haadi@portfolio:~$ cat wireshark-traffic-analysis.md
Room notes · SOC Level 1 · Network traffic analysis
Wireshark: TrafficAnalysis
Anomaly-based analysis approach Rather than looking for specific known signatures, anomaly detection asks: what looks different from normal?
What This Room Covers
Applying Wireshark to real-world traffic analysis scenarios: identifying anomalies, detecting specific attack signatures, and analyzing malicious traffic patterns.
Key Concepts Learned
This room took significant time: it required connecting all previous Wireshark knowledge under time pressure to find specific evidence in real traffic captures.
Anomaly-based analysis approach Rather than looking for specific known signatures, anomaly detection asks: what looks different from normal? Unusually large DNS queries, HTTP requests with no user agent, periodic connections at exact intervals (C2 beaconing), plaintext credentials in unencrypted protocols: these stand out against a baseline of normal traffic.
C2 traffic signatures in Wireshark
- Regular, periodic connections to the same external host (beacon interval)
- HTTP C2 often uses unusual URI paths, fake User-Agent strings, or encoded data in URL parameters
- DNS C2 uses unusually long domain names or high-frequency queries to unusual domains
- Traffic volume asymmetry: small requests, large responses (data being pulled from victim)
Data exfiltration signatures
- Large outbound transfers to external IPs, especially outside business hours
- DNS queries with unusually long subdomains (DNS tunneling: data encoded in subdomain labels)
- ICMP packets with unusually large payloads (ICMP tunneling)
- HTTP POST requests with large bodies to external endpoints
Real captures = real complexity Real traffic is messy: retransmissions, keep-alives, broadcast traffic, and normal application noise all mix with the malicious activity. The filtering and statistics skills from the previous rooms are essential for cutting through noise.
How This Applies to Real SOC Work
The analysis scenarios in this room mirror exactly what a SOC analyst does when examining network evidence from a security incident. Building this pattern recognition: what normal looks like versus what attack traffic looks like: is one of the most valuable skills developed in this entire module.
Originally published on GitHub
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