RRepoGEO

REPOGEO REPORT · LITE

aws-samples/aws-incident-response-playbooks

Default branch master · commit 83b954a8 · scanned 5/26/2026, 5:11:44 AM

GitHub: 1,057 stars · 223 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface aws-samples/aws-incident-response-playbooks, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise 'About' description

    Why:

    COPY-PASTE FIX
    Sample incident response playbooks and AI-driven playbooks (for LLMs/IDEs) to help organizations respond to security incidents in AWS environments, following NIST guidelines.
  • hightopics#2
    Add relevant topics

    Why:

    COPY-PASTE FIX
    aws, incident-response, security, playbooks, templates, cloud-security, nist, llm, ai-driven, devsecops
  • mediumreadme#3
    Clarify the README's opening to differentiate from generic guides and SOAR platforms

    Why:

    CURRENT
    ## AWS Incident Response Playbook Samples These playbooks and ai-playbooks are created to be used as templates only. They should be customized by administrators working with AWS to suit their particular needs, risks, available tools and work processes. These guides are not official AWS documentation and are provided as-is to customers using AWS products and who are looking to improve their incident response capability.
    COPY-PASTE FIX
    ## AWS Incident Response Playbook Samples: Customizable Templates for Human and AI-Assisted Response These playbooks and ai-playbooks provide actionable, customizable templates for responding to security incidents in AWS environments. Unlike generic guides or full SOAR platforms, this repository offers practical, human-readable markdown playbooks and AI-consumable "steering files" for LLM-integrated development environments. They are designed to be adapted by administrators to suit specific needs, risks, available tools, and work processes, aligning with NIST Computer Security Incident Handling Guide principles.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface aws-samples/aws-incident-response-playbooks
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NIST Special Publication 800-61 Revision 2, Computer Security Incident Handling Guide
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NIST Special Publication 800-61 Revision 2, Computer Security Incident Handling Guide · recommended 1×
  2. AWS Security Incident Response Guide · recommended 1×
  3. Azure Security Incident Response Guide · recommended 1×
  4. Google Cloud Incident Response Playbooks · recommended 1×
  5. SANS Institute Incident Handler's Handbook · recommended 1×
  • CATEGORY QUERY
    Need templates for handling security incidents in cloud environments, following best practices.
    you: not recommended
    AI recommended (in order):
    1. NIST Special Publication 800-61 Revision 2, Computer Security Incident Handling Guide
    2. AWS Security Incident Response Guide
    3. Azure Security Incident Response Guide
    4. Google Cloud Incident Response Playbooks
    5. SANS Institute Incident Handler's Handbook
    6. Cloud Security Alliance (CSA) Cloud Incident Response Framework

    AI recommended 6 alternatives but never named aws-samples/aws-incident-response-playbooks. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for automated incident response guides or AI-driven playbooks for cloud security.
    you: not recommended
    AI recommended (in order):
    1. Palo Alto Networks Cortex XSOAR
    2. Splunk SOAR
    3. IBM Security QRadar SOAR
    4. Microsoft Sentinel
    5. Swimlane
    6. Rapid7 InsightConnect
    7. ServiceNow Security Operations (SecOps)

    AI recommended 7 alternatives but never named aws-samples/aws-incident-response-playbooks. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of aws-samples/aws-incident-response-playbooks?
    pass
    AI did not name aws-samples/aws-incident-response-playbooks — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts aws-samples/aws-incident-response-playbooks in production, what risks or prerequisites should they evaluate first?
    pass
    AI named aws-samples/aws-incident-response-playbooks explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo aws-samples/aws-incident-response-playbooks solve, and who is the primary audience?
    pass
    AI did not name aws-samples/aws-incident-response-playbooks — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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