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
Best use case
performing-network-traffic-analysis-with-tshark is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Automate network traffic analysis using tshark and pyshark for protocol statistics, suspicious flow detection, DNS anomaly identification, and IOC extraction from PCAP files
Teams using performing-network-traffic-analysis-with-tshark should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/performing-network-traffic-analysis-with-tshark/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How performing-network-traffic-analysis-with-tshark Compares
| Feature / Agent | performing-network-traffic-analysis-with-tshark | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Automate network traffic analysis using tshark and pyshark for protocol statistics, suspicious flow detection, DNS anomaly identification, and IOC extraction from PCAP files
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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