RRepoGEO

REPOGEO REPORT · LITE

protectai/ai-exploits

Default branch main · commit 0df6408c · scanned 6/28/2026, 7:36:46 PM

GitHub: 1,733 stars · 163 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, relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-security, machine-learning-security, ml-exploits, vulnerability-research, adversarial-ai, security-exploits, proof-of-concept
  • highreadme#2
    Reposition the core definition of the repository to immediately follow the main heading in the README

    Why:

    CURRENT
    The AI world has a security problem and it's not just in the inputs given to LLMs such as ChatGPT. Based on research done by Protect AI and independent security experts on the Huntr Bug Bounty Platform, there are far more impactful and practical attacks against the tools, libraries and frameworks used to build, train, and deploy machine learning models. Many of these attacks lead to complete system takeovers and/or loss of sensitive data, models, or credentials most often without the need for authentication.
    COPY-PASTE FIX
    This repository, **AI Exploits**, is a curated collection of real-world exploits and scanning templates for responsibly disclosed vulnerabilities affecting machine learning tools, libraries, and frameworks. It aims to demystify practical attacks against AI/ML infrastructure and raise awareness of vulnerable components in the ecosystem. Based on research by Protect AI and independent security experts, these attacks demonstrate critical security problems beyond just LLM inputs, often leading to system takeovers or data loss.
  • mediumreadme#3
    Add a clear statement in the README explaining the terms of the existing license

    Why:

    COPY-PASTE FIX
    ## License
This project is released under the terms detailed in the `LICENSE` file. Please refer to that file for specific conditions and permissions.

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
MITRE ATLAS™
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. MITRE ATLAS™ · recommended 1×
  2. arXiv.org · recommended 1×
  3. Black Hat · recommended 1×
  4. DEF CON · recommended 1×
  5. Google AI Security Research Blog · recommended 1×
  • CATEGORY QUERY
    Where can I find examples of real-world security exploits targeting machine learning systems?
    you: not recommended
    AI recommended (in order):
    1. MITRE ATLAS™
    2. arXiv.org
    3. Black Hat
    4. DEF CON
    5. Google AI Security Research Blog
    6. Microsoft Security Blog
    7. IBM Security Research
    8. OWASP Top 10 for Machine Learning
    9. The Hacker News
    10. BleepingComputer
    11. Dark Reading
    12. ZDNet Security
    13. Robust Intelligence
    14. HiddenLayer
    15. Protect AI

    AI recommended 15 alternatives but never named protectai/ai-exploits. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are common attack vectors and vulnerabilities in AI/ML development and deployment environments?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow
    2. PyTorch
    3. scikit-learn
    4. Docker
    5. Kubernetes
    6. S3 buckets
    7. IAM roles

    AI recommended 7 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?

Embed your GEO score

Drop this badge into the README of protectai/ai-exploits. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/protectai/ai-exploits.svg)](https://repogeo.com/en/r/protectai/ai-exploits)
HTML
<a href="https://repogeo.com/en/r/protectai/ai-exploits"><img src="https://repogeo.com/badge/protectai/ai-exploits.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

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