Imported from oyi77/1ai-skills (cybersecurity/deploying-osquery-for-endpoint-monitoring/SKILL.md). Install upstream with npx skills add oyi77/1ai-skills --skill deploying-osquery-for-endpoint-monitoring. Copyright stays with the author (Apache-2.0).

Deploying Osquery For Endpoint Monitoring

Overview

Cybersecurity skill for deploying osquery for endpoint monitoring. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "deploying osquery for endpoint monitoring"
• "Deploying osquery across Windows, macOS, and Linux endpoints for fleet-wide visi"
• "Building threat hunting queries using osquery's SQL interface"
• "Monitoring endpoint compliance (installed software, open ports, running services"

Use this skill when:

• Deploying osquery across Windows, macOS, and Linux endpoints for fleet-wide visibility
• Building threat hunting queries using osquery's SQL interface
• Monitoring endpoint compliance (installed software, open ports, running services)
• Integrating osquery data with SIEM or Kolide/Fleet for centralized management

Do not use for real-time alerting (osquery is periodic/on-demand; use EDR for real-time).

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Osquery package for target OS (https://osquery.io/downloads)
• Fleet management server (Kolide Fleet or FleetDM) for enterprise deployment
• TLS certificates for secure agent-to-server communication
• Log aggregation pipeline (Filebeat, Fluentd) for osquery result logs

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. Define Objectives — Clarify the goals and scope for osquery.
2. Gather Resources — Collect tools, data, and access needed for osquery.
3. Execute Process — Carry out osquery operations methodically.
4. Verify Quality — Check results against acceptance criteria.
5. Document Outcomes — Record findings, decisions, and next steps.

Tools

• endpoint monitoring — Primary tool for this skill
• Analysis Platform — Data processing and visualization
• Collaboration Tools — Team coordination and knowledge sharing

Process

1. Design — Define interface, identify patterns, plan implementation
2. Implement — Write code following existing conventions, add tests
3. Verify — Run tests, check integration, validate behavior

Verification

• All osquery procedures executed completely and documented
• Findings validated against multiple data sources
• False positives identified and filtered
• Results documented with evidence and timestamps
• Recommendations provided with risk-based prioritization

Anti-Rationalization Table