implementing-velociraptor-for-ir-collection▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Deploy and configure Velociraptor for scalable endpoint forensic artifact collection during incident response using VQL queries, hunts, and pre-built artifact packs across Windows, Linux, and macOS environments.
| name | implementing-velociraptor-for-ir-collection |
| description | Deploy and configure Velociraptor for scalable endpoint forensic artifact collection during incident response using VQL queries, hunts, and pre-built artifact packs across Windows, Linux, and macOS environments. |
| domain | cybersecurity |
| subdomain | incident-response |
| tags | - velociraptor - dfir - endpoint-collection - vql - forensic-artifacts - rapid7 - threat-hunting - incident-response |
| mitre_attack | - T1059 - T1003 - T1070 - T1547 |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| d3fend_techniques | - Executable Denylisting - Execution Isolation - File Metadata Consistency Validation - Content Format Conversion - File Content Analysis |
| nist_csf | - RS.MA-01 - RS.MA-02 - RS.AN-03 - RC.RP-01 |
Implementing Velociraptor for IR Collection
Overview
Velociraptor is an advanced open-source endpoint monitoring, digital forensics, and incident response platform developed by Rapid7. It uses the Velociraptor Query Language (VQL) to create custom artifacts that collect, query, and monitor almost any aspect of an endpoint. Velociraptor enables incident response teams to rapidly collect and examine forensic artifacts from across a network, supporting large-scale deployments with minimal performance impact. The client-server architecture with Fleetspeak communication enables real-time data collection from thousands of endpoints simultaneously, with offline endpoints picking up hunts when they reconnect.
When to Use
- When deploying or configuring implementing velociraptor for ir collection capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- Familiarity with incident response concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Architecture
Components
- Velociraptor Server: Central management console with web UI and API
- Velociraptor Client (Agent): Lightweight agent deployed to endpoints
- Fleetspeak: Communication framework between client and server
- VQL Engine: Query language engine for artifact collection
- Filestore: Server-side storage for collected artifacts
- Datastore: Metadata storage for hunts, flows, and client information
Supported Platforms
- Windows (7+, Server 2008R2+)
- Linux (Debian, Ubuntu, CentOS, RHEL)
- macOS (10.13+)
Deployment
Server Installation
# Download latest release
wget https://github.com/Velocidex/velociraptor/releases/latest/download/velociraptor-linux-amd64
# Generate server configuration
./velociraptor-linux-amd64 config generate -i
# Start the server
./velociraptor-linux-amd64 --config server.config.yaml frontend
# Or run as systemd service
sudo cp velociraptor-linux-amd64 /usr/local/bin/velociraptor
sudo velociraptor --config /etc/velociraptor/server.config.yaml service install
Client Deployment
# Repack client MSI for Windows deployment
velociraptor --config server.config.yaml config client > client.config.yaml
velociraptor config repack --msi velociraptor-windows-amd64.msi client.config.yaml output.msi
# Deploy via Group Policy, SCCM, or Intune
# Client runs as a Windows service: "Velociraptor"
# Linux client deployment
velociraptor --config client.config.yaml client -v
# macOS client deployment
velociraptor --config client.config.yaml client -v
Docker Deployment
docker run --name velociraptor \
-v /opt/velociraptor:/velociraptor/data \
-p 8000:8000 -p 8001:8001 -p 8889:8889 \
velocidex/velociraptor
Core IR Artifact Collection
Windows Forensic Artifacts
-- Collect Windows Event Logs
SELECT * FROM Artifact.Windows.EventLogs.EvtxHunter(
EvtxGlob="C:/Windows/System32/winevt/Logs/*.evtx",
IDRegex="4624|4625|4648|4672|4688|4698|4769|7045"
)
-- Collect Prefetch files for execution evidence
SELECT * FROM Artifact.Windows.Forensics.Prefetch()
-- Collect Shimcache entries
SELECT * FROM Artifact.Windows.Registry.AppCompatCache()
-- Collect Amcache entries
SELECT * FROM Artifact.Windows.Forensics.Amcache()
-- Collect UserAssist data
SELECT * FROM Artifact.Windows.Forensics.UserAssist()
-- Collect NTFS MFT timestamps
SELECT * FROM Artifact.Windows.NTFS.MFT(
MFTFilename="C:/$MFT",
FileRegex=".(exe|dll|ps1|bat|cmd)$"
)
-- Collect scheduled tasks
SELECT * FROM Artifact.Windows.System.TaskScheduler()
-- Collect running processes with hashes
SELECT * FROM Artifact.Windows.System.Pslist()
-- Collect network connections
SELECT * FROM Artifact.Windows.Network.Netstat()
-- Collect DNS cache
SELECT * FROM Artifact.Windows.Network.DNSCache()
-- Collect browser history
SELECT * FROM Artifact.Windows.Applications.Chrome.History()
-- Collect PowerShell history
SELECT * FROM Artifact.Windows.Forensics.PowerShellHistory()
-- Collect autoruns/persistence
SELECT * FROM Artifact.Windows.Persistence.PermanentWMIEvents()
SELECT * FROM Artifact.Windows.System.Services()
SELECT * FROM Artifact.Windows.System.StartupItems()
Linux Forensic Artifacts
-- Collect auth logs
SELECT * FROM Artifact.Linux.Sys.AuthLogs()
-- Collect bash history
