A clean, focused server containing bug bounty hunting workflows and REST API endpoints.
For AI coding assistants, see AGENTS.md for repository-specific guidance.
- Clean Architecture: Removed bloat and unnecessary dependencies while maintaining core functionality
- Bug Bounty Focused: Specialized workflows for reconnaissance, vulnerability hunting, business logic testing, OSINT, and file upload testing
- REST API Endpoints: Simple HTTP API for workflow generation and management
- Comprehensive Assessments: Combine multiple workflows for complete bug bounty assessments
- REST API Server (
src/rest_api_server/app.py) - Flask-based HTTP API server with bug bounty workflow endpoints - MCP Server (
src/mcp_server/app.py) - FastMCP-based server for AI agent communication - Bug Bounty Workflows (
src/rest_api_server/workflows/) - Specialized workflow generation for different phases of testing - Tool Integration (
src/rest_api_server/tools/) - Consolidated security tool wrappers - Shared Utilities (
src/rest_api_server/utils/&src/rest_api_server/logger.py) - Registry, logging, and helper utilities shared across endpoints
# Install dependencies with uv
uv sync
# Install development dependencies (optional)
uv sync --dev
# Set up pre-commit hooks (recommended for development)
uv run pre-commit install
# Start the server
uv run -m src.rest_api_server
# Or with environment variables
DEBUG=true BUGBOUNTY_MCP_PORT=8888 uv run -m src.rest_api_server
# Or use the launcher script
./start-server.sh --debug --port 8888# Create reconnaissance workflow
curl -X POST http://127.0.0.1:8888/api/bugbounty/reconnaissance-workflow \
-H "Content-Type: application/json" \
-d '{"domain": "example.com", "program_type": "web"}'BUGBOUNTY_MCP_PORT: Server port (default: 8888)BUGBOUNTY_MCP_HOST: Server host (default: 127.0.0.1)DEBUG: Enable debug mode (default: false)
# Start with default configuration
uv run -m src.rest_api_server
# Start with custom configuration
DEBUG=true BUGBOUNTY_MCP_PORT=9999 BUGBOUNTY_MCP_HOST=0.0.0.0 uv run -m src.rest_api_server- Bug Bounty Workflow Management: Complete workflow generation for different phases of bug bounty hunting
- Vulnerability Prioritization: Intelligence-driven prioritization based on impact and bounty potential
- File Upload Testing: Specialized framework for file upload vulnerability testing
- OSINT Integration: Comprehensive OSINT gathering workflows
- Business Logic Testing: Structured approach to business logic vulnerability discovery
This repository integrates with GitHub Spec-Kit for specification-driven development workflow, enhanced with AI assistance for codebase exploration, planning, and verification.
The repository includes integration with Google's Gemini CLI for enhanced AI-powered development assistance:
# Install Gemini CLI (nightly version for latest features)
npx @google/gemini-cli@nightlyCodebase Exploration
- Analyze complex bug bounty tool integrations and workflows
- Understand relationships between MCP server components and REST API endpoints
- Navigate through security tool configurations and vulnerability detection patterns
Planning & Specification
- Generate comprehensive implementation plans for new bug bounty workflows
- Create detailed specifications for security tool integrations
- Plan testing strategies for vulnerability detection capabilities
Code Review & Verification
- Validate implementation quality against security best practices
- Review bug bounty workflow logic for completeness and accuracy
- Verify API endpoint security and error handling
- Analyze tool output parsing and vulnerability classification
The Gemini CLI complements the existing spec-kit commands:
-
Specify Phase (
.claude/commands/specify.md)# Use Gemini CLI to analyze requirements and generate specifications npx @google/gemini-cli@nightly analyze-requirements --input "feature_description"
-
Planning Phase (
.claude/commands/plan.md)# Use Gemini CLI to validate and enhance implementation plans npx @google/gemini-cli@nightly review-plan --spec-file "path/to/spec.md"
-
Implementation Verification
# Use Gemini CLI as a code reviewer and security auditor npx @google/gemini-cli@nightly audit-security --focus bug-bounty-workflows
# 1. Explore codebase before making changes
npx @google/gemini-cli@nightly explore --focus "bug bounty tools integration"
# 2. Plan new features with AI assistance
npx @google/gemini-cli@nightly plan --spec-driven --security-focused
# 3. Verify implementations against security standards
npx @google/gemini-cli@nightly verify --check-security --validate-workflowsProject uses uv for fast, reliable dependency management:
- Flask: Web framework for REST API
- FastMCP: MCP server framework
- Requests: HTTP client library
- Python 3.11+: Core runtime (supports Python 3.11, 3.12, 3.13)
- Ruff: Fast Python linter and formatter
- Bandit: Security vulnerability scanner
- Pydocstyle: Documentation quality checker
- Pyright: Static type checker
- Pre-commit: Git pre-commit hooks framework
Install dependencies:
uv sync # Core dependencies only
uv sync --dev # Include development toolsAdd new dependencies:
uv add package-nameThis project enforces code quality through automated pre-commit hooks:
# Install pre-commit hooks
uv run pre-commit install
# Run checks on all files
uv run pre-commit run --all-files
# Run specific checks
uv run ruff check # Linting
uv run ruff format # Formatting
uv run bandit -c pyproject.toml # Security scan
uv run pydocstyle # Documentation checkStandards:
- Line length: 88 characters
- Documentation: Google docstring convention
- Type hints: Required for public APIs
- Security: Bandit security scanning enabled
We welcome contributions. Please see CONTRIBUTING.md for guidelines.
Using an AI coding assistant? Start with AGENTS.md for repository-specific guidance.