Agent skill

Analyzing Network Traffic With Wireshark

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations…

Apache-2.0Auto-check passedSecurity

Install Analyzing Network Traffic With Wireshark

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-traffic-with-wireshark -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-network-traffic-with-wireshark --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-traffic-with-wireshark .claude/skills/analyzing-network-traffic-with-wireshark && 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-traffic-with-wireshark
GitHub stars
34k
Token cost
~2.6k tokens
SKILL.md length
638 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations…

  • Works in 6 steps: Configure Capture Environment → Apply Display Filters for Targeted… → Protocol-Specific Deep Analysis → …
  • Tasks that involve Network security
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Analyzing Network Traffic With Wireshark is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

Its SKILL.md is about 2.6k 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 Network security. It works with Wireshark. 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 Network security

Example prompts

  • “Use the analyzing-network-traffic-with-wireshark skill to capture and analyzes network packet data using Wireshark and tshark to identify malicious…”
  • “/analyzing-network-traffic-with-wireshark”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Configure Capture Environment
  2. Apply Display Filters for Targeted Analysis
  3. Protocol-Specific Deep Analysis
  4. Extract Artifacts and IOCs
  5. Statistical Analysis and Anomaly Detection
  6. Generate Reports and Export Evidence

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.

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

  • Network

    No URLs in SKILL.md.

    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 Traffic With Wireshark loads about 2.6k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 68 tokens; SKILL.md has 638 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.3k

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). 638 words, ~2,594 tokens.

Download SKILL.mdSave it as .claude/skills/analyzing-network-traffic-with-wireshark/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
analyzing-network-traffic-with-wireshark
description
Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.
domain
cybersecurity
subdomain
network-security
tags
network-security, wireshark, packet-analysis, traffic-analysis, pcap
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
T1040, T1071, T1557, T1046

Analyzing Network Traffic with Wireshark

When to Use

  • Investigating suspected network intrusions by examining packet-level evidence of command-and-control traffic, data exfiltration, or lateral movement
  • Diagnosing network performance issues such as retransmissions, fragmentation, or DNS resolution failures
  • Analyzing malware communication patterns by capturing traffic from sandboxed or isolated hosts
  • Validating firewall and IDS rules by confirming what traffic is actually traversing network segments
  • Extracting files, credentials, or indicators of compromise from captured network sessions

Do not use to capture traffic on networks without authorization, to intercept private communications without legal authority, or as a substitute for full-featured SIEM platforms in production monitoring.

Prerequisites

  • Wireshark 4.0+ and tshark command-line utility installed
  • Root/sudo privileges or membership in the wireshark group for live packet capture
  • Network interface access (physical NIC, span port, or network tap) to the monitored segment
  • Sufficient disk space for packet capture files (estimate 1 GB per minute on busy gigabit links)
  • Familiarity with TCP/IP protocols, HTTP, DNS, TLS, and SMB at the packet level

Workflow

Step 1: Configure Capture Environment

Set up the capture interface and filters to target relevant traffic:

bash
# List available interfaces
tshark -D

# Start capture on eth0 with a capture filter to limit scope
tshark -i eth0 -f "host 10.10.5.23 and (port 80 or port 443 or port 445)" -w /tmp/capture.pcapng

# Capture with ring buffer to manage disk usage (10 files, 100MB each)
tshark -i eth0 -b filesize:102400 -b files:10 -w /tmp/rolling_capture.pcapng

# Capture on multiple interfaces simultaneously
tshark -i eth0 -i eth1 -w /tmp/multi_interface.pcapng

For Wireshark GUI, set capture filter in the Capture Options dialog before starting.

Step 2: Apply Display Filters for Targeted Analysis
bash
# Filter HTTP traffic containing suspicious user agents
tshark -r capture.pcapng -Y "http.user_agent contains \"curl\" or http.user_agent contains \"Wget\""

# Find DNS queries to suspicious TLDs
tshark -r capture.pcapng -Y "dns.qry.name contains \".xyz\" or dns.qry.name contains \".top\" or dns.qry.name contains \".tk\""

# Identify TCP retransmissions indicating network issues
tshark -r capture.pcapng -Y "tcp.analysis.retransmission"

# Filter SMB traffic for lateral movement detection
tshark -r capture.pcapng -Y "smb2.cmd == 5 or smb2.cmd == 3" -T fields -e ip.src -e ip.dst -e smb2.filename

# Find cleartext credential transmission
tshark -r capture.pcapng -Y "ftp.request.command == \"PASS\" or http.authbasic"

# Detect beaconing patterns (regular interval connections)
tshark -r capture.pcapng -Y "ip.dst == 203.0.113.50" -T fields -e frame.time_relative -e ip.src -e tcp.dstport
Step 3: Protocol-Specific Deep Analysis
bash
# Follow a TCP stream to reconstruct a conversation
tshark -r capture.pcapng -q -z follow,tcp,ascii,0

