Agent skill

Performing Network Forensics With Wireshark

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Capture and analyze network traffic using Wireshark and tshark to reconstruct network events from PCAP/PCAPNG files, extract transferred files and credentials, and identify command-and-control…

Apache-2.0Auto-check: notesSecurity

Install Performing Network Forensics With Wireshark

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

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-network-forensics-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/performing-network-forensics-with-wireshark .claude/skills/performing-network-forensics-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
performing-network-forensics-with-wireshark
GitHub stars
34k
Token cost
~3k tokens
SKILL.md length
454 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Capture and analyze network traffic using Wireshark and tshark to reconstruct network events from PCAP/PCAPNG files, extract transferred files and credentials, and identify command-and-control…

  • Works in 6 steps: Prepare and Validate the Capture File → Filter and Identify Suspicious Traffic → Extract Files and Objects from Traffic → …
  • Analyzing captured traffic from a security incident
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; calls apt-get, curl and python3; reaches virustotal.com and netresec.com

What it does

Performing Network Forensics With Wireshark is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Capture and analyze network traffic using Wireshark and tshark to reconstruct network events from PCAP/PCAPNG files, extract transferred files and credentials, and identify command-and-control communications. Use when analyzing captured traffic from a security incident, reconstructing data exfiltration, or finding network indicators of compromise during malware analysis.

Its SKILL.md is about 3k 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

  • Analyzing captured traffic from a security incident
  • Reconstructing data exfiltration
  • Finding network indicators of compromise during malware analysis

Example prompts

  • “/performing-network-forensics-with-wireshark”

Requirements

  • Python 3
  • A credential in YOUR_API_KEY

Workflow steps

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

  1. Prepare and Validate the Capture File
  2. Filter and Identify Suspicious Traffic
  3. Extract Files and Objects from Traffic
  4. Reconstruct TCP Streams and Sessions
  5. Use NetworkMiner for Automated Analysis
  6. Generate Network Forensics 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:

    • apt-get
    • curl
    • python3
    • wget

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • virustotal.com
    • netresec.com

    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

Performing Network Forensics With Wireshark loads about 3k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 454 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~104
When it runs · the whole SKILL.md, loaded when a task matches
~3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.4k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteRuns commands with sudoSKILL.md:51
    sudo apt-get install wireshark tshark
  • NoteRuns commands with sudoSKILL.md:200
    sudo apt-get install mono-complete

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). 454 words, ~2,991 tokens.

Download SKILL.mdSave it as .claude/skills/performing-network-forensics-with-wireshark/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
performing-network-forensics-with-wireshark
description
Capture and analyze network traffic using Wireshark and tshark to reconstruct network events from PCAP/PCAPNG files, extract transferred files and credentials, and identify command-and-control communications. Use when analyzing captured traffic from a security incident, reconstructing data exfiltration, or finding network indicators of compromise during malware analysis.
domain
cybersecurity
subdomain
digital-forensics
tags
forensics, network-forensics, wireshark, pcap, packet-analysis, traffic-analysis
version
1.0
author
mahipal
license
Apache-2.0
nist_csf
RS.AN-03, DE.AE-02, RS.MA-01
mitre_attack
T1005, T1074, T1119, T1070, T1059

Performing Network Forensics with Wireshark

When to Use

  • When analyzing captured network traffic (PCAP files) from a security incident
  • For identifying command-and-control (C2) communications in captured traffic
  • When reconstructing data exfiltration activities from packet captures
  • During malware analysis to identify network indicators of compromise
  • For extracting files, credentials, and artifacts transferred over the network

Prerequisites

  • Wireshark or tshark installed for packet analysis
  • PCAP/PCAPNG files from network captures (tcpdump, Wireshark, network TAP)
  • NetworkMiner for automated artifact extraction
  • Sufficient RAM for large capture files (1GB+ PCAPs need 8GB+ RAM)
  • Understanding of TCP/IP, HTTP, DNS, TLS protocols
  • GeoIP databases for IP geolocation

Workflow

Step 1: Prepare and Validate the Capture File
bash
# Install Wireshark and tshark
sudo apt-get install wireshark tshark

