building accessibility scanning tools, rule engines, document parsers, report generators, and audit automation. WCAG criterion mapping, severity scoring, CLI/GUI scanner architecture, CI/CD integration.

#broad-capability#accessibilityMIT