# Analyze HTTP request/response pairs
tshark -r capture.pcapng -Y "http" -T fields -e frame.time -e ip.src -e ip.dst -e http.request.method -e http.request.uri -e http.response.code

# Extract DNS query/response statistics
tshark -r capture.pcapng -q -z dns,tree

# Analyze TLS handshakes for weak cipher suites
tshark -r capture.pcapng -Y "tls.handshake.type == 2" -T fields -e ip.src -e ip.dst -e tls.handshake.ciphersuite

# SMB file access enumeration
tshark -r capture.pcapng -Y "smb2" -T fields -e frame.time -e ip.src -e ip.dst -e smb2.filename -e smb2.cmd
Step 4: Extract Artifacts and IOCs
bash
# Export HTTP objects (files transferred over HTTP)
tshark -r capture.pcapng --export-objects http,/tmp/http_objects/

# Export SMB objects (files transferred over SMB)
tshark -r capture.pcapng --export-objects smb,/tmp/smb_objects/

# Extract all unique destination IPs for threat intelligence lookup
tshark -r capture.pcapng -T fields -e ip.dst | sort -u > unique_dest_ips.txt

# Extract SSL/TLS certificate information
tshark -r capture.pcapng -Y "tls.handshake.type == 11" -T fields -e x509sat.uTF8String -e x509ce.dNSName

# Extract all URLs accessed
tshark -r capture.pcapng -Y "http.request" -T fields -e http.host -e http.request.uri | sort -u > urls.txt

# Hash extracted files for IOC matching
find /tmp/http_objects/ -type f -exec sha256sum {} \; > extracted_file_hashes.txt
Step 5: Statistical Analysis and Anomaly Detection
bash
# Protocol hierarchy statistics
tshark -r capture.pcapng -q -z io,phs

# Conversation statistics sorted by bytes
tshark -r capture.pcapng -q -z conv,tcp -z conv,udp

# Identify top talkers
tshark -r capture.pcapng -q -z endpoints,ip

# IO graph data (packets per second)
tshark -r capture.pcapng -q -z io,stat,1,"COUNT(frame) frame"

# Detect port scanning patterns
tshark -r capture.pcapng -Y "tcp.flags.syn == 1 and tcp.flags.ack == 0" -T fields -e ip.src -e tcp.dstport | sort | uniq -c | sort -rn | head -20
Step 6: Generate Reports and Export Evidence
bash
# Export filtered packets to a new PCAP for evidence preservation
tshark -r capture.pcapng -Y "ip.addr == 10.10.5.23 and tcp.port == 4444" -w evidence_c2_traffic.pcapng

# Generate packet summary in CSV format
tshark -r capture.pcapng -T fields -E header=y -E separator=, -e frame.number -e frame.time -e ip.src -e ip.dst -e ip.proto -e tcp.srcport -e tcp.dstport -e frame.len > traffic_summary.csv

# Create PDML (XML) output for programmatic analysis
tshark -r capture.pcapng -T pdml > capture_analysis.xml

# Calculate capture file hash for chain of custody
sha256sum capture.pcapng > capture_hash.txt

Key Concepts

TermDefinition
Capture Filter (BPF)Berkeley Packet Filter syntax applied at capture time to limit which packets are recorded, reducing file size and improving performance
Display FilterWireshark-specific filter syntax applied to already-captured packets for focused analysis without altering the capture file
PCAPNGNext-generation packet capture format supporting multiple interfaces, name resolution, annotations, and metadata in a single file
TCP StreamReassembled sequence of TCP segments representing a complete bidirectional conversation between two endpoints
Protocol DissectorWireshark module that decodes a specific protocol's fields and structure, enabling deep inspection of packet contents
IO GraphTime-series visualization of packet or byte rates over the capture duration, useful for identifying traffic spikes or beaconing

Tools & Systems

  • Wireshark 4.0+: GUI-based packet analyzer with protocol dissectors for 3,000+ protocols, stream reassembly, and export capabilities
  • tshark: Command-line version of Wireshark for headless capture, batch processing, and scripted analysis pipelines
  • tcpdump: Lightweight packet capture tool for quick captures on remote systems without GUI dependencies
  • mergecap: Wireshark utility for combining multiple capture files into a single PCAP for unified analysis
  • editcap: Wireshark utility for splitting, filtering, and converting between capture file formats
Show full SKILL.md (224 more words)Show less

Common Scenarios

Scenario: Investigating Suspected Data Exfiltration via DNS Tunneling

Context: The SOC team detected unusually high DNS query volumes from a workstation (10.10.3.45) to an external domain. The SIEM alert flagged DNS queries averaging 200 per minute compared to the baseline of 15. A packet capture was initiated from the network tap on the workstation's VLAN.

