Network Traffic Analyzer · Hacking Project

Enable a student to capture, dissect, and analyze network traffic to detect suspicious behavior and produce actionable indicators.

**The problem**
Most organizations lack deep visibility into east-west and north-south network traffic, allowing malicious command-and-control, data exfiltration, and lateral movement to blend into normal flows. SOC analysts frequently drown in raw packet data without the context needed to distinguish benign anomalies from active intrusions. Without a foundational packet/flow analysis capability, defenders cannot baseline "normal" or hunt for deviations.

**What you'll build**
Build a Python-based network traffic analyzer that captures live packets (or ingests PCAPs), parses protocols across L2–L7, extracts flow metadata (5-tuples, JA3/JA4 TLS fingerprints, DNS/HTTP fields), and flags anomalies via rule-based and statistical heuristics. Integrate with Zeek/Suricata for enriched connection logs and export findings to a dashboard or SIEM. The tool provides analysts with searchable, contextualized traffic intelligence rather than raw hex.

**Objective** — Enable a student to capture, dissect, and analyze network traffic to detect suspicious behavior and produce actionable indicators.

**Expected outcome** — A working CLI/dashboard traffic analyzer that ingests live traffic or PCAPs, emits parsed flow records with anomaly flags, and generates an analyst-ready incident summary report.

**Difficulty** — Beginner — foundational networking and Python scripting suffice, though protocol depth can scale to Intermediate.

**Primary category** — SOC / Network Security Monitoring; Secondary = Threat Hunting, DFIR (network forensics)

**Security domains** — Primary = Blue Team; Secondary = Threat Intelligence, Incident Response, Threat Hunting, Digital Forensics, Purple Team

**Technical focus** — Packet capture, protocol dissection, NetFlow/IPFIX analysis, PCAP forensics, TLS/JA3-JA4 fingerprinting, DNS analytics, IDS/IPS integration, anomaly detection, IOC extraction, SIEM enrichment

**Core technologies** — Languages: Python (Scapy, PyShark), some Go optional; Frameworks/Libraries: Scapy, PyShark/dpkt, pandas, matplotlib/Plotly; Security Tools: Wireshark/tshark, Zeek, Suricata, tcpdump; Cloud/Infra: Docker, optional VPC traffic mirroring/ELK stack; AI/Data: pandas/NumPy, optional scikit-learn for anomaly scoring; Databases: SQLite/Elasticsearch for flow storage

**Where it's valued** — Finance, healthcare, telecom, MSSPs/SOCs, government, critical infrastructure, technology

**Careers it builds toward** — SOC Analyst (Tier 1/2), Network Security Analyst, Threat Hunter, Incident Responder, Detection Engineer

**Framework alignment**
• MITRE ATT&CK: Command and Control — Application Layer Protocol (T1071), Non-Standard Port (T1571), DNS (T1071.004); Exfiltration Over C2 Channel (T1041); Discovery — Network Service Discovery (T1046)
• NIST CSF 2.0: Detect (Continuous Monitoring, Adverse Event Analysis), Identify (asset/network mapping), Respond
• OWASP: N/A (network-layer focus; tangential to API Top 10 for HTTP analysis)
• CIS Controls v8: 8 (Audit Log Management), 13 (Network Monitoring and Defense), 12 (Network Infrastructure Management)

**Innovation** — Improved Existing Solution — packet analyzers are well-established, but adding JA3/JA4 fingerprinting, statistical baselining, and SIEM enrichment elevates it above a toy sniffer. Scores: Innovation 5/10, Startup 4/10, Enterprise-Readiness 5/10, Patent = No.