mirror of
https://github.com/FuzzingLabs/fuzzforge_ai.git
synced 2026-02-28 08:33:25 +00:00
315 lines
10 KiB
Python
315 lines
10 KiB
Python
"""
|
|
File Scanner Module - Scans and enumerates files in the workspace
|
|
"""
|
|
|
|
# Copyright (c) 2025 FuzzingLabs
|
|
#
|
|
# Licensed under the Business Source License 1.1 (BSL). See the LICENSE file
|
|
# at the root of this repository for details.
|
|
#
|
|
# After the Change Date (four years from publication), this version of the
|
|
# Licensed Work will be made available under the Apache License, Version 2.0.
|
|
# See the LICENSE-APACHE file or http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Additional attribution and requirements are provided in the NOTICE file.
|
|
|
|
import logging
|
|
import mimetypes
|
|
from pathlib import Path
|
|
from typing import Dict, Any, List
|
|
import hashlib
|
|
|
|
try:
|
|
from toolbox.modules.base import BaseModule, ModuleMetadata, ModuleResult, ModuleFinding
|
|
except ImportError:
|
|
try:
|
|
from modules.base import BaseModule, ModuleMetadata, ModuleResult, ModuleFinding
|
|
except ImportError:
|
|
from src.toolbox.modules.base import BaseModule, ModuleMetadata, ModuleResult, ModuleFinding
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class FileScanner(BaseModule):
|
|
"""
|
|
Scans files in the mounted workspace and collects information.
|
|
|
|
This module:
|
|
- Enumerates files based on patterns
|
|
- Detects file types
|
|
- Calculates file hashes
|
|
- Identifies potentially sensitive files
|
|
"""
|
|
|
|
def get_metadata(self) -> ModuleMetadata:
|
|
"""Get module metadata"""
|
|
return ModuleMetadata(
|
|
name="file_scanner",
|
|
version="1.0.0",
|
|
description="Scans and enumerates files in the workspace",
|
|
author="FuzzForge Team",
|
|
category="scanner",
|
|
tags=["files", "enumeration", "discovery"],
|
|
input_schema={
|
|
"patterns": {
|
|
"type": "array",
|
|
"items": {"type": "string"},
|
|
"description": "File patterns to scan (e.g., ['*.py', '*.js'])",
|
|
"default": ["*"]
|
|
},
|
|
"max_file_size": {
|
|
"type": "integer",
|
|
"description": "Maximum file size to scan in bytes",
|
|
"default": 10485760 # 10MB
|
|
},
|
|
"check_sensitive": {
|
|
"type": "boolean",
|
|
"description": "Check for sensitive file patterns",
|
|
"default": True
|
|
},
|
|
"calculate_hashes": {
|
|
"type": "boolean",
|
|
"description": "Calculate SHA256 hashes for files",
|
|
"default": False
|
|
}
|
|
},
|
|
output_schema={
|
|
"findings": {
|
|
"type": "array",
|
|
"description": "List of discovered files with metadata"
|
|
}
|
|
},
|
|
requires_workspace=True
|
|
)
|
|
|
|
def validate_config(self, config: Dict[str, Any]) -> bool:
|
|
"""Validate module configuration"""
|
|
patterns = config.get("patterns", ["*"])
|
|
if not isinstance(patterns, list):
|
|
raise ValueError("patterns must be a list")
|
|
|
|
max_size = config.get("max_file_size", 10485760)
|
|
if not isinstance(max_size, int) or max_size <= 0:
|
|
raise ValueError("max_file_size must be a positive integer")
|
|
|
|
return True
|
|
|
|
async def execute(self, config: Dict[str, Any], workspace: Path) -> ModuleResult:
|
|
"""
|
|
Execute the file scanning module.
