Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
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Collect volatile forensic evidence from a compromised system following order of volatility, preserving memory, network connections, processes, and system state before they are lost.
中文简介正在准备中。当前显示原文说明。
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# Mount forensic USB toolkit (do NOT install tools on compromised system)
# Verify toolkit integrity
sha256sum /mnt/forensic_usb/tools/* > /tmp/toolkit_hashes.txt
diff /mnt/forensic_usb/tools/known_good_hashes.txt /tmp/toolkit_hashes.txt
# Create evidence output directory with timestamps
EVIDENCE_DIR="/mnt/evidence/$(hostname)_$(date +%Y%m%d_%H%M%S)"
mkdir -p "$EVIDENCE_DIR"
echo "Collection started: $(date -u)" > "$EVIDENCE_DIR/collection_log.txt"
echo "Collector: $(whoami)" >> "$EVIDENCE_DIR/collection_log.txt"
echo "System: $(hostname)" >> "$EVIDENCE_DIR/collection_log.txt"
# Windows - WinPmem memory acquisition
winpmem_mini_x64.exe "$EVIDENCE_DIR\memdump_$(hostname).raw"
# Linux - LiME kernel module for memory acquisition
insmod /mnt/forensic_usb/lime.ko "path=$EVIDENCE_DIR/memdump_$(hostname).lime format=lime"
# Linux - Alternative using /proc/kcore
dd if=/proc/kcore of="$EVIDENCE_DIR/kcore_dump.raw" bs=1M
# macOS - osxpmem
osxpmem -o "$EVIDENCE_DIR/memdump_$(hostname).aff4"
# Hash the memory dump immediately
sha256sum "$EVIDENCE_DIR/memdump_"* > "$EVIDENCE_DIR/memory_hash.sha256"
# Active network connections
# Windows
netstat -anob > "$EVIDENCE_DIR/netstat_connections.txt" 2>&1
Get-NetTCPConnection | Export-Csv "$EVIDENCE_DIR/tcp_connections.csv" -NoTypeInformation
Get-NetUDPEndpoint | Export-Csv "$EVIDENCE_DIR/udp_endpoints.csv" -NoTypeInformation
# Linux
ss -tulnp > "$EVIDENCE_DIR/socket_stats.txt"
netstat -anp > "$EVIDENCE_DIR/netstat_all.txt" 2>/dev/null
cat /proc/net/tcp > "$EVIDENCE_DIR/proc_net_tcp.txt"
cat /proc/net/udp > "$EVIDENCE_DIR/proc_net_udp.txt"
# ARP cache
arp -a > "$EVIDENCE_DIR/arp_cache.txt"
# Routing table
route print > "$EVIDENCE_DIR/routing_table.txt" # Windows
ip route show > "$EVIDENCE_DIR/routing_table.txt" # Linux
# DNS cache
ipconfig /displaydns > "$EVIDENCE_DIR/dns_cache.txt" # Windows
# Linux: varies by resolver, check systemd-resolve or nscd
systemd-resolve --statistics > "$EVIDENCE_DIR/dns_stats.txt" 2>/dev/null
# Active firewall rules
netsh advfirewall show allprofiles > "$EVIDENCE_DIR/firewall_rules.txt" # Windows
iptables -L -n -v > "$EVIDENCE_DIR/iptables_rules.txt" # Linux
# Windows - Detailed process list
tasklist /V /FO CSV > "$EVIDENCE_DIR/process_list_verbose.csv"
wmic process list full > "$EVIDENCE_DIR/wmic_process_full.txt"
Get-Process | Select-Object Id,ProcessName,Path,StartTime,CPU,WorkingSet |
Export-Csv "$EVIDENCE_DIR/ps_processes.csv" -NoTypeInformation
# Windows - Process with command line and parent
wmic process get ProcessId,Name,CommandLine,ParentProcessId,ExecutablePath /FORMAT:CSV > \
"$EVIDENCE_DIR/process_commandlines.csv"
# Linux - Full process tree
ps auxwwf > "$EVIDENCE_DIR/process_tree.txt"
ps -eo pid,ppid,user,args --forest > "$EVIDENCE_DIR/process_forest.txt"
cat /proc/*/cmdline 2>/dev/null | tr '\0' ' ' > "$EVIDENCE_DIR/proc_cmdline_all.txt"
# Process modules/DLLs loaded
# Windows
listdlls.exe -accepteula > "$EVIDENCE_DIR/loaded_dlls.txt"
# Linux
for pid in $(ls /proc/ | grep -E '^[0-9]+$'); do
echo "=== PID $pid ===" >> "$EVIDENCE_DIR/proc_maps.txt"
cat "/proc/$pid/maps" 2>/dev/null >> "$EVIDENCE_DIR/proc_maps.txt"
done
# Open file handles
handle.exe -accepteula > "$EVIDENCE_DIR/open_handles.txt" # Windows (Sysinternals)
lsof > "$EVIDENCE_DIR/open_files.txt" # Linux
# Windows
query user > "$EVIDENCE_DIR/logged_in_users.txt"
