Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add adriannoes/awesome-agentic-ai --skill implementing-velociraptor-for-ir-collectiongit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-velociraptor-for-ir-collection)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-velociraptor-for-ir-collection"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/implementing-velociraptor-for-ir-collection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-velociraptor-for-ir-collection"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/implementing-velociraptor-for-ir-collection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Privilege Escalation · line 89 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
- medium Privilege Escalation · line 90 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
- medium MCP Rug Pull · line 111 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.02272 |
| Opus 5.5 | $0.00020 | $0.00909 |
| Sonnet 5.5 | $0.00010 | $0.00454 |
| Haiku 4.5 | $0.00005 | $0.00227 |
Grade B, and why
implementing-velociraptor-for-ir-collection scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo cp velociraptor-linux-amd64 /usr/local/bin/velociraptor Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
wget https://github.com/Velocidex/velociraptor/releases/latest/download/velociraptor-linux-amd64 How it starts
The opening of the file, as written. The whole thing — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 304 lines · 50 tokens per session scan B 5b2b2950ff90
implementing-velociraptor-for-ir-collection is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (72 stars, last pushed 3d ago), licensed MIT. It adds 50 tokens to every session and 2,272 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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