RRepoGEO

REPOGEO REPORT · LITE

Kim-Hammar/awesome-rl-for-cybersecurity

Default branch master · commit 6db96ecd · scanned 5/28/2026, 12:28:03 AM

GitHub: 1,057 stars · 145 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 Kim-Hammar/awesome-rl-for-cybersecurity, 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
    Clarify README opening to emphasize 'awesome list' project type

    Why:

    CURRENT
    A curated list of resources dedicated to reinforcement learning applied to cyber security.
    COPY-PASTE FIX
    This is an awesome list project: a curated collection of resources dedicated to reinforcement learning applied to cyber security.
  • mediumreadme#2
    Clarify license information in README

    Why:

    COPY-PASTE FIX
    ## License
    This project is licensed under the terms found in the [LICENSE](LICENSE) file. Please refer to the file for full details regarding usage and distribution.

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 Kim-Hammar/awesome-rl-for-cybersecurity
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Gym
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Gym · recommended 2×
  2. Stable Baselines3 · recommended 1×
  3. Microsoft Security Copilot · recommended 1×
  4. Cisco SecureX · recommended 1×
  5. Splunk SOAR · recommended 1×
  • CATEGORY QUERY
    How can I apply reinforcement learning techniques to enhance my cybersecurity systems?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym
    2. Stable Baselines3
    3. Microsoft Security Copilot
    4. Cisco SecureX
    5. Splunk SOAR
    6. RLlib
    7. Ray
    8. Malmo

    AI recommended 8 alternatives but never named Kim-Hammar/awesome-rl-for-cybersecurity. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources for learning about reinforcement learning in cyber defense?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym
    2. CyberBattleSim

    AI recommended 2 alternatives but never named Kim-Hammar/awesome-rl-for-cybersecurity. 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 Kim-Hammar/awesome-rl-for-cybersecurity?
    pass
    AI did not name Kim-Hammar/awesome-rl-for-cybersecurity — 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 Kim-Hammar/awesome-rl-for-cybersecurity in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Kim-Hammar/awesome-rl-for-cybersecurity 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 Kim-Hammar/awesome-rl-for-cybersecurity solve, and who is the primary audience?
    pass
    AI did not name Kim-Hammar/awesome-rl-for-cybersecurity — 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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Kim-Hammar/awesome-rl-for-cybersecurity — 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