pcap-analysis

To analyze PCAP files for network intrusions, you load packet captures and run built-in detectors to identify port scans, DoS patterns, and beaconing using calibrated thresholds. This extracts traffic statistics and IP/TCP/UDP protocol distributions to flag anomalous network behavior.

Yes, you can use Python with Scapy to extract network statistics from a PCAP file. Validated utilities load packets, filter traffic into IP/TCP/UDP/ICMP/ARP streams, and compute graph metrics and inter-arrival time statistics for targeted network analysis.

The best way to compute graph metrics and flow summaries from packet captures is using dedicated Python utilities that calculate unique-source/destination degrees and bidirectional flow counts. This characterizes network topology and provides per-flow summaries for performance analysis.

Yes, this network analysis approach supports splitting traffic by protocol for targeted security monitoring. It loads PCAPs and separates traffic into distinct IP, TCP, UDP, ICMP, and ARP streams, allowing analysts to verify anomalous traffic patterns against established baselines.

Inter-arrival time statistics help with anomaly detection in enterprise network traffic by characterizing communication timing patterns. Computing IAT statistics alongside graph metrics allows security analysts to detect beaconing and verify whether a PCAP contains anomalous traffic by comparing results to baselines.