# Verify the PCAP file
capinfos /cases/case-2024-001/network/capture.pcap

# Output includes: file type, packet count, capture duration, data size
# Example output:
# File name:           capture.pcap
# File type:           Wireshark/tcpdump/... - pcap
# Number of packets:   1,245,678
# File size:           856 MB
# Data size:           823 MB
# Capture duration:    3600.123456 seconds
# First packet time:   2024-01-15 14:00:00.000000
# Last packet time:    2024-01-15 15:00:00.123456

# Hash the PCAP for integrity
sha256sum /cases/case-2024-001/network/capture.pcap \
   > /cases/case-2024-001/network/pcap_hash.txt

# Get a protocol hierarchy statistics overview
tshark -r /cases/case-2024-001/network/capture.pcap -q -z io,phs
Step 2: Filter and Identify Suspicious Traffic
bash
# Extract conversation statistics
tshark -r /cases/case-2024-001/network/capture.pcap -q -z conv,tcp

# Find top talkers by bytes transferred
tshark -r /cases/case-2024-001/network/capture.pcap -q -z endpoints,ip \
   | sort -t$'\t' -k3 -rn | head -20

# Filter for DNS queries (potential C2 or exfiltration)
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "dns.qr == 0" \
   -T fields -e frame.time -e ip.src -e dns.qry.name \
   > /cases/case-2024-001/analysis/dns_queries.txt

# Find DNS queries to unusual TLDs or long domain names (DNS tunneling)
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "dns.qr == 0 && dns.qry.name matches \"[a-z0-9]{30,}\"" \
   -T fields -e frame.time -e ip.src -e dns.qry.name \
   > /cases/case-2024-001/analysis/suspicious_dns.txt

# Filter HTTP traffic
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "http.request" \
   -T fields -e frame.time -e ip.src -e ip.dst -e http.request.method \
   -e http.host -e http.request.uri -e http.user_agent \
   > /cases/case-2024-001/analysis/http_requests.txt

# Find connections to known malicious ports
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "tcp.dstport == 4444 || tcp.dstport == 8080 || tcp.dstport == 1337 || tcp.dstport == 6667" \
   -T fields -e frame.time -e ip.src -e ip.dst -e tcp.dstport \
   > /cases/case-2024-001/analysis/suspicious_ports.txt

# Detect beaconing patterns (regular interval connections)
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "ip.dst == 185.0.0.1" \
   -T fields -e frame.time_epoch \
   > /tmp/beacon_times.txt
Step 3: Extract Files and Objects from Traffic
bash
# Export HTTP objects (files transferred over HTTP)
tshark -r /cases/case-2024-001/network/capture.pcap \
   --export-objects http,/cases/case-2024-001/analysis/http_objects/

# Export SMB objects
tshark -r /cases/case-2024-001/network/capture.pcap \
   --export-objects smb,/cases/case-2024-001/analysis/smb_objects/

# Export DICOM objects (medical imaging)
tshark -r /cases/case-2024-001/network/capture.pcap \
   --export-objects dicom,/cases/case-2024-001/analysis/dicom_objects/

# Export FTP data transfers
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "ftp-data" \
   -T fields -e ftp-data.data \
   --export-objects ftp-data,/cases/case-2024-001/analysis/ftp_objects/

# Hash all extracted objects
find /cases/case-2024-001/analysis/http_objects/ -type f -exec sha256sum {} \; \
   > /cases/case-2024-001/analysis/extracted_file_hashes.txt

# Check extracted file hashes against VirusTotal
while read hash filepath; do
   echo "Checking $filepath ($hash)"
   curl -s "https://www.virustotal.com/api/v3/files/$hash" \
      -H "x-apikey: YOUR_API_KEY" | python3 -c "
import json,sys
data=json.load(sys.stdin)
if 'data' in data:
   stats=data['data']['attributes']['last_analysis_stats']
   print(f'  Malicious: {stats[\"malicious\"]}, Undetected: {stats[\"undetected\"]}')
else:
   print('  Not found on VT')
"
done < /cases/case-2024-001/analysis/extracted_file_hashes.txt
Step 4: Reconstruct TCP Streams and Sessions
bash
# Follow a specific TCP stream (stream index 42)
tshark -r /cases/case-2024-001/network/capture.pcap \
   -q -z "follow,tcp,ascii,42" \
   > /cases/case-2024-001/analysis/stream_42.txt

