For cybersecurity professionals deploying AI across investigation, detection, response, governance, and team operations
Claude for Security Professionals
Integrate AI into your security workflow — investigation, detection, reporting, and automation.
Use AI as a force multiplier across security operations. Build AI-assisted investigation methodologies, generate and validate detection rules, draft incident response documentation at machine speed, automate compliance and policy work, deploy Claude Code for security scripting, and implement the governance framework that keeps AI use trustworthy.
Text-based · Persistent labs on your own hardware · 2 free modules available now · Content last updated: May 2026
What you'll be able to do
AI as an operational multiplier
This course teaches you to integrate AI into security operations workflows — investigation, detection engineering, IR reporting, governance, and automation. Every module produces a deployable asset: prompt libraries, detection templates, governance frameworks, and deployment playbooks. The methodology is platform-agnostic — examples use Claude but the techniques transfer to any AI assistant.
Who this course is for
Security operations practitioners. You investigate incidents, write detection rules, and manage security programs. This course teaches you to use AI to accelerate these workflows — not replace them.
Security managers building AI capability. You need to deploy AI across your team with governance, measurement, and a business case for leadership.
Anyone responsible for AI governance in a security context. Shadow AI detection, acceptable use policies, data classification, and AI incident response.
Anyone with a genuine interest in Claude for security. Whatever your background — whether you're transitioning from another domain, early in your career, or exploring a new direction — if the subject interests you and you're willing to put in the work, this course is for you. Backgrounds vary. Motivation is what matters.
Environment-agnostic
This course is not tied to Microsoft 365. The investigation methodology, detection engineering process, governance frameworks, and automation patterns apply to any security environment. Examples use KQL and Sentinel for illustration, but every technique translates to Splunk, CrowdStrike, Elastic, or any other platform. Updated for Claude Code, Cowork, MCP Connectors, and Computer Use.
What this produces
AI-assisted investigation methodologies, detection rule generation workflows, IR documentation templates, compliance automation procedures, and an AI governance framework. The operational AI toolkit for security teams — with the adversarial risk assessment that keeps it trustworthy.
What you will be able to do
1. Integrate AI into investigation workflows — using structured prompts to accelerate alert triage, evidence analysis, and IOC correlation across any SIEM or EDR platform.
2. Build a detection engineering pipeline with AI assistance — converting threat advisories into deployed detection rules using repeatable prompt templates and testing frameworks.
3. Generate IR reports and executive communications using AI-assisted drafting with verification discipline.
4. Deploy an AI governance framework — shadow AI detection, acceptable use policies, data classification, and AI incident response procedures.
5. Build organizational AI capability — team onboarding, role-specific configurations, ROI measurement, and a 12-month AI capability roadmap.
Course at a glance
Modules: 11 (C0–C10)
Estimated duration: 20–25 hours (self-paced)
Format: Written content — worked prompt examples, SVG diagrams, deployable artifacts, knowledge checks
Free content: C0 (1 module) — no account required
Paid content: C1–C10 (10 modules) — Premium or Team subscription
Platform: Updated for Claude Code, Cowork, MCP Connectors, and Computer Use
Typical pace: ~5-10 weeks at 5 hrs/week
MITRE ATT&CK coverage: 15 techniques mapped
Built by Ridgeline Cyber
Ridgeline Cyber Defence builds security operations training grounded in practical and operational experience. The team behind this course runs CSOC operations across on-prem, Splunk, and Microsoft 365 security stacks, Cisco and Palo Alto networks, and managed SOC partnerships.
Experience spans detection engineering, incident response, and DFIR investigation across on-prem, M365, and Linux environments — including leading cyber incident response engagements, deploying security controls and managing Governance, Risk and Compliance operations.
The investigation scenarios in this course are grounded in that operational work. The techniques, decision points, and mistakes are drawn from real investigations, sanitized and adapted for training.
What this course does NOT cover
Deliberate scope boundaries. If any of these is your primary need, the sibling course is the better fit.
- Traditional SOC operations and alert triage — see SOC Operations
- Classical detection engineering without LLMs — see Detection Engineering
Technical requirements
AI assistant account: Claude Pro/Team or equivalent with project/workspace capability.
Security operations environment: Access to any SIEM and EDR platform for the investigation and detection modules. The course uses M365 and Sentinel for examples but the methodology is platform-agnostic.
Prerequisite: Complete Claude Essentials for Security Professionals or have equivalent AI tool experience.
How to get the most from this course
Recommended pace: 1–2 modules per week, 20–25 hours total over 5–8 weeks.
Each module produces a deployable asset. Start with whichever matches your most immediate operational need.
Verify everything. AI-assisted output requires verification discipline. The course teaches you when and how to verify — this is the skill that separates productive AI use from dangerous AI use.
Support and community
Questions about course content: training@ridgelinecyber.com
Billing and account management: Self-service via your account page or training@ridgelinecyber.com
LinkedIn: Follow Ridgeline Cyber for operational security content and course updates
Course Syllabus
Four tracks. C0 is free — no account required.
Free Foundations
00Operational Skills
02Governance and Risk
06Strategic Deployment
08What you get that you will not find elsewhere
This is not a prompt engineering course. Prompt engineering courses teach generic techniques. This course teaches AI-assisted security operations — how to use AI effectively for investigation, detection engineering, threat analysis, and reporting within your security workflow.
Security-specific AI integration. Every prompt, every workflow, every technique is built for security practitioners working with real security data. Not generic business AI.
The human judgment boundary. Where AI accelerates and where human expertise must remain. The course teaches both — and the verification discipline that keeps AI-assisted work trustworthy.
Where this course fits
AI-assisted techniques complement every other Ridgeline course. Practical IR uses AI for report drafting. Detection Engineering uses AI for rule specification. Threat Hunting uses AI for hypothesis generation.
This course teaches the AI integration skills those courses reference.
The outcome
You start copying prompts from Twitter. You finish with a systematic AI-assisted security workflow.
Security-specific AI workflows — investigation, detection, threat analysis, reporting.
Verification discipline — AI output validation techniques for security-critical decisions.
Measurable acceleration — time savings on investigation, documentation, and analysis tasks.
Prerequisites
Required: 1+ years in a security operations, detection engineering, or incident response role. Working knowledge of KQL, Sentinel, and security investigation methodology. Claude Essentials for Security Professionals or equivalent AI tool experience.
Recommended: Experience writing detection rules and investigating security incidents — the course applies Claude to these workflows directly.
Usage rights and disclaimer
Course materials: Licensed for individual professional development. You may use scripts, queries, detection rules, templates, and frameworks from this course in your professional work. You may not redistribute course content, share account credentials, or republish course materials.
Fictional environment: All scenarios use the fictional Northgate Engineering environment. Any resemblance to real organizations, incidents, or individuals is coincidental.
No legal advice: Compliance and regulatory content in this course is educational, not legal advice. Consult qualified legal counsel for obligations in your jurisdiction.
Version and changelog
Current version: 1.0 | Last updated: 2026
2026 — v1.0: Complete course. All 11 modules (C0–C10) active. Updated for Claude Code, Cowork, MCP Connectors, and Computer Use.
This course is actively maintained. Content is updated as the security landscape evolves.
End of Course Exam
Complete the course, then prove your skills under time pressure. Pass mark: 70. Earn your certificate with CPE credits.
Requires 80% course completion. One random scenario per attempt. Certificate issued on pass.