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.
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
@@ -0,0 +1,113 @@
name: ossfuzz_campaign
version: "1.0.0"
vertical: ossfuzz
description: "Generic OSS-Fuzz fuzzing campaign. Automatically reads project configuration from OSS-Fuzz repo and runs fuzzing using Google's infrastructure."
author: "FuzzForge Team"
tags:
- "fuzzing"
- "oss-fuzz"
- "libfuzzer"
- "afl"
- "honggfuzz"
- "memory-safety"
- "security"
# Workspace isolation mode
# OSS-Fuzz campaigns use isolated mode for safe concurrent campaigns
workspace_isolation: "isolated"
default_parameters:
project_name: null
campaign_duration_hours: 1
override_engine: null
override_sanitizer: null
max_iterations: null
parameters:
type: object
required:
- project_name
properties:
project_name:
type: string
description: "OSS-Fuzz project name (e.g., 'curl', 'sqlite3', 'libxml2')"
examples:
- "curl"
- "sqlite3"
- "libxml2"
- "openssl"
- "zlib"
campaign_duration_hours:
type: integer
default: 1
minimum: 1
maximum: 168 # 1 week max
description: "How many hours to run the fuzzing campaign"
override_engine:
type: string
enum: ["libfuzzer", "afl", "honggfuzz"]
description: "Override fuzzing engine from project.yaml (optional)"
override_sanitizer:
type: string
enum: ["address", "memory", "undefined", "dataflow"]
description: "Override sanitizer from project.yaml (optional)"
max_iterations:
type: integer
minimum: 1000
description: "Optional limit on fuzzing iterations (optional)"
output_schema:
type: object
properties:
project_name:
type: string
description: "OSS-Fuzz project that was fuzzed"
summary:
type: object
description: "Campaign execution summary"
properties:
total_executions:
type: integer
crashes_found:
type: integer
unique_crashes:
type: integer
duration_hours:
type: number
engine_used:
type: string
sanitizer_used:
type: string
crashes:
type: array
description: "List of crash file paths"
items:
type: string
sarif:
type: object
description: "SARIF-formatted crash reports (future)"
examples:
- name: "Fuzz curl for 1 hour"
parameters:
project_name: "curl"
campaign_duration_hours: 1
- name: "Fuzz sqlite3 with AFL"
parameters:
project_name: "sqlite3"
campaign_duration_hours: 2
override_engine: "afl"
- name: "Fuzz libxml2 with memory sanitizer"
parameters:
project_name: "libxml2"
campaign_duration_hours: 6
override_sanitizer: "memory"
@@ -0,0 +1,219 @@
"""
OSS-Fuzz Campaign Workflow - Temporal Version
Generic workflow for running OSS-Fuzz campaigns using Google's infrastructure.
Automatically reads project configuration from OSS-Fuzz project.yaml files.
"""
import asyncio
from datetime import timedelta
from typing import Dict, Any, Optional
from temporalio import workflow
from temporalio.common import RetryPolicy
# Import for type hints (will be executed by worker)
with workflow.unsafe.imports_passed_through():
import logging
logger = logging.getLogger(__name__)
@workflow.defn
class OssfuzzCampaignWorkflow:
"""
Generic OSS-Fuzz fuzzing campaign workflow.
User workflow:
1. User runs: ff workflow run ossfuzz_campaign . project_name=curl
2. Worker loads project config from OSS-Fuzz repo
3. Worker builds project using OSS-Fuzz's build system
4. Worker runs fuzzing with engines from project.yaml
5. Crashes and corpus reported as findings
"""
@workflow.run
async def run(
self,
target_id: str, # Required by FuzzForge (not used, OSS-Fuzz downloads from Google)
project_name: str, # Required: OSS-Fuzz project name (e.g., "curl", "sqlite3")
campaign_duration_hours: int = 1,
override_engine: Optional[str] = None, # Override engine from project.yaml
override_sanitizer: Optional[str] = None, # Override sanitizer from project.yaml
max_iterations: Optional[int] = None # Optional: limit fuzzing iterations
) -> Dict[str, Any]:
"""
Main workflow execution.
