Files
fuzzforge_ai/sdk/examples/basic_workflow.py
tduhamel42 60ca088ecf CI/CD Integration with Ephemeral Deployment Model (#14)
* 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.
2025-10-14 10:13:45 +02:00

311 lines
11 KiB
Python

#!/usr/bin/env python3
# Copyright (c) 2025 FuzzingLabs
#
# Licensed under the Business Source License 1.1 (BSL). See the LICENSE file
# at the root of this repository for details.
#
# After the Change Date (four years from publication), this version of the
# Licensed Work will be made available under the Apache License, Version 2.0.
# See the LICENSE-APACHE file or http://www.apache.org/licenses/LICENSE-2.0
#
# Additional attribution and requirements are provided in the NOTICE file.
"""
Basic workflow submission example.
This example demonstrates how to:
1. Connect to FuzzForge API
2. List available workflows
3. Submit a workflow for analysis
4. Monitor the run status
5. Retrieve findings when complete
"""
import asyncio
import time
from pathlib import Path
from fuzzforge_sdk import FuzzForgeClient
from fuzzforge_sdk.utils import create_workflow_submission, format_sarif_summary, format_duration
def main():
"""Run basic workflow submission example."""
# Initialize the client
client = FuzzForgeClient(base_url="http://localhost:8000")
try:
# Check API status
print("🔗 Connecting to FuzzForge API...")
status = client.get_api_status()
print(f"✅ Connected to {status.name} v{status.version}")
print(f"📊 {status.workflows_loaded} workflows loaded\n")
# List available workflows
print("📋 Available workflows:")
workflows = client.list_workflows()
for workflow in workflows:
print(f"{workflow.name} v{workflow.version}")
print(f" {workflow.description}")
if workflow.tags:
print(f" Tags: {', '.join(workflow.tags)}")
print()
if not workflows:
print("❌ No workflows available")
return
# Select the first workflow for demo
selected_workflow = workflows[0]
print(f"🎯 Selected workflow: {selected_workflow.name}")
# Get workflow metadata
metadata = client.get_workflow_metadata(selected_workflow.name)
print("📝 Workflow metadata:")
print(f" Author: {metadata.author}")
print(f" Required modules: {metadata.required_modules}")
print(f" Supported volume modes: {metadata.supported_volume_modes}")
print()
# Prepare target path (use current directory as example)
target_path = Path.cwd().absolute()
print(f"🎯 Target path: {target_path}")
# Create workflow submission
submission = create_workflow_submission(
target_path=target_path,
volume_mode="ro",
timeout=300, # 5 minutes
)
# Submit the workflow
print(f"🚀 Submitting workflow '{selected_workflow.name}'...")
response = client.submit_workflow(selected_workflow.name, submission)
print("✅ Workflow submitted!")
print(f" Run ID: {response.run_id}")
print(f" Status: {response.status}")
print()
# Monitor the run
print("⏱️ Monitoring run progress...")
start_time = time.time()
while True:
status = client.get_run_status(response.run_id)
elapsed = time.time() - start_time
print(f" Status: {status.status} (elapsed: {format_duration(int(elapsed))})")
if status.is_completed:
print("✅ Run completed successfully!")
break
elif status.is_failed:
print("❌ Run failed!")
print(f" Final status: {status.status}")
return
elif not status.is_running:
print("⏸️ Run is not active")
print(f" Current status: {status.status}")
# Wait before next check
time.sleep(5)
print()
# Get findings
print("📊 Retrieving findings...")
