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