RRepoGEO

REPOGEO REPORT · LITE

BlackSnufkin/LitterBox

Default branch main · commit a609527c · scanned 5/27/2026, 6:02:14 PM

GitHub: 1,432 stars · 161 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 BlackSnufkin/LitterBox, 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
    Clarify the AI's role in the README's opening statement

    Why:

    CURRENT
    A self-hosted payload-analysis sandbox for red teams.
    COPY-PASTE FIX
    LitterBox is a self-hosted payload-analysis sandbox for red teams, designed to test offensive payloads against modern detection before deployment. It leverages MCP integration with an LLM agent to drive end-to-end analysis, providing automated insights into payload behavior and EDR evasion within the sandbox environment.
  • highhomepage#2
    Add the homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://deepwiki.com/BlackSnufkin/LitterBox
  • mediumtopics#3
    Refine topics to emphasize EDR testing and clarify AI's role

    Why:

    CURRENT
    ai, docker-compose, malware-analysis, malware-development, mcp, mcp-server, offensive-security, redteam, sandbox
    COPY-PASTE FIX
    ai, docker-compose, edr-testing, llm-agent, malware-analysis, malware-development, mcp, offensive-security, payload-analysis, redteam, sandbox, threat-emulation

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 BlackSnufkin/LitterBox
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Cobalt Strike
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Cobalt Strike · recommended 1×
  2. Mythic · recommended 1×
  3. Sliver · recommended 1×
  4. VMware Workstation/ESXi · recommended 1×
  5. VirtualBox · recommended 1×
  • CATEGORY QUERY
    How can red teams test offensive payloads against EDRs before deployment?
    you: not recommended
    AI recommended (in order):
    1. Cobalt Strike
    2. Mythic
    3. Sliver
    4. VMware Workstation/ESXi
    5. VirtualBox
    6. Hyper-V
    7. AWS EC2
    8. Azure VMs
    9. ScareCrow
    10. Inceptor
    11. sRDI
    12. Sysmon
    13. Elastic Agent
    14. Winlogbeat
    15. Elastic Security
    16. Splunk Universal Forwarder
    17. Splunk Enterprise Security
    18. x64dbg
    19. ConfuserEx
    20. Obfuscar
    21. PyInstaller
    22. Nuitka

    AI recommended 22 alternatives but never named BlackSnufkin/LitterBox. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a self-hosted malware analysis sandbox with AI-driven detection insights.
    you: not recommended
    AI recommended (in order):
    1. ANY.RUN
    2. Cuckoo Sandbox
    3. VMRay Analyzer
    4. Intezer Analyze
    5. Joe Sandbox

    AI recommended 5 alternatives but never named BlackSnufkin/LitterBox. 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 BlackSnufkin/LitterBox?
    pass
    AI named BlackSnufkin/LitterBox explicitly

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

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