REPOGEO REPORT · LITE

0xSteph/pentest-ai

Default branch main · commit 4fb2652a · scanned 6/3/2026, 7:41:37 AM

GitHub: 586 stars · 107 forks

AI VISIBILITY SCORE

33 /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

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 0xSteph/pentest-ai, 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

Reposition README H1 tagline to emphasize LLM/AI

Why:

CURRENT

Autonomous pentests from one command. Real tools, working PoCs, audit-ready reports.

COPY-PASTE FIX

Autonomous, LLM-powered pentests from one command. Real tools, working PoCs, audit-ready reports. BYO LLM, no API key needed.

mediumreadme#2

Add a 'Why pentest-ai?' section highlighting LLM differentiation

Why:

COPY-PASTE FIX

## Why pentest-ai?

Unlike traditional pentesting tools, `pentest-ai` leverages Large Language Models (LLMs) to orchestrate offensive security tasks, generate exploit chains, and produce audit-ready reports. It's an open-source, modular platform designed for autonomous, AI-driven penetration testing, allowing you to bring your own LLM without cloud dependencies or API keys.

mediumtopics#3

Expand topics with more specific LLM/AI terms

Why:

CURRENT

ai-security, bug-bounty, claude, ctf, cybersecurity, exploit, exploit-chaining, hacking-tools, mcp, model-context-protocol, nmap, offensive-security, osint, penetration-testing, pentest-ai, pentesting, python, red-team, security, vulnerability-scanner

COPY-PASTE FIX

ai-security, bug-bounty, claude, ctf, cybersecurity, exploit, exploit-chaining, generative-ai, hacking-tools, large-language-models, llm-security, mcp, model-context-protocol, nmap, offensive-security, osint, penetration-testing, pentest-ai, pentesting, python, red-team, security, vulnerability-scanner

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 0xSteph/pentest-ai

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OWASP ZAP (Zed Attack Proxy)

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

OWASP ZAP (Zed Attack Proxy) · recommended 1×
AppSec Flow · recommended 1×
PortSwigger Burp Suite Enterprise Edition · recommended 1×
projectdiscovery/nuclei · recommended 1×
Scrapy · recommended 1×

CATEGORY QUERY
How to automate penetration testing for web applications using AI agents?
you: not recommended
AI recommended (in order):
1. OWASP ZAP (Zed Attack Proxy)
2. AppSec Flow
3. PortSwigger Burp Suite Enterprise Edition
4. Nuclei (projectdiscovery/nuclei)
5. Scrapy
6. Selenium
7. Playwright
8. TensorFlow
9. PyTorch
10. Scikit-learn
11. spaCy
12. Apache Airflow
13. Prefect
AI recommended 13 alternatives but never named 0xSteph/pentest-ai. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for an offline AI-driven security tool to generate exploit chains and audit reports.
you: not recommended
AI recommended (in order):
1. Metasploit Framework (rapid7/metasploit-framework)
2. Pwnagotchi (evilsocket/pwnagotchi)
3. Immunity Canvas
4. Core Impact
5. Vuls (future-architect/vuls)
6. OpenVAS (greenbone/openvas)
7. scikit-learn (scikit-learn/scikit-learn)
8. TensorFlow Lite (tensorflow/tensorflow)
9. PyTorch Mobile (pytorch/pytorch)
AI recommended 9 alternatives but never named 0xSteph/pentest-ai. 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 0xSteph/pentest-ai?
pass
AI named 0xSteph/pentest-ai explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts 0xSteph/pentest-ai in production, what risks or prerequisites should they evaluate first?
pass
AI named 0xSteph/pentest-ai 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 0xSteph/pentest-ai solve, and who is the primary audience?
pass
AI did not name 0xSteph/pentest-ai — 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?

Embed your GEO score

Drop this badge into the README of 0xSteph/pentest-ai. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/0xSteph/pentest-ai.svg)](https://repogeo.com/en/r/0xSteph/pentest-ai)

HTML

<a href="https://repogeo.com/en/r/0xSteph/pentest-ai"><img src="https://repogeo.com/badge/0xSteph/pentest-ai.svg" alt="RepoGEO" /></a>

Pro

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0xSteph/pentest-ai — 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