analyzing-network-packets-with-scapy
This Claude Code skill teaches packet analysis and manipulation using Scapy, a Python library for crafting, sending, and dissecting network packets across protocol layers. Use it when investigating security incidents, analyzing pcap files for anomalies like SYN floods or DNS exfiltration, extracting protocol fields, implementing network scans, or building threat detection rules that require granular packet-level inspection.
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills /tmp/analyzing-network-packets-with-scapy && cp -r /tmp/analyzing-network-packets-with-scapy/skills/analyzing-network-packets-with-scapy ~/.claude/skills/analyzing-network-packets-with-scapySKILL.md
# Analyzing Network Packets with Scapy ## Overview Scapy is a Python packet manipulation library that enables crafting, sending, sniffing, and dissecting network packets at granular protocol layers. This skill covers using Scapy for security-relevant tasks including TCP/UDP/ICMP packet crafting, pcap file analysis, protocol field extraction, SYN scan implementation, DNS query analysis, and detecting anomalous traffic patterns such as unusually fragmented packets or malformed headers. ## When to Use - When investigating security incidents that require analyzing network packets with scapy - When building detection rules or threat hunting queries for this domain - When SOC analysts need structured procedures for this analysis type - When validating security monitoring coverage for related attack techniques ## Prerequisites - Python 3.8+ with `scapy` library installed (`pip install scapy`) - Root/administrator privileges for raw socket operations (sniffing, sending) - Npcap (Windows) or libpcap (Linux) for packet capture - Authorization to perform packet operations on target network ## Steps 1. Read and parse pcap/pcapng files with `rdpcap()` for offline analysis 2. Extract protocol layers (IP, TCP, UDP, DNS, HTTP) and field values 3. Compute traffic statistics: top talkers, protocol distribution, port frequency 4. Detect SYN flood patterns by analyzing TCP flag ratios 5. Identify DNS exfiltration indicators via query length and entropy analysis 6. Craft custom probe packets for authorized network testing 7. Export findings as structured JSON report ## Expected Output JSON report containing packet statistics, protocol distribution, top source/destination IPs, detected anomalies (SYN floods, DNS tunneling indicators, fragmentation attacks), and per-flow summaries.
Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.
Detect dangerous ACL misconfigurations in Active Directory using ldap3
Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect
Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups' TTPs for detection-gap analysis. Use to compare threat-actor technique coverage, find gaps in detection engineering, or produce Navigator visualizations for threat-intel reporting.
Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query