mirror of
https://github.com/FuzzingLabs/fuzzforge_ai.git
synced 2026-05-19 22:08:12 +02:00
432 lines
12 KiB
Python
432 lines
12 KiB
Python
"""
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Utility functions for the FuzzForge SDK.
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Provides helper functions for path validation, SARIF processing,
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volume mount creation, and other common operations.
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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 os
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import json
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from pathlib import Path
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from typing import Dict, Any, List, Optional, Union
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from datetime import datetime
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from .models import VolumeMount, ResourceLimits, WorkflowSubmission
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from .exceptions import ValidationError
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def validate_absolute_path(path: Union[str, Path]) -> Path:
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"""
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Validate that a path is absolute and exists.
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Args:
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path: Path to validate
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Returns:
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Validated Path object
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Raises:
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ValidationError: If path is not absolute or doesn't exist
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"""
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path_obj = Path(path)
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if not path_obj.is_absolute():
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raise ValidationError(f"Path must be absolute: {path}")
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if not path_obj.exists():
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raise ValidationError(f"Path does not exist: {path}")
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return path_obj
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def create_volume_mount(
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host_path: Union[str, Path],
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container_path: str,
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mode: str = "ro"
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) -> VolumeMount:
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"""
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Create a volume mount with path validation.
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Args:
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host_path: Host path to mount (must exist)
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container_path: Container path for the mount
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mode: Mount mode ("ro" or "rw")
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Returns:
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VolumeMount object
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Raises:
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ValidationError: If paths are invalid
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"""
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# Validate host path exists and is absolute
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validated_host_path = validate_absolute_path(host_path)
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# Validate container path is absolute
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if not container_path.startswith('/'):
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raise ValidationError(f"Container path must be absolute: {container_path}")
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# Validate mode
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if mode not in ["ro", "rw"]:
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raise ValidationError(f"Mode must be 'ro' or 'rw': {mode}")
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return VolumeMount(
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host_path=str(validated_host_path),
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container_path=container_path,
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mode=mode # type: ignore
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)
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def create_resource_limits(
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cpu_limit: Optional[str] = None,
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memory_limit: Optional[str] = None,
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cpu_request: Optional[str] = None,
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memory_request: Optional[str] = None
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) -> ResourceLimits:
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"""
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Create resource limits with validation.
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Args:
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cpu_limit: CPU limit (e.g., "2", "500m")
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memory_limit: Memory limit (e.g., "1Gi", "512Mi")
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cpu_request: CPU request (guaranteed)
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memory_request: Memory request (guaranteed)
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Returns:
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ResourceLimits object
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Raises:
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ValidationError: If resource specifications are invalid
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"""
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# Basic validation for CPU limits
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if cpu_limit is not None:
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if not (cpu_limit.endswith('m') or cpu_limit.isdigit()):
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raise ValidationError(f"Invalid CPU limit format: {cpu_limit}")
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if cpu_request is not None:
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if not (cpu_request.endswith('m') or cpu_request.isdigit()):
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raise ValidationError(f"Invalid CPU request format: {cpu_request}")
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# Basic validation for memory limits
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memory_suffixes = ['Ki', 'Mi', 'Gi', 'Ti', 'K', 'M', 'G', 'T']
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if memory_limit is not None:
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if not any(memory_limit.endswith(suffix) for suffix in memory_suffixes):
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if not memory_limit.isdigit():
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raise ValidationError(f"Invalid memory limit format: {memory_limit}")
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if memory_request is not None:
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if not any(memory_request.endswith(suffix) for suffix in memory_suffixes):
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if not memory_request.isdigit():
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raise ValidationError(f"Invalid memory request format: {memory_request}")
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return ResourceLimits(
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cpu_limit=cpu_limit,
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memory_limit=memory_limit,
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cpu_request=cpu_request,
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memory_request=memory_request
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)
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def create_workflow_submission(
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target_path: Union[str, Path],
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volume_mode: str = "ro",
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parameters: Optional[Dict[str, Any]] = None,
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timeout: Optional[int] = None,
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resource_limits: Optional[ResourceLimits] = None,
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additional_volumes: Optional[List[VolumeMount]] = None
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) -> WorkflowSubmission:
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"""
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Create a workflow submission with path validation.
