external/anthropic-cybersecurity-skills/skills/collecting-volatile-evidence-from-compromised-host/SKILL.md
Collect volatile forensic evidence from a compromised host by following the order of volatility, preserving memory, network connections, running processes, and system state with documented chain of custody before they are lost. Use before isolating, shutting down, or remediating a compromised host, especially when fileless or memory-resident malware is suspected, root cause analysis is needed, or the evidence must hold up in legal proceedings.
npx skillsauth add seikaikyo/dash-skills collecting-volatile-evidence-from-compromised-hostInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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 |
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.