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CI/CD Integration with Ephemeral Deployment Model (#14)

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* feat: Complete migration from Prefect to Temporal

BREAKING CHANGE: Replaces Prefect workflow orchestration with Temporal

## Major Changes
- Replace Prefect with Temporal for workflow orchestration
- Implement vertical worker architecture (rust, android)
- Replace Docker registry with MinIO for unified storage
- Refactor activities to be co-located with workflows
- Update all API endpoints for Temporal compatibility

## Infrastructure
- New: docker-compose.temporal.yaml (Temporal + MinIO + workers)
- New: workers/ directory with rust and android vertical workers
- New: backend/src/temporal/ (manager, discovery)
- New: backend/src/storage/ (S3-cached storage with MinIO)
- New: backend/toolbox/common/ (shared storage activities)
- Deleted: docker-compose.yaml (old Prefect setup)
- Deleted: backend/src/core/prefect_manager.py
- Deleted: backend/src/services/prefect_stats_monitor.py
- Deleted: Docker registry and insecure-registries requirement

## Workflows
- Migrated: security_assessment workflow to Temporal
- New: rust_test workflow (example/test workflow)
- Deleted: secret_detection_scan (Prefect-based, to be reimplemented)
- Activities now co-located with workflows for independent testing

## API Changes
- Updated: backend/src/api/workflows.py (Temporal submission)
- Updated: backend/src/api/runs.py (Temporal status/results)
- Updated: backend/src/main.py (727 lines, TemporalManager integration)
- Updated: All 16 MCP tools to use TemporalManager

## Testing
- ✅ All services healthy (Temporal, PostgreSQL, MinIO, workers, backend)
- ✅ All API endpoints functional
- ✅ End-to-end workflow test passed (72 findings from vulnerable_app)
- ✅ MinIO storage integration working (target upload/download, results)
- ✅ Worker activity discovery working (6 activities registered)
- ✅ Tarball extraction working
- ✅ SARIF report generation working

## Documentation
- ARCHITECTURE.md: Complete Temporal architecture documentation
- QUICKSTART_TEMPORAL.md: Getting started guide
- MIGRATION_DECISION.md: Why we chose Temporal over Prefect
- IMPLEMENTATION_STATUS.md: Migration progress tracking
- workers/README.md: Worker development guide

## Dependencies
- Added: temporalio>=1.6.0
- Added: boto3>=1.34.0 (MinIO S3 client)
- Removed: prefect>=3.4.18

* feat: Add Python fuzzing vertical with Atheris integration

This commit implements a complete Python fuzzing workflow using Atheris:

## Python Worker (workers/python/)
- Dockerfile with Python 3.11, Atheris, and build tools
- Generic worker.py for dynamic workflow discovery
- requirements.txt with temporalio, boto3, atheris dependencies
- Added to docker-compose.temporal.yaml with dedicated cache volume

## AtherisFuzzer Module (backend/toolbox/modules/fuzzer/)
- Reusable module extending BaseModule
- Auto-discovers fuzz targets (fuzz_*.py, *_fuzz.py, fuzz_target.py)
- Recursive search to find targets in nested directories
- Dynamically loads TestOneInput() function
- Configurable max_iterations and timeout
- Real-time stats callback support for live monitoring
- Returns findings as ModuleFinding objects

## Atheris Fuzzing Workflow (backend/toolbox/workflows/atheris_fuzzing/)
- Temporal workflow for orchestrating fuzzing
- Downloads user code from MinIO
- Executes AtherisFuzzer module
- Uploads results to MinIO
- Cleans up cache after execution
- metadata.yaml with vertical: python for routing

## Test Project (test_projects/python_fuzz_waterfall/)
- Demonstrates stateful waterfall vulnerability
- main.py with check_secret() that leaks progress
- fuzz_target.py with Atheris TestOneInput() harness
- Complete README with usage instructions

## Backend Fixes
- Fixed parameter merging in REST API endpoints (workflows.py)
- Changed workflow parameter passing from positional args to kwargs (manager.py)
- Default parameters now properly merged with user parameters

