RRepoGEO

REPOGEO REPORT · LITE

protectai/ai-exploits

Default branch main · commit 0df6408c · scanned 5/17/2026, 2:56:49 PM

GitHub: 1,720 stars · 157 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 protectai/ai-exploits, 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
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-security, ml-security, machine-learning-security, ai-exploits, vulnerability-research, red-teaming, adversarial-ai, cybersecurity, infosec, metasploit, nuclei-templates
  • mediumreadme#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is released under [describe the actual license(s) here, e.g., 'a custom license combining elements of X and Y']. Please see the [LICENSE](LICENSE) file for full details.
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://protectai.com/

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 protectai/ai-exploits
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NGINX
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. NGINX · recommended 2×
  2. MITRE ATLAS · recommended 1×
  3. IBM Adversarial Robustness Toolbox (ART) · recommended 1×
  4. CleverHans Library · recommended 1×
  5. OWASP Top 10 for Large Language Model Applications (LLM Top 10) · recommended 1×
  • CATEGORY QUERY
    Where can I find practical examples of security exploits targeting AI/ML infrastructure?
    you: not recommended
    AI recommended (in order):
    1. MITRE ATLAS
    2. IBM Adversarial Robustness Toolbox (ART)
    3. CleverHans Library
    4. OWASP Top 10 for Large Language Model Applications (LLM Top 10)
    5. Hugging Face Security & Responsible AI Documentation
    6. Kaggle

    AI recommended 6 alternatives but never named protectai/ai-exploits. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are common attack patterns and vulnerabilities in machine learning systems and tools?
    you: not recommended
    AI recommended (in order):
    1. Foolbox
    2. CleverHans
    3. Great Expectations
    4. Pandera
    5. Opacus
    6. TensorFlow Privacy
    7. Microsoft SEAL
    8. HElib
    9. NGINX
    10. AWS API Gateway
    11. OpenMined's PySyft
    12. Isolation Forest
    13. One-Class SVM
    14. SHAP
    15. LIME
    16. ART - Adversarial Robustness Toolbox by IBM
    17. Snyk
    18. Black Duck
    19. Hugging Face Hub
    20. TensorFlow Hub
    21. AWS Shield
    22. Azure DDoS Protection
    23. HAProxy
    24. NGINX

    AI recommended 24 alternatives but never named protectai/ai-exploits. 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 protectai/ai-exploits?
    pass
    AI named protectai/ai-exploits explicitly

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

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

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

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protectai/ai-exploits — 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