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Args:
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target_path: Path to analyze (must exist)
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volume_mode: Mount mode for target path
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parameters: Workflow-specific parameters
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timeout: Execution timeout in seconds
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resource_limits: Resource limits for the container
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additional_volumes: Additional volume mounts
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Returns:
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WorkflowSubmission object
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Raises:
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ValidationError: If parameters are invalid
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"""
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# Validate target path
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validated_target_path = validate_absolute_path(target_path)
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# Validate volume mode
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if volume_mode not in ["ro", "rw"]:
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raise ValidationError(f"Volume mode must be 'ro' or 'rw': {volume_mode}")
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# Validate timeout
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if timeout is not None:
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if timeout < 1 or timeout > 604800: # Max 7 days
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raise ValidationError(f"Timeout must be between 1 and 604800 seconds: {timeout}")
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return WorkflowSubmission(
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target_path=str(validated_target_path),
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volume_mode=volume_mode, # type: ignore
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parameters=parameters or {},
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timeout=timeout,
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resource_limits=resource_limits,
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additional_volumes=additional_volumes or []
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)
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def extract_sarif_results(sarif_data: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""
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Extract results from SARIF format findings.
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Args:
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sarif_data: SARIF formatted data
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Returns:
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List of result objects from SARIF
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Raises:
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ValidationError: If SARIF data is malformed
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"""
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if not isinstance(sarif_data, dict):
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raise ValidationError("SARIF data must be a dictionary")
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runs = sarif_data.get("runs", [])
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if not isinstance(runs, list):
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raise ValidationError("SARIF runs must be a list")
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results = []
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for run in runs:
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if not isinstance(run, dict):
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continue
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run_results = run.get("results", [])
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if isinstance(run_results, list):
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results.extend(run_results)
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return results
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def count_sarif_severity_levels(sarif_data: Dict[str, Any]) -> Dict[str, int]:
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"""
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Count findings by severity level in SARIF data.
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Args:
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sarif_data: SARIF formatted data
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Returns:
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Dictionary mapping severity levels to counts
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"""
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results = extract_sarif_results(sarif_data)
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severity_counts = {"error": 0, "warning": 0, "note": 0, "info": 0}
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for result in results:
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level = result.get("level", "warning")
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if level in severity_counts:
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severity_counts[level] += 1
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else:
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# Default unknown levels to warning
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severity_counts["warning"] += 1
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return severity_counts
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def format_sarif_summary(sarif_data: Dict[str, Any]) -> str:
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"""
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Create a human-readable summary of SARIF findings.
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Args:
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sarif_data: SARIF formatted data
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Returns:
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Formatted summary string
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"""
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severity_counts = count_sarif_severity_levels(sarif_data)
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total_findings = sum(severity_counts.values())
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if total_findings == 0:
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return "No findings detected."
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summary_parts = [f"Total findings: {total_findings}"]
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for level, count in severity_counts.items():
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if count > 0:
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summary_parts.append(f"{level.title()}: {count}")
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return " | ".join(summary_parts)
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def save_sarif_to_file(sarif_data: Dict[str, Any], file_path: Union[str, Path]) -> None:
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"""
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Save SARIF data to a JSON file.
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Args:
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sarif_data: SARIF formatted data
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file_path: Path to save the file
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Raises:
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ValidationError: If file cannot be written
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"""
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try:
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path_obj = Path(file_path)
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# Create parent directories if they don't exist
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path_obj.parent.mkdir(parents=True, exist_ok=True)
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with open(path_obj, 'w', encoding='utf-8') as f:
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json.dump(sarif_data, f, indent=2, ensure_ascii=False)
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except (OSError, json.JSONEncodeError) as e:
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raise ValidationError(f"Failed to save SARIF file: {e}")
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def format_duration(seconds: int) -> str:
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"""
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Format duration in seconds to human-readable string.
