RRepoGEO

REPOGEO REPORT · LITE

PromptLabs/Prompt-Hacking-Resources

Default branch main · commit 2db3931e · scanned 6/15/2026, 8:42:58 PM

GitHub: 584 stars · 70 forks

AI VISIBILITY SCORE
22 /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
1 / 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 PromptLabs/Prompt-Hacking-Resources, 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
    Add a clarifying sentence to the README's introduction

    Why:

    COPY-PASTE FIX
    This repository is a curated collection of learning materials and research references, designed to help you understand and explore AI model vulnerabilities, red teaming, and prompt injection techniques. It is not an active tool, framework, or API for securing LLMs.
  • mediumhomepage#2
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://learnprompting.org

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 PromptLabs/Prompt-Hacking-Resources
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OWASP Top 10 for Large Language Model Applications (LLM Top 10)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OWASP Top 10 for Large Language Model Applications (LLM Top 10) · recommended 1×
  2. MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) · recommended 1×
  3. Hugging Face · recommended 1×
  4. Google's Responsible AI Toolkit · recommended 1×
  5. Microsoft's AI Red Team · recommended 1×
  • CATEGORY QUERY
    Where can I find resources to learn about AI model vulnerability testing and red teaming?
    you: not recommended
    AI recommended (in order):
    1. OWASP Top 10 for Large Language Model Applications (LLM Top 10)
    2. MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems)
    3. Hugging Face
    4. Google's Responsible AI Toolkit
    5. Microsoft's AI Red Team
    6. Adversarial ML Threat Matrix
    7. NeurIPS
    8. ICML
    9. Black Hat
    10. DEF CON

    AI recommended 10 alternatives but never named PromptLabs/Prompt-Hacking-Resources. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How do I secure large language models against prompt injection and adversarial attacks?
    you: not recommended
    AI recommended (in order):
    1. Guardrails AI
    2. Microsoft Azure AI Content Safety
    3. NVIDIA NeMo Guardrails
    4. Lakera Guard
    5. OpenAI Moderation API
    6. Rebuff
    7. LangChain Expression Language (LCEL)

    AI recommended 7 alternatives but never named PromptLabs/Prompt-Hacking-Resources. 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 PromptLabs/Prompt-Hacking-Resources?
    pass
    AI did not name PromptLabs/Prompt-Hacking-Resources — likely talking about a different project

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

  • If a team adopts PromptLabs/Prompt-Hacking-Resources in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PromptLabs/Prompt-Hacking-Resources 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 PromptLabs/Prompt-Hacking-Resources solve, and who is the primary audience?
    pass
    AI did not name PromptLabs/Prompt-Hacking-Resources — likely talking about a different project

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

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PromptLabs/Prompt-Hacking-Resources — 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