RRepoGEO

REPOGEO REPORT · LITE

cyberark/FuzzyAI

Default branch main · commit 8184b966 · scanned 5/26/2026, 4:22:27 PM

GitHub: 1,440 stars · 202 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 cyberark/FuzzyAI, 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 README's opening sentence to clarify its purpose

    Why:

    CURRENT
    The FuzzyAI Fuzzer is a powerful tool for automated LLM fuzzing. It is designed to help developers and security researchers identify jailbreaks and mitigate potential security vulnerabilities in their LLM APIs.
    COPY-PASTE FIX
    FuzzyAI is a dedicated **LLM security fuzzing framework** designed to automatically identify and mitigate jailbreaks and vulnerabilities in Large Language Models. It provides a powerful, automated approach for developers and security researchers to red-team their LLM APIs.
  • mediumabout#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add a relevant project homepage URL (e.g., a GitHub Pages site or project documentation) to the repository's 'About' section.
  • lowcomparison#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README titled 'Comparison with LLM Security Fuzzers' or 'How FuzzyAI Compares' that briefly outlines its unique strengths relative to tools like Garak, LLM Guard, or Prompt Security.

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 cyberark/FuzzyAI
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Garak
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Garak · recommended 1×
  2. LLM Guard · recommended 1×
  3. Prompt Security · recommended 1×
  4. Gradiant · recommended 1×
  5. Rebuff · recommended 1×
  • CATEGORY QUERY
    How can I automatically test my LLM for security vulnerabilities and jailbreak attempts?
    you: not recommended
    AI recommended (in order):
    1. Garak
    2. LLM Guard
    3. Prompt Security
    4. Gradiant
    5. Rebuff
    6. Adversa AI Platform
    7. OWASP Top 10 for LLM Applications
    8. Snyk
    9. Checkmarx

    AI recommended 9 alternatives but never named cyberark/FuzzyAI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking tools to evaluate large language model robustness against adversarial prompts and security exploits.
    you: not recommended
    AI recommended (in order):
    1. Garak (llm-attacks/garak)
    2. Adversarial GLUE (AdvGLUE) (microsoft/AdvGLUE)
    3. Robustness Gym (RobustnessGym/RobustnessGym)
    4. OpenAI Evals (openai/evals)
    5. SecAI (IBM/SecAI)
    6. IBM Adversarial Robustness Toolbox (ART) (Trusted-AI/adversarial-robustness-toolbox)

    AI recommended 6 alternatives but never named cyberark/FuzzyAI. 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 cyberark/FuzzyAI?
    pass
    AI named cyberark/FuzzyAI explicitly

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

  • If a team adopts cyberark/FuzzyAI in production, what risks or prerequisites should they evaluate first?
    pass
    AI named cyberark/FuzzyAI 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 cyberark/FuzzyAI solve, and who is the primary audience?
    pass
    AI named cyberark/FuzzyAI 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 cyberark/FuzzyAI. 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/cyberark/FuzzyAI.svg)](https://repogeo.com/en/r/cyberark/FuzzyAI)
HTML
<a href="https://repogeo.com/en/r/cyberark/FuzzyAI"><img src="https://repogeo.com/badge/cyberark/FuzzyAI.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

cyberark/FuzzyAI — 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