mirror of
https://github.com/FuzzingLabs/fuzzforge_ai.git
synced 2026-02-13 22:32:47 +00:00
* 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.
368 lines
14 KiB
Python
368 lines
14 KiB
Python
"""
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Security Analyzer Module - Analyzes code for security vulnerabilities
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"""
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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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import logging
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import re
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from pathlib import Path
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from typing import Dict, Any, List
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try:
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from toolbox.modules.base import BaseModule, ModuleMetadata, ModuleResult, ModuleFinding
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except ImportError:
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try:
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from modules.base import BaseModule, ModuleMetadata, ModuleResult, ModuleFinding
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except ImportError:
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from src.toolbox.modules.base import BaseModule, ModuleMetadata, ModuleResult, ModuleFinding
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logger = logging.getLogger(__name__)
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class SecurityAnalyzer(BaseModule):
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"""
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Analyzes source code for common security vulnerabilities.
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This module:
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- Detects hardcoded secrets and credentials
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- Identifies dangerous function calls
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- Finds SQL injection vulnerabilities
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- Detects insecure configurations
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"""
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def get_metadata(self) -> ModuleMetadata:
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"""Get module metadata"""
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return ModuleMetadata(
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name="security_analyzer",
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version="1.0.0",
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description="Analyzes code for security vulnerabilities",
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author="FuzzForge Team",
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category="analyzer",
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tags=["security", "vulnerabilities", "static-analysis"],
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input_schema={
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"file_extensions": {
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"type": "array",
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"items": {"type": "string"},
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"description": "File extensions to analyze",
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"default": [".py", ".js", ".java", ".php", ".rb", ".go"]
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},
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"check_secrets": {
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"type": "boolean",
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"description": "Check for hardcoded secrets",
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"default": True
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},
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"check_sql": {
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"type": "boolean",
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"description": "Check for SQL injection risks",
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"default": True
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},
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"check_dangerous_functions": {
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"type": "boolean",
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"description": "Check for dangerous function calls",
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"default": True
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}
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},
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output_schema={
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"findings": {
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"type": "array",
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"description": "List of security findings"
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}
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},
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requires_workspace=True
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)
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def validate_config(self, config: Dict[str, Any]) -> bool:
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"""Validate module configuration"""
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extensions = config.get("file_extensions", [])
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if not isinstance(extensions, list):
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raise ValueError("file_extensions must be a list")
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return True
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async def execute(self, config: Dict[str, Any], workspace: Path) -> ModuleResult:
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"""
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Execute the security analysis module.
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Args:
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config: Module configuration
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workspace: Path to the workspace directory
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Returns:
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ModuleResult with security findings
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"""
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self.start_timer()
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self.validate_workspace(workspace)
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self.validate_config(config)
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findings = []
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files_analyzed = 0
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# Get configuration
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file_extensions = config.get("file_extensions", [".py", ".js", ".java", ".php", ".rb", ".go"])
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check_secrets = config.get("check_secrets", True)
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check_sql = config.get("check_sql", True)
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check_dangerous = config.get("check_dangerous_functions", True)
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logger.info(f"Analyzing files with extensions: {file_extensions}")
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try:
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# Analyze each file
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for ext in file_extensions:
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for file_path in workspace.rglob(f"*{ext}"):
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if not file_path.is_file():
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continue
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files_analyzed += 1
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relative_path = file_path.relative_to(workspace)
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try:
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content = file_path.read_text(encoding='utf-8', errors='ignore')
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lines = content.splitlines()
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# Check for secrets
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if check_secrets:
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secret_findings = self._check_hardcoded_secrets(
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content, lines, relative_path
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)
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findings.extend(secret_findings)
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# Check for SQL injection
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if check_sql and ext in [".py", ".php", ".java", ".js"]:
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sql_findings = self._check_sql_injection(
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content, lines, relative_path
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)
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findings.extend(sql_findings)
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# Check for dangerous functions
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if check_dangerous:
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dangerous_findings = self._check_dangerous_functions(
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content, lines, relative_path, ext
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)
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findings.extend(dangerous_findings)
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except Exception as e:
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logger.error(f"Error analyzing file {relative_path}: {e}")
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# Create summary
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summary = {
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"files_analyzed": files_analyzed,
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"total_findings": len(findings),
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"extensions_scanned": file_extensions
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}
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return self.create_result(
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findings=findings,
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status="success" if files_analyzed > 0 else "partial",
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summary=summary,
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metadata={
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"workspace": str(workspace),
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"config": config
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}
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)
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except Exception as e:
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logger.error(f"Security analyzer failed: {e}")
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return self.create_result(
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findings=findings,
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status="failed",
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error=str(e)
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)
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def _check_hardcoded_secrets(
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self, content: str, lines: List[str], file_path: Path
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) -> List[ModuleFinding]:
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"""
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Check for hardcoded secrets in code.
