🤖 CyberAI

AI-powered pentest platform — built by someone who red-teams AI, not just with it.

Status: Active development
Stack:  Python · Multi-agent orchestration · LLM APIs

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What is this?

CyberAI is an AI orchestration layer for offensive security workflows. It connects the phantom toolchain — OOB detection, CVE intelligence, TLS analysis — and routes findings through an AI pipeline that surfaces actionable attack paths.

Not a chatbot for pentesters. An agentic system where AI agents handle recon, correlation, and reporting — while you focus on exploitation.

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Architecture

┌─────────────────────────────────────────────────┐
│                   CyberAI Core                  │
│                                                 │
│  ┌─────────────┐      ┌──────────────────────┐  │
│  │  Orchestrat │      │   Agent Pool         │  │
│  │  or Agent   │─────▶│   Recon · Intel      │  │
│  └─────────────┘      │   Exploit · Report   │  │
│         │             └──────────────────────┘  │
│         ▼                                       │
│  ┌─────────────────────────────────────────┐    │
│  │           Phantom Stack                 │    │
│  │  phantom-grid · phantom-intel           │    │
│  │  reality-probe                          │    │
│  └─────────────────────────────────────────┘    │
└─────────────────────────────────────────────────┘

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Design constraints

This platform is built with multi-agent security as a first-class concern:

• Agent trust boundaries — agents operate with minimal necessary permissions
• Input validation — all external data sanitized before entering the LLM context
• Prompt injection resistance — structured prompts, output parsing, no raw passthrough
• Audit trail — every agent action logged with inputs and outputs

The irony of building an AI pentest tool while studying AI attack surfaces is intentional. Adversarial thinking is a design input, not an afterthought.

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Roadmap

[x] AI Orchestrator skeleton
[ ] phantom-intel integration — CVE context injection
[ ] phantom-grid integration — OOB result correlation
[ ] Recon agent — target enumeration pipeline
[ ] Exploit suggestion agent — CVE → PoC mapping
[ ] Report generation agent — findings → markdown/PDF
[ ] Multi-agent safety protocol layer

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Quick Start

git clone https://github.com/user70616E6461/CyberAI.git
cd CyberAI
pip install -r requirements.txt
# configuration: cp config.example.yml config.yml
python main.py

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Related tools

Tool	Role in the stack
phantom-grid	OOB interaction capture
phantom-intel	CVE intelligence feed
reality-probe	TLS analysis & config

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License

MIT

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_{Part of the panda security toolchain.}