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Use Scapy, a Python library for working with network packets, to inspect saved captures or authorized live traffic. Summarize protocols and connections, identify suspicious patterns, craft test packets, and export findings as structured JSON reports.

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• Investigating saved network captures
• Summarizing traffic volumes, protocols, and connection endpoints
• Checking for SYN floods and DNS data leakage indicators

Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and traffic anomaly detection in authorized security testing

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Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and traffic anomaly detection in authorized security testing

中文简介正在准备中。当前显示原文说明。

Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and traffic anomaly detection in authorized security testing

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Capture and analyze network traffic to understand custom protocols, including message boundaries and field meanings. Use the findings to document formats, investigate communication problems, and validate behavior through replay and tests with unusual inputs.

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• Investigating network communication failures
• Understanding proprietary message formats
• Documenting protocol specifications

PCAP/network capture analizi — Wireshark, tshark, Python scapy/pyshark ile SMTP/FTP/DNS/custom protokol çözme, gizli veri çıkarma.

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Analyze Modbus industrial network traffic to identify unauthorized commands, write operations, and unusual polling intervals. Compare activity with normal traffic patterns and allowed operations, then report anomalies by type and severity.

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• Investigating suspicious Modbus traffic
• Establishing normal polling patterns
• Defining allowed Modbus function codes

Monitor Modbus traffic in industrial control networks to identify unauthorized writes, unusual commands, and departures from normal communication. Use packet analysis and intrusion detection rules to investigate suspected controller changes and produce reports with recommended actions.

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• Investigating unauthorized changes to PLC registers
• Setting up Modbus intrusion detection rules
• Checking communication patterns after a suspected compromise

Monitor local network traffic for ARP spoofing, where false address mappings can redirect traffic. Use ARPWatch, Wireshark, switch inspection settings, and Python monitoring to flag address changes, duplicate IP claims, gateway impersonation, and unusual ARP volumes.

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• Investigating suspected interception on a local network
• Monitoring changes in IP-to-MAC address mappings
• Checking duplicate IP claims and gateway impersonation

Inspect DNP3 traffic, a communication protocol used in industrial control systems, for unauthorized sources and unexpected commands. The skill compares captured traffic with normal patterns and reports suspicious control actions, restarts, and file operations.

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• Investigating suspicious DNP3 control commands
• Checking substation traffic against normal patterns
• Preparing DNP3 intrusion detection rules

Develop attack detection for SCADA systems that monitor and control industrial equipment. Compare network traffic and process measurements with normal behavior to identify unauthorized commands, altered sensor data, communication disruption, and indicators of known industrial malware.

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• Introducing intrusion detection in a SCADA environment
• Investigating suspected attacks on industrial control systems
• Creating detection rules for industrial protocol abuse

Analyze malware network captures to investigate command-and-control traffic, data theft, and downloaded files. Use packet analysis tools to identify suspicious destinations and recurring connections, extract artifacts, and create detection rules from observed patterns.

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• Analyzing malware sandbox network captures
• Investigating command-and-control traffic
• Tracing data theft and file downloads

Examine captured network traffic for hidden malware communications in DNS, ICMP, and HTTP. Analyze domain patterns, packet sizes, and traffic frequency to identify suspicious channels used for remote control or data theft.

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• Investigating suspicious DNS, ICMP, or HTTP traffic
• Hunting for hidden malware control channels in packet captures
• Assessing possible data theft through unusual network traffic

Use when analyzing pcap or pcapng files, triaging network captures, labeling IPs with evidence, generating PNG charts, or writing packet analysis reports. Keywords: pcap, pcapng, tshark, Wireshark, scapy, DNS, TLS SNI, RDAP, graph, matplotlib, gnuplot, packet capture.

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