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# Collections Management
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Tools for working with ATT&CK Collections, converting between collection formats, and generating documentation from collection data. ATT&CK Collections are curated sets of ATT&CK techniques, groups, software, and other objects organized around specific themes, threat actors, or analytical frameworks.
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## Capabilities
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### Collection to Index Conversion
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Convert ATT&CK Collection files to index format for easier processing and analysis.
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```python { .api }
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class CollectionToIndex:
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    def __init__(self):
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        """
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        Initialize collection to index converter.
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        """
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    def convert(self, collection_file: str, output_file: str) -> None:
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        """
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        Convert ATT&CK Collection file to index format.
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        Args:
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            collection_file (str): Path to input ATT&CK Collection JSON file
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            output_file (str): Path to output index file
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        """
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    def parse_collection(self, collection_data: dict) -> dict:
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        """
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        Parse collection data into structured index format.
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        Args:
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            collection_data (dict): Raw collection data from JSON file
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        Returns:
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            dict: Structured index data with metadata and object listings
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        """
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    def extract_objects(self, collection_data: dict) -> Dict[str, List[dict]]:
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        """
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        Extract and categorize objects from collection.
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        Args:
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            collection_data (dict): Collection data
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        Returns:
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            Dict[str, List[dict]]: Objects organized by type (techniques, groups, etc.)
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        """
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    def validate_collection(self, collection_data: dict) -> bool:
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        """
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        Validate collection format and required fields.
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        Args:
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            collection_data (dict): Collection data to validate
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        Returns:
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            bool: True if valid, False otherwise
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        """
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```
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### Index to Markdown Conversion
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Generate comprehensive Markdown documentation from collection index files.
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```python { .api }
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class IndexToMarkdown:
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    def __init__(self):
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        """
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        Initialize index to markdown converter.
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        """
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    def convert(self, index_file: str, output_file: str) -> None:
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        """
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        Convert collection index to Markdown documentation.
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        Args:
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            index_file (str): Path to collection index file
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            output_file (str): Path to output Markdown file
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        """
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    def generate_overview(self, index_data: dict) -> str:
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        """
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        Generate overview section with collection metadata.
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        Args:
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            index_data (dict): Index data from collection
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        Returns:
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            str: Markdown overview section
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        """
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    def generate_object_tables(self, index_data: dict) -> str:
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        """
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        Generate tables for each object type in the collection.
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        Args:
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            index_data (dict): Index data with object listings
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        Returns:
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            str: Markdown tables for techniques, groups, software, etc.
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        """
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    def generate_relationships_section(self, index_data: dict) -> str:
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        """
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        Generate section documenting relationships between objects.
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        Args:
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            index_data (dict): Index data with relationship information
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        Returns:
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            str: Markdown section with relationship mappings
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        """
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    def format_technique_table(self, techniques: List[dict]) -> str:
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        """
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        Format techniques as Markdown table.
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        Args:
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            techniques (List[dict]): List of technique objects
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        Returns:
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            str: Markdown table with technique details
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        """
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    def format_group_table(self, groups: List[dict]) -> str:
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        """
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        Format groups as Markdown table.
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        Args:
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            groups (List[dict]): List of group objects
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        Returns:
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            str: Markdown table with group details
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        """
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    def format_software_table(self, software: List[dict]) -> str:
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        """
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        Format software as Markdown table.
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        Args:
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            software (List[dict]): List of software objects
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        Returns:
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            str: Markdown table with software details
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        """
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```
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### CLI Functions
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Command-line interfaces for collection processing workflows.
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```python { .api }
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def collection_to_index_main(args: List[str]) -> None:
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    """
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    CLI entry point for collectionToIndex_cli command.
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    Args:
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        args (List[str]): Command-line arguments
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            --input: Input collection file path
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            --output: Output index file path
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            --validate: Validate collection format
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    """
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def index_to_markdown_main(args: List[str]) -> None:
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    """
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    CLI entry point for indexToMarkdown_cli command.