Args:
target_id: UUID of uploaded target (not used, required by FuzzForge)
project_name: Name of OSS-Fuzz project (e.g., "curl", "sqlite3", "libxml2")
campaign_duration_hours: How many hours to fuzz (default: 1)
override_engine: Override fuzzing engine from project.yaml
override_sanitizer: Override sanitizer from project.yaml
max_iterations: Optional limit on fuzzing iterations
Returns:
Dictionary containing crashes, stats, and SARIF report
"""
workflow_id = workflow.info().workflow_id
workflow.logger.info(
f"Starting OSS-Fuzz Campaign for project '{project_name}' "
f"(workflow_id={workflow_id}, duration={campaign_duration_hours}h)"
)
results = {
"workflow_id": workflow_id,
"project_name": project_name,
"status": "running",
"steps": []
}
try:
# Step 1: Load OSS-Fuzz project configuration
workflow.logger.info(f"Step 1: Loading project config for '{project_name}'")
project_config = await workflow.execute_activity(
"load_ossfuzz_project",
args=[project_name],
start_to_close_timeout=timedelta(minutes=5),
retry_policy=RetryPolicy(
initial_interval=timedelta(seconds=1),
maximum_interval=timedelta(seconds=30),
maximum_attempts=3
)
)
results["steps"].append({
"step": "load_config",
"status": "success",
"language": project_config.get("language"),
"engines": project_config.get("fuzzing_engines", []),
"sanitizers": project_config.get("sanitizers", [])
})
workflow.logger.info(
f"✓ Loaded config: language={project_config.get('language')}, "
f"engines={project_config.get('fuzzing_engines')}"
)
# Step 2: Build project using OSS-Fuzz infrastructure
workflow.logger.info(f"Step 2: Building project '{project_name}'")
build_result = await workflow.execute_activity(
"build_ossfuzz_project",
args=[
project_name,
project_config,
override_sanitizer,
override_engine
],
start_to_close_timeout=timedelta(minutes=30),
retry_policy=RetryPolicy(
initial_interval=timedelta(seconds=2),
maximum_interval=timedelta(seconds=60),
maximum_attempts=2
)
)
results["steps"].append({
"step": "build_project",
"status": "success",
"fuzz_targets": len(build_result.get("fuzz_targets", [])),
"sanitizer": build_result.get("sanitizer_used"),
"engine": build_result.get("engine_used")
})
workflow.logger.info(
f"✓ Build completed: {len(build_result.get('fuzz_targets', []))} fuzz targets found"
)
if not build_result.get("fuzz_targets"):
raise Exception(f"No fuzz targets found for project {project_name}")
# Step 3: Run fuzzing on discovered targets
workflow.logger.info(f"Step 3: Fuzzing {len(build_result['fuzz_targets'])} targets")
# Determine which engine to use
engine_to_use = override_engine if override_engine else build_result["engine_used"]
duration_seconds = campaign_duration_hours * 3600
# Fuzz each target (in parallel if multiple targets)
fuzz_futures = []
for target_path in build_result["fuzz_targets"]:
future = workflow.execute_activity(
"fuzz_target",
args=[target_path, engine_to_use, duration_seconds, None, None],
start_to_close_timeout=timedelta(seconds=duration_seconds + 300),
retry_policy=RetryPolicy(
initial_interval=timedelta(seconds=2),
maximum_interval=timedelta(seconds=60),
maximum_attempts=1 # Fuzzing shouldn't retry
)
)
fuzz_futures.append(future)
# Wait for all fuzzing to complete
fuzz_results = await asyncio.gather(*fuzz_futures, return_exceptions=True)
# Aggregate results
total_execs = 0
total_crashes = 0
all_crashes = []
for i, result in enumerate(fuzz_results):
if isinstance(result, Exception):
workflow.logger.error(f"Fuzzing failed for target {i}: {result}")
continue
total_execs += result.get("total_executions", 0)
total_crashes += result.get("crashes", 0)
all_crashes.extend(result.get("crash_files", []))
results["steps"].append({
"step": "fuzzing",
"status": "success",
"total_executions": total_execs,
"crashes_found": total_crashes,
"targets_fuzzed": len(build_result["fuzz_targets"])
})
workflow.logger.info(
f"✓ Fuzzing completed: {total_execs} executions, {total_crashes} crashes"
)
# Step 4: Generate SARIF report
workflow.logger.info("Step 4: Generating SARIF report")
# TODO: Implement crash minimization and SARIF generation
# For now, return raw results
results["status"] = "success"
results["summary"] = {
"project": project_name,
"total_executions": total_execs,
"crashes_found": total_crashes,
"unique_crashes": len(set(all_crashes)),
"duration_hours": campaign_duration_hours,
"engine_used": engine_to_use,
"sanitizer_used": build_result.get("sanitizer_used")
}
results["crashes"] = all_crashes[:100] # Limit to first 100 crashes
workflow.logger.info(
f"✓ Campaign completed: {project_name} - "
f"{total_execs} execs, {total_crashes} crashes"
)
return results
except Exception as e:
workflow.logger.error(f"Workflow failed: {e}")
results["status"] = "error"
results["error"] = str(e)
results["steps"].append({
"step": "error",
"status": "failed",
"error": str(e)
})
raise