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OWASP/www-project-top-10-for-large-language-model-applications

Default branch main · commit 02059576 · scanned 5/17/2026, 5:11:15 AM

GitHub: 1,250 stars · 312 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
20 /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
0 / 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 OWASP/www-project-top-10-for-large-language-model-applications, 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 the project's nature as a security guideline in the README's opening

    Why:

    CURRENT
    The core definition 'The OWASP Top 10 for Large Language Model Applications is a standard awareness document...' appears under '## Overview and Audience 🗣️'.
    COPY-PASTE FIX
    # OWASP Top 10 for Large Language Model Applications

The OWASP Top 10 for Large Language Model Applications is a standard awareness document for developers and web application security. It represents a broad consensus about the most critical security risks to Large Language Model (LLM) applications. This repository contains the official content for this project, which is housed under the comprehensive **OWASP GenAI Security Project**.

Visit our main project site: genai.owasp.org
  • mediumtopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    ai, appsec, llm, llm-security
    COPY-PASTE FIX
    ai, appsec, llm, llm-security, ai-security-guidelines, llm-security-standards, generative-ai-risk, security-best-practices
  • lowlicense#3
    Clarify the project's license directly in the README

    Why:

    COPY-PASTE FIX
    ## License

This project is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). For details, see the [LICENSE](LICENSE) file.

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 OWASP/www-project-top-10-for-large-language-model-applications
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AWS API Gateway
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. AWS API Gateway · recommended 2×
  2. Azure API Management · recommended 2×
  3. NVIDIA/NeMo-Guardrails · recommended 1×
  4. microsoft/presidio · recommended 1×
  5. Lakera Guard · recommended 1×
  • CATEGORY QUERY
    What are the most critical security vulnerabilities when building large language model applications?
    you: not recommended
    AI recommended (in order):
    1. NeMo Guardrails (NVIDIA/NeMo-Guardrails)
    2. Presidio (microsoft/presidio)
    3. Lakera Guard
    4. Microsoft Purview DLP
    5. Google Cloud DLP
    6. Symantec DLP
    7. OAuth 2.0
    8. OpenID Connect
    9. AWS API Gateway
    10. Azure API Management
    11. Kong Gateway (Kong/kong)
    12. Cloudflare
    13. NGINX (nginx/nginx)
    14. AWS API Gateway
    15. Azure API Management
    16. Snyk
    17. OWASP Dependency-Check (jeremylong/DependencyCheck)
    18. Black Duck
    19. OpenAI
    20. Google
    21. Anthropic
    22. Hugging Face Hub
    23. Aqua Security
    24. Twistlock

    AI recommended 24 alternatives but never named OWASP/www-project-top-10-for-large-language-model-applications. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find best practices for securing generative AI applications against common threats?
    you: not recommended
    AI recommended (in order):
    1. OWASP Top 10 for Large Language Model Applications (LLM Top 10)
    2. NIST AI Risk Management Framework (AI RMF)
    3. Microsoft Azure AI Security Best Practices
    4. Google Cloud AI Security Best Practices
    5. Hugging Face Security Best Practices
    6. MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems)

    AI recommended 6 alternatives but never named OWASP/www-project-top-10-for-large-language-model-applications. 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 OWASP/www-project-top-10-for-large-language-model-applications?
    pass
    AI did not name OWASP/www-project-top-10-for-large-language-model-applications — 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 OWASP/www-project-top-10-for-large-language-model-applications in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name OWASP/www-project-top-10-for-large-language-model-applications — 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?

  • In one sentence, what problem does the repo OWASP/www-project-top-10-for-large-language-model-applications solve, and who is the primary audience?
    pass
    AI did not name OWASP/www-project-top-10-for-large-language-model-applications — 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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OWASP/www-project-top-10-for-large-language-model-applications — 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