mirror of
https://github.com/FuzzingLabs/fuzzforge_ai.git
synced 2026-08-21 16:17:11 +02:00
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
This commit is contained in:
Tanguy Duhamel
@@ -0,0 +1,9 @@
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"""
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Fuzzing modules for FuzzForge
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This package contains fuzzing modules for different fuzzing engines.
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"""
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from .atheris_fuzzer import AtherisFuzzer
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__all__ = ["AtherisFuzzer"]
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@@ -0,0 +1,377 @@
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"""
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Atheris Fuzzer Module
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Reusable module for fuzzing Python code using Atheris.
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Discovers and fuzzes user-provided Python targets with TestOneInput() function.
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"""
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import asyncio
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import base64
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import importlib.util
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import logging
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import sys
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import time
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import traceback
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from pathlib import Path
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from typing import Dict, Any, List, Optional, Callable
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import uuid
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from modules.base import BaseModule, ModuleMetadata, ModuleResult, ModuleFinding
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logger = logging.getLogger(__name__)
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class AtherisFuzzer(BaseModule):
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"""
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Atheris fuzzing module - discovers and fuzzes Python code.
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This module can be used by any workflow to fuzz Python targets.
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"""
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def __init__(self):
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super().__init__()
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self.crashes = []
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self.total_executions = 0
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self.start_time = None
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self.last_stats_time = 0
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def get_metadata(self) -> ModuleMetadata:
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"""Return module metadata"""
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return ModuleMetadata(
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name="atheris_fuzzer",
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version="1.0.0",
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description="Python fuzzing using Atheris - discovers and fuzzes TestOneInput() functions",
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author="FuzzForge Team",
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category="fuzzer",
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tags=["fuzzing", "atheris", "python", "coverage"],
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input_schema={
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"type": "object",
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"properties": {
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"target_file": {
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"type": "string",
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"description": "Python file with TestOneInput() function (auto-discovered if not specified)"
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},
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"max_iterations": {
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"type": "integer",
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"description": "Maximum fuzzing iterations",
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"default": 100000
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},
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"timeout_seconds": {
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"type": "integer",
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"description": "Fuzzing timeout in seconds",
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"default": 300
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},
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"stats_callback": {
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"description": "Optional callback for real-time statistics"
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}
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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 fuzzing configuration"""
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max_iterations = config.get("max_iterations", 100000)
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if not isinstance(max_iterations, int) or max_iterations <= 0:
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raise ValueError(f"max_iterations must be positive integer, got: {max_iterations}")
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timeout = config.get("timeout_seconds", 300)
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if not isinstance(timeout, int) or timeout <= 0:
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raise ValueError(f"timeout_seconds must be positive integer, got: {timeout}")
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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 Atheris fuzzing on user code.
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Args:
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config: Fuzzing configuration
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workspace: Path to user's uploaded code
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Returns:
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ModuleResult with crash findings
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"""
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self.start_timer()
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self.start_time = time.time()
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# Validate configuration
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self.validate_config(config)
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self.validate_workspace(workspace)
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# Extract config
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target_file = config.get("target_file")
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max_iterations = config.get("max_iterations", 100000)
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timeout_seconds = config.get("timeout_seconds", 300)
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stats_callback = config.get("stats_callback")
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logger.info(
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f"Starting Atheris fuzzing (max_iterations={max_iterations}, "
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f"timeout={timeout_seconds}s, target={target_file or 'auto-discover'})"
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)
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try:
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# Step 1: Discover or load target
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target_path = self._discover_target(workspace, target_file)
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logger.info(f"Using fuzz target: {target_path}")
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# Step 2: Load target module
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test_one_input = self._load_target_module(target_path)
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logger.info(f"Loaded TestOneInput function from {target_path}")
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# Step 3: Run fuzzing
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await self._run_fuzzing(
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test_one_input=test_one_input,
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target_path=target_path,
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max_iterations=max_iterations,
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timeout_seconds=timeout_seconds,
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stats_callback=stats_callback
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)
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# Step 4: Generate findings from crashes
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findings = self._generate_findings(target_path)
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logger.info(
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f"Fuzzing completed: {self.total_executions} executions, "
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f"{len(self.crashes)} crashes found"
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)
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return self.create_result(
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findings=findings,
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status="success",
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summary={
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"total_executions": self.total_executions,
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"crashes_found": len(self.crashes),
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"execution_time": self.get_execution_time(),
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"target_file": str(target_path.relative_to(workspace))
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},
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metadata={
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"max_iterations": max_iterations,
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"timeout_seconds": timeout_seconds
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}
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)
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except Exception as e:
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logger.error(f"Fuzzing failed: {e}", exc_info=True)
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return self.create_result(
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findings=[],
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status="failed",
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error=str(e)
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)
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def _discover_target(self, workspace: Path, target_file: Optional[str]) -> Path:
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"""
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Discover fuzz target in workspace.
