Implements Issue #5 - Python SAST workflow that combines:
- Dependency scanning (pip-audit) for CVE detection
- Security linting (Bandit) for vulnerability patterns
- Type checking (Mypy) for type safety issues
## Changes
**New Modules:**
- `DependencyScanner`: Scans Python dependencies for known CVEs using pip-audit
- `BanditAnalyzer`: Analyzes Python code for security issues using Bandit
- `MypyAnalyzer`: Checks Python code for type safety issues using Mypy
**New Workflow:**
- `python_sast`: Temporal workflow that orchestrates all three SAST tools
- Runs tools in parallel for fast feedback (3-5 min vs hours for fuzzing)
- Generates unified SARIF report with findings from all tools
- Supports configurable severity/confidence thresholds
**Updates:**
- Added SAST dependencies to Python worker (bandit, pip-audit, mypy)
- Updated module __init__.py files to export new analyzers
- Added type_errors.py test file to vulnerable_app for Mypy validation
## Testing
Workflow tested successfully on vulnerable_app:
- ✅ Bandit: Detected 9 security issues (command injection, unsafe functions)
- ✅ Mypy: Detected 5 type errors
- ✅ DependencyScanner: Ran successfully (no CVEs in test dependencies)
- ✅ SARIF export: Generated valid SARIF with 14 total findings
Add three production-ready secret detection workflows with full benchmarking infrastructure:
**New Workflows:**
- gitleaks_detection: Pattern-based secret scanning (13/32 benchmark secrets)
- trufflehog_detection: Entropy-based detection with verification (1/32 benchmark secrets)
- llm_secret_detection: AI-powered semantic analysis (32/32 benchmark secrets - 100% recall)
**Benchmarking Infrastructure:**
- Ground truth dataset with 32 documented secrets (12 Easy, 10 Medium, 10 Hard)
- Automated comparison tools for precision/recall testing
- SARIF output format for all workflows
- Performance metrics and tool comparison reports
**Fixes:**
- Set gitleaks default to no_git=True for uploaded directories
- Update documentation with correct secret counts and workflow names
- Temporarily deactivate AI agent command
- Clean up deprecated test files and GitGuardian workflow
**Testing:**
All workflows verified on secret_detection_benchmark and vulnerable_app test projects.
Workers healthy and system fully functional.
LLM Analysis Workflow:
- Add llm_analyzer module for AI-powered code security analysis
- Add llm_analysis workflow with SARIF output support
- Mount AI module in Python worker for A2A wrapper access
- Add a2a-sdk dependency to Python worker requirements
- Fix workflow parameter ordering in Temporal manager
Ruff Linter Fixes:
- Fix bare except clauses (E722) across AI and CLI modules
- Add noqa comments for intentional late imports (E402)
- Replace undefined get_ai_status_async with TODO placeholder
- Remove unused imports and variables
- Remove container diagnostics display from exception handler
MCP Configuration:
- Reactivate FUZZFORGE_MCP_URL with default value
- Set default MCP URL to http://localhost:8010/mcp in init
