RRepoGEO

REPOGEO REPORT · LITE

westonbrown/Cyber-AutoAgent

Default branch main · commit 54897ff9 · scanned 5/29/2026, 1:52:26 AM

GitHub: 530 stars · 130 forks

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 westonbrown/Cyber-AutoAgent, 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
  • highreadme#1
    Reposition the project's core purpose to appear before the archive notice

    Why:

    CURRENT
    <div align="center">

# ⚠️ PROJECT ARCHIVED

Cyber-AutoAgent started as an experimental side project to explore autonomous offensive security agents and black box pentesting. After achieving 85% on the XBOW valdiation benchmark and building an engaged community, it became clear this work requires dedicated full-time focus to reach production-grade maturity.
    COPY-PASTE FIX
    <div align="center">

# Cyber-AutoAgent: An experimental AI agent for autonomous offensive security and black box pentesting. ⚠️ PROJECT ARCHIVED

This project started as an experimental side project to explore autonomous offensive security agents and black box pentesting. After achieving 85% on the XBOW valdiation benchmark and building an engaged community, it became clear this work requires dedicated full-time focus to reach production-grade maturity.
  • mediumtopics#2
    Add more specific topics related to offensive security and LLM agents

    Why:

    CURRENT
    agents, autoagents, cybersecurity-tools, strands-agent
    COPY-PASTE FIX
    agents, autoagents, cybersecurity-tools, strands-agent, offensive-security, penetration-testing, red-teaming, llm-agents
  • lowhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/westonbrown/Cyber-AutoAgent

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 westonbrown/Cyber-AutoAgent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. AutoGPT · recommended 1×
  3. BabyAGI · recommended 1×
  4. PlexTrac · recommended 1×
  5. Intruder · recommended 1×
  • CATEGORY QUERY
    How can I automate black-box penetration testing using AI agents for security assessments?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGPT
    3. BabyAGI
    4. PlexTrac
    5. Intruder
    6. ImmuniWeb AI Platform
    7. AFL++
    8. Boofuzz

    AI recommended 8 alternatives but never named westonbrown/Cyber-AutoAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help with intelligent offensive security assessments using LLMs for dynamic tool selection?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. LangChain
    3. LlamaIndex
    4. Hugging Face Transformers
    5. Microsoft Azure OpenAI Service
    6. Google Cloud Vertex AI
    7. Cortex

    AI recommended 7 alternatives but never named westonbrown/Cyber-AutoAgent. 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 westonbrown/Cyber-AutoAgent?
    pass
    AI named westonbrown/Cyber-AutoAgent explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of westonbrown/Cyber-AutoAgent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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westonbrown/Cyber-AutoAgent — 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