SELECT * FROM Artifact.Linux.Forensics.BashHistory()
-- Collect crontab entries
SELECT * FROM Artifact.Linux.Sys.Crontab()
-- Collect running processes
SELECT * FROM Artifact.Linux.Sys.Pslist()
-- Collect network connections
SELECT * FROM Artifact.Linux.Network.Netstat()
-- Collect SSH authorized keys
SELECT * FROM Artifact.Linux.Ssh.AuthorizedKeys()
-- Collect systemd services
SELECT * FROM Artifact.Linux.Services()
Triage Collection (All-in-One)
-- Windows Triage Collection artifact
-- Collects event logs, prefetch, registry, browser data, and more
SELECT * FROM Artifact.Windows.KapeFiles.Targets(
Device="C:",
_AllFiles=FALSE,
_EventLogs=TRUE,
_Prefetch=TRUE,
_RegistryHives=TRUE,
_WebBrowsers=TRUE,
_WindowsTimeline=TRUE
)
Hunt Operations
Creating a Hunt
1. Navigate to Hunt Manager in Velociraptor Web UI
2. Click "New Hunt"
3. Configure:
- Description: "IR Triage - Case 2025-001"
- Include/Exclude labels for targeting
- Artifact selection (e.g., Windows.Forensics.Prefetch)
- Resource limits (CPU, IOPS, timeout)
4. Launch hunt
5. Monitor progress in real-time
VQL Hunt Examples
-- Hunt for specific file hash across all endpoints
SELECT * FROM Artifact.Generic.Detection.HashHunter(
Hashes="e99a18c428cb38d5f260853678922e03"
)
-- Hunt for YARA signatures in memory
SELECT * FROM Artifact.Windows.Detection.Yara.Process(
YaraRule='rule malware { strings: $s1 = "malicious_string" condition: $s1 }'
)
-- Hunt for Sigma rule matches in event logs
SELECT * FROM Artifact.Server.Import.SigmaRules()
-- Hunt for suspicious scheduled tasks
SELECT * FROM Artifact.Windows.System.TaskScheduler()
WHERE Command =~ "powershell|cmd|wscript|mshta|rundll32"
-- Hunt for processes with network connections to suspicious IPs
SELECT * FROM Artifact.Windows.Network.Netstat()
WHERE RemoteAddr =~ "10\\.13\\.37\\."
Real-Time Monitoring
-- Monitor for new process creation
SELECT * FROM watch_etw(guid="{22fb2cd6-0e7b-422b-a0c7-2fad1fd0e716}")
WHERE EventData.ImageName =~ "powershell|cmd|wscript"
-- Monitor file system changes
SELECT * FROM watch_directory(path="C:/Windows/Temp/")
-- Monitor registry changes
SELECT * FROM watch_registry(key="HKLM/SOFTWARE/Microsoft/Windows/CurrentVersion/Run/**")
Integration with SIEM/SOAR
Splunk Integration
Velociraptor Server --> Elastic/OpenSearch --> Splunk HEC
--> Direct syslog forwarding
--> Velociraptor API --> Custom scripts --> Splunk
Elastic Stack Integration
# Velociraptor server config for Elastic output
Monitoring:
elastic:
addresses:
- https://elastic.local:9200
username: velociraptor
password: secure_password
index: velociraptor
MITRE ATT&CK Mapping
| Technique | VQL Artifact |
|---|---|
| T1059 - Command Scripting | Windows.EventLogs.EvtxHunter (4104, 4688) |
| T1053 - Scheduled Task | Windows.System.TaskScheduler |
| T1547 - Boot/Logon Autostart | Windows.Persistence.PermanentWMIEvents |
| T1003 - OS Credential Dumping | Windows.Detection.Yara.Process |
| T1021 - Remote Services | Windows.EventLogs.EvtxHunter (4624 Type 3/10) |
| T1070 - Indicator Removal | Windows.EventLogs.Cleared |
References
How to use implementing-velociraptor-for-ir-collection on Cursor
AI-first code editor with Composer
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 implementing-velociraptor-for-ir-collection
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches implementing-velociraptor-for-ir-collection 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 implementing-velociraptor-for-ir-collection. Access the skill through slash commands (e.g., /implementing-velociraptor-for-ir-collection) 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.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
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
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★26 reviews- ★★★★★Ganesh Mohane· Dec 24, 2024
implementing-velociraptor-for-ir-collection reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Rahul Santra· Nov 15, 2024
I recommend implementing-velociraptor-for-ir-collection for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Oct 6, 2024
Useful defaults in implementing-velociraptor-for-ir-collection — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Neel Bansal· Sep 13, 2024
implementing-velociraptor-for-ir-collection reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Neel Gill· Aug 4, 2024
Registry listing for implementing-velociraptor-for-ir-collection matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sakshi Patil· Jul 27, 2024
implementing-velociraptor-for-ir-collection has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Neel Ramirez· Jul 23, 2024
Useful defaults in implementing-velociraptor-for-ir-collection — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Michael Park· Jul 19, 2024
implementing-velociraptor-for-ir-collection is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chaitanya Patil· Jun 18, 2024
Solid pick for teams standardizing on skills: implementing-velociraptor-for-ir-collection is focused, and the summary matches what you get after install.
- ★★★★★Nikhil Chawla· Jun 14, 2024
I recommend implementing-velociraptor-for-ir-collection for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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