RRepoGEO

REPOGEO REPORT · LITE

mrwadams/attackgen

Default branch main · commit 228ef9b0 · scanned 5/19/2026, 7:26:56 AM

GitHub: 1,218 stars · 163 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 mrwadams/attackgen, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition README opening to emphasize cybersecurity domain and audience

    Why:

    CURRENT
    AttackGen is a cybersecurity incident response testing tool that leverages the power of large language models and the comprehensive MITRE ATT&CK and ATLAS frameworks. The tool generates tailored incident response scenarios based on user-selected threat actor groups, AI attack case studies, and your organisation's details.
    COPY-PASTE FIX
    AttackGen is a **specialized cybersecurity incident response testing tool** designed for security teams and incident responders. It leverages large language models and the comprehensive MITRE ATT&CK and ATLAS frameworks to generate tailored incident response scenarios based on user-selected threat actor groups, AI attack case studies, and your organisation's details, helping organizations proactively test and validate their incident response plans.
  • mediumhomepage#2
    Add a project homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/mrwadams/attackgen

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 mrwadams/attackgen
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4 / GPT-3.5 Turbo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
  2. Anthropic Claude 3 · recommended 1×
  3. Google Gemini · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. Llama 2 · recommended 1×
  • CATEGORY QUERY
    How to generate realistic cybersecurity incident response scenarios using AI?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. Anthropic Claude 3
    3. Google Gemini
    4. Hugging Face Transformers
    5. Llama 2
    6. Falcon
    7. Microsoft Azure OpenAI Service
    8. AWS Bedrock
    9. Mistral 7B
    10. Zephyr

    AI recommended 10 alternatives but never named mrwadams/attackgen. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to simulate cyber attacks for incident response plan validation with MITRE ATT&CK?
    you: not recommended
    AI recommended (in order):
    1. Mandiant Advantage
    2. Picus Security
    3. AttackIQ
    4. Cymulate
    5. Safeguard Cyber
    6. Palo Alto Networks Cortex Xpanse
    7. Cortex XDR
    8. Cortex XSOAR
    9. Red Canary

    AI recommended 9 alternatives but never named mrwadams/attackgen. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 mrwadams/attackgen?
    pass
    AI named mrwadams/attackgen explicitly

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

  • If a team adopts mrwadams/attackgen in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mrwadams/attackgen 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 mrwadams/attackgen solve, and who is the primary audience?
    pass
    AI named mrwadams/attackgen explicitly

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

Embed your GEO score

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MARKDOWN (README)
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mrwadams/attackgen — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite