RRepoGEO

REPOGEO REPORT · LITE

cmu-sei/GHOSTS

Default branch master · commit 2d28edce · scanned 6/14/2026, 3:16:52 PM

GitHub: 693 stars · 90 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 cmu-sei/GHOSTS, 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
    Refine the 'About' description for precision

    Why:

    CURRENT
    GHOSTS (General Human-Oriented Synthetic Teammates and Systems) is a realistic user simulation framework for cyber experimentation, simulation, training, and exercise
    COPY-PASTE FIX
    GHOSTS (General Human-Oriented Synthetic Teammates and Systems) is a framework for **simulating realistic human user behavior and network activity** in cyber environments, enabling high-fidelity **cybersecurity training, exercises, and research**.
  • highreadme#2
    Add a clarifying sentence to the README's opening

    Why:

    COPY-PASTE FIX
    Add this sentence immediately after the H1/tagline:
"Unlike attack simulation or red-teaming tools, GHOSTS focuses on generating authentic human-like activity and network traffic from simulated users for defensive training and research."
  • mediumtopics#3
    Add topics for AI/LLM agents

    Why:

    CURRENT
    behavior, cyber, cybersecurity, cybertraining, exercise, human, network-simulation, network-simulations, network-simulator, simulation, simulation-modeling, training, user-simulator
    COPY-PASTE FIX
    behavior, cyber, cybersecurity, cybertraining, exercise, human, network-simulation, network-simulations, network-simulator, simulation, simulation-modeling, training, user-simulator, llm-agents, ai-agents

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 cmu-sei/GHOSTS
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
splunk/attack_range
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. splunk/attack_range · recommended 1×
  2. mitre/caldera · recommended 1×
  3. redcanaryco/atomic-red-team · recommended 1×
  4. rapid7/metasploit-framework · recommended 1×
  5. locustio/locust · recommended 1×
  • CATEGORY QUERY
    How to simulate realistic human user behavior for cybersecurity training and exercises?
    you: not recommended
    AI recommended (in order):
    1. Splunk Attack Range (splunk/attack_range)
    2. Caldera (mitre/caldera)
    3. Atomic Red Team (redcanaryco/atomic-red-team)
    4. Metasploit Framework (rapid7/metasploit-framework)

    AI recommended 4 alternatives but never named cmu-sei/GHOSTS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Framework for generating realistic network traffic with AI-driven user agents for testing?
    you: not recommended
    AI recommended (in order):
    1. Locust (locustio/locust)
    2. scikit-learn (scikit-learn/scikit-learn)
    3. TensorFlow (tensorflow/tensorflow)
    4. PyTorch (pytorch/pytorch)
    5. Gatling (gatling/gatling)
    6. Deeplearning4j (deeplearning4j/deeplearning4j)
    7. H2O.ai (h2oai/h2o-3)
    8. k6 (grafana/k6)
    9. TensorFlow.js (tensorflow/tfjs)
    10. Brain.js (BrainJS/brain.js)
    11. BlazeMeter
    12. JMeter (apache/jmeter)
    13. Selenium (SeleniumHQ/selenium)

    AI recommended 13 alternatives but never named cmu-sei/GHOSTS. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 cmu-sei/GHOSTS?
    pass
    AI named cmu-sei/GHOSTS explicitly

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

  • If a team adopts cmu-sei/GHOSTS in production, what risks or prerequisites should they evaluate first?
    pass
    AI named cmu-sei/GHOSTS 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 cmu-sei/GHOSTS solve, and who is the primary audience?
    pass
    AI named cmu-sei/GHOSTS 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 cmu-sei/GHOSTS. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/cmu-sei/GHOSTS.svg)](https://repogeo.com/en/r/cmu-sei/GHOSTS)
HTML
<a href="https://repogeo.com/en/r/cmu-sei/GHOSTS"><img src="https://repogeo.com/badge/cmu-sei/GHOSTS.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

cmu-sei/GHOSTS — 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