RRepoGEO

REPOGEO REPORT · LITE

NoDataFound/hackGPT

Default branch main · commit b3981418 · scanned 5/21/2026, 7:38:12 PM

GitHub: 1,189 stars · 293 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
28 /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
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 NoDataFound/hackGPT, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository with a standard open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that reflects the project's intended usage.
  • mediumtopics#2
    Refine repository topics for better categorization

    Why:

    CURRENT
    chatbot, chatgpt, chatgpt-api, chatgpt-app, chatgpt-python, chatgpt3, chatgpt4, malware, malwareanalysis, managers, openai, openai-api, python
    COPY-PASTE FIX
    llm-security, red-teaming, offensive-security, vulnerability-analysis, exploit-generation, threat-intelligence, malware-analysis, chatgpt, openai, python, ai-security, prompt-engineering

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 NoDataFound/hackGPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
CodeQL
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. CodeQL · recommended 1×
  2. OpenAI GPT-4 · recommended 1×
  3. Google Gemini Advanced · recommended 1×
  4. GitHub Copilot Enterprise · recommended 1×
  5. huggingface/transformers · recommended 1×
  • CATEGORY QUERY
    How to automate vulnerability analysis and exploit generation using large language models?
    you: not recommended
    AI recommended (in order):
    1. CodeQL
    2. OpenAI GPT-4
    3. Google Gemini Advanced
    4. GitHub Copilot Enterprise
    5. Hugging Face Transformers (huggingface/transformers)
    6. CodeBERT
    7. CodeT5
    8. InCoder
    9. Semgrep (returntocorp/semgrep)
    10. Prowler (prowler-cloud/prowler)
    11. Metasploit Framework (rapid7/metasploit-framework)

    AI recommended 11 alternatives but never named NoDataFound/hackGPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Python tool to integrate AI chatbots for malware analysis and threat data parsing.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex

    AI recommended 2 alternatives but never named NoDataFound/hackGPT. 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 NoDataFound/hackGPT?
    pass
    AI did not name NoDataFound/hackGPT — 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 NoDataFound/hackGPT in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NoDataFound/hackGPT 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 NoDataFound/hackGPT solve, and who is the primary audience?
    pass
    AI named NoDataFound/hackGPT 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 NoDataFound/hackGPT. 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/NoDataFound/hackGPT.svg)](https://repogeo.com/en/r/NoDataFound/hackGPT)
HTML
<a href="https://repogeo.com/en/r/NoDataFound/hackGPT"><img src="https://repogeo.com/badge/NoDataFound/hackGPT.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

NoDataFound/hackGPT — 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