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Args:
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workspace: Path to workspace
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target_file: Explicit target file or None for auto-discovery
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Returns:
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Path to target file
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"""
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if target_file:
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# Use specified target
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target_path = workspace / target_file
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if not target_path.exists():
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raise FileNotFoundError(f"Target file not found: {target_file}")
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return target_path
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# Auto-discover: look for fuzz_*.py or *_fuzz.py
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logger.info("Auto-discovering fuzz targets...")
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candidates = []
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# Use rglob for recursive search (searches all subdirectories)
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for pattern in ["fuzz_*.py", "*_fuzz.py", "fuzz_target.py"]:
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matches = list(workspace.rglob(pattern))
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candidates.extend(matches)
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if not candidates:
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raise FileNotFoundError(
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"No fuzz targets found. Expected files matching: fuzz_*.py, *_fuzz.py, or fuzz_target.py"
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)
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# Use first candidate
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target = candidates[0]
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if len(candidates) > 1:
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logger.warning(
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f"Multiple fuzz targets found: {[str(c) for c in candidates]}. "
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f"Using: {target.name}"
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)
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return target
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def _load_target_module(self, target_path: Path) -> Callable:
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"""
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Load target module and get TestOneInput function.
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Args:
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target_path: Path to Python file with TestOneInput
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Returns:
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TestOneInput function
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"""
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# Add target directory to sys.path
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target_dir = target_path.parent
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if str(target_dir) not in sys.path:
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sys.path.insert(0, str(target_dir))
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# Load module dynamically
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module_name = target_path.stem
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spec = importlib.util.spec_from_file_location(module_name, target_path)
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if spec is None or spec.loader is None:
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raise ImportError(f"Cannot load module from {target_path}")
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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# Get TestOneInput function
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if not hasattr(module, "TestOneInput"):
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raise AttributeError(
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f"Module {module_name} does not have TestOneInput() function. "
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"Atheris requires a TestOneInput(data: bytes) function."
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)
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return module.TestOneInput
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async def _run_fuzzing(
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self,
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test_one_input: Callable,
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target_path: Path,
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max_iterations: int,
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timeout_seconds: int,
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stats_callback: Optional[Callable] = None
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):
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"""
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Run Atheris fuzzing with real-time monitoring.
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Args:
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test_one_input: TestOneInput function to fuzz
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target_path: Path to target file
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max_iterations: Max iterations
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timeout_seconds: Timeout in seconds
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stats_callback: Optional callback for stats
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"""
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import atheris
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self.crashes = []
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self.total_executions = 0
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corpus_size = 0
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# Wrapper to track executions and crashes
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def fuzz_wrapper(data):
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self.total_executions += 1
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try:
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test_one_input(data)
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except Exception as e:
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# Capture crash
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crash_info = {
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"input": data,
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"exception": e,
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"exception_type": type(e).__name__,
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"stack_trace": traceback.format_exc(),
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"execution": self.total_executions
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}
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self.crashes.append(crash_info)
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logger.warning(
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f"Crash found (execution {self.total_executions}): "
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f"{type(e).__name__}: {str(e)}"
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)
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# Re-raise so Atheris detects it
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raise
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# Configure Atheris
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atheris.Setup(
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[
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"atheris_fuzzer",
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f"-runs={max_iterations}",
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f"-max_total_time={timeout_seconds}",
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"-print_final_stats=1"
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],
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fuzz_wrapper
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)
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logger.info(f"Starting Atheris fuzzer (max_runs={max_iterations}, timeout={timeout_seconds}s)...")
