Agent skill

Implementing Velociraptor For Ir Collection

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

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…

Apache-2.0Auto-check: notesDevOps & Cloud

Install Implementing Velociraptor For Ir Collection

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-velociraptor-for-ir-collection -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-velociraptor-for-ir-collection --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-velociraptor-for-ir-collection .claude/skills/implementing-velociraptor-for-ir-collection && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
implementing-velociraptor-for-ir-collection
GitHub stars
34k
Token cost
~2.3k tokens
SKILL.md length
318 words
Files
8 (incl. scripts, references, assets)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

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…

  • Tasks that involve Incident response
  • SKILL.md covers Overview, When to Use, Prerequisites and Architecture, plus 7 more sections
  • Runs Python scripts from its folder; calls wget and docker; reaches github.com

What it does

Implementing Velociraptor For Ir Collection is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. 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.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).

It sits in DevOps & Cloud, covering Incident response. It works with Linux and macOS. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Incident response

Example prompts

  • “/implementing-velociraptor-for-ir-collection”

Requirements

  • Python 3
  • Docker

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • wget
    • docker

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    Also links to:

    • docs.velociraptor.app
    • rapid7.com
    • cisa.gov
    • pentestpartners.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Implementing Velociraptor For Ir Collection loads about 2.3k tokens when it runs, and up to ~4.7k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 318 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteRuns commands with sudoSKILL.md:89
    sudo cp velociraptor-linux-amd64 /usr/local/bin/velociraptor
  • NoteRuns commands with sudoSKILL.md:90
    sudo velociraptor --config /etc/velociraptor/server.config.yaml service install

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 318 words, ~2,303 tokens.

Download SKILL.mdSave it as .claude/skills/implementing-velociraptor-for-ir-collection/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
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
T1486, T1490, T1070, T1078, T1005
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
bash
# 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
bash
# 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
bash
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
sql
-- 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
sql
-- 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)
sql
-- 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
sql
-- 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

sql
-- 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
yaml
# Velociraptor server config for Elastic output
Monitoring:
  elastic:
    addresses:
      - https://elastic.local:9200
    username: velociraptor
    password: secure_password
    index: velociraptor

MITRE ATT&CK Mapping

TechniqueVQL Artifact
T1059 - Command ScriptingWindows.EventLogs.EvtxHunter (4104, 4688)
T1053 - Scheduled TaskWindows.System.TaskScheduler
T1547 - Boot/Logon AutostartWindows.Persistence.PermanentWMIEvents
T1003 - OS Credential DumpingWindows.Detection.Yara.Process
T1021 - Remote ServicesWindows.EventLogs.EvtxHunter (4624 Type 3/10)
T1070 - Indicator RemovalWindows.EventLogs.Cleared

References

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references, assets) in skills/implementing-velociraptor-for-ir-collection of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • assets/template.md
  • references/api-reference.md
  • references/standards.md
  • references/workflows.md
  • scripts/agent.py
  • scripts/process.py

Open the folder on GitHubat commit 54a7988

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Works with

Questions about Implementing Velociraptor For Ir Collection

What does Implementing Velociraptor For Ir Collection do?

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…. Implementing Velociraptor For Ir Collection is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. 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.

When should I use Implementing Velociraptor For Ir Collection?

Implementing Velociraptor For Ir Collection fits situations like: tasks that involve Incident response.

How do I install Implementing Velociraptor For Ir Collection in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-velociraptor-for-ir-collection -a claude-code`. Or copy the skill folder (skills/implementing-velociraptor-for-ir-collection in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-velociraptor-for-ir-collection in your project. Claude Code loads it when a task matches its description.

How do I install Implementing Velociraptor For Ir Collection in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-velociraptor-for-ir-collection -a codex`. Or copy the skill folder (skills/implementing-velociraptor-for-ir-collection in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-velociraptor-for-ir-collection in your project. Codex loads it when a task matches its description.

Can I use Implementing Velociraptor For Ir Collection in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-velociraptor-for-ir-collection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-velociraptor-for-ir-collection, .gemini/skills/implementing-velociraptor-for-ir-collection, .github/skills/implementing-velociraptor-for-ir-collection and .opencode/skills/implementing-velociraptor-for-ir-collection in your project.

What does Implementing Velociraptor For Ir Collection need to run?

Going by SKILL.md and its folder, Implementing Velociraptor For Ir Collection needs Python for the scripts in its folder and the command-line tools its instructions call (wget and docker). Our summary lists: Python 3; Docker.

Does Implementing Velociraptor For Ir Collection access the network?

SKILL.md names 5 domains. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. As links in the text: docs.velociraptor.app, rapid7.com, cisa.gov and pentestpartners.com. This is read from the text; nothing was executed.

Is Implementing Velociraptor For Ir Collection safe to install?

Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Implementing Velociraptor For Ir Collection use?

Implementing Velociraptor For Ir Collection is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Implementing Velociraptor For Ir Collection use?

About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to Implementing Velociraptor For Ir Collection?

Skills that share tags, products or a category with Implementing Velociraptor For Ir Collection: Forensics Osquery (AgentSecOps/SecOpsAgentKit, 220 stars), Openclaw Live Updater (openclaw/openclaw, 392k stars), .NET Crash Dump Collection (dotnet/skills, 5.6k stars) and Release All (paperboytm/spool, 592 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implementing Velociraptor For Ir Collection?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.