RRepoGEO

REPOGEO REPORT · LITE

haizelabs/llama3-jailbreak

Default branch master · commit d2a2c529 · scanned 6/14/2026, 1:06:55 AM

GitHub: 570 stars · 65 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 haizelabs/llama3-jailbreak, 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 relevant topics for LLM red-teaming and jailbreaking

    Why:

    COPY-PASTE FIX
    llm-jailbreak, llama3, red-teaming, ai-safety, vulnerability-research, adversarial-ai, prompt-engineering
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    (Create a LICENSE file in the root of the repository with your chosen open-source license, e.g., MIT or Apache-2.0.)
  • mediumreadme#3
    Clarify the README's opening to emphasize red-teaming and vulnerability research

    Why:

    CURRENT
    # A Trivial Jailbreak Against Llama 3

Zuck and Meta dropped the "OpenAI killer" Llama 3 on Thursday. It is no doubt a very impressive model.
    COPY-PASTE FIX
    # Llama 3 Jailbreak: A Trivial Programmatic Bypass for Red-Teaming and Vulnerability Research

This repository demonstrates a simple, programmatic method to bypass Llama 3's safety filters. It is intended for AI safety researchers, red teamers, and developers investigating model vulnerabilities. Zuck and Meta dropped the "OpenAI killer" Llama 3 on Thursday. It is no doubt a very impressive model.

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 haizelabs/llama3-jailbreak
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
meta-llama/llama-models
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. meta-llama/llama-models · recommended 1×
  2. mistralai/mistral-src · recommended 1×
  3. tiiuae/falcon-7b · recommended 1×
  4. CleverHans · recommended 1×
  5. Foolbox · recommended 1×
  • CATEGORY QUERY
    How can I programmatically bypass safety restrictions in large language models?
    you: not recommended
    AI recommended (in order):
    1. Llama 3 (meta-llama/llama-models)
    2. Mixtral (mistralai/mistral-src)
    3. Falcon (tiiuae/falcon-7b)

    AI recommended 3 alternatives but never named haizelabs/llama3-jailbreak. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What methods exist for red-teaming AI models to find security vulnerabilities?
    you: not recommended
    AI recommended (in order):
    1. CleverHans
    2. Foolbox
    3. ART (Adversarial Robustness Toolbox)
    4. BackdoorBench
    5. PyTorch
    6. TensorFlow
    7. Pandas
    8. NumPy
    9. MIA (Membership Inference Attack) by Google
    10. Gandalf (from Lakera AI)
    11. PromptBench
    12. Red Teaming LLMs (OpenAI's approach)
    13. ChipWhisperer
    14. perf
    15. SciPy

    AI recommended 15 alternatives but never named haizelabs/llama3-jailbreak. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 haizelabs/llama3-jailbreak?
    pass
    AI did not name haizelabs/llama3-jailbreak — 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 haizelabs/llama3-jailbreak in production, what risks or prerequisites should they evaluate first?
    pass
    AI named haizelabs/llama3-jailbreak 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 haizelabs/llama3-jailbreak solve, and who is the primary audience?
    pass
    AI named haizelabs/llama3-jailbreak explicitly

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

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haizelabs/llama3-jailbreak — 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