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# Run fuzzing in a separate task with monitoring
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async def monitor_stats():
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"""Monitor and report stats every 5 seconds"""
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while True:
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await asyncio.sleep(5)
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if stats_callback:
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elapsed = time.time() - self.start_time
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execs_per_sec = self.total_executions / elapsed if elapsed > 0 else 0
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await stats_callback({
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"total_execs": self.total_executions,
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"execs_per_sec": execs_per_sec,
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"crashes": len(self.crashes),
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"corpus_size": corpus_size,
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"coverage": 0.0, # Atheris doesn't expose coverage easily
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"elapsed_time": int(elapsed)
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})
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# Start monitoring task
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monitor_task = None
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if stats_callback:
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monitor_task = asyncio.create_task(monitor_stats())
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try:
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# Run fuzzing (blocking)
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atheris.Fuzz()
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except SystemExit:
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# Atheris exits when done
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pass
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finally:
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# Stop monitoring
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if monitor_task:
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monitor_task.cancel()
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try:
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await monitor_task
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except asyncio.CancelledError:
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pass
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def _generate_findings(self, target_path: Path) -> List[ModuleFinding]:
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"""
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Generate ModuleFinding objects from crashes.
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Args:
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target_path: Path to target file
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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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for crash in self.crashes:
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# Encode crash input for storage
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crash_input_b64 = base64.b64encode(crash["input"]).decode()
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finding = self.create_finding(
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title=f"Crash: {crash['exception_type']}",
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description=(
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f"Atheris found crash during fuzzing:\n"
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f"Exception: {crash['exception_type']}\n"
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f"Message: {str(crash['exception'])}\n"
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f"Execution: {crash['execution']}"
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),
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severity="critical",
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category="crash",
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file_path=str(target_path),
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metadata={
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"crash_input_base64": crash_input_b64,
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"crash_input_hex": crash["input"].hex(),
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"exception_type": crash["exception_type"],
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"stack_trace": crash["stack_trace"],
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"execution_number": crash["execution"]
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},
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recommendation=(
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"Review the crash stack trace and input to identify the vulnerability. "
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"The crash input is provided in base64 and hex formats for reproduction."
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)
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)
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findings.append(finding)
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return findings
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@@ -0,0 +1,9 @@
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"""
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Atheris Fuzzing Workflow
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Fuzzes user-provided Python code using Atheris.
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"""
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from .workflow import AtherisFuzzingWorkflow
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__all__ = ["AtherisFuzzingWorkflow"]
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@@ -0,0 +1,90 @@
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"""
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Atheris Fuzzing Workflow Activities
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Activities specific to the Atheris fuzzing workflow.
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"""
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import logging
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import sys
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from datetime import datetime
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from pathlib import Path
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from typing import Dict, Any
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from temporalio import activity
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# Configure logging
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logger = logging.getLogger(__name__)
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# Add toolbox to path for module imports
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sys.path.insert(0, '/app/toolbox')
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@activity.defn(name="fuzz_with_atheris")
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async def fuzz_activity(workspace_path: str, config: dict) -> dict:
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"""
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Fuzzing activity using the AtherisFuzzer module on user code.
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This activity:
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1. Imports the reusable AtherisFuzzer module
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2. Sets up real-time stats callback
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3. Executes fuzzing on user's TestOneInput() function
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4. Returns findings as ModuleResult
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Args:
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workspace_path: Path to the workspace directory (user's uploaded code)
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config: Fuzzer configuration (target_file, max_iterations, timeout_seconds)
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Returns:
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Fuzzer results dictionary (findings, summary, metadata)
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"""
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logger.info(f"Activity: fuzz_with_atheris (workspace={workspace_path})")
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try:
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# Import reusable AtherisFuzzer module
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from modules.fuzzer import AtherisFuzzer
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workspace = Path(workspace_path)
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if not workspace.exists():
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raise FileNotFoundError(f"Workspace not found: {workspace_path}")
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# Get activity info for real-time stats
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info = activity.info()
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run_id = info.workflow_id
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# Define stats callback for real-time monitoring
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async def stats_callback(stats_data: Dict[str, Any]):
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"""Callback for live fuzzing statistics"""
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try:
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logger.info("LIVE_STATS", extra={
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"stats_type": "fuzzing_live_update",
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"workflow_type": "atheris_fuzzing",
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"run_id": run_id,
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"executions": stats_data.get("total_execs", 0),
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"executions_per_sec": stats_data.get("execs_per_sec", 0.0),
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"crashes": stats_data.get("crashes", 0),
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"corpus_size": stats_data.get("corpus_size", 0),
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"coverage": stats_data.get("coverage", 0.0),
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"elapsed_time": stats_data.get("elapsed_time", 0),
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"timestamp": datetime.utcnow().isoformat()
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})
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except Exception as e:
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logger.warning(f"Error in stats callback: {e}")
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# Add stats callback to config
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config["stats_callback"] = stats_callback
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# Execute the fuzzer module
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fuzzer = AtherisFuzzer()
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result = await fuzzer.execute(config, workspace)
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logger.info(
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f"✓ Fuzzing completed: "
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f"{result.summary.get('total_executions', 0)} executions, "
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f"{result.summary.get('crashes_found', 0)} crashes"
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)
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return result.dict()
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except Exception as e:
|
||||
logger.error(f"Fuzzing failed: {e}", exc_info=True)
|
||||
raise
|
||||
@@ -0,0 +1,76 @@
|
||||
name: atheris_fuzzing
|
||||
version: "1.0.0"
|
||||
vertical: python
|
||||
description: "Fuzz Python code using Atheris with real-time monitoring. Automatically discovers and fuzzes TestOneInput() functions in user code."