## Testing
✅ Worker discovered AtherisFuzzingWorkflow
✅ Workflow executed end-to-end successfully
✅ Fuzz target auto-discovered in nested directories
✅ Atheris ran 100,000 iterations
✅ Results uploaded and cache cleaned

* chore: Complete Temporal migration with updated CLI/SDK/docs

This commit includes all remaining Temporal migration changes:

## CLI Updates (cli/)
- Updated workflow execution commands for Temporal
- Enhanced error handling and exceptions
- Updated dependencies in uv.lock

## SDK Updates (sdk/)
- Client methods updated for Temporal workflows
- Updated models for new workflow execution
- Updated dependencies in uv.lock

## Documentation Updates (docs/)
- Architecture documentation for Temporal
- Workflow concept documentation
- Resource management documentation (new)
- Debugging guide (new)
- Updated tutorials and how-to guides
- Troubleshooting updates

## README Updates
- Main README with Temporal instructions
- Backend README
- CLI README
- SDK README

## Other
- Updated IMPLEMENTATION_STATUS.md
- Removed old vulnerable_app.tar.gz

These changes complete the Temporal migration and ensure the
CLI/SDK work correctly with the new backend.

* fix: Use positional args instead of kwargs for Temporal workflows

The Temporal Python SDK's start_workflow() method doesn't accept
a 'kwargs' parameter. Workflows must receive parameters as positional
arguments via the 'args' parameter.

Changed from:
  args=workflow_args  # Positional arguments

This fixes the error:
  TypeError: Client.start_workflow() got an unexpected keyword argument 'kwargs'

Workflows now correctly receive parameters in order:
- security_assessment: [target_id, scanner_config, analyzer_config, reporter_config]
- atheris_fuzzing: [target_id, target_file, max_iterations, timeout_seconds]
- rust_test: [target_id, test_message]

* fix: Filter metadata-only parameters from workflow arguments

SecurityAssessmentWorkflow was receiving 7 arguments instead of 2-5.
The issue was that target_path and volume_mode from default_parameters
were being passed to the workflow, when they should only be used by
the system for configuration.

Now filters out metadata-only parameters (target_path, volume_mode)
before passing arguments to workflow execution.

* refactor: Remove Prefect leftovers and volume mounting legacy

Complete cleanup of Prefect migration artifacts:

Backend:
- Delete registry.py and workflow_discovery.py (Prefect-specific files)
- Remove Docker validation from setup.py (no longer needed)
- Remove ResourceLimits and VolumeMount models
- Remove target_path and volume_mode from WorkflowSubmission
- Remove supported_volume_modes from API and discovery
- Clean up metadata.yaml files (remove volume/path fields)
- Simplify parameter filtering in manager.py

SDK:
- Remove volume_mode parameter from client methods
- Remove ResourceLimits and VolumeMount models
- Remove Prefect error patterns from docker_logs.py
- Clean up WorkflowSubmission and WorkflowMetadata models

CLI:
- Remove Volume Modes display from workflow info

All removed features are Prefect-specific or Docker volume mounting
artifacts. Temporal workflows use MinIO storage exclusively.

* feat: Add comprehensive test suite and benchmark infrastructure

- Add 68 unit tests for fuzzer, scanner, and analyzer modules
- Implement pytest-based test infrastructure with fixtures
- Add 6 performance benchmarks with category-specific thresholds
- Configure GitHub Actions for automated testing and benchmarking
- Add test and benchmark documentation

Test coverage:
- AtherisFuzzer: 8 tests
- CargoFuzzer: 14 tests
- FileScanner: 22 tests
- SecurityAnalyzer: 24 tests

All tests passing (68/68)
All benchmarks passing (6/6)

* fix: Resolve all ruff linting violations across codebase

Fixed 27 ruff violations in 12 files:
- Removed unused imports (Depends, Dict, Any, Optional, etc.)
- Fixed undefined workflow_info variable in workflows.py
- Removed dead code with undefined variables in atheris_fuzzer.py
- Changed f-string to regular string where no placeholders used

All files now pass ruff checks for CI/CD compliance.