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Args:
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content: File content
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lines: File lines
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file_path: Relative file path
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Returns:
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List of findings
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"""
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findings = []
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# Patterns for secrets
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secret_patterns = [
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(r'api[_-]?key\s*=\s*["\']([^"\']{20,})["\']', 'API Key'),
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(r'api[_-]?secret\s*=\s*["\']([^"\']{20,})["\']', 'API Secret'),
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(r'password\s*=\s*["\']([^"\']+)["\']', 'Hardcoded Password'),
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(r'token\s*=\s*["\']([^"\']{20,})["\']', 'Authentication Token'),
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(r'aws[_-]?access[_-]?key\s*=\s*["\']([^"\']+)["\']', 'AWS Access Key'),
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(r'aws[_-]?secret[_-]?key\s*=\s*["\']([^"\']+)["\']', 'AWS Secret Key'),
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(r'private[_-]?key\s*=\s*["\']([^"\']+)["\']', 'Private Key'),
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(r'["\']([A-Za-z0-9]{32,})["\']', 'Potential Secret Hash'),
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(r'Bearer\s+([A-Za-z0-9\-_]+\.[A-Za-z0-9\-_]+\.[A-Za-z0-9\-_]+)', 'JWT Token'),
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]
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for pattern, secret_type in secret_patterns:
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for match in re.finditer(pattern, content, re.IGNORECASE):
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# Find line number
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line_num = content[:match.start()].count('\n') + 1
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line_content = lines[line_num - 1] if line_num <= len(lines) else ""
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# Skip common false positives
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if self._is_false_positive_secret(match.group(0)):
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continue
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findings.append(self.create_finding(
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title=f"Hardcoded {secret_type} detected",
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description=f"Found potential hardcoded {secret_type} in {file_path}",
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severity="high" if "key" in secret_type.lower() else "medium",
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category="hardcoded_secret",
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file_path=str(file_path),
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line_start=line_num,
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code_snippet=line_content.strip()[:100],
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recommendation=f"Remove hardcoded {secret_type} and use environment variables or secure vault",
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metadata={"secret_type": secret_type}
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))
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return findings
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def _check_sql_injection(
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self, content: str, lines: List[str], file_path: Path
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) -> List[ModuleFinding]:
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"""
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Check for potential SQL injection vulnerabilities.