|
||||
author: "FuzzForge Team"
|
||||
category: "fuzzing"
|
||||
tags:
|
||||
- "fuzzing"
|
||||
- "atheris"
|
||||
- "python"
|
||||
- "coverage"
|
||||
- "security"
|
||||
|
||||
supported_volume_modes:
|
||||
- "ro"
|
||||
|
||||
default_volume_mode: "ro"
|
||||
default_target_path: "/workspace"
|
||||
|
||||
requirements:
|
||||
tools:
|
||||
- "atheris_fuzzer"
|
||||
resources:
|
||||
memory: "512Mi"
|
||||
cpu: "500m"
|
||||
timeout: 3600
|
||||
|
||||
has_docker: false
|
||||
|
||||
default_parameters:
|
||||
target_file: null
|
||||
max_iterations: 100000
|
||||
timeout_seconds: 300
|
||||
|
||||
parameters:
|
||||
type: object
|
||||
properties:
|
||||
target_file:
|
||||
type: string
|
||||
description: "Python file with TestOneInput() function (auto-discovered if not specified)"
|
||||
max_iterations:
|
||||
type: integer
|
||||
default: 100000
|
||||
description: "Maximum fuzzing iterations"
|
||||
timeout_seconds:
|
||||
type: integer
|
||||
default: 300
|
||||
description: "Fuzzing timeout in seconds (5 minutes)"
|
||||
|
||||
output_schema:
|
||||
type: object
|
||||
properties:
|
||||
findings:
|
||||
type: array
|
||||
description: "Crashes and vulnerabilities found during fuzzing"
|
||||
items:
|
||||
type: object
|
||||
properties:
|
||||
title:
|
||||
type: string
|
||||
severity:
|
||||
type: string
|
||||
category:
|
||||
type: string
|
||||
metadata:
|
||||
type: object
|
||||
summary:
|
||||
type: object
|
||||
description: "Fuzzing execution summary"
|
||||
properties:
|
||||
total_executions:
|
||||
type: integer
|
||||
crashes_found:
|
||||
type: integer
|
||||
execution_time:
|
||||
type: number
|
||||
@@ -0,0 +1,171 @@
|
||||
"""
|
||||
Atheris Fuzzing Workflow - Temporal Version
|
||||
|
||||
Fuzzes user-provided Python code using Atheris with real-time monitoring.
|
||||
"""
|
||||
|
||||
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 AtherisFuzzingWorkflow:
|
||||
"""
|
||||
Fuzz Python code using Atheris.
|
||||
|
||||
User workflow:
|
||||
1. User runs: ff workflow run atheris_fuzzing .
|
||||
2. CLI uploads project to MinIO
|
||||
3. Worker downloads project
|
||||
4. Worker fuzzes TestOneInput() function
|
||||
5. Crashes reported as findings
|
||||
"""
|
||||
|
||||
@workflow.run
|
||||
async def run(
|
||||
self,
|
||||
target_id: str, # MinIO UUID of uploaded user code
|
||||
target_file: Optional[str] = None, # Optional: specific file to fuzz
|
||||
max_iterations: int = 100000,
|
||||
timeout_seconds: int = 300
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Main workflow execution.
