Network Activity Forensics - SOC Analyst Cheatsheet

Practical Guide for Network Connection & Usage Investigation


Quick Reference: Network Artifacts Matrix

Artifact
What Reveals
Time Range
Key Data
Live/Dead
Volatility

Network List

Networks connected

Historical

SSIDs, first/last connect

Both

Low

TCP/IP Interfaces

IP addresses

Current + recent

IPs, gateways, DNS

Both

Medium

SRUM

Data usage, apps

30-60 days

Bytes sent/received, per-app

Both

Low


Investigation Priority Matrix

Priority
Artifact
Best For
OS Support
Key Value

CRITICAL

SRUM

Data exfiltration, app usage

Win8+

Bytes sent/received per app

HIGH

Network List

Wi-Fi history, VPN

All Windows

Connection timeline

MEDIUM

TCP/IP Interfaces

Current/recent IPs

All Windows

Active network config


Core Investigation Questions

Primary Questions:

  1. What networks has the device connected to? (Wi-Fi, VPN history)

  2. What is the current/last IP address? (Network configuration)

  3. Which applications used the network heavily? (Data exfiltration)

Secondary Questions:

  1. When were networks first/last used? (Timeline)

  2. How much data was sent/received? (Volume analysis)

  3. Were VPN connections used? (Anonymisation attempts)


SOC Investigation Workflows

Workflow 1: Data Exfiltration Investigation (CRITICAL)

Scenario: Suspected data theft via network transfer

Investigation Priority Order:

Step 1: Analyse SRUM (Network Data Usage) - CRITICAL Why first: Shows bytes sent/received per application (smoking gun for data exfil)

Location:

Required Companion File:

Collection Commands:

PowerShell - Copy SRUM and SOFTWARE:

Using SrumECmd (Zimmerman Tool) - REQUIRED:

Critical SRUM Tables:

1. Network Data Usage Table

2. Application Resource Usage Table

3. Network Connectivity Usage Table

Analysis - Data Exfiltration Detection:

PowerShell - Analyze SRUM CSV (After Parsing):

Red Flags in SRUM:

High Data Upload Indicators:

  • βœ— High upload ratio (sent >> received) β†’ Data exfiltration

  • βœ— Unusual applications with high network usage

  • βœ— Applications from temp directories using network

  • βœ— Non-browser apps with massive uploads

  • βœ— Compression tools (7z, WinRAR) with network usage

  • βœ— Unknown executables with high bandwidth

Typical Patterns:

Normal (High Download, Low Upload):

Suspicious (High Upload):

Data Exfiltration Tools in SRUM:


Step 2: Check Network Connection History Why second: Identifies what networks were used (including VPN)

Registry Location:

PowerShell - Parse Network List:

Network List Forensic Value:

  • Network names (SSIDs)

  • First connection timestamp

  • Last connection timestamp

  • Managed vs. Unmanaged (corporate vs. public)

  • VPN connections appear as network entries

Red Flags in Network List:

  • βœ— VPN connections during incident timeframe

  • βœ— Public/unknown Wi-Fi on corporate device

  • βœ— Personal hotspot connections

  • βœ— Connection timing correlates with exfiltration

  • βœ— New networks appearing during investigation period


Step 3: Identify Current/Recent IP Configuration Why third: Shows IP addresses used

Registry Location:

PowerShell - Enumerate Network Interfaces:

TCP/IP Forensic Value:

  • Current and historical IP addresses

  • DHCP vs. static configuration

  • Default gateway (router)

  • DNS server configuration

  • DHCP server addresses

Red Flags in Network Config:

  • βœ— Unusual DNS servers (attacker DNS, privacy DNS)

  • βœ— Suspicious gateways (man-in-the-middle)

  • βœ— IP changes during incident window

  • βœ— VPN interface IP addresses


PowerShell Script: Complete Network Activity Investigation


Workflow 2: VPN & Anonymisation Detection

Scenario: Detect use of VPN or anonymisation tools

Investigation Steps:

Step 1: Check Network List for VPN Connections

PowerShell - Detect VPN Networks:

Step 2: Check SRUM for VPN Application Usage

Step 3: Correlate VPN Usage with Data Transfer


Workflow 3: Baseline vs. Anomaly Detection

Scenario: Identify abnormal network usage patterns

Analysis Technique:

Compare Application Network Usage:

PowerShell - Baseline Analysis:


Detection Patterns & Red Flags

Data Exfiltration Indicators

SRUM Patterns:


VPN/Anonymisation Usage

Network List Indicators:

SRUM Indicators:


Lateral Movement Detection

SRUM Indicators:


Common Investigation Scenarios

Scenario 1: Cloud Storage Exfiltration

Evidence Chain:

Analysis:


Scenario 2: VPN-Based Data Theft

Evidence Chain:

Timeline Correlation:


Scenario 3: Insider Threat Baseline Deviation

Evidence Chain:


SRUM Analysis Deep Dive

Understanding SRUM Data

Recording Interval:

  • Data recorded approximately every hour

  • Cumulative counters (total since boot)

  • Requires aggregation for analysis

Table Relationships:

Key Metrics:

BytesSent:

  • Total bytes uploaded by application

  • Cumulative counter

  • Resets on system reboot

BytesRecvd:

  • Total bytes downloaded by application

  • Cumulative counter

  • Resets on system reboot

Upload Ratio Calculation:


SRUM CSV Output Columns Reference

NetworkUsage.csv:

  • Timestamp - Recording time

  • App - Application path

  • UserId - User SID

  • BytesSent - Bytes uploaded

  • BytesRecvd - Bytes downloaded

  • InterfaceLuid - Network interface ID

  • L2ProfileId - Network profile ID

  • L2ProfileFlags - Profile flags

AppResourceUseInfo.csv:

  • Timestamp - Recording time

  • AppId - Application ID

  • UserId - User SID

  • ForegroundCycleTime - CPU time (foreground)

  • BackgroundCycleTime - CPU time (background)

  • FaceTime - Face detection time

  • ForegroundContextSwitches - Context switches

  • BackgroundContextSwitches - Context switches

  • ForegroundBytesRead - Disk read (foreground)

  • ForegroundBytesWritten - Disk write (foreground)

NetworkConnections.csv:

  • Timestamp - Recording time

  • AppId - Application ID

  • UserId - User SID

  • InterfaceLuid - Network interface

  • L2ProfileId - Network profile

  • ConnectedTime - Connection duration (seconds)

  • ConnectStartTime - Connection start


Tools & Commands Reference

SrumECmd (Eric Zimmerman)

Basic Usage:

Output Files:

Analysis Priority:

  1. NetworkUsage.csv - Primary for data exfiltration

  2. AppResourceUseInfo.csv - Context (app was running)

  3. NetworkConnections.csv - Connection duration


Registry Queries

Network List:

TCP/IP Interfaces:


Live Network Commands


Investigation Checklists

Data Exfiltration Investigation

  • [ ] Collect SRUM database (SRUDB.dat)

  • [ ] Collect SOFTWARE hive for app resolution

  • [ ] Parse with SrumECmd

  • [ ] Analyse NetworkUsage CSV

  • [ ] Sort by BytesSent (descending)

  • [ ] Calculate upload ratios

  • [ ] Identify applications with >50% upload ratio

  • [ ] Check for unusual application paths

  • [ ] Correlate with execution artifacts (Prefetch/BAM)

  • [ ] Check Network List for VPN usage

  • [ ] Build timeline of high upload events

  • [ ] Cross-reference with file access artifacts

VPN Detection Investigation

  • [ ] Parse Network List registry

  • [ ] Search for VPN keywords (OpenVPN, NordVPN, etc.)

  • [ ] Check first/last connection times

  • [ ] Parse SRUM for VPN client executables

  • [ ] Correlate VPN connection with data uploads

  • [ ] Check browser history for VPN provider sites

  • [ ] Review execution artifacts for VPN installers

  • [ ] Document VPN usage timeline

Network Baseline Investigation

  • [ ] Parse SRUM for full 30-60 day history

  • [ ] Calculate average daily usage per application

  • [ ] Identify maximum usage per application

  • [ ] Detect anomalies (>3x average)

  • [ ] Focus on anomalies during incident window

  • [ ] Correlate with user activity timeline

  • [ ] Document deviation patterns


Best Practices

SRUM Collection

βœ… DO:

  • Collect both SRUDB.dat and SOFTWARE hive

  • Collect .LOG files (transaction logs)

  • Parse offline (don't open database live)

  • Hash files before analysis

  • Document collection timestamp

❌ DON'T:

  • Open SRUDB.dat without SOFTWARE hive (app names won't resolve)

  • Modify database during collection

  • Skip transaction logs

  • Forget OS version check (Win8+ only)


Analysis Methodology

βœ… DO:

  • Start with NetworkUsage.csv

  • Calculate upload ratios

  • Look for anomalies in app paths

  • Correlate with execution artifacts

  • Build timeline of network events

  • Cross-reference multiple artifacts

❌ DON'T:

  • Rely solely on SRUM

  • Ignore low upload volumes (persistence C2)

  • Skip baseline comparison

  • Forget timezone conversions


Limitations & Caveats

SRUM Limitations

Network List Limitations

TCP/IP Limitations


Summary: Critical Takeaways

Artifact Strengths

SRUM:

  • βœ“ Best for: Data exfiltration detection

  • βœ“ Shows: Bytes sent/received per application

  • βœ“ Retention: 30-60 days

  • βœ— Limitation: Windows 8+ only

Network List:

  • βœ“ Best for: Wi-Fi/VPN history

  • βœ“ Shows: Networks connected, first/last times

  • βœ“ Retention: Persistent

  • βœ— Limitation: No bandwidth data

TCP/IP Interfaces:

  • βœ“ Best for: IP address history

  • βœ“ Shows: Current and recent IPs

  • βœ“ Retention: Recent only

  • βœ— Limitation: No historical timeline

Investigation Strategy

  1. Check SRUM first (data exfiltration smoking gun)

  2. Analyse upload ratios (sent vs. received)

  3. Identify suspicious apps (temp paths, unknown)

  4. Check Network List (VPN usage)

  5. Review TCP/IP config (IP addresses)

  6. Correlate with execution artifacts (validate findings)

Key Principle

SRUM is the gold standard for data exfiltration detection on Windows 8+. High upload ratios combined with unusual applications provide strong evidence of data theft.


Remember: SRUM's bytes sent/received per application is your best evidence for data exfiltration. Calculate upload ratios and look for anomaliesβ€”normal applications download more than they upload!

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