investigating-ransomware-attack-artifacts▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Identify, collect, and analyze ransomware attack artifacts to determine the variant, initial access vector, encryption scope, and recovery options.
| name | investigating-ransomware-attack-artifacts |
| description | Identify, collect, and analyze ransomware attack artifacts to determine the variant, initial access vector, encryption scope, and recovery options. |
| domain | cybersecurity |
| subdomain | digital-forensics |
| tags | - forensics - ransomware - malware-analysis - incident-response - encryption-recovery - evidence-collection |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - RS.AN-01 - RS.AN-03 - DE.AE-02 - RS.MA-01 |
Investigating Ransomware Attack Artifacts
When to Use
- Immediately after discovering ransomware encryption on systems
- When performing forensic analysis to understand the full scope of a ransomware incident
- For identifying the ransomware variant and determining if decryption is possible
- When tracing the attack chain from initial access to encryption
- For documenting evidence to support law enforcement and insurance claims
Prerequisites
- Forensic images of affected systems (preserve before remediation)
- Memory dumps captured before system shutdown (if available)
- Ransom notes and encrypted file samples
- Network traffic captures from the attack period
- Windows Event Logs, Prefetch files, and registry hives
- Access to ransomware identification tools (ID Ransomware, No More Ransom)
- Isolated sandbox environment for malware analysis
Workflow
Step 1: Preserve Evidence and Identify the Ransomware Variant
# CRITICAL: Do NOT restart systems. Preserve memory first if possible.
# Encryption keys may still be in memory.
# Capture memory from running systems
# Windows: DumpIt.exe (generates memory.raw)
# Linux: sudo insmod lime.ko "path=/evidence/memory.lime format=lime"
# Collect ransom note
cp /mnt/evidence/Users/*/Desktop/README*.txt /cases/case-2024-001/ransomware/ransom_notes/
cp /mnt/evidence/Users/*/Desktop/DECRYPT*.txt /cases/case-2024-001/ransomware/ransom_notes/
cp /mnt/evidence/Users/*/Desktop/HOW_TO*.txt /cases/case-2024-001/ransomware/ransom_notes/
find /mnt/evidence/ -name "*.hta" -o -name "*DECRYPT*" -o -name "*RANSOM*" -o -name "*README*" \
2>/dev/null | head -20 > /cases/case-2024-001/ransomware/note_locations.txt
# Collect sample encrypted files (for identification)
find /mnt/evidence/Users/ -name "*.encrypted" -o -name "*.locked" -o -name "*.crypted" \
-o -name "*.crypt" -o -name "*.enc" | head -10 > /cases/case-2024-001/ransomware/encrypted_samples.txt
# Copy sample encrypted files
mkdir -p /cases/case-2024-001/ransomware/samples/
head -5 /cases/case-2024-001/ransomware/encrypted_samples.txt | while read f; do
cp "$f" /cases/case-2024-001/ransomware/samples/
done
# Identify ransomware variant using file extension and ransom note
python3 << 'PYEOF'
import os, hashlib, json
ransomware_indicators = {
'.lockbit': 'LockBit',
'.blackcat': 'BlackCat/ALPHV',
'.royal': 'Royal',
'.akira': 'Akira',
'.clop': 'Cl0p',
'.conti': 'Conti',
'.ryuk': 'Ryuk',
'.revil': 'REvil/Sodinokibi',
'.maze': 'Maze',
'.phobos': 'Phobos',
'.dharma': 'Dharma/CrySIS',
'.stop': 'STOP/Djvu',
'.hive': 'Hive',
'.blackbasta': 'Black Basta',
'.play': 'Play',
}
# Check encrypted file extensions
samples_dir = '/cases/case-2024-001/ransomware/samples/'
for f in os.listdir(samples_dir):
ext = os.path.splitext(f)[1].lower()
variant = ransomware_indicators.get(ext, 'Unknown')
sha256 = hashlib.sha256(open(os.path.join(samples_dir, f), 'rb').read()).hexdigest()
print(f"File: {f}")
print(f" Extension: {ext}")
print(f" Suspected Variant: {variant}")
print(f" SHA-256: {sha256}")
print()
# Parse ransom note for IoCs
note_dir = '/cases/case-2024-001/ransomware/ransom_notes/'
for note in os.listdir(note_dir):
with open(os.path.join(note_dir, note), 'r', errors='ignore') as f:
content = f.read()
print(f"\n=== Ransom Note: {note} ===")
# Extract bitcoin addresses
import re
btc = re.findall(r'[13][a-km-zA-HJ-NP-Z1-9]{25,34}|bc1[a-zA-HJ-NP-Z0-9]{25,39}', content)
tor = re.findall(r'[a-z2-7]{56}\.onion', content)
emails = re.findall(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', content)
if btc: print(f" Bitcoin addresses: {btc}")
