Files
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

204 lines
7.3 KiB
Python

"""
Cargo Fuzzing Workflow Activities
Activities specific to the cargo-fuzz fuzzing workflow.
"""
import logging
import sys
from datetime import datetime
from pathlib import Path
from typing import Dict, Any
import os
import httpx
from temporalio import activity
# Configure logging
logger = logging.getLogger(__name__)
# Add toolbox to path for module imports
sys.path.insert(0, '/app/toolbox')
@activity.defn(name="fuzz_with_cargo")
async def fuzz_activity(workspace_path: str, config: dict) -> dict:
"""
Fuzzing activity using the CargoFuzzer module on user code.
This activity:
1. Imports the reusable CargoFuzzer module
2. Sets up real-time stats callback
3. Executes fuzzing on user's fuzz_target!() functions
4. Returns findings as ModuleResult
Args:
workspace_path: Path to the workspace directory (user's uploaded Rust project)
config: Fuzzer configuration (target_name, max_iterations, timeout_seconds, sanitizer)
Returns:
Fuzzer results dictionary (findings, summary, metadata)
"""
logger.info(f"Activity: fuzz_with_cargo (workspace={workspace_path})")
try:
# Import reusable CargoFuzzer module
from modules.fuzzer import CargoFuzzer
workspace = Path(workspace_path)
if not workspace.exists():
raise FileNotFoundError(f"Workspace not found: {workspace_path}")
# Get activity info for real-time stats
info = activity.info()
run_id = info.workflow_id
# Define stats callback for real-time monitoring
async def stats_callback(stats_data: Dict[str, Any]):
"""Callback for live fuzzing statistics"""
try:
# Prepare stats payload for backend
coverage_value = stats_data.get("coverage", 0)
stats_payload = {
"run_id": run_id,
"workflow": "cargo_fuzzing",
"executions": stats_data.get("total_execs", 0),
"executions_per_sec": stats_data.get("execs_per_sec", 0.0),
"crashes": stats_data.get("crashes", 0),
"unique_crashes": stats_data.get("crashes", 0),
"coverage": coverage_value,
"corpus_size": stats_data.get("corpus_size", 0),
"elapsed_time": stats_data.get("elapsed_time", 0),
"last_crash_time": None
}
# POST stats to backend API for real-time monitoring
backend_url = os.getenv("BACKEND_URL", "http://backend:8000")
async with httpx.AsyncClient(timeout=5.0) as client:
try:
await client.post(
f"{backend_url}/fuzzing/{run_id}/stats",
json=stats_payload
)
except Exception as http_err:
logger.debug(f"Failed to post stats to backend: {http_err}")
# Also log for debugging
logger.info("LIVE_STATS", extra={
"stats_type": "fuzzing_live_update",
"workflow_type": "cargo_fuzzing",
"run_id": run_id,
"executions": stats_data.get("total_execs", 0),
"executions_per_sec": stats_data.get("execs_per_sec", 0.0),
"crashes": stats_data.get("crashes", 0),
"corpus_size": stats_data.get("corpus_size", 0),
"coverage": stats_data.get("coverage", 0.0),
"elapsed_time": stats_data.get("elapsed_time", 0),
"timestamp": datetime.utcnow().isoformat()
})
except Exception as e:
logger.error(f"Stats callback error: {e}")
# Initialize CargoFuzzer module
fuzzer = CargoFuzzer()
# Execute fuzzing with stats callback
module_result = await fuzzer.execute(
config=config,
workspace=workspace,
stats_callback=stats_callback
)
# Convert ModuleResult to dictionary
result_dict = {
"findings": [],
"summary": module_result.summary,
"metadata": module_result.metadata,
"status": module_result.status,
"error": module_result.error
}
# Convert findings to dict format
for finding in module_result.findings:
finding_dict = {
"id": finding.id,
"title": finding.title,
"description": finding.description,
"severity": finding.severity,
"category": finding.category,
"file_path": finding.file_path,
"line_start": finding.line_start,
"line_end": finding.line_end,
"code_snippet": finding.code_snippet,
"recommendation": finding.recommendation,
"metadata": finding.metadata
}
result_dict["findings"].append(finding_dict)
# Generate SARIF report from findings
if module_result.findings:
# Convert findings to SARIF format
severity_map = {
"critical": "error",
"high": "error",
"medium": "warning",
"low": "note",
"info": "note"
}
results = []
for finding in module_result.findings:
result = {
"ruleId": finding.metadata.get("rule_id", finding.category),
"level": severity_map.get(finding.severity, "warning"),
"message": {"text": finding.description},
"locations": []
}
if finding.file_path:
location = {
"physicalLocation": {
"artifactLocation": {"uri": finding.file_path},
"region": {
"startLine": finding.line_start or 1,
"endLine": finding.line_end or finding.line_start or 1
}
}
}
result["locations"].append(location)
results.append(result)
result_dict["sarif"] = {
"version": "2.1.0",
"$schema": "https://raw.githubusercontent.com/oasis-tcs/sarif-spec/master/Schemata/sarif-schema-2.1.0.json",
"runs": [{
"tool": {
"driver": {
"name": "cargo-fuzz",
"version": "0.11.2"
}
},
"results": results
}]
}
else:
result_dict["sarif"] = {
"version": "2.1.0",
"$schema": "https://raw.githubusercontent.com/oasis-tcs/sarif-spec/master/Schemata/sarif-schema-2.1.0.json",
"runs": []
}
logger.info(
f"Fuzzing activity completed: {len(module_result.findings)} crashes found, "
f"{module_result.summary.get('total_executions', 0)} executions"
)
return result_dict
except Exception as e:
logger.error(f"Fuzzing activity failed: {e}", exc_info=True)
raise