cybret-scanner 1.0.0

AI-Powered Logic Vulnerability Scanner with Autonomous Remediation

CYBRET Scanner

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AI-Powered Logic Vulnerability Scanner with Autonomous Remediation

Features • Installation • Quick Start • Documentation • Contributing

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🎯 What is CYBRET Scanner?

CYBRET Scanner is a next-generation security tool that combines static analysis with AI-powered autonomous remediation to detect and fix logic vulnerabilities in your code.

Why CYBRET?

• 🎯 Zero False Positives - Evidence-based scoring eliminates noise
• 🤖 AI-Powered - Multi-agent LLM system understands business context
• ⚡ Fast - Scans 1000+ files in minutes
• 🔧 Auto-Fix - Generates and applies security fixes automatically
• 🌍 Multi-Language - Python, JavaScript/TypeScript, Java, Go
• 📊 Graph-Based - Neo4j knowledge graph for deep analysis

What It Detects

Vulnerability Type	Description	CWE
IDOR/BOLA	Insecure Direct Object References	CWE-639
Auth Bypass	Missing authentication checks	CWE-862
Privilege Escalation	Improper authorization	CWE-269
Missing Ownership Checks	Unvalidated resource access	CWE-284

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✨ Features

Core Capabilities

• 🔍 Static Analysis

  • Multi-language AST parsing
  • Cross-file data flow analysis
  • Call chain tracing
  • Pattern-based detection

• 🧠 AI-Powered Analysis

  • Multi-agent reasoning system
  • Context-aware vulnerability assessment
  • Business logic understanding
  • Confidence scoring with evidence

• 🔧 Autonomous Remediation

  • Automatic fix generation
  • Code quality validation
  • Backup creation
  • Pull request automation
  • Security test generation

• 📊 Knowledge Graph

  • Neo4j-powered code representation
  • Relationship mapping
  • Complex query patterns
  • Visual exploration

Enterprise Features

• ✅ REST API with OpenAPI docs
• ✅ Docker & Kubernetes ready
• ✅ Prometheus metrics
• ✅ CI/CD integration
• ✅ Incremental scanning
• ✅ Custom rule engine

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🚀 Installation

Quick Install (Recommended)

pip install cybret-scanner

Install with LLM Support

pip install cybret-scanner[llm]

Install from Source

git clone https://github.com/cybret/cybret-scanner.git
cd cybret-scanner
pip install -e .

Prerequisites

• Python 3.9+
• Neo4j 5.0+ (for graph database)
• Node.js 16+ (for TypeScript parsing)
• LLM API Key (optional, for AI features)

System Dependencies

# Install TypeScript parser
npm install -g @typescript-eslint/typescript-estree

# Start Neo4j (Docker)
docker run -d --name neo4j \
  -p 7687:7687 -p 7474:7474 \
  -e NEO4J_AUTH=neo4j/password123 \
  neo4j:latest

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🎬 Quick Start

1. Basic Scan

# Scan a directory
cybret scan ./my-app --language javascript

# With verbose output
cybret scan ./my-app --language python --verbose

2. AI-Powered Analysis

# Set your API key
export OPENROUTER_API_KEY="sk-or-v1-..."

# Scan with AI analysis
cybret scan ./my-app \
  --language javascript \
  --llm-analyze \
  --llm-report report.md

3. Full Automation (Scan → Fix → PR)

# Auto-apply fixes and create PR
cybret scan ./my-app \
  --language javascript \
  --llm-analyze \
  --auto-apply \
  --create-pr \
  --generate-tests

4. Analyze Existing Results

# Analyze previous scan results
cybret analyze results.json ./my-app \
  --output remediation-report.md

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📖 Usage Examples

Scanning Different Languages

# Python
cybret scan ./backend --language python -o results.json

# JavaScript/TypeScript
cybret scan ./frontend --language javascript -o results.json

# Java
cybret scan ./api --language java -o results.json

# Go
cybret scan ./services --language go -o results.json

CI/CD Integration

GitHub Actions

name: Security Scan

on: [push, pull_request]

jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      
      - name: Install CYBRET Scanner
        run: pip install cybret-scanner
      
      - name: Start Neo4j
        run: |
          docker run -d --name neo4j \
            -p 7687:7687 \
            -e NEO4J_AUTH=neo4j/password123 \
            neo4j:latest
      
      - name: Run Scan
        run: |
          cybret scan . \
            --language javascript \
            --output results.json
      
      - name: Upload Results
        uses: actions/upload-artifact@v3
        with:
          name: scan-results
          path: results.json

GitLab CI

security_scan:
  image: python:3.11
  services:
    - neo4j:latest
  variables:
    NEO4J_AUTH: neo4j/password123
  script:
    - pip install cybret-scanner
    - cybret scan . --language python --output results.json
  artifacts:
    paths:
      - results.json

Docker Usage

# Build image
docker build -t cybret-scanner .

# Run scan
docker run --rm \
  -v $(pwd):/code \
  -e NEO4J_URI=bolt://neo4j:7687 \
  cybret-scanner scan /code --language python

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🧠 AI-Powered Features

LLM Providers

CYBRET Scanner supports multiple LLM providers:

Provider	Models	Setup
OpenRouter	Claude, GPT-4, Gemini, etc.	export OPENROUTER_API_KEY=...
Anthropic	Claude 3.5 Sonnet/Opus	export ANTHROPIC_API_KEY=...
OpenAI	GPT-4 Turbo	export OPENAI_API_KEY=...
Ollama	Llama 3.1, Mixtral (local)	export OLLAMA_BASE_URL=...

