Implement AI-powered bug bounty automation tool with self-improving capabilities

[Copilot]

This PR implements a comprehensive AI-powered bug bounty automation tool that transforms the Codex CLI into a sophisticated penetration testing platform with self-improving capabilities, as requested in the issue.

🎯 Key Features Implemented

Bug Bounty CLI Mode

• New --bounty flag launches specialized security assessment mode
• Dual AI provider support for OpenAI (default) and Google Gemini via --ai-provider flag
• Target and scan type parameters for focused security assessments
• Comprehensive error handling with clear usage guidance

Security Tool Integration

• 15+ integrated security tools including nmap, gobuster, sqlmap, nikto, nuclei, subfinder, amass, httpx, ffuf, and more
• Automatic tool detection and installation with generated installation scripts
• Categorized tools by function (reconnaissance, scanning, exploitation, analysis)
• Enhanced approval system with safe command recognition for security tools

AI-Powered Analysis & Self-Improvement

• Automated vulnerability detection with pattern matching and classification
• CVSS scoring system with proper severity ratings (Critical/High/Medium/Low/Info)
• Vulnerability database with 7+ common patterns (SQL Injection, XSS, RCE, Directory Traversal, etc.)
• Self-improvement through scan analysis - learns from results to enhance future assessments
• False positive reduction through AI-powered result analysis

Advanced Security Features

• Session management for tracking multiple assessments over time
• Comprehensive report generation with executive summaries and technical details
• Evidence collection with remediation recommendations and CWE mapping
• Multi-target campaign support for large-scale assessments

🚀 Usage Examples

# Web application security assessment
codex --bounty example.com "web application scan"

# Network enumeration with Google Gemini
codex --bounty --ai-provider gemini 192.168.1.0/24 "network enumeration"

# Subdomain discovery and analysis  
codex --bounty target.com "subdomain discovery"

# Comprehensive multi-target assessment
codex --bounty "target1.com target2.com" "comprehensive security scan"

🛡️ Ethical Guidelines & Safety

• Built-in ethical guidelines with permission reminders before any testing
• Responsible disclosure guidance integrated into workflow
• Rate limiting awareness to prevent DoS conditions
• Scope boundary enforcement to stay within authorized testing boundaries
• Sandboxed execution when appropriate for additional safety

🧪 Testing & Quality Assurance

• Complete test suite with 126 passing tests (15 new bug bounty specific tests)
• All linting issues resolved - fully ESLint compliant
• TypeScript type safety maintained throughout implementation
• Full build validation passed

📁 Files Added/Modified

Core Integration:

• codex-cli/src/cli.tsx - Added bounty mode CLI integration
• codex-cli/src/utils/config.ts - Added Gemini API support and bounty configuration
• codex-cli/src/approvals.ts - Enhanced with security tool recognition

Bug Bounty Module (src/utils/bounty/):

• analyzer.ts - Vulnerability analysis and reporting system
• bounty-agent.ts - Main AI agent for penetration testing
• gemini-client.ts - Google Gemini API integration
• instructions.ts - Specialized prompts for security testing
• tools.ts - Security tool definitions and management
• vulnerability-db.ts - CVSS scoring and vulnerability patterns
• index.ts - Module exports

Documentation & Testing:

• codex-cli/examples/bug-bounty-guide.md - Comprehensive usage guide
• codex-cli/tests/bug-bounty.test.ts - Complete test suite
• codex-cli/demo-bounty.sh - Interactive demo script

🔄 Self-Improvement Capabilities

The AI agent continuously learns and improves through:

• Scan result analysis to identify gaps in methodology
• Tool parameter optimization based on target responses
• False positive learning to improve accuracy over time
• Coverage improvement suggestions for missed attack vectors
• Technique evolution adapting strategies based on target types

🎭 Example AI-Powered Workflow

1. Target Analysis - AI determines appropriate testing approach
2. Tool Selection - Automatically chooses relevant security tools
3. Sequential Scanning - Executes tools in logical order with AI guidance
4. Result Analysis - AI parses output to identify vulnerabilities
5. Verification - Confirms findings and eliminates false positives
6. Report Generation - Creates structured reports with CVSS scoring
7. Improvement Learning - Analyzes performance to enhance future scans

This implementation delivers exactly what was requested: a self-improving, AI-powered bug bounty automation tool that rivals commercial platforms like HackerOne's automation features, with support for both OpenAI and Google Gemini APIs.

Closes #[issue_number]

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