if tor: print(f" Tor addresses: {tor}")
if emails: print(f" Contact emails: {emails}")
PYEOF
Step 2: Determine the Attack Timeline
# Find the earliest encrypted file (encryption start time)
find /mnt/evidence/ -name "*.encrypted" -printf '%T+ %p\n' 2>/dev/null | sort | head -5 \
> /cases/case-2024-001/ransomware/encryption_start.txt
# Find the latest encrypted file (encryption end time)
find /mnt/evidence/ -name "*.encrypted" -printf '%T+ %p\n' 2>/dev/null | sort -r | head -5 \
> /cases/case-2024-001/ransomware/encryption_end.txt
# Analyze Prefetch for ransomware executable
ls /mnt/evidence/Windows/Prefetch/ | grep -iE "(encrypt|ransom|lock|crypt)" \
> /cases/case-2024-001/ransomware/prefetch_hits.txt
# Check Windows Event Logs for key events
python3 << 'PYEOF'
import json
from evtx import PyEvtxParser
# Security log - authentication and access events
parser = PyEvtxParser("/cases/case-2024-001/evtx/Security.evtx")
attack_events = []
for record in parser.records_json():
data = json.loads(record['data'])
event_id = str(data['Event']['System']['EventID'])
timestamp = data['Event']['System']['TimeCreated']['#attributes']['SystemTime']
# Key events for ransomware investigation
if event_id in ('4624', '4625', '4648', '4672', '4697', '4698', '4688', '1102'):
event_data = data['Event'].get('EventData', {})
attack_events.append({
'time': timestamp,
'event_id': event_id,
'data': json.dumps(event_data, default=str)[:200]
})
# Sort and display timeline
attack_events.sort(key=lambda x: x['time'])
print("=== RANSOMWARE ATTACK TIMELINE ===\n")
for event in attack_events[-50:]:
print(f" [{event['time']}] EventID {event['event_id']}: {event['data'][:150]}")
PYEOF
# Check for Volume Shadow Copy deletion (common ransomware behavior)
# Look for vssadmin.exe or wmic shadowcopy in event logs and Prefetch
grep -l "vssadmin" /cases/case-2024-001/evtx/*.evtx 2>/dev/null
ls /mnt/evidence/Windows/Prefetch/ | grep -i "vssadmin\|wmic\|bcdedit\|wbadmin"
Step 3: Trace Initial Access and Lateral Movement
# Check for common ransomware initial access vectors
# RDP brute force
python3 << 'PYEOF'
import json
from evtx import PyEvtxParser
from collections import defaultdict
parser = PyEvtxParser("/cases/case-2024-001/evtx/Security.evtx")
failed_rdp = defaultdict(int)
successful_rdp = []
for record in parser.records_json():
data = json.loads(record['data'])
event_id = str(data['Event']['System']['EventID'])
event_data = data['Event'].get('EventData', {})
timestamp = data['Event']['System']['TimeCreated']['#attributes']['SystemTime']
if event_id == '4625': # Failed logon
logon_type = str(event_data.get('LogonType', ''))
if logon_type == '10': # RDP
source_ip = event_data.get('IpAddress', 'Unknown')
failed_rdp[source_ip] += 1
if event_id == '4624': # Successful logon
logon_type = str(event_data.get('LogonType', ''))
if logon_type in ('10', '3'): # RDP or Network
source_ip = event_data.get('IpAddress', 'Unknown')
username = event_data.get('TargetUserName', 'Unknown')
successful_rdp.append({'time': timestamp, 'user': username, 'ip': source_ip, 'type': logon_type})
print("=== FAILED RDP ATTEMPTS ===")
for ip, count in sorted(failed_rdp.items(), key=lambda x: x[1], reverse=True)[:10]:
print(f" {ip}: {count} failed attempts")
print(f"\n=== SUCCESSFUL NETWORK/RDP LOGONS ===")
for logon in successful_rdp[-20:]:
type_name = 'RDP' if logon['type'] == '10' else 'Network'
print(f" [{logon['time']}] {logon['user']} from {logon['ip']} ({type_name})")
PYEOF
# Check for phishing-related artifacts
# Browser downloads, email attachments, Office macros
find /mnt/evidence/Users/*/Downloads/ -name "*.exe" -o -name "*.dll" -o -name "*.js" \
-o -name "*.vbs" -o -name "*.hta" -o -name "*.ps1" 2>/dev/null \
> /cases/case-2024-001/ransomware/suspicious_downloads.txt
# Check PowerShell execution
ls /mnt/evidence/Windows/Prefetch/ | grep -i powershell
Step 4: Assess Encryption Scope and Recovery Options
# Count encrypted files by directory
find /mnt/evidence/ -name "*.encrypted" 2>/dev/null | \
awk -F/ '{OFS="/"; NF--; print}' | sort | uniq -c | sort -rn | head -20 \
> /cases/case-2024-001/ransomware/encryption_scope.txt
# Check if Volume Shadow Copies survived
vssadmin list shadows 2>/dev/null > /cases/case-2024-001/ransomware/vss_status.txt