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Args:
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seconds: Duration in seconds
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Returns:
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Formatted duration string
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"""
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if seconds < 60:
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return f"{seconds}s"
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elif seconds < 3600:
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minutes, secs = divmod(seconds, 60)
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return f"{minutes}m {secs}s"
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else:
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hours, remainder = divmod(seconds, 3600)
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minutes, secs = divmod(remainder, 60)
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return f"{hours}h {minutes}m {secs}s"
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def format_execution_rate(executions_per_sec: float) -> str:
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"""
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Format execution rate for display.
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Args:
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executions_per_sec: Executions per second
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Returns:
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Formatted rate string
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"""
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if executions_per_sec < 1:
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return f"{executions_per_sec:.2f} exec/s"
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elif executions_per_sec < 1000:
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return f"{executions_per_sec:.1f} exec/s"
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else:
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return f"{executions_per_sec/1000:.1f}k exec/s"
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def format_memory_size(size_bytes: int) -> str:
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"""
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Format memory size in bytes to human-readable string.
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Args:
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size_bytes: Size in bytes
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Returns:
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Formatted size string
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"""
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for unit in ['B', 'KB', 'MB', 'GB', 'TB']:
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if size_bytes < 1024.0:
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return f"{size_bytes:.1f} {unit}"
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size_bytes /= 1024.0
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return f"{size_bytes:.1f} PB"
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def get_project_files(
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project_path: Union[str, Path],
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extensions: Optional[List[str]] = None,
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exclude_dirs: Optional[List[str]] = None
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) -> List[Path]:
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"""
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Get list of files in a project directory.
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Args:
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project_path: Path to project directory
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extensions: List of file extensions to include (e.g., ['.py', '.js'])
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exclude_dirs: List of directory names to exclude (e.g., ['.git', 'node_modules'])
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Returns:
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List of file paths
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Raises:
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ValidationError: If project path is invalid
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"""
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project_path_obj = validate_absolute_path(project_path)
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if not project_path_obj.is_dir():
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raise ValidationError(f"Project path must be a directory: {project_path}")
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exclude_dirs = exclude_dirs or ['.git', '__pycache__', 'node_modules', '.pytest_cache']
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extensions = extensions or []
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files = []
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for root, dirs, filenames in os.walk(project_path_obj):
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# Remove excluded directories from search
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dirs[:] = [d for d in dirs if d not in exclude_dirs]
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root_path = Path(root)
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for filename in filenames:
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file_path = root_path / filename
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# Filter by extensions if specified
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if extensions and not any(filename.endswith(ext) for ext in extensions):
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continue
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files.append(file_path)
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return sorted(files)
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def estimate_analysis_time(
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project_path: Union[str, Path],
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workflow_type: str = "static"
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) -> int:
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"""
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Estimate analysis time based on project size and workflow type.
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Args:
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project_path: Path to project directory
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workflow_type: Type of workflow ("static", "dynamic", "fuzzing")
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Returns:
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Estimated time in seconds
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Raises:
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ValidationError: If project path is invalid
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"""
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files = get_project_files(project_path)
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total_size = sum(f.stat().st_size for f in files if f.exists())
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# Base estimates (very rough)
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if workflow_type == "static":
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# ~1MB per second for static analysis
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base_time = max(30, total_size // (1024 * 1024))
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elif workflow_type == "dynamic":
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# Dynamic analysis is slower
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base_time = max(60, total_size // (512 * 1024))
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elif workflow_type == "fuzzing":
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# Fuzzing can run for hours/days
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base_time = 3600 # Default to 1 hour
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else:
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# Unknown workflow type
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base_time = max(60, total_size // (1024 * 1024))
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# Factor in number of files
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file_factor = max(1, len(files) // 100)
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return base_time * file_factor |