# Extract all HTTP request-response pairs for a suspicious host
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "http && ip.addr == 185.0.0.1" \
   -T fields -e frame.time -e http.request.method -e http.host \
   -e http.request.uri -e http.response.code -e http.content_length \
   > /cases/case-2024-001/analysis/suspicious_http.txt

# Extract TLS/SSL certificate information
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "tls.handshake.type == 11" \
   -T fields -e ip.dst -e tls.handshake.certificate \
   > /cases/case-2024-001/analysis/tls_certs.txt

# Extract TLS SNI (Server Name Indication) values
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "tls.handshake.extensions_server_name" \
   -T fields -e frame.time -e ip.src -e ip.dst \
   -e tls.handshake.extensions_server_name \
   > /cases/case-2024-001/analysis/tls_sni.txt

# Extract credentials from unencrypted protocols
tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "ftp.request.command == \"USER\" || ftp.request.command == \"PASS\"" \
   -T fields -e frame.time -e ip.src -e ftp.request.command -e ftp.request.arg

tshark -r /cases/case-2024-001/network/capture.pcap \
   -Y "http.authorization" \
   -T fields -e frame.time -e ip.src -e http.host -e http.authorization
Step 5: Use NetworkMiner for Automated Analysis
bash
# Install NetworkMiner (Mono required on Linux)
sudo apt-get install mono-complete
wget https://www.netresec.com/?download=NetworkMiner -O NetworkMiner.zip
unzip NetworkMiner.zip -d /opt/NetworkMiner/

# Run NetworkMiner
mono /opt/NetworkMiner/NetworkMiner.exe /cases/case-2024-001/network/capture.pcap

# NetworkMiner automatically extracts:
# - Host inventory (OS fingerprinting, open ports)
# - Files transferred over HTTP, FTP, SMB, TFTP
# - Images from web traffic
# - Credentials (plaintext and NTLM hashes)
# - DNS records
# - Session parameters
# - Anomalies and alerts
Step 6: Generate Network Forensics Report
bash
# Compile findings
cat << 'EOF' > /cases/case-2024-001/analysis/network_forensics_report.txt
NETWORK FORENSICS ANALYSIS REPORT
===================================
Case: 2024-001
Capture File: capture.pcap (856 MB, 1,245,678 packets)
Capture Period: 2024-01-15 14:00 to 15:00 UTC
Analyst: [Examiner Name]

TRAFFIC OVERVIEW:
  Total packets: 1,245,678
  Unique source IPs: 45
  Unique destination IPs: 234
  Protocols: TCP (78%), UDP (18%), ICMP (2%), Other (2%)

C2 COMMUNICATION:
  Destination: 185.0.0.1:443
  Beaconing interval: ~60 seconds
  Total connections: 58
  Data transferred: 4.2 MB outbound, 12.3 MB inbound
  TLS SNI: update-service.malware-c2.com

EXFILTRATION:
  Method: HTTPS POST to 185.0.0.1
  Volume: 4.2 MB over 45 minutes
  Files: 3 ZIP archives extracted from HTTP objects

DNS TUNNELING:
  Suspicious queries to: data.evil-dns.com
  Average subdomain length: 45 characters
  Query count: 1,234 (normal baseline: 50)
EOF

Key Concepts

ConceptDescription
PCAP/PCAPNGPacket capture file formats storing raw network traffic
TCP streamComplete bidirectional communication between two endpoints
Deep packet inspectionAnalysis of packet payload content beyond header information
BeaconingRegular-interval callbacks from malware to C2 servers
DNS tunnelingEncoding data within DNS queries for covert exfiltration
TLS/SNIServer Name Indication revealing the target hostname in encrypted connections
Network flowSummary of communication between endpoints (IPs, ports, bytes, duration)
Protocol hierarchyStatistical breakdown of protocols present in a capture

Tools & Systems

ToolPurpose
WiresharkGUI-based packet analyzer with deep protocol dissection
tsharkCommand-line version of Wireshark for scripted analysis
NetworkMinerAutomated network forensic analysis and file extraction
tcpdumpCommand-line packet capture utility
zeek (Bro)Network security monitor generating structured connection logs
ngrepNetwork grep for pattern matching in packet content
capinfosPCAP file statistics and metadata utility
mergecapMerge multiple PCAP files into a single capture
Show full SKILL.md (162 more words)Show less

Common Scenarios

Scenario 1: Malware C2 Communication Analysis Load PCAP in Wireshark, identify beaconing patterns to external IPs, examine TLS certificates for self-signed or unusual issuers, extract HTTP POST data containing encoded commands, correlate C2 IPs with threat intelligence feeds.