# Check for backup integrity
find /mnt/evidence/ -name "*.bak" -o -name "*.backup" 2>/dev/null | head -20
# Check No More Ransom project for available decryptors
# https://www.nomoreransom.org/en/decryption-tools.html
echo "Check https://www.nomoreransom.org/ for decryption tools" \
> /cases/case-2024-001/ransomware/decryption_options.txt
# Attempt to recover encryption keys from memory dump
if [ -f /cases/case-2024-001/memory/memory.raw ]; then
# Search for AES key schedules in memory
vol -f /cases/case-2024-001/memory/memory.raw yarascan \
--yara-rules 'rule AES_Key { strings: $aes = { 63 7C 77 7B F2 6B 6F C5 30 01 67 2B FE D7 AB 76 } condition: $aes }' \
> /cases/case-2024-001/ransomware/aes_key_search.txt
# Search for RSA key material
vol -f /cases/case-2024-001/memory/memory.raw yarascan \
--yara-rules 'rule RSA_Key { strings: $rsa = "RSA PRIVATE KEY" condition: $rsa }' \
> /cases/case-2024-001/ransomware/rsa_key_search.txt
fi
Step 5: Document Findings and Generate Report
# Generate comprehensive ransomware investigation report
cat << 'REPORT' > /cases/case-2024-001/ransomware/investigation_report.txt
RANSOMWARE INCIDENT INVESTIGATION REPORT
==========================================
Case Number: 2024-001
Date: $(date -u)
Analyst: [Examiner Name]
1. INCIDENT OVERVIEW
- Ransomware Variant: [Identified variant]
- First Encryption: [Timestamp from earliest encrypted file]
- Last Encryption: [Timestamp from latest encrypted file]
- Systems Affected: [Count]
- Data Encrypted: [Volume estimate]
2. INITIAL ACCESS VECTOR
- Method: [RDP brute force / Phishing / Exploit / etc.]
- Entry Point: [System and IP]
- Timestamp: [First unauthorized access]
- Credentials Used: [Account names]
3. ATTACK CHAIN
a. Initial Access: [Details]
b. Execution: [Ransomware binary details]
c. Persistence: [Services, scheduled tasks]
d. Privilege Escalation: [Method used]
e. Lateral Movement: [Systems accessed, methods]
f. Collection/Staging: [Data staging before encryption]
g. Impact: [Encryption execution]
4. INDICATORS OF COMPROMISE
- Ransomware Binary SHA-256: [Hash]
- C2 Servers: [IPs/Domains]
- Bitcoin Wallet: [Address]
- Tor Site: [.onion address]
- Attacker IPs: [Source IPs]
5. RECOVERY ASSESSMENT
- Decryptor Available: [Yes/No]
- Shadow Copies: [Survived/Deleted]
- Backups: [Status and integrity]
- Memory Key Recovery: [Attempted/Results]
6. RECOMMENDATIONS
- [Remediation steps]
- [Prevention measures]
- [Monitoring improvements]
REPORT
Key Concepts
| Concept | Description |
|---|---|
| Ransomware variant identification | Determining the specific ransomware family from extensions, notes, and behavior |
| Double extortion | Attack combining encryption with data theft and threatened public release |
| Volume Shadow Copies | Windows backup mechanism often deleted by ransomware to prevent recovery |
| Encryption scope | Assessment of which files, directories, and systems were encrypted |
| Dwell time | Period between initial access and ransomware deployment (often days to weeks) |
| Ransom note IoCs | Bitcoin addresses, Tor sites, and email addresses in ransom demands |
| Key recovery | Attempting to extract encryption keys from memory before shutdown |
| No More Ransom | Law enforcement initiative providing free decryption tools for some variants |
Tools & Systems
| Tool | Purpose |
|---|---|
| ID Ransomware | Online service identifying ransomware variant from samples |
| No More Ransom | Free decryption tools from law enforcement partnerships |
| Volatility | Memory forensics for encryption key and malware artifact recovery |
| Chainsaw/Hayabusa | Windows Event Log analysis for attack timeline reconstruction |
| PECmd | Prefetch analysis confirming ransomware executable execution |
| YARA | Pattern matching for ransomware variant identification |
| Any.Run/Joe Sandbox | Online malware sandboxes for ransomware behavior analysis |
| Capa | Mandiant tool identifying malware capabilities from static analysis |
Common Scenarios
Scenario 1: LockBit Attack via RDP Trace initial access through RDP brute force in event logs, identify attacker IP and compromised account, follow lateral movement through network logons, find LockBit deployment via PsExec or GPO, document encryption timeline from file timestamps, check for data exfiltration before encryption.
