RRepoGEO

REPOGEO REPORT · LITE

aliasrobotics/cai

Default branch main · commit 1c795071 · scanned 6/28/2026, 12:42:53 AM

GitHub: 9,240 stars · 1,366 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
40 /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
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 aliasrobotics/cai, 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
    Immediately clarify CAI's core purpose as an AI cybersecurity framework

    Why:

    CURRENT
    The first descriptive sentence after the initial badges and edition comparison is "Cybersecurity AI (CAI) is a lightweight, open-source framework that empowe".
    COPY-PASTE FIX
    Move a clear, concise statement of purpose directly under the H1, e.g., "Cybersecurity AI (CAI) is a lightweight, open-source framework designed for automated cybersecurity threat detection, pentesting, and securing large language models (LLMs) against adversarial attacks."
  • mediumreadme#2
    Add explicit license information to the README

    Why:

    COPY-PASTE FIX
    Add a section to the README, ideally near the top, that clearly states the specific license(s) under which CAI is distributed, referencing the existing LICENSE file.
  • lowtopics#3
    Refine GitHub topics for better specificity

    Why:

    CURRENT
    artificial-intelligence, cybersecurity, framework, generative-ai, llm, pentesting
    COPY-PASTE FIX
    artificial-intelligence, cybersecurity, framework, generative-ai, llm, pentesting, ai-security-framework, llm-security, ai-pentesting, threat-detection

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 aliasrobotics/cai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 · recommended 1×
  2. GPT-3.5 Turbo · recommended 1×
  3. Anthropic Claude · recommended 1×
  4. Google Gemini · recommended 1×
  5. huggingface/transformers · recommended 1×
  • CATEGORY QUERY
    How can I leverage generative AI models for automated cybersecurity threat detection and pentesting?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. GPT-3.5 Turbo
    3. Anthropic Claude
    4. Google Gemini
    5. Hugging Face Transformers Library (huggingface/transformers)
    6. BERT
    7. RoBERTa
    8. T5
    9. IBM Watson for Cybersecurity
    10. QRadar
    11. DeepMind AlphaCode
    12. Google DeepMind
    13. TensorFlow (tensorflow/tensorflow)
    14. PyTorch (pytorch/pytorch)
    15. Microsoft Security Copilot
    16. Microsoft Sentinel
    17. Defender

    AI recommended 17 alternatives but never named aliasrobotics/cai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source frameworks are available for securing large language models against adversarial attacks?
    you: not recommended
    AI recommended (in order):
    1. Adversarial Robustness Toolbox (ART) (IBM/adversarial-robustness-toolbox)
    2. TextAttack (TextAttack/TextAttack)
    3. OpenAttack (THUDM/OpenAttack)
    4. CleverHans (cleverhans-lab/cleverhans)
    5. Foolbox (bethgelab/foolbox)
    6. SecML (pralab/SecML)

    AI recommended 6 alternatives but never named aliasrobotics/cai. 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 aliasrobotics/cai?
    pass
    AI named aliasrobotics/cai explicitly

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

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

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

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aliasrobotics/cai — 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