RRepoGEO

REPOGEO REPORT · LITE

Arcanum-Sec/arc_pi_taxonomy

Default branch main · commit 61d37139 · scanned 6/8/2026, 6:57:54 AM

GitHub: 629 stars · 107 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 Arcanum-Sec/arc_pi_taxonomy, 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 'PI' in the README's opening paragraph

    Why:

    CURRENT
    This repository provides a structured taxonomy of **prompt injection attacks**, categorizing different types of attack intents, techniques, and evasions.
    COPY-PASTE FIX
    This repository provides a structured taxonomy of **prompt injection (PI) attacks**, categorizing different types of attack intents, techniques, and evasions.
  • mediumtopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    prompt-injection, llm-security, ai-security, taxonomy, red-teaming, cybersecurity, large-language-models
  • lowreadme#3
    Add a license clarification to the README

    Why:

    COPY-PASTE FIX
    ## License

This project is licensed under a custom license. Please refer to the [LICENSE file](LICENSE) for the full terms and conditions.

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 Arcanum-Sec/arc_pi_taxonomy
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. Prompt Injection Attack and Defense (Anthropic) · recommended 1×
  3. Gandalf · recommended 1×
  4. NCC Group Research on LLM Security · recommended 1×
  5. Hugging Face Blog Posts and Discussions · recommended 1×
  • CATEGORY QUERY
    How can I categorize different types of prompt injection attacks and their techniques?
    you: not recommended
    Show full AI answer
  • CATEGORY QUERY
    What resources exist for AI developers to understand and prevent prompt injection vulnerabilities?
    you: not recommended
    AI recommended (in order):
    1. OWASP Top 10 for Large Language Model Applications (LLM Top 10)
    2. Prompt Injection Attack and Defense (Anthropic)
    3. Gandalf
    4. NCC Group Research on LLM Security
    5. Hugging Face Blog Posts and Discussions
    6. Microsoft Azure AI Security Documentation
    7. Google Cloud AI Security Best Practices

    AI recommended 7 alternatives but never named Arcanum-Sec/arc_pi_taxonomy. 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 Arcanum-Sec/arc_pi_taxonomy?
    pass
    AI named Arcanum-Sec/arc_pi_taxonomy explicitly

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

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

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

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Arcanum-Sec/arc_pi_taxonomy — 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