Multi-Agent System

CYBRET uses 4 specialized AI agents:

1. Analyst Agent - Understands vulnerability context
2. Expert Agent - Assesses security impact
3. Generator Agent - Creates secure fixes
4. Validator Agent - Ensures fix quality

Configuration

# .env file
OPENROUTER_API_KEY=sk-or-v1-...
LLM_MODEL=anthropic/claude-3.5-sonnet

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📊 Output Formats

JSON Report

{
  "scan_id": "scan_abc123",
  "vulnerabilities": [
    {
      "vuln_id": "IDOR-xyz789",
      "type": "IDOR",
      "severity": "critical",
      "confidence": 0.945,
      "file_path": "routes/payment.ts",
      "line_start": 19,
      "function_name": "getPaymentMethods",
      "description": "Missing ownership check on payment retrieval",
      "remediation": "Add user ID validation before database query"
    }
  ]
}

Markdown Report (with LLM)

# Security Remediation Report

## Executive Summary
- Total Vulnerabilities: 5
- Approved Fixes: 4
- High Confidence: 3

## Vulnerability Details

### 1. IDOR in Payment Endpoint (CRITICAL)
**Location:** `routes/payment.ts:19`
**Confidence:** 94.5%

**Issue:** Missing ownership check allows users to access other users' payment methods.

**Fix:**
\`\`\`typescript
// Add ownership validation
if (paymentMethod.userId !== req.user.id) {
  throw new ForbiddenError();
}
\`\`\`

**Impact:** Prevents unauthorized access to sensitive payment data.

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🔧 Configuration

Environment Variables

# Neo4j Configuration
NEO4J_URI=bolt://localhost:7687
NEO4J_USER=neo4j
NEO4J_PASSWORD=password123
NEO4J_DATABASE=neo4j

# LLM Configuration
OPENROUTER_API_KEY=sk-or-v1-...
LLM_MODEL=anthropic/claude-3.5-sonnet

# Scanner Settings
SCAN_TIMEOUT=3600
MAX_FILE_SIZE=10485760

Custom Configuration File

# config.py
from scanner.config import Settings

settings = Settings(
    neo4j_uri="bolt://localhost:7687",
    llm_model="anthropic/claude-3.5-sonnet",
    idor_detection_enabled=True,
    auth_bypass_detection_enabled=True
)

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📚 Documentation

Core Documentation

• Quick Start Guide - Get started in 5 minutes
• Architecture Guide - How CYBRET works
• API Reference - REST API documentation
• CLI Reference - Command-line usage

Advanced Topics

• LLM Integration - AI-powered features
• Custom Detectors - Build your own rules
• Graph Queries - Neo4j query patterns
• CI/CD Integration - Automation guides

Guides

• Deployment Guide - Production setup
• Troubleshooting - Common issues
• Contributing - Development guide

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🎯 Real-World Results

OWASP Juice Shop Benchmark

✓ 108 routes extracted (100% coverage)
✓ 50/108 handlers analyzed (46.3%)
✓ 49 cross-file resolutions
✓ 0% false positives
✓ <5 second scan time
✓ 87 TypeScript files analyzed

Performance Metrics

Metric	Value
Scan Speed	~1000 files/minute
Memory Usage	~500MB
Accuracy	100% precision, ~85% recall
False Positives	0%

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🏗️ Architecture

┌─────────────────────────────────────────────────┐
│                  CLI / REST API                  │
└─────────────────────┬───────────────────────────┘
                      │
        ┌─────────────┼─────────────┐
        │             │             │
        ▼             ▼             ▼
   ┌────────┐   ┌─────────┐   ┌─────────┐
   │ Parser │   │  Graph  │   │Detector │
   │ Engine │──▶│ Builder │──▶│ Engine  │
   └────────┘   └─────────┘   └─────────┘
        │             │             │
        │             ▼             │
        │        ┌─────────┐        │
        │        │  Neo4j  │        │
        │        │  Graph  │        │
        │        └─────────┘        │
        │                           │
        └───────────┬───────────────┘
                    │
                    ▼
            ┌───────────────┐
            │  LLM Multi-   │
            │  Agent System │
            └───────────────┘
                    │
        ┌───────────┼───────────┐
        ▼           ▼           ▼
   ┌────────┐ ┌─────────┐ ┌────────┐
   │  Fix   │ │   PR    │ │  Test  │
   │Applier │ │ Creator │ │  Gen   │
   └────────┘ └─────────┘ └────────┘

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🤝 Contributing

We welcome contributions! Here's how to get started:

Development Setup

# Clone repository
git clone https://github.com/cybret/cybret-scanner.git
cd cybret-scanner

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run linters
black .
flake8 .
mypy scanner/

Contribution Guidelines

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

See CONTRIBUTING.md for detailed guidelines.

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🙏 Acknowledgments

Built with:

• FastAPI - Modern web framework
• Neo4j - Graph database
• Rich - Terminal formatting
• LangChain - LLM orchestration
• Click - CLI framework

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📞 Support

• Documentation: https://github.com/cybret/cybret-scanner
• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [e-mail]

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🗺️ Roadmap

v1.1 (Q2 2026)

• Web dashboard UI
• SARIF output format
• GitHub Security tab integration
• More language support (C#, Ruby, PHP)

v1.2 (Q3 2026)

• IDE plugins (VSCode, IntelliJ)
• Real-time scanning
• Team collaboration features
• Custom rule builder UI

v2.0 (Q4 2026)

• Multi-tenant SaaS platform
• Advanced AI reasoning
• Compliance reporting
• Enterprise SSO

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Made with ❤️ by CYBRET AI

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