Agent skill
packet-capture
Expert skill for packet capture and analysis using libpcap/Wireshark. Execute tcpdump/tshark commands, write BPF filter expressions, analyze pcap files, decode protocol layers, calculate statistics, and generate Wireshark dissectors.
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/network-programming/skills/packet-capture
Metadata
Additional technical details for this skill
- author
- babysitter-sdk
- version
- 1.0.0
- category
- network-analysis
- backlog id
- SK-003
SKILL.md
packet-capture
You are packet-capture - a specialized skill for network packet capture and analysis, providing expert capabilities with libpcap, tcpdump, tshark, and Wireshark for deep network traffic inspection.
Overview
This skill enables AI-powered packet capture and analysis including:
- Executing tcpdump/tshark commands and interpreting output
- Writing and validating BPF filter expressions
- Analyzing pcap/pcapng files
- Decoding protocol layers (Ethernet, IP, TCP, UDP, application)
- Calculating packet statistics and flow analysis
- Generating Wireshark dissectors
- Creating custom capture filters
Prerequisites
tcpdumportsharkinstalled- Root/admin privileges for live capture
- Optional: Wireshark for GUI analysis
- Optional: Python with scapy for programmatic analysis
Capabilities
1. Live Packet Capture
Capture network traffic with tcpdump and tshark:
# Basic capture on interface
tcpdump -i eth0 -nn
# Capture with timestamp precision
tcpdump -i eth0 -nn -tttt
# Capture to file
tcpdump -i eth0 -w capture.pcap
# Capture with rotation (100MB files, keep 10)
tcpdump -i eth0 -w capture_%Y%m%d_%H%M%S.pcap -C 100 -W 10
# Capture specific traffic
tcpdump -i eth0 -nn 'port 80 or port 443'
# tshark capture with display filter
tshark -i eth0 -Y 'http.request.method == "GET"'
# tshark capture specific fields
tshark -i eth0 -T fields \
-e frame.time \
-e ip.src \
-e ip.dst \
-e tcp.port \
-e http.host
2. BPF Filter Expressions
Write efficient Berkeley Packet Filter expressions:
# Host filters
tcpdump host 192.168.1.100
tcpdump src host 192.168.1.100
tcpdump dst host 192.168.1.100
# Network filters
tcpdump net 192.168.1.0/24
tcpdump src net 10.0.0.0/8
# Port filters
tcpdump port 80
tcpdump src port 443
tcpdump portrange 8000-8100
# Protocol filters
tcpdump tcp
tcpdump udp
tcpdump icmp
tcpdump 'ip proto 47' # GRE
# Combining filters
tcpdump 'host 192.168.1.100 and port 80'
tcpdump 'src host 192.168.1.100 or dst host 192.168.1.100'
tcpdump 'tcp and (port 80 or port 443)'
tcpdump 'not port 22' # Exclude SSH
# TCP flag filters
tcpdump 'tcp[tcpflags] & (tcp-syn|tcp-fin) != 0'
tcpdump 'tcp[tcpflags] & tcp-syn != 0' # SYN packets
tcpdump 'tcp[tcpflags] & tcp-rst != 0' # RST packets
# Payload filters
tcpdump 'tcp[((tcp[12:1] & 0xf0) >> 2):4] = 0x47455420' # HTTP GET
tcpdump 'tcp[((tcp[12:1] & 0xf0) >> 2):4] = 0x504f5354' # HTTP POST
# VLAN filters
tcpdump 'vlan 100'
tcpdump 'vlan and host 192.168.1.100'
3. PCAP File Analysis
Analyze captured packet files:
# Read pcap file
tcpdump -r capture.pcap -nn
# Count packets
tcpdump -r capture.pcap | wc -l
# Extract specific fields with tshark
tshark -r capture.pcap -T fields \
-e frame.number \
-e frame.time_relative \
-e ip.src \
-e ip.dst \
-e tcp.stream \
-e http.request.uri
# Protocol hierarchy statistics
tshark -r capture.pcap -q -z io,phs
# Conversation statistics
tshark -r capture.pcap -q -z conv,tcp
tshark -r capture.pcap -q -z conv,ip
# Endpoint statistics
tshark -r capture.pcap -q -z endpoints,tcp
# HTTP statistics
tshark -r capture.pcap -q -z http,tree
tshark -r capture.pcap -q -z http_req,tree
# Follow TCP stream
tshark -r capture.pcap -q -z follow,tcp,ascii,0
# Export objects (HTTP, SMB, etc.)
tshark -r capture.pcap --export-objects http,./http_exports/
# Time-based statistics
tshark -r capture.pcap -q -z io,stat,1
4. Protocol Layer Decoding
Decode and analyze protocol layers:
from scapy.all import *
def analyze_packet(packet):
"""Analyze packet layers."""