Scenario 2: Data Exfiltration Detection Analyze traffic statistics for unusually large outbound transfers, examine DNS query lengths for DNS tunneling indicators, track FTP and HTTP file uploads to external servers, reconstruct exfiltrated files from packet data.

Scenario 3: Lateral Movement in Enterprise Network Filter for SMB, RDP, WMI, and PSExec traffic between internal hosts, identify credential usage patterns across multiple systems, trace the propagation path of the attacker through the network, correlate with Windows Event Log authentication events.

Scenario 4: Web Application Attack Reconstruction Filter HTTP traffic to the web server, identify SQL injection, XSS, and directory traversal attempts, follow the TCP stream of the successful exploit, extract uploaded webshells or payloads, document the attack chain for the incident report.

Output Format

Network Forensics Summary:
  Capture: capture.pcap
  Duration: 1 hour (14:00-15:00 UTC, 2024-01-15)
  Packets: 1,245,678 | Size: 856 MB

  Top Suspicious Connections:
    192.168.1.50 -> 185.0.0.1:443   (C2, 58 connections, 4.2MB out)
    192.168.1.50 -> 10.0.0.25:445   (SMB lateral movement)
    192.168.1.50 -> 10.0.0.30:3389  (RDP lateral movement)

  Extracted Artifacts:
    Files:        23 (3 malicious per VT)
    Credentials:  2 plaintext FTP logins
    DNS Queries:  1,234 suspicious (possible tunneling)
    TLS Certs:    5 self-signed certificates

  IOCs Identified:
    IPs:     185.0.0.1, 203.0.113.50
    Domains: update-service.malware-c2.com, data.evil-dns.com
    Hashes:  3 file hashes flagged as malware

© 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/performing-network-forensics-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

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Works with

Categories

Questions about Performing Network Forensics With Wireshark

What does Performing Network Forensics With Wireshark do?

Capture and analyze network traffic using Wireshark and tshark to reconstruct network events from PCAP/PCAPNG files, extract transferred files and credentials, and identify command-and-control…. Performing Network Forensics With Wireshark is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Capture and analyze network traffic using Wireshark and tshark to reconstruct network events from PCAP/PCAPNG files, extract transferred files and credentials, and identify command-and-control communications.

When should I use Performing Network Forensics With Wireshark?

Performing Network Forensics With Wireshark fits situations like: analyzing captured traffic from a security incident; reconstructing data exfiltration; finding network indicators of compromise during malware analysis.

How do I install Performing Network Forensics With Wireshark in Claude Code?

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

How do I install Performing Network Forensics With Wireshark in Codex?

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

Can I use Performing Network Forensics 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 performing-network-forensics-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/performing-network-forensics-with-wireshark, .gemini/skills/performing-network-forensics-with-wireshark, .github/skills/performing-network-forensics-with-wireshark and .opencode/skills/performing-network-forensics-with-wireshark in your project.

What does Performing Network Forensics With Wireshark need to run?

Going by SKILL.md and its folder, Performing Network Forensics With Wireshark needs Python for the scripts in its folder and the command-line tools its instructions call (apt-get, curl, python3 and wget). Our summary lists: Python 3; A credential in YOUR_API_KEY.

Does Performing Network Forensics With Wireshark access the network?

SKILL.md names 2 domains. In commands or code: virustotal.com and netresec.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Performing Network Forensics With Wireshark safe to install?

Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. 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 Performing Network Forensics With Wireshark use?

Performing Network Forensics 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 Performing Network Forensics With Wireshark use?

About 3k tokens (SKILL.md is roughly 12k 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 408 tokens, read only when the agent opens those files.

What are the alternatives to Performing Network Forensics With Wireshark?

Skills that share tags, products or a category with Performing Network Forensics 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 Performing Network Forensics 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.