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Args:
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content: File content
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lines: File lines
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file_path: Relative file path
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Returns:
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List of findings
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"""
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findings = []
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# SQL injection patterns
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sql_patterns = [
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(r'(SELECT|INSERT|UPDATE|DELETE).*\+\s*[\'"]?\s*\+?\s*\w+', 'String concatenation in SQL'),
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(r'(SELECT|INSERT|UPDATE|DELETE).*%\s*[\'"]?\s*%?\s*\w+', 'String formatting in SQL'),
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(r'f[\'"].*?(SELECT|INSERT|UPDATE|DELETE).*?\{.*?\}', 'F-string in SQL query'),
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(r'query\s*=.*?\+', 'Dynamic query building'),
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(r'execute\s*\(.*?\+.*?\)', 'Dynamic execute statement'),
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]
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for pattern, vuln_type in sql_patterns:
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for match in re.finditer(pattern, content, re.IGNORECASE):
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line_num = content[:match.start()].count('\n') + 1
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line_content = lines[line_num - 1] if line_num <= len(lines) else ""
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findings.append(self.create_finding(
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title=f"Potential SQL Injection: {vuln_type}",
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description=f"Detected potential SQL injection vulnerability via {vuln_type}",
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severity="high",
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category="sql_injection",
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file_path=str(file_path),
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line_start=line_num,
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code_snippet=line_content.strip()[:100],
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recommendation="Use parameterized queries or prepared statements instead",
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metadata={"vulnerability_type": vuln_type}
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))
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return findings
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def _check_dangerous_functions(
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self, content: str, lines: List[str], file_path: Path, ext: str
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) -> List[ModuleFinding]:
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"""
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Check for dangerous function calls.
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Args:
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content: File content
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lines: File lines
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file_path: Relative file path
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ext: File extension
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Returns:
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List of findings
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"""
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findings = []
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# Language-specific dangerous functions
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dangerous_functions = {
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".py": [
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(r'eval\s*\(', 'eval()', 'Arbitrary code execution'),
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(r'exec\s*\(', 'exec()', 'Arbitrary code execution'),
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(r'os\.system\s*\(', 'os.system()', 'Command injection risk'),
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(r'subprocess\.call\s*\(.*shell=True', 'subprocess with shell=True', 'Command injection risk'),
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(r'pickle\.loads?\s*\(', 'pickle.load()', 'Deserialization vulnerability'),
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],
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".js": [
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(r'eval\s*\(', 'eval()', 'Arbitrary code execution'),
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(r'new\s+Function\s*\(', 'new Function()', 'Arbitrary code execution'),
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(r'innerHTML\s*=', 'innerHTML', 'XSS vulnerability'),
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(r'document\.write\s*\(', 'document.write()', 'XSS vulnerability'),
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],
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".php": [
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(r'eval\s*\(', 'eval()', 'Arbitrary code execution'),
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(r'exec\s*\(', 'exec()', 'Command execution'),
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(r'system\s*\(', 'system()', 'Command execution'),
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(r'shell_exec\s*\(', 'shell_exec()', 'Command execution'),
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(r'\$_GET\[', 'Direct $_GET usage', 'Input validation missing'),
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(r'\$_POST\[', 'Direct $_POST usage', 'Input validation missing'),
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]
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}
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if ext in dangerous_functions:
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for pattern, func_name, risk_type in dangerous_functions[ext]:
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for match in re.finditer(pattern, content):
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line_num = content[:match.start()].count('\n') + 1
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line_content = lines[line_num - 1] if line_num <= len(lines) else ""
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findings.append(self.create_finding(
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title=f"Dangerous function: {func_name}",
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description=f"Use of potentially dangerous function {func_name}: {risk_type}",
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severity="medium",
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category="dangerous_function",
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file_path=str(file_path),
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line_start=line_num,
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code_snippet=line_content.strip()[:100],
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recommendation=f"Consider safer alternatives to {func_name}",
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metadata={
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"function": func_name,
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"risk": risk_type
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}
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))
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return findings
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def _is_false_positive_secret(self, value: str) -> bool:
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"""
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Check if a potential secret is likely a false positive.
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Args:
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value: Potential secret value
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Returns:
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True if likely false positive
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"""
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false_positive_patterns = [
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'example',
|
|
'test',
|
|
'demo',
|
|
'sample',
|
|
'dummy',
|
|
'placeholder',
|
|
'xxx',
|
|
'123',
|
|
'change',
|
|
'your',
|
|
'here'
|
|
]
|
|
|
|
value_lower = value.lower()
|
|
return any(pattern in value_lower for pattern in false_positive_patterns) |