analysis = {}
# Ethernet layer
if Ether in packet:
eth = packet[Ether]
analysis['ethernet'] = {
'src': eth.src,
'dst': eth.dst,
'type': hex(eth.type)
}
# IP layer
if IP in packet:
ip = packet[IP]
analysis['ip'] = {
'version': ip.version,
'ihl': ip.ihl,
'tos': ip.tos,
'len': ip.len,
'id': ip.id,
'flags': str(ip.flags),
'frag': ip.frag,
'ttl': ip.ttl,
'proto': ip.proto,
'src': ip.src,
'dst': ip.dst
}
# TCP layer
if TCP in packet:
tcp = packet[TCP]
analysis['tcp'] = {
'sport': tcp.sport,
'dport': tcp.dport,
'seq': tcp.seq,
'ack': tcp.ack,
'flags': str(tcp.flags),
'window': tcp.window,
'options': [(name, val) for name, val in tcp.options]
}
# UDP layer
if UDP in packet:
udp = packet[UDP]
analysis['udp'] = {
'sport': udp.sport,
'dport': udp.dport,
'len': udp.len
}
# HTTP layer (raw)
if Raw in packet:
payload = packet[Raw].load
if payload.startswith(b'GET ') or payload.startswith(b'POST ') or \
payload.startswith(b'HTTP/'):
analysis['http'] = {
'payload': payload[:500].decode('utf-8', errors='replace')
}
return analysis
def analyze_pcap(filename):
"""Analyze all packets in a pcap file."""
packets = rdpcap(filename)
results = []
for i, pkt in enumerate(packets):
result = {
'number': i + 1,
'time': float(pkt.time),
'length': len(pkt),
'layers': analyze_packet(pkt)
}
results.append(result)
return results
5. Flow Analysis
Analyze network flows and connections:
from collections import defaultdict
from scapy.all import *
def extract_flows(pcap_file):
"""Extract TCP/UDP flows from pcap file."""
packets = rdpcap(pcap_file)
flows = defaultdict(lambda: {
'packets': [],
'bytes': 0,
'start_time': None,
'end_time': None
})
for pkt in packets:
if IP not in pkt:
continue
src_ip = pkt[IP].src
dst_ip = pkt[IP].dst
if TCP in pkt:
src_port = pkt[TCP].sport
dst_port = pkt[TCP].dport
proto = 'tcp'
elif UDP in pkt:
src_port = pkt[UDP].sport
dst_port = pkt[UDP].dport
proto = 'udp'
else:
continue
# Create bidirectional flow key
if (src_ip, src_port) < (dst_ip, dst_port):
flow_key = (src_ip, src_port, dst_ip, dst_port, proto)
else:
flow_key = (dst_ip, dst_port, src_ip, src_port, proto)
flow = flows[flow_key]
flow['packets'].append(pkt)
flow['bytes'] += len(pkt)
pkt_time = float(pkt.time)
if flow['start_time'] is None or pkt_time < flow['start_time']:
flow['start_time'] = pkt_time
if flow['end_time'] is None or pkt_time > flow['end_time']:
flow['end_time'] = pkt_time
return flows
def flow_statistics(flows):
"""Calculate statistics for flows."""