* fix: Configure CI for unit tests only

- Renamed docker-compose.temporal.yaml → docker-compose.yml for CI compatibility
- Commented out integration-tests job (no integration tests yet)
- Updated test-summary to only depend on lint and unit-tests

CI will now run successfully with 68 unit tests. Integration tests can be added later.

* feat: Add CI/CD integration with ephemeral deployment model

Implements comprehensive CI/CD support for FuzzForge with on-demand worker management:

**Worker Management (v0.7.0)**
- Add WorkerManager for automatic worker lifecycle control
- Auto-start workers from stopped state when workflows execute
- Auto-stop workers after workflow completion
- Health checks and startup timeout handling (90s default)

**CI/CD Features**
- `--fail-on` flag: Fail builds based on SARIF severity levels (error/warning/note/info)
- `--export-sarif` flag: Export findings in SARIF 2.1.0 format
- `--auto-start`/`--auto-stop` flags: Control worker lifecycle
- Exit code propagation: Returns 1 on blocking findings, 0 on success

**Exit Code Fix**
- Add `except typer.Exit: raise` handlers at 3 critical locations
- Move worker cleanup to finally block for guaranteed execution
- Exit codes now propagate correctly even when build fails

**CI Scripts & Examples**
- ci-start.sh: Start FuzzForge services with health checks
- ci-stop.sh: Clean shutdown with volume preservation option
- GitHub Actions workflow example (security-scan.yml)
- GitLab CI pipeline example (.gitlab-ci.example.yml)
- docker-compose.ci.yml: CI-optimized compose file with profiles

**OSS-Fuzz Integration**
- New ossfuzz_campaign workflow for running OSS-Fuzz projects
- OSS-Fuzz worker with Docker-in-Docker support
- Configurable campaign duration and project selection

**Documentation**
- Comprehensive CI/CD integration guide (docs/how-to/cicd-integration.md)
- Updated architecture docs with worker lifecycle details
- Updated workspace isolation documentation
- CLI README with worker management examples

**SDK Enhancements**
- Add get_workflow_worker_info() endpoint
- Worker vertical metadata in workflow responses

**Testing**
- All workflows tested: security_assessment, atheris_fuzzing, secret_detection, cargo_fuzzing
- All monitoring commands tested: stats, crashes, status, finding
- Full CI pipeline simulation verified
- Exit codes verified for success/failure scenarios

Ephemeral CI/CD model: ~3-4GB RAM, ~60-90s startup, runs entirely in CI containers.

* fix: Resolve ruff linting violations in CI/CD code

- Remove unused variables (run_id, defaults, result)
- Remove unused imports
- Fix f-string without placeholders