query session > "$EVIDENCE_DIR/active_sessions.txt"
net session > "$EVIDENCE_DIR/net_sessions.txt" 2>&1
net use > "$EVIDENCE_DIR/mapped_drives.txt" 2>&1
# Linux
who > "$EVIDENCE_DIR/who_output.txt"
w > "$EVIDENCE_DIR/w_output.txt"
last -50 > "$EVIDENCE_DIR/last_logins.txt"
lastlog > "$EVIDENCE_DIR/lastlog.txt"
cat /var/log/auth.log | tail -200 > "$EVIDENCE_DIR/recent_auth.txt" 2>/dev/null
# System time (critical for timeline)
date -u > "$EVIDENCE_DIR/system_time_utc.txt"
w32tm /query /status > "$EVIDENCE_DIR/ntp_status.txt" # Windows
ntpq -p > "$EVIDENCE_DIR/ntp_status.txt" # Linux
# Environment variables
set > "$EVIDENCE_DIR/environment_vars.txt" # Windows
env > "$EVIDENCE_DIR/environment_vars.txt" # Linux
# Scheduled tasks / Cron jobs
schtasks /query /fo CSV /v > "$EVIDENCE_DIR/scheduled_tasks.csv" # Windows
crontab -l > "$EVIDENCE_DIR/crontab_current.txt" 2>/dev/null # Linux
ls -la /etc/cron.* > "$EVIDENCE_DIR/cron_dirs.txt" 2>/dev/null
# Services
sc queryex type=service state=all > "$EVIDENCE_DIR/services_all.txt" # Windows
systemctl list-units --type=service --all > "$EVIDENCE_DIR/systemd_services.txt" # Linux
# Windows Registry - key autostart locations
reg export "HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Run" "$EVIDENCE_DIR/reg_run_hklm.reg" /y
reg export "HKCU\SOFTWARE\Microsoft\Windows\CurrentVersion\Run" "$EVIDENCE_DIR/reg_run_hkcu.reg" /y
reg export "HKLM\SYSTEM\CurrentControlSet\Services" "$EVIDENCE_DIR/reg_services.reg" /y
# Generate SHA256 hashes for all collected evidence
cd "$EVIDENCE_DIR"
sha256sum * > evidence_manifest.sha256
# Create chain of custody record
cat > "$EVIDENCE_DIR/chain_of_custody.txt" << EOF
CHAIN OF CUSTODY RECORD
========================
Case ID: IR-YYYY-NNN
Collection Date: $(date -u)
Collected By: $(whoami)
System: $(hostname)
System IP: $(hostname -I 2>/dev/null || ipconfig | grep IPv4)
Collection Method: Live forensic collection via trusted USB toolkit
Evidence Items:
$(ls -la "$EVIDENCE_DIR/" | grep -v chain_of_custody)
SHA256 Manifest: evidence_manifest.sha256
Transfer: [TO BE COMPLETED]
Storage Location: [TO BE COMPLETED]
EOF
| Concept | Description |
|---|---|
| Order of Volatility | RFC 3227 - Collect most volatile data first: registers > cache > memory > disk |
| Live Forensics | Collecting evidence from a running system before shutdown |
| Chain of Custody | Documentation tracking evidence handling from collection to court |
| Forensic Soundness | Ensuring evidence collection doesn't alter the original evidence |
| Trusted Tools | Using verified tools from external media, not from the compromised system |
| Evidence Integrity | SHA256 hashing of all evidence immediately after collection |
| Locard's Exchange Principle | Every contact leaves a trace - minimize investigator artifacts |
| Tool | Purpose |
|---|---|
| WinPmem | Windows memory acquisition |
| LiME (Linux Memory Extractor) | Linux kernel memory acquisition |
| Sysinternals Suite | Process, handle, and DLL analysis (Windows) |
| Velociraptor | Remote forensic collection at scale |
| KAPE (Kroll Artifact Parser) | Automated artifact collection on Windows |
| CyLR | Cross-platform live response collection |
| GRR Rapid Response | Remote live forensics framework |
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Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
中文简介正在准备中。当前显示原文说明。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
中文简介正在准备中。当前显示原文说明。
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
中文简介正在准备中。当前显示原文说明。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
中文简介正在准备中。当前显示原文说明。
Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
中文简介正在准备中。当前显示原文说明。
Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.
中文简介正在准备中。当前显示原文说明。