Step 1 – Start with an Alert

For example:

ALERT: Multiple failed logins

Source IP: 203.0.113.50
Target: server01
Username: admin

This alone doesn’t prove an attack.

It simply gives you something to investigate.

Step 2 – Ask AI for Triage Steps

Try:

I'm investigating this alert in an authorized environment.

Create a SOC triage workflow.

Start with:
1. Validate the alert
2. Gather additional evidence
3. Check related activity
4. Determine scope
5. Decide whether escalation is warranted

For each step, tell me what evidence I should look for.
Do not assume malicious activity without evidence.

AI can turn the single alert into an investigation plan.

Step 3 – Feed It additional evidence

Suppose you discover:

Failed login: 13:41
Failed login: 13:42
Failed login: 13:43
Successful login: 13:44

Source IP: 203.0.113.50
Username: admin

Give the new information to AI:

Update the investigation based on this new evidence.

Identify:
- confirmed facts
- unanswered questions
- additional logs to check
- possible explanations

Do not conclude that the account was compromised without supporting evidence.

This creates an iterative investigation rather than a single AI-generated answer.

Step 4 – Generate the Investigation Report

Once you’ve collected enough evidence:

Create a concise incident investigation report containing:

- Alert
- Timeline
- Evidence
- Findings
- Unknowns
- Actions taken
- Recommended follow-up

Clearly separate confirmed facts from assumptions.

The Mini SOC Workflow

Alert
 ↓
Triage
 ↓
Evidence
 ↓
Investigation
 ↓
Scope
 ↓
Decision
 ↓
Report

The interesting part is that AI isn’t making the final security decision. It’s helping organize the investigation, suggest useful questions, and turn scattered evidence into a structured workflow. For a home lab, SOC training environment, or internal security exercise, this is a simple way to experiment with AI-assisted incident response.