All CI/CD integration files now pass ruff checks.
This commit is contained in:
tduhamel42
2025-10-14 10:13:45 +02:00
committed by GitHub
parent 056cde35b2
commit ec812461d6
167 changed files with 26101 additions and 5703 deletions
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docs/docs/tutorial/getting-started.md
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@@ -85,24 +85,23 @@ docker pull localhost:5001/hello-world 2>/dev/null || echo "Registry not accessi
Start all FuzzForge services:
```bash
docker compose up -d
docker-compose -f docker-compose.temporal.yaml up -d
```
This will start 8 services:
- **prefect-server**: Workflow orchestration server
- **prefect-worker**: Executes workflows in Docker containers
This will start 6+ services:
- **temporal**: Workflow orchestration server (includes embedded PostgreSQL for dev)
- **minio**: S3-compatible storage for uploaded targets and results
- **minio-setup**: One-time setup for MinIO buckets (exits after setup)
- **fuzzforge-backend**: FastAPI backend and workflow management
- **postgres**: Metadata and workflow state storage
- **redis**: Message broker and caching
- **registry**: Local Docker registry for workflow images
- **docker-proxy**: Secure Docker socket proxy
- **prefect-services**: Additional Prefect services
- **worker-rust**: Long-lived worker for Rust/native security analysis
- **worker-android**: Long-lived worker for Android security analysis (if configured)
- **worker-web**: Long-lived worker for web security analysis (if configured)
Wait for all services to be healthy (this may take 2-3 minutes on first startup):
```bash
# Check service health
docker compose ps
docker-compose -f docker-compose.temporal.yaml ps
# Verify FuzzForge is ready
curl http://localhost:8000/health
@@ -154,33 +153,41 @@ You should see 6 production workflows:
## Step 6: Run Your First Workflow
Let's run a static analysis workflow on one of the included vulnerable test projects.
Let's run a security assessment workflow on one of the included vulnerable test projects.
### Using the CLI (Recommended):
```bash
# Navigate to a test project
cd /path/to/fuzzforge/test_projects/static_analysis_vulnerable
cd /path/to/fuzzforge/test_projects/vulnerable_app
# Submit the workflow
fuzzforge runs submit static_analysis_scan .
# Submit the workflow - CLI automatically uploads the local directory
fuzzforge workflow run security_assessment .
# The CLI will:
# 1. Detect that '.' is a local directory
# 2. Create a compressed tarball of the directory
# 3. Upload it to the backend via HTTP
# 4. The backend stores it in MinIO
# 5. The worker downloads it when ready to analyze
# Monitor the workflow
fuzzforge runs status <run-id>
fuzzforge workflow status <run-id>
# View results when complete
fuzzforge findings get <run-id>
fuzzforge finding <run-id>
```
### Using the API:
For local files, you can use the upload endpoint:
```bash
# Submit workflow
curl -X POST "http://localhost:8000/workflows/static_analysis_scan/submit" \
-H "Content-Type: application/json" \
-d '{
"target_path": "/path/to/your/project"
}'
# Create tarball and upload
tar -czf project.tar.gz /path/to/your/project
curl -X POST "http://localhost:8000/workflows/security_assessment/upload-and-submit" \
-F "file=@project.tar.gz" \
-F "volume_mode=ro"
# Check status
curl "http://localhost:8000/runs/{run-id}/status"
@@ -189,6 +196,8 @@ curl "http://localhost:8000/runs/{run-id}/status"
curl "http://localhost:8000/runs/{run-id}/findings"
```
**Note**: The CLI handles file upload automatically. For remote workflows where the target path exists on the backend server, you can still use path-based submission for backward compatibility.
## Step 7: Understanding the Results
The workflow will complete in 30-60 seconds and return results in SARIF format. For the test project, you should see:
@@ -216,13 +225,19 @@ Example output:
}
```
## Step 8: Access the Prefect Dashboard
## Step 8: Access the Temporal Web UI
You can monitor workflow execution in real-time using the Prefect dashboard:
You can monitor workflow execution in real-time using the Temporal Web UI:
1. Open http://localhost:4200 in your browser
2. Navigate to "Flow Runs" to see workflow executions
3. Click on a run to see detailed logs and execution graph
1. Open http://localhost:8233 in your browser
2. Navigate to "Workflows" to see workflow executions
3. Click on a workflow to see detailed execution history and activity results
You can also access the MinIO console to view uploaded targets:
1. Open http://localhost:9001 in your browser
2. Login with: `fuzzforge` / `fuzzforge123`
3. Browse the `targets` bucket to see uploaded files
## Next Steps
@@ -242,9 +257,10 @@ Congratulations! You've successfully:
If you encounter problems:
1. **Workflow crashes with registry errors**: Check Docker insecure registry configuration
2. **Services won't start**: Ensure ports 4200, 5001, 8000 are available
2. **Services won't start**: Ensure ports 8000, 8233, 9000, 9001 are available
3. **No findings returned**: Verify the target path contains analyzable code files
4. **CLI not found**: Ensure Python/pip installation path is in your PATH
5. **Upload fails**: Check that MinIO is running and accessible at http://localhost:9000
See the [Troubleshooting Guide](../how-to/troubleshooting.md) for detailed solutions.