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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 987c49569c
commit 60ca088ecf
167 changed files with 26101 additions and 5703 deletions
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128
backend/README.md
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@@ -1,6 +1,6 @@
# FuzzForge Backend
A stateless API server for security testing workflow orchestration using Prefect. This system dynamically discovers workflows, executes them in isolated Docker containers with volume mounting, and returns findings in SARIF format.
A stateless API server for security testing workflow orchestration using Temporal. This system dynamically discovers workflows, executes them in isolated worker environments, and returns findings in SARIF format.
## Architecture Overview
@@ -8,17 +8,17 @@ A stateless API server for security testing workflow orchestration using Prefect
1. **Workflow Discovery System**: Automatically discovers workflows at startup
2. **Module System**: Reusable components (scanner, analyzer, reporter) with a common interface
3. **Prefect Integration**: Handles container orchestration, workflow execution, and monitoring
4. **Volume Mounting**: Secure file access with configurable permissions (ro/rw)
3. **Temporal Integration**: Handles workflow orchestration, execution, and monitoring with vertical workers
4. **File Upload & Storage**: HTTP multipart upload to MinIO for target files
5. **SARIF Output**: Standardized security findings format
### Key Features
- **Stateless**: No persistent data, fully scalable
- **Generic**: No hardcoded workflows, automatic discovery
- **Isolated**: Each workflow runs in its own Docker container
- **Isolated**: Each workflow runs in specialized vertical workers
- **Extensible**: Easy to add new workflows and modules
- **Secure**: Read-only volume mounts by default, path validation
- **Secure**: File upload with MinIO storage, automatic cleanup via lifecycle policies
- **Observable**: Comprehensive logging and status tracking
## Quick Start
@@ -32,19 +32,17 @@ A stateless API server for security testing workflow orchestration using Prefect
From the project root, start all services:
```bash
docker-compose up -d
docker-compose -f docker-compose.temporal.yaml up -d
```
This will start:
- Prefect server (API at http://localhost:4200/api)
- PostgreSQL database
- Redis cache
- Docker registry (port 5001)
- Prefect worker (for running workflows)
- Temporal server (Web UI at http://localhost:8233, gRPC at :7233)
- MinIO (S3 storage at http://localhost:9000, Console at http://localhost:9001)
- PostgreSQL database (for Temporal state)
- Vertical workers (worker-rust, worker-android, worker-web, etc.)
- FuzzForge backend API (port 8000)
- FuzzForge MCP server (port 8010)
**Note**: The Prefect UI at http://localhost:4200 is not currently accessible from the host due to the API being configured for inter-container communication. Use the REST API or MCP interface instead.
**Note**: MinIO console login: `fuzzforge` / `fuzzforge123`
## API Endpoints
@@ -54,7 +52,8 @@ This will start:
- `GET /workflows/{name}/metadata` - Get workflow metadata and parameters
- `GET /workflows/{name}/parameters` - Get workflow parameter schema
- `GET /workflows/metadata/schema` - Get metadata.yaml schema
- `POST /workflows/{name}/submit` - Submit a workflow for execution
- `POST /workflows/{name}/submit` - Submit a workflow for execution (path-based, legacy)
- `POST /workflows/{name}/upload-and-submit` - **Upload local files and submit workflow** (recommended)
### Runs
@@ -68,12 +67,13 @@ Each workflow must have:
```
toolbox/workflows/{workflow_name}/
workflow.py # Prefect flow definition
metadata.yaml # Mandatory metadata (parameters, version, etc.)
Dockerfile # Optional custom container definition
requirements.txt # Optional Python dependencies
workflow.py # Temporal workflow definition
metadata.yaml # Mandatory metadata (parameters, version, vertical, etc.)
requirements.txt # Optional Python dependencies (installed in vertical worker)
```
**Note**: With Temporal architecture, workflows run in pre-built vertical workers (e.g., `worker-rust`, `worker-android`), not individual Docker containers. The workflow code is mounted as a volume and discovered at runtime.