Approach:

  1. Capture traffic from the workstation's subnet using tshark -i eth2 -f "host 10.10.3.45 and port 53" -w dns_exfil_investigation.pcapng
  2. Analyze DNS query patterns: tshark -r dns_exfil_investigation.pcapng -Y "dns.qry.name contains \"suspect-domain.xyz\"" -T fields -e frame.time -e dns.qry.name
  3. Examine subdomain labels for encoded data (long base64-like subdomains indicate tunneling): tshark -r dns_exfil_investigation.pcapng -Y "dns.qry.type == 16" -T fields -e dns.qry.name -e dns.txt
  4. Calculate data volume by summing query name lengths to estimate exfiltration bandwidth
  5. Extract unique query names and decode base64 subdomains to recover exfiltrated content
  6. Export evidence packets to a separate PCAP and generate SHA-256 hash for chain of custody

Pitfalls:

  • Capturing unfiltered traffic on a busy network and running out of disk space before collecting relevant data
  • Using display filters instead of capture filters, resulting in massive files that are slow to process
  • Overlooking encrypted DNS (DoH/DoT) traffic that bypasses traditional DNS capture on port 53
  • Failing to establish packet capture hash and chain of custody documentation for forensic evidence

Output Format

## Traffic Analysis Report

**Case ID**: IR-2024-0847
**Capture File**: dns_exfil_investigation.pcapng
**SHA-256**: a3f2b8c1d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1
**Duration**: 2024-03-15 14:00:00 to 14:45:00 UTC
**Source Interface**: eth2 (VLAN 30 span port)

### Findings

**1. DNS Tunneling Confirmed**
- Source: 10.10.3.45
- Destination DNS: 8.8.8.8 (forwarded to ns1.suspect-domain.xyz)
- Query volume: 9,247 queries in 45 minutes (205/min vs 15/min baseline)
- Average subdomain label length: 63 characters (base64-encoded data)
- Estimated data exfiltrated: ~2.3 MB via TXT record responses

**2. Indicators of Compromise**
- Domain: suspect-domain.xyz (registered 3 days prior)
- Nameserver: ns1.suspect-domain.xyz (203.0.113.50)
- Query pattern: TXT record requests with base64-encoded subdomains
- Response pattern: TXT records containing base64-encoded payloads

© 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-traffic-with-wireshark 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 Traffic With Wireshark 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 Traffic With Wireshark compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Analyzing Network Traffic With Wireshark this skillmukul975/Anthropic-Cybersecurity-Skills34k—~2.6kAutomated safety check: PassApache-2.0
Wireshark Analysiszebbern/claude-code-guide4.7k8 repos~3kAutomated safety check: PassMIT
IotnetBrownFineSecurity/iothackbot8591 repos~1kAutomated safety check: NotesMIT
Netzhinkgit/embeddedskills734—~1.1kAutomated safety check: PassMIT
Network Packet Labmingchen666/Reviva244—~657Automated safety check: PassNone
Traffic Analysis Pcapyaklang/hack-skills2.4k—~2.8kAutomated safety check: NotesMIT

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Works with

Categories

Questions about Analyzing Network Traffic With Wireshark

What does Analyzing Network Traffic With Wireshark do?

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations…. Analyzing Network Traffic With Wireshark is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

When should I use Analyzing Network Traffic With Wireshark?

Analyzing Network Traffic With Wireshark fits situations like: tasks that involve Network security.

How do I install Analyzing Network Traffic With Wireshark in Claude Code?

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

How do I install Analyzing Network Traffic With Wireshark in Codex?

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

Can I use Analyzing Network Traffic With Wireshark 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-traffic-with-wireshark -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-traffic-with-wireshark, .gemini/skills/analyzing-network-traffic-with-wireshark, .github/skills/analyzing-network-traffic-with-wireshark and .opencode/skills/analyzing-network-traffic-with-wireshark in your project.

What does Analyzing Network Traffic With Wireshark need to run?

Going by SKILL.md and its folder, Analyzing Network Traffic With Wireshark needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Analyzing Network Traffic With Wireshark access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Analyzing Network Traffic With Wireshark 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 Traffic With Wireshark use?

Analyzing Network Traffic With Wireshark 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 Traffic With Wireshark use?

About 2.6k tokens (SKILL.md is roughly 10k 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 743 tokens, read only when the agent opens those files.

What are the alternatives to Analyzing Network Traffic With Wireshark?

Skills that share tags, products or a category with Analyzing Network Traffic With Wireshark: Wireshark Analysis (zebbern/claude-code-guide, 4.7k stars), Iotnet (BrownFineSecurity/iothackbot, 859 stars), Net (zhinkgit/embeddedskills, 734 stars) and Network Packet Lab (mingchen666/Reviva, 244 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyzing Network Traffic With Wireshark?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 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.