Analyzing Network Traffic For IncidentsCAUTION

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The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: analyzing-network-traffic-for-incidents
description: 'Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including
  command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek,
  and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation,
  PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

  '
domain: cybersecurity
subdomain: incident-response
tags:
- network-forensics
- PCAP-analysis
- Wireshark
- Zeek
- traffic-analysis
mitre_attack:
- T1071
- T1095
- T1573
- T1572
version: 1.0.0
author: mahipal
license: Apache-2.0
nist_csf:
- RS.MA-01
- RS.MA-02
- RS.AN-03
- RC.RP-01
---

# Analyzing Network Traffic for Incidents

## When to Use

- SIEM alerts on anomalous network traffic patterns requiring deeper investigation
- C2 beaconing is suspected and needs confirmation through packet-level analysis
- Data exfiltration volume or destination must be quantified from network evidence
- Lateral movement between systems needs to be traced through network connections
- An IDS/IPS alert requires packet-level validation to confirm or dismiss

**Do not use** for host-based forensic analysis (process execution, file system artifacts); use endpoint forensics tools instead.

## Prerequisites

- Full packet capture (PCAP) infrastructure or on-demand capture capability (network tap, SPAN port)
- Wireshark installed on the analysis workstation with appropriate display filters knowledge
- Zeek (formerly Bro) deployed for network metadata generation (conn.log, dns.log, http.log, ssl.log)
- NetFlow/IPFIX collection from network devices for traffic flow analysis
- Network architecture diagram showing VLAN layout, firewall placement, and monitoring points
- Threat intelligence feeds for correlating observed network indicators

## Workflow

### Step 1: Capture or Acquire Network Traffic

Obtain the relevant traffic data for the investigation:

**Live Capture (if incident is active):**
```bash
# Capture on specific interface filtering by host
tcpdump -i eth0 -w capture.pcap host 10.1.5.42

# Capture C2 traffic to specific external IP
tcpdump -i eth0 -w c2_traffic.pcap host 185.220.101.42

# Capture with rotation (1GB files, keep 10)
tcpdump -i eth0 -w capture_%Y%m%d%H%M.pcap -C 1000 -W 10
```

**From Existing Infrastructure:**
- Export PCAP from full packet capture appliance (Arkime/Moloch, ExtraHop, Corelight)
- Pull Zeek logs from the Zeek cluster for the investigation timeframe
- Export NetFlow data from network devices for high-level traffic analysis

### Step 2: Identify C2 Communications

Detect command-and-control traffic patterns:

**Beaconing Detection (Zeek conn.log):**
```bash
# Extract connections to external IPs with regular intervals
cat conn.log | zeek-cut ts id.orig_h id.resp_h id.resp_p duration orig_bytes resp_bytes \
  | awk '$4 ~ /^185\.220/' | sort -t. -k1,1n -k2,2n
```

**Wireshark Beacon Analysis:**
```
# Filter for traffic to suspected C2 IP
ip.addr == 185.220.101.42

# Filter HTTPS traffic to non-standard ports
tcp.port != 443 && ssl

# Filter DNS queries for suspicious domains
dns.qry.name contains "evil" or dns.qry.name matches "^[a-z0-9]{32}\."

# Filter HTTP POST (common C2 check-in method)
http.request.method == "POST" && ip.dst == 185.220.101.42
```

Beaconing characteristics to identify:
- Regular time intervals between connections (e.g., every 60 seconds with 10-15% jitter)
- Consistent packet sizes in requests and responses
- HTTPS to external IPs not associated with legitimate CDNs or services
- DNS queries with high entropy subdomains (DNS tunneling indicator)

### Step 3: Analyze Lateral Movement Traffic

Trace adversary movement between internal systems:

```
Key protocols for lateral movement detection:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
SMB (TCP 445):     PsExec, file share access, ransomware propagation
RDP (TCP 3389):    Remote desktop sessions
WinRM (TCP 5985):  PowerShell remoting
WMI (TCP 135):     Remote command execution
SSH (TCP 22):      Linux lateral movement
DCE/RPC (TCP 135): DCOM-based lateral movement
```

**Wireshark Filters for Lateral Movement:**
```
# SMB lateral movement
smb2 && ip.src == 10.1.5.42 && ip.dst != 10.1.5.42

# RDP connections from compromised host
tcp.dstport == 3389 && ip.src == 10.1.5.42

# Kerberos ticket requests (potential pass-the-ticket)
kerberos.msg_type == 12 && ip.src == 10.1.5.42

# NTLM authentication (potential pass-the-hash)
ntlmssp.auth.username && ip.src == 10.1.5.42
```

### Step 4: Detect Data Exfiltration

Identify unauthorized data transfers leaving the network:

```
# Identify large outbound transfers in Zeek conn.log
cat conn.log | zeek-cut ts id.orig_h id.resp_h id.resp_p orig_bytes \
  | awk '$5 > 100000000' | sort -t$'\t' -k5 -rn

# DNS tunneling detection (high volume of TXT queries)
cat dns.log | zeek-cut query qtype | grep TXT | cut -f1 \
  | rev | cut -d. -f1,2 | rev | sort | uniq -c | sort -rn | head

# Unusual protocol usage (ICMP tunneling, DNS over HTTPS)
cat conn.log | zeek-cut proto id.resp_p orig_bytes | awk '$1 == "icmp" && $3 > 1000'
```

**Wireshark Exfiltration Filters:**
```
# Large HTTP POST uploads
http.request.method == "POST" && tcp.len > 10000

# FTP data transfers
ftp-data && ip.src == 10.0.0.0/8

# DNS with large TXT responses (tunneling)
dns.resp.type == 16 && dns.resp.len > 200
```

### Step 5: Extract and Correlate IOCs

Pull network-based indicators from traffic analysis:

- External IP addresses contacted by compromised hosts
- Domains resolved via DNS during the incident timeframe
- URLs accessed via HTTP/HTTPS (if SSL inspection is in place)
- TLS certificate details (subject, issuer, serial number, JA3/JA3S hashes)
- User-Agent strings from HTTP requests
- File transfers captured in PCAP (extract using Wireshark Export Objects)

### Step 6: Document Network Fo

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

What the source does

Filesystem

none-observed

Network

declared (5 observation(s))

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (5)

def generate_incident_report(pcap_path, beacons, lateral, exfil, dns_queries):

"exfiltration_suspects": len(exfil),

"exfiltration": exfil,

print("Beaconing, lateral movement, exfiltration detection")

print("\n--- Beacon Detection ---")

Gates applied: no_behavioural_pass.