### Example metadata.yaml
```yaml
@@ -82,6 +82,7 @@ version: "1.0.0"
description: "Comprehensive security analysis workflow"
author: "FuzzForge Team"
category: "comprehensive"
vertical: "rust" # Routes to worker-rust
tags:
- "security"
- "analysis"
@@ -169,6 +170,57 @@ curl -X POST "http://localhost:8000/workflows/security_assessment/submit" \
Resource precedence: User limits > Workflow requirements > System defaults
## File Upload and Target Access
### Upload Endpoint
The backend provides an upload endpoint for submitting workflows with local files:
```
POST /workflows/{workflow_name}/upload-and-submit
Content-Type: multipart/form-data
Parameters:
file: File upload (supports .tar.gz for directories)
parameters: JSON string of workflow parameters (optional)
volume_mode: "ro" or "rw" (default: "ro")
timeout: Execution timeout in seconds (optional)
```
Example using curl:
```bash
# Upload a directory (create tarball first)
tar -czf project.tar.gz /path/to/project
curl -X POST "http://localhost:8000/workflows/security_assessment/upload-and-submit" \
-F "file=@project.tar.gz" \
-F "parameters={\"check_secrets\":true}" \
-F "volume_mode=ro"
# Upload a single file
curl -X POST "http://localhost:8000/workflows/security_assessment/upload-and-submit" \
-F "file=@binary.elf" \
-F "volume_mode=ro"
```
### Storage Flow
1. **CLI/API uploads file** via HTTP multipart
2. **Backend receives file** and streams to temporary location (max 10GB)
3. **Backend uploads to MinIO** with generated `target_id`
4. **Workflow is submitted** to Temporal with `target_id`
5. **Worker downloads target** from MinIO to local cache
6. **Workflow processes target** from cache
7. **MinIO lifecycle policy** deletes files after 7 days
### Advantages
- **No host filesystem access required** - workers can run anywhere
- **Automatic cleanup** - lifecycle policies prevent disk exhaustion
- **Caching** - repeated workflows reuse cached targets
- **Multi-host ready** - targets accessible from any worker
- **Secure** - isolated storage, no arbitrary host path access
## Module Development
Modules implement the `BaseModule` interface:
@@ -198,7 +250,21 @@ class MyModule(BaseModule):
## Submitting a Workflow
### With File Upload (Recommended)
```bash
# Automatic tarball and upload
tar -czf project.tar.gz /home/user/project
curl -X POST "http://localhost:8000/workflows/security_assessment/upload-and-submit" \
-F "file=@project.tar.gz" \
-F "parameters={\"scanner_config\":{\"patterns\":[\"*.py\"]},\"analyzer_config\":{\"check_secrets\":true}}" \
-F "volume_mode=ro"
```
### Legacy Path-Based Submission
```bash
# Only works if backend and target are on same machine
curl -X POST "http://localhost:8000/workflows/security_assessment/submit" \
-H "Content-Type: application/json" \
-d '{
@@ -235,23 +301,31 @@ Returns SARIF-formatted findings:
## Security Considerations
1. **Volume Mounting**: Only allowed directories can be mounted
2. **Read-Only Default**: Volumes mounted as read-only unless explicitly set
3. **Container Isolation**: Each workflow runs in an isolated container
4. **Resource Limits**: Can set CPU/memory limits via Prefect
5. **Network Isolation**: Containers use bridge networking
1. **File Upload Security**: Files uploaded to MinIO with isolated storage
2. **Read-Only Default**: Target files accessed as read-only unless explicitly set
3. **Worker Isolation**: Each workflow runs in isolated vertical workers
4. **Resource Limits**: Can set CPU/memory limits per worker
5. **Automatic Cleanup**: MinIO lifecycle policies delete old files after 7 days
## Development
### Adding a New Workflow
1. Create directory: `toolbox/workflows/my_workflow/`
2. Add `workflow.py` with a Prefect flow
3. Add mandatory `metadata.yaml`
4. Restart backend: `docker-compose restart fuzzforge-backend`
2. Add `workflow.py` with a Temporal workflow (using `@workflow.defn`)
3. Add mandatory `metadata.yaml` with `vertical` field
4. Restart the appropriate worker: `docker-compose -f docker-compose.temporal.yaml restart worker-rust`
5. Worker will automatically discover and register the new workflow
### Adding a New Module
1. Create module in `toolbox/modules/{category}/`
2. Implement `BaseModule` interface
3. Use in workflows via import
3. Use in workflows via import
### Adding a New Vertical Worker
1. Create worker directory: `workers/{vertical}/`
2. Create `Dockerfile` with required tools
3. Add worker to `docker-compose.temporal.yaml`
4. Worker will automatically discover workflows with matching `vertical` in metadata