|
||||
|
||||
Args:
|
||||
target_id: UUID of the uploaded target in MinIO
|
||||
target_file: Optional specific Python file with TestOneInput() (auto-discovered if None)
|
||||
max_iterations: Maximum fuzzing iterations
|
||||
timeout_seconds: Fuzzing timeout in seconds
|
||||
|
||||
Returns:
|
||||
Dictionary containing findings and summary
|
||||
"""
|
||||
workflow_id = workflow.info().workflow_id
|
||||
|
||||
workflow.logger.info(
|
||||
f"Starting AtherisFuzzingWorkflow "
|
||||
f"(workflow_id={workflow_id}, target_id={target_id}, "
|
||||
f"target_file={target_file or 'auto-discover'}, max_iterations={max_iterations}, "
|
||||
f"timeout_seconds={timeout_seconds})"
|
||||
)
|
||||
|
||||
results = {
|
||||
"workflow_id": workflow_id,
|
||||
"target_id": target_id,
|
||||
"status": "running",
|
||||
"steps": []
|
||||
}
|
||||
|
||||
try:
|
||||
# Step 1: Download user's project from MinIO
|
||||
workflow.logger.info("Step 1: Downloading user code from MinIO")
|
||||
target_path = await workflow.execute_activity(
|
||||
"get_target",
|
||||
target_id,
|
||||
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": "download_target",
|
||||
"status": "success",
|
||||
"target_path": target_path
|
||||
})
|
||||
workflow.logger.info(f"✓ User code downloaded to: {target_path}")
|
||||
|
||||
# Step 2: Run Atheris fuzzing
|
||||
workflow.logger.info("Step 2: Running Atheris fuzzing")
|
||||
|
||||
# Use defaults if parameters are None
|
||||
max_iterations = max_iterations if max_iterations is not None else 100000
|
||||
timeout_seconds = timeout_seconds if timeout_seconds is not None else 300
|
||||
|
||||
fuzz_config = {
|
||||
"target_file": target_file,
|
||||
"max_iterations": max_iterations,
|
||||
"timeout_seconds": timeout_seconds
|
||||
}
|
||||
|
||||
fuzz_results = await workflow.execute_activity(
|
||||
"fuzz_with_atheris",
|
||||
args=[target_path, fuzz_config],
|
||||
start_to_close_timeout=timedelta(seconds=timeout_seconds + 60),
|
||||
retry_policy=RetryPolicy(
|
||||
initial_interval=timedelta(seconds=2),
|
||||
maximum_interval=timedelta(seconds=60),
|
||||
maximum_attempts=1 # Fuzzing shouldn't retry
|
||||
)
|
||||
)
|
||||
|
||||
results["steps"].append({
|
||||
"step": "fuzzing",
|
||||
"status": "success",
|
||||
"executions": fuzz_results.get("summary", {}).get("total_executions", 0),
|
||||
"crashes": fuzz_results.get("summary", {}).get("crashes_found", 0)
|
||||
})
|
||||
workflow.logger.info(
|
||||
f"✓ Fuzzing completed: "
|
||||
f"{fuzz_results.get('summary', {}).get('total_executions', 0)} executions, "
|
||||
f"{fuzz_results.get('summary', {}).get('crashes_found', 0)} crashes"
|
||||
)
|
||||
|
||||
# Step 3: Upload results to MinIO
|
||||
workflow.logger.info("Step 3: Uploading results")
|
||||
try:
|
||||
results_url = await workflow.execute_activity(
|
||||
"upload_results",
|
||||
args=[workflow_id, fuzz_results, "json"],
|
||||
start_to_close_timeout=timedelta(minutes=2)
|
||||
)
|
||||
results["results_url"] = results_url
|
||||
workflow.logger.info(f"✓ Results uploaded to: {results_url}")
|
||||
except Exception as e:
|
||||
workflow.logger.warning(f"Failed to upload results: {e}")
|
||||
results["results_url"] = None
|
||||
|
||||
# Step 4: Cleanup cache
|
||||
workflow.logger.info("Step 4: Cleaning up cache")
|
||||
try:
|
||||
await workflow.execute_activity(
|
||||
"cleanup_cache",
|
||||
target_path,
|
||||
start_to_close_timeout=timedelta(minutes=1)
|
||||
)
|
||||
workflow.logger.info("✓ Cache cleaned up")
|
||||
except Exception as e:
|
||||
workflow.logger.warning(f"Cache cleanup failed: {e}")
|
||||
|
||||
# Mark workflow as successful
|
||||
results["status"] = "success"
|
||||
results["findings"] = fuzz_results.get("findings", [])
|
||||
results["summary"] = fuzz_results.get("summary", {})
|
||||
workflow.logger.info(
|
||||
f"✓ Workflow completed successfully: {workflow_id} "
|
||||
f"({results['summary'].get('crashes_found', 0)} crashes found)"
|
||||
)
|
||||
|
||||
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
|
||||
Reference in New Issue
Block a user