stats = []
for key, flow in flows.items():
src_ip, src_port, dst_ip, dst_port, proto = key
duration = flow['end_time'] - flow['start_time'] if flow['end_time'] != flow['start_time'] else 0.001
stats.append({
'src': f"{src_ip}:{src_port}",
'dst': f"{dst_ip}:{dst_port}",
'protocol': proto,
'packets': len(flow['packets']),
'bytes': flow['bytes'],
'duration': duration,
'bps': flow['bytes'] * 8 / duration,
'pps': len(flow['packets']) / duration
})
return sorted(stats, key=lambda x: x['bytes'], reverse=True)
6. Wireshark Dissector Generation
Generate custom Wireshark dissectors:
-- Custom Protocol Dissector for Lua
-- Save as myprotocol.lua in Wireshark plugins directory
local myproto = Proto("myproto", "My Custom Protocol")
-- Define fields
local f_magic = ProtoField.uint8("myproto.magic", "Magic", base.HEX)
local f_version = ProtoField.uint8("myproto.version", "Version", base.DEC)
local f_type = ProtoField.uint8("myproto.type", "Message Type", base.DEC)
local f_flags = ProtoField.uint8("myproto.flags", "Flags", base.HEX)
local f_length = ProtoField.uint32("myproto.length", "Payload Length", base.DEC)
local f_payload = ProtoField.bytes("myproto.payload", "Payload")
myproto.fields = { f_magic, f_version, f_type, f_flags, f_length, f_payload }
-- Message type names
local type_names = {
[0x01] = "HANDSHAKE",
[0x02] = "DATA",
[0x03] = "ACK",
[0x04] = "ERROR",
[0x05] = "CLOSE"
}
-- Dissector function
function myproto.dissector(buffer, pinfo, tree)
local length = buffer:len()
if length < 8 then return end -- Minimum header size
pinfo.cols.protocol = myproto.name
local subtree = tree:add(myproto, buffer(), "My Protocol Data")
-- Parse header
local magic = buffer(0, 1):uint()
if magic ~= 0xAB then return 0 end -- Not our protocol
subtree:add(f_magic, buffer(0, 1))
subtree:add(f_version, buffer(1, 1))
local msg_type = buffer(2, 1):uint()
local type_item = subtree:add(f_type, buffer(2, 1))
type_item:append_text(" (" .. (type_names[msg_type] or "UNKNOWN") .. ")")
subtree:add(f_flags, buffer(3, 1))
local payload_len = buffer(4, 4):uint()
subtree:add(f_length, buffer(4, 4))
-- Parse payload if present
if payload_len > 0 and length >= 8 + payload_len then
subtree:add(f_payload, buffer(8, payload_len))
end
-- Update info column
pinfo.cols.info = type_names[msg_type] or "Unknown"
return 8 + payload_len
end
-- Register on TCP port
local tcp_port = DissectorTable.get("tcp.port")
tcp_port:add(12345, myproto)
MCP Server Integration
This skill can leverage the following MCP servers for enhanced capabilities:
| Server | Description | Integration |
|---|---|---|
| Wireshark MCP (sarthaksiddha) | Live capture and analysis | AI-powered packet inspection |
| WireMCP | Real-time traffic analysis | Threat detection |
| mcp-wireshark | Wireshark/tshark integration | IDE integration |
| Network Monitor MCP | Security analysis | Real-time monitoring |
Wireshark MCP Server
# Install from npm
npm install -g @sarthaksiddha/wireshark-mcp
# Add to Claude
claude mcp add wireshark -- npx @sarthaksiddha/wireshark-mcp
Capabilities:
- Live traffic capture
- PCAP file analysis
- Protocol statistics
- TCP stream following
- JSON export
Best Practices
- Use capture filters - Reduce capture overhead at kernel level
- Rotate capture files - Prevent disk exhaustion
- Set snap length - Capture only needed bytes with
-s - Use ring buffers - For continuous capture with
-W - Filter early - BPF filters are more efficient than display filters
- Anonymize data - Remove sensitive information before sharing
Process Integration
This skill integrates with the following processes:
packet-capture-analysis.js- Packet capture and analysisprotocol-dissector.js- Protocol dissectionnetwork-traffic-analyzer.js- Traffic pattern analysis
Output Format
When executing operations, provide structured output:
{
"operation": "analyze",
"file": "capture.pcap",
"status": "success",
"summary": {
"packets": 10000,
"bytes": 5242880,
"duration": 60.5,
"avgPacketSize": 524
},
"protocols": {
"tcp": 8500,
"udp": 1200,
"icmp": 300
},
"topTalkers": [
{"ip": "192.168.1.100", "packets": 3000, "bytes": 1500000}
],
"flows": 150,
"artifacts": ["analysis.json", "flows.csv"]
}
Constraints
- Require appropriate permissions for live capture
- Respect privacy and legal requirements
- Limit capture duration and size
- Filter sensitive protocols (credentials, PII)
- Store captures securely
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