|
|
|
|
Args:
|
|
config: Module configuration
|
|
workspace: Path to the workspace directory
|
|
|
|
Returns:
|
|
ModuleResult with file findings
|
|
"""
|
|
self.start_timer()
|
|
self.validate_workspace(workspace)
|
|
self.validate_config(config)
|
|
|
|
findings = []
|
|
file_count = 0
|
|
total_size = 0
|
|
file_types = {}
|
|
|
|
# Get configuration
|
|
patterns = config.get("patterns", ["*"])
|
|
max_file_size = config.get("max_file_size", 10485760)
|
|
check_sensitive = config.get("check_sensitive", True)
|
|
calculate_hashes = config.get("calculate_hashes", False)
|
|
|
|
logger.info(f"Scanning workspace with patterns: {patterns}")
|
|
|
|
try:
|
|
# Scan for each pattern
|
|
for pattern in patterns:
|
|
for file_path in workspace.rglob(pattern):
|
|
if not file_path.is_file():
|
|
continue
|
|
|
|
file_count += 1
|
|
relative_path = file_path.relative_to(workspace)
|
|
|
|
# Get file stats
|
|
try:
|
|
stats = file_path.stat()
|
|
file_size = stats.st_size
|
|
total_size += file_size
|
|
|
|
# Skip large files
|
|
if file_size > max_file_size:
|
|
logger.warning(f"Skipping large file: {relative_path} ({file_size} bytes)")
|
|
continue
|
|
|
|
# Detect file type
|
|
file_type = self._detect_file_type(file_path)
|
|
if file_type not in file_types:
|
|
file_types[file_type] = 0
|
|
file_types[file_type] += 1
|
|
|
|
# Check for sensitive files
|
|
if check_sensitive and self._is_sensitive_file(file_path):
|
|
findings.append(self.create_finding(
|
|
title=f"Potentially sensitive file: {relative_path.name}",
|
|
description=f"Found potentially sensitive file at {relative_path}",
|
|
severity="medium",
|
|
category="sensitive_file",
|
|
file_path=str(relative_path),
|
|
metadata={
|
|
"file_size": file_size,
|
|
"file_type": file_type
|
|
}
|
|
))
|
|
|
|
# Calculate hash if requested
|
|
file_hash = None
|
|
if calculate_hashes and file_size < 1048576: # Only hash files < 1MB
|
|
file_hash = self._calculate_hash(file_path)
|
|
|
|
# Create informational finding for each file
|
|
findings.append(self.create_finding(
|
|
title=f"File discovered: {relative_path.name}",
|
|
description=f"File: {relative_path}",
|
|
severity="info",
|
|
category="file_enumeration",
|
|
file_path=str(relative_path),
|
|
metadata={
|
|
"file_size": file_size,
|
|
"file_type": file_type,
|
|
"file_hash": file_hash
|
|
}
|
|
))
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error processing file {relative_path}: {e}")
|
|
|
|
# Create summary
|
|
summary = {
|
|
"total_files": file_count,
|
|
"total_size_bytes": total_size,
|
|
"file_types": file_types,
|
|
"patterns_scanned": patterns
|
|
}
|
|
|
|
return self.create_result(
|
|
findings=findings,
|
|
status="success",
|
|
summary=summary,
|
|
metadata={
|
|
"workspace": str(workspace),
|
|
"config": config
|
|
}
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(f"File scanner failed: {e}")
|
|
return self.create_result(
|
|
findings=findings,
|
|
status="failed",
|
|
error=str(e)
|
|
)
|
|
|
|
def _detect_file_type(self, file_path: Path) -> str:
|
|
"""
|
|
Detect the type of a file.
|
|
|
|
Args:
|
|
file_path: Path to the file
|
|
|
|
Returns:
|
|
File type string
|
|
"""
|
|
# Try to determine from extension
|
|
mime_type, _ = mimetypes.guess_type(str(file_path))
|
|
if mime_type:
|
|
return mime_type
|
|
|
|
# Check by extension
|
|
ext = file_path.suffix.lower()
|
|
type_map = {
|
|
'.py': 'text/x-python',
|
|
'.js': 'application/javascript',
|
|
'.java': 'text/x-java',
|
|
'.cpp': 'text/x-c++',
|
|
'.c': 'text/x-c',
|
|
'.go': 'text/x-go',
|
|
'.rs': 'text/x-rust',
|
|
'.rb': 'text/x-ruby',
|
|
'.php': 'text/x-php',
|
|
'.yaml': 'text/yaml',
|
|
'.yml': 'text/yaml',
|
|
'.json': 'application/json',
|
|
'.xml': 'text/xml',
|
|
'.md': 'text/markdown',
|
|
'.txt': 'text/plain',
|
|
'.sh': 'text/x-shellscript',
|
|
'.bat': 'text/x-batch',
|
|
'.ps1': 'text/x-powershell'
|
|
}
|
|
|
|
return type_map.get(ext, 'application/octet-stream')
|
|
|
|
def _is_sensitive_file(self, file_path: Path) -> bool:
|
|
"""
|
|
Check if a file might contain sensitive information.
|
|
|
|
Args:
|
|
file_path: Path to the file
|
|
|
|
Returns:
|
|
True if potentially sensitive
|
|
"""
|
|
sensitive_patterns = [
|
|
'.env',
|
|
'.env.local',
|
|
'.env.production',
|
|
'credentials',
|
|
'password',
|
|
'secret',
|
|
'private_key',
|
|
'id_rsa',
|
|
'id_dsa',
|
|
'.pem',
|
|
'.key',
|
|
'.pfx',
|
|
'.p12',
|
|
'wallet',
|
|
'.ssh',
|
|
'token',
|
|
'api_key',
|
|
'config.json',
|
|
'settings.json',
|
|
'.git-credentials',
|
|
'.npmrc',
|
|
'.pypirc',
|
|
'.docker/config.json'
|
|
]
|
|
|
|
file_name_lower = file_path.name.lower()
|
|
for pattern in sensitive_patterns:
|
|
if pattern in file_name_lower:
|
|
return True
|
|
|
|
return False
|
|
|
|
def _calculate_hash(self, file_path: Path) -> str:
|
|
"""
|
|
Calculate SHA256 hash of a file.
|
|
|
|
Args:
|
|
file_path: Path to the file
|
|
|
|
Returns:
|
|
Hex string of SHA256 hash
|
|
"""
|
|
try:
|
|
sha256_hash = hashlib.sha256()
|
|
with open(file_path, "rb") as f:
|
|
for byte_block in iter(lambda: f.read(4096), b""):
|
|
sha256_hash.update(byte_block)
|
|
return sha256_hash.hexdigest()
|
|
except Exception as e:
|
|
logger.error(f"Failed to calculate hash for {file_path}: {e}")
|
|
return None |