try:
findings = client.get_run_findings(response.run_id)
print(f"✅ Findings retrieved for workflow: {findings.workflow}")
# Display SARIF summary
sarif_summary = format_sarif_summary(findings.sarif)
print(f"📈 {sarif_summary}")
# Display metadata
if findings.metadata:
print("🔍 Metadata:")
for key, value in findings.metadata.items():
print(f" {key}: {value}")
print()
# Extract and display detailed findings
from fuzzforge_sdk.utils import extract_sarif_results
results = extract_sarif_results(findings.sarif)
if results:
print("🔍 Detailed Findings:")
print("=" * 60)
for i, result in enumerate(results, 1):
print(f"\n📋 Finding #{i}")
# Rule information
rule_id = result.get('ruleId', 'unknown')
level = result.get('level', 'warning')
message = result.get('message', {})
print(f" Rule ID: {rule_id}")
print(f" Severity: {level.upper()}")
# Message
if isinstance(message, dict):
msg_text = message.get('text', 'No message')
else:
msg_text = str(message)
print(f" Message: {msg_text}")
# Location information
locations = result.get('locations', [])
if locations:
for loc in locations:
physical_loc = loc.get('physicalLocation', {})
artifact_loc = physical_loc.get('artifactLocation', {})
region = physical_loc.get('region', {})
file_path = artifact_loc.get('uri', 'unknown file')
start_line = region.get('startLine', 'unknown')
start_col = region.get('startColumn', 'unknown')
print(f" Location: {file_path}:{start_line}:{start_col}")
# Show code snippet if available
snippet = region.get('snippet', {})
if snippet and isinstance(snippet, dict):
snippet_text = snippet.get('text', '').strip()
if snippet_text:
print(f" Code: {snippet_text}")
# Additional properties
properties = result.get('properties', {})
if properties:
print(" Properties:")
for prop_key, prop_value in properties.items():
print(f" {prop_key}: {prop_value}")
print("-" * 40)
print(f"\n📁 Total findings: {len(results)}")
print("\n💾 Tip: Use save_sarif_to_file() to save findings to disk")
except Exception as e:
print(f"❌ Failed to retrieve findings: {e}")
except KeyboardInterrupt:
print("\n⏹️ Interrupted by user")
except Exception as e:
print(f"❌ Error: {e}")
finally:
client.close()
async def async_main():
"""Run basic workflow submission example (async version)."""
# Initialize the async client
async with FuzzForgeClient(base_url="http://localhost:8000") as client:
try:
# Check API status
print("🔗 Connecting to FuzzForge API...")
status = await client.aget_api_status()
print(f"✅ Connected to {status.name} v{status.version}")
print(f"📊 {status.workflows_loaded} workflows loaded\n")
# List available workflows
print("📋 Available workflows:")
workflows = await client.alist_workflows()
for workflow in workflows:
print(f"{workflow.name} v{workflow.version}")
print(f" {workflow.description}")
if workflow.tags:
print(f" Tags: {', '.join(workflow.tags)}")
print()
if not workflows:
print("❌ No workflows available")
return
# Select the first workflow for demo
selected_workflow = workflows[0]
print(f"🎯 Selected workflow: {selected_workflow.name}")
# Prepare target path
target_path = Path.cwd().absolute()
submission = create_workflow_submission(
target_path=target_path,
volume_mode="ro",
timeout=300,
)
# Submit the workflow
print(f"🚀 Submitting workflow '{selected_workflow.name}'...")
response = await client.asubmit_workflow(selected_workflow.name, submission)
print(f"✅ Workflow submitted! Run ID: {response.run_id}")
# Wait for completion
print("⏱️ Waiting for completion...")
final_status = await client.await_for_completion(
response.run_id,
poll_interval=3.0,
timeout=600.0 # 10 minutes max
)
print(f"✅ Run completed with status: {final_status.status}")
# Get findings
findings = await client.aget_run_findings(response.run_id)
sarif_summary = format_sarif_summary(findings.sarif)
print(f"📈 {sarif_summary}")
# Extract and display detailed findings
from fuzzforge_sdk.utils import extract_sarif_results
results = extract_sarif_results(findings.sarif)
if results:
print("\n🔍 Detailed Findings:")
print("=" * 60)
for i, result in enumerate(results, 1):
print(f"\n📋 Finding #{i}")
rule_id = result.get('ruleId', 'unknown')
level = result.get('level', 'warning')
message = result.get('message', {})
print(f" Rule ID: {rule_id}")
print(f" Severity: {level.upper()}")
if isinstance(message, dict):
msg_text = message.get('text', 'No message')
else:
msg_text = str(message)
print(f" Message: {msg_text}")
locations = result.get('locations', [])
if locations:
for loc in locations:
physical_loc = loc.get('physicalLocation', {})
artifact_loc = physical_loc.get('artifactLocation', {})
region = physical_loc.get('region', {})
file_path = artifact_loc.get('uri', 'unknown file')
start_line = region.get('startLine', 'unknown')
start_col = region.get('startColumn', 'unknown')
print(f" Location: {file_path}:{start_line}:{start_col}")
print("-" * 40)
except Exception as e:
print(f"❌ Error: {e}")
if __name__ == "__main__":
import sys
if len(sys.argv) > 1 and sys.argv[1] == "--async":
print("🔄 Running async version...")
asyncio.run(async_main())
else:
print("🔄 Running synchronous version...")
print("💡 Use --async flag to run async version")
main()