Scenario 2: Phishing-Initiated Ransomware Trace phishing email through browser history and email artifacts, identify malicious attachment execution in Prefetch, follow Cobalt Strike beacon communication in network logs, trace privilege escalation and domain compromise, document ransomware deployment across the network.
Scenario 3: Supply Chain Ransomware Attack Identify the compromised software update mechanism, trace the malicious update distribution in application logs, analyze the ransomware payload delivered via the trusted channel, assess which systems received the update, determine if the vendor was notified.
Scenario 4: Recovery from Partial Encryption Determine which systems and files were encrypted before containment, check for surviving volume shadow copies, verify backup integrity and restoration capability, attempt memory-based key recovery, contact law enforcement for potential decryptor availability.
Output Format
Ransomware Investigation Summary:
Variant: LockBit 3.0
First Seen: 2024-01-18 02:00:00 UTC
Encryption Duration: 4 hours 23 minutes
Systems Encrypted: 45 out of 200 (containment stopped spread)
Attack Timeline:
2024-01-10 14:32 - RDP brute force from 203.0.113.45 (1,234 attempts)
2024-01-10 15:00 - Successful RDP login as admin_backup
2024-01-12 02:00 - Mimikatz executed (credential dump)
2024-01-12 02:30 - Domain Admin credentials obtained
2024-01-15 03:00 - Data exfiltration (45 GB to 185.x.x.x)
2024-01-18 02:00 - LockBit deployed via PsExec to 45 systems
2024-01-18 06:23 - Encryption completed on affected systems
Recovery Options:
Decryptor: Not available (LockBit 3.0)
Shadow Copies: Deleted on all systems
Backups: Last clean backup 2024-01-09 (9 days of data loss)
Memory Keys: Not recovered (systems rebooted)
IOCs:
Ransomware Hash: a1b2c3d4e5f6...
C2 IP: 185.x.x.x
Bitcoin: bc1q...
Tor: http://lockbit...onion
How to use investigating-ransomware-attack-artifacts on Cursor
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Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add investigating-ransomware-attack-artifacts
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches investigating-ransomware-attack-artifacts from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate investigating-ransomware-attack-artifacts. Access the skill through slash commands (e.g., /investigating-ransomware-attack-artifacts) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Automate repetitive workflows and reduce manual effort
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Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
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Ratings
4.6★★★★★52 reviews- ★★★★★Aditi Rao· Dec 20, 2024
investigating-ransomware-attack-artifacts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Daniel Chen· Dec 20, 2024
Keeps context tight: investigating-ransomware-attack-artifacts is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kofi Shah· Dec 12, 2024
Solid pick for teams standardizing on skills: investigating-ransomware-attack-artifacts is focused, and the summary matches what you get after install.
- ★★★★★Omar Tandon· Dec 12, 2024
investigating-ransomware-attack-artifacts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Olivia Flores· Dec 8, 2024
investigating-ransomware-attack-artifacts reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ira Garcia· Dec 8, 2024
Registry listing for investigating-ransomware-attack-artifacts matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Noah Haddad· Nov 27, 2024
Solid pick for teams standardizing on skills: investigating-ransomware-attack-artifacts is focused, and the summary matches what you get after install.
- ★★★★★Ira Johnson· Nov 19, 2024
investigating-ransomware-attack-artifacts reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Isabella Sanchez· Nov 3, 2024
Registry listing for investigating-ransomware-attack-artifacts matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Noah Agarwal· Nov 3, 2024
We added investigating-ransomware-attack-artifacts from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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