Cheatsheets

AI Prompts Cheatsheet for Incident Response

by n8n admin

🤖 AI Prompts Cheatsheet

Daniel Osei — AI-Assisted Security Engineer

Why AI Changes the Game for Incident Response

AI tools can significantly streamline the incident response process, allowing security teams to quickly analyze threats, gather evidence, and report findings. By leveraging AI for data analysis, pattern recognition, and automated reporting, organizations can improve response times and accuracy.

Before You Start: How to Set Context Properly

Setting the right context is crucial for getting useful outputs from AI. This involves clearly defining the scope of the incident, the type of data available, and the desired outcome of the interaction.

Core Prompts Cheatsheet

“Based on the recent incident where the organization faced a phishing attack, outline the steps taken for triaging the incident and mitigating further risks.”
“Generate a summary report of the last five security incidents, including key metrics and response times.”
“Create an evidence collection checklist that a security analyst should follow during a breach.”
“List common indicators of compromise (IoCs) for ransomware attacks, and explain how to track them.”
“What are the best practices for coordinating with law enforcement during a cyber incident?”
“Summarize the incident response process into five key phases and provide actionable steps for each phase.”
“Draft a communication plan template to notify stakeholders in case of a data breach incident.”
“Identify and describe the tools commonly used in the incident response phase, including their pros and cons.”
“Explain the significance of a post-incident review and what key metrics to track for continuous improvement.”
“Suggest methods for continuous endpoint monitoring to detect anomalies in real-time during an incident.”

Weak vs Strong Prompt Examples

❌ Weak: “How to handle incidents?”
✅ Strong: “Outline a step-by-step action plan for security analysts to manage a malware outbreak.”

Advanced Prompt Techniques

Prompt engineering is key for better AI results. Use these techniques:

  • Role Prompting: Define the AI’s role, e.g., “You are a cybersecurity expert…” to frame the responses.
  • Chain-of-Thought: Prompt the AI to explain its reasoning, e.g., “Explain the rationale behind each step you recommend for triage.”
  • Few-Shot Examples: Provide examples of expected output formats to guide the AI.
  • Output Formatting: Specify how you want the output structured clearly.

Claude vs ChatGPT: Which Works Better For This

Depending on the context and the specific details required for incident response scenarios, you may find one tool delivers better results than the other. Generally, ChatGPT (especially the latest models) excels with detailed prompt engineering and contextual understanding, while Claude may be more concise.

Tips for Getting Consistent Results

  • Be specific about the context and type of incident.
  • Iteratively refine your prompts based on outputs.
  • Use past incident reports as references for better context.
  • Experiment with varying levels of detail in your prompts to see what works best.

Quick Reference: All Prompts in One Place

1. Outline the steps for triaging a phishing incident.

2. Generate a summary report of last five incidents.

3. Create an evidence collection checklist.

4. List IoCs for ransomware.

5. Best practices for law enforcement coordination.

6. Summarize incident response phases with actionable steps.

7. Draft a communication plan template for data breaches.

8. Identify tools for incident response.

9. Explain post-incident reviews metrics.

10. Suggest continuous monitoring methods.

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