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analyzing-network-traffic-with-wireshark

'Captures and analyzes network packet data using Wireshark and tshark

Install / Use

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-traffic-with-wireshark

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

95/100

Category

Security

Supported Platforms

Zed

Our assessment of analyzing-network-traffic-with-wireshark

analyzing-network-traffic-with-wireshark scores 95/100 on our quality scale, 129th of 544 Security skills we index (top 24%).

Its SKILL.md is 10 KB long, well organised into 47 sections with 7 code examples: a thorough specification that gives an agent plenty to work with.

With 33,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
12/15
Adoption
19/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 25 days ago, so analyzing-network-traffic-with-wireshark is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

analyzing-network-traffic-with-wireshark compared with similar skills

All 4 of these similar skills score higher than analyzing-network-traffic-with-wireshark; compare them before choosing.

SkillScoreStarsUpdatedFormat
analyzing-network-traffic-with-wireshark (this skill)by mukul9759533.3k25d agoSKILL.md
algorithmic-artby anthropics100177.9k3d agoSKILL.md
pptxby anthropics100177.9k3d agoSKILL.md
designby nextlevelbuilder100130.2k4d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k4d agoSKILL.md

Frequently asked questions

How do I install analyzing-network-traffic-with-wireshark?
Run npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-traffic-with-wireshark. The install tabs above show the steps for each supported agent.
Which AI agents does analyzing-network-traffic-with-wireshark work with?
It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
Is analyzing-network-traffic-with-wireshark safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is analyzing-network-traffic-with-wireshark still maintained?
The repository was last updated 25 days ago, so analyzing-network-traffic-with-wireshark is actively maintained.

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:

# 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

# 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

# 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

# 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

# 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

# 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

| Term | Definition | |------|------------| | Capture Filter (BPF) | Berkeley Packet Filter syntax applied at capture time to limit which packets are recorded, reducing file size and improving performance | | Display Filter | Wireshark-specific filter syntax applied to already-captured packets for focused analysis without altering the capture file | | PCAPNG | Next-generation packet capture format supporting multiple interfaces, name resolution, annotations, and metadata in a single file | | TCP Stream | Reassembled sequence of TCP segments representing a complete bidirectional conversation between two endpoints | | Protocol Dissector | Wireshark module that decodes a specific protocol's fields and structure, enabling deep inspection of packet contents | | IO Graph | Time-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

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

Related Skills

View on GitHub
GitHub Stars33.3k
CategorySecurity
Updated25d ago
Forks4.0k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions