Leveraging AI to Review and Strengthen Your Incident Response Plan: A Proof of Concept
summary
A proof of concept uses free Google Gemini, Microsoft Copilot, and ChatGPT to evaluate an incident response plan against NIST 800‑61 R3 mapped to CSF 2.0, standardizing on 50 controls (41 from ChatGPT plus 8 detect controls from Copilot). Results vary: ChatGPT finds 22 gaps, Copilot 17, Gemini 9; Copilot supplies direct plan quotes and the most detailed fixes, Gemini invents some IDs, all require prompt tuning and human validation before adoption.
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chapters (17)
- 0:00AI-driven IRP review intro
- 1:05Manual IRP reviews limits
- 3:34AI augments IRP assessments
- 5:47Proof of concept setup and tools tested
- 7:13Prompt engineering for AI eval
- 9:25AI vs NIST CSF 2.0
- 12:17Manual review findings before AI testing
- 13:20AI gap analysis results
- 17:35AI plan improvement recs
- 20:08Can AI fill its own gaps
- 21:56Key findings and tool comparison
- 23:04AI risks in IRP reviews
- 24:51Humans essential in IR
- 25:33AI adoption guidance
- 27:22AI beyond IRP reviews
- 28:05AI vs modern cyber threats
- 29:12Final takeaways and call
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