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    Args:
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        args (List[str]): Command-line arguments
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            --input: Input index file path
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            --output: Output markdown file path
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            --template: Markdown template to use
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            --include-relationships: Include relationship mappings
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    """
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```
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## Usage Examples
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### Converting Collections to Index Format
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```python
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from mitreattack.collections import CollectionToIndex
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# Initialize converter
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converter = CollectionToIndex()
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# Convert collection file to index
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converter.convert(
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    collection_file="apt29_collection.json",
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    output_file="apt29_index.json"
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)
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print("Collection converted to index format")
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```
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### Working with Collection Data
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```python
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import json
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from mitreattack.collections import CollectionToIndex
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# Load and parse collection manually
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converter = CollectionToIndex()
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with open("threat_collection.json", "r") as f:
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    collection_data = json.load(f)
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# Validate collection
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if converter.validate_collection(collection_data):
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    print("Collection format is valid")
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    # Extract objects by type
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    objects_by_type = converter.extract_objects(collection_data)
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    print(f"Techniques: {len(objects_by_type.get('techniques', []))}")
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    print(f"Groups: {len(objects_by_type.get('groups', []))}")
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    print(f"Software: {len(objects_by_type.get('software', []))}")
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    # Convert to structured index
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    index_data = converter.parse_collection(collection_data)
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    with open("structured_index.json", "w") as f:
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        json.dump(index_data, f, indent=2)
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else:
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    print("Collection format is invalid")
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```
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### Generating Markdown Documentation
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```python
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from mitreattack.collections import IndexToMarkdown
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# Initialize markdown generator
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generator = IndexToMarkdown()
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# Convert index to markdown documentation
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generator.convert(
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    index_file="apt29_index.json", 
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    output_file="apt29_report.md"
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)
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print("Markdown documentation generated")
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```
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### Custom Markdown Generation
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```python
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import json
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from mitreattack.collections import IndexToMarkdown
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# Load index data
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with open("threat_index.json", "r") as f:
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    index_data = json.load(f)
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generator = IndexToMarkdown()
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# Generate individual sections
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overview = generator.generate_overview(index_data)
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object_tables = generator.generate_object_tables(index_data)
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relationships = generator.generate_relationships_section(index_data)
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# Combine into custom report
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custom_report = f"""
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# Threat Intelligence Report
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{overview}
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## Detailed Analysis
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{object_tables}
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## Relationship Analysis
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{relationships}
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## Appendix
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Additional analysis and recommendations...
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"""
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with open("custom_threat_report.md", "w") as f:
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    f.write(custom_report)
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```
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### Working with Specific Object Types
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```python
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import json
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from mitreattack.collections import IndexToMarkdown
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# Load index data
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with open("collection_index.json", "r") as f:
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    index_data = json.load(f)
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generator = IndexToMarkdown()
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# Generate tables for specific object types
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if "techniques" in index_data:
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    techniques_table = generator.format_technique_table(index_data["techniques"])
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    print("Techniques Table:")
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    print(techniques_table)
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if "groups" in index_data:
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    groups_table = generator.format_group_table(index_data["groups"])
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    print("\\nGroups Table:")
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    print(groups_table)
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if "software" in index_data:
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    software_table = generator.format_software_table(index_data["software"])
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    print("\\nSoftware Table:")
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    print(software_table)
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```
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### CLI Usage Examples
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```bash
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# Convert ATT&CK Collection to index format
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collectionToIndex_cli --input apt29_collection.json --output apt29_index.json --validate
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# Generate comprehensive markdown report
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indexToMarkdown_cli --input apt29_index.json --output apt29_report.md --include-relationships
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# Batch process multiple collections
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for collection in collections/*.json; do
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    base_name=$(basename "$collection" .json)
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    collectionToIndex_cli --input "$collection" --output "indices/${base_name}_index.json"
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    indexToMarkdown_cli --input "indices/${base_name}_index.json" --output "reports/${base_name}_report.md"
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done
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```
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### Collection Validation and Quality Checks
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```python
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import json
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from mitreattack.collections import CollectionToIndex
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def analyze_collection_quality(collection_file):
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    """Analyze collection for completeness and quality."""
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    converter = CollectionToIndex()
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    with open(collection_file, "r") as f:
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        collection_data = json.load(f)
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    # Basic validation
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    is_valid = converter.validate_collection(collection_data)
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    print(f"Collection valid: {is_valid}")
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    if not is_valid:
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        return
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    # Extract and analyze objects
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    objects = converter.extract_objects(collection_data)
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    # Quality metrics
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    total_objects = sum(len(obj_list) for obj_list in objects.values())
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    print(f"Total objects: {total_objects}")
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    for obj_type, obj_list in objects.items():
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        print(f"{obj_type.capitalize()}: {len(obj_list)}")
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        # Check for missing descriptions
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        missing_desc = [obj for obj in obj_list if not obj.get("description")]
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        if missing_desc:
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            print(f"  - {len(missing_desc)} {obj_type} missing descriptions")
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    # Check metadata completeness
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    metadata = collection_data.get("metadata", {})
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    required_fields = ["name", "version", "description", "created"]
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    missing_metadata = [field for field in required_fields if not metadata.get(field)]
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    if missing_metadata:
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        print(f"Missing metadata fields: {missing_metadata}")
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    else:
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        print("All required metadata fields present")
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# Analyze collection quality
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analyze_collection_quality("my_collection.json")
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```
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## Collection Format
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ATT&CK Collections follow a standard JSON format:
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```json
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{
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  "id": "collection-uuid",
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  "spec_version": "2.1",
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  "type": "x-mitre-collection",
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  "name": "Collection Name",
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  "description": "Collection description",
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  "created": "2023-01-01T00:00:00.000Z",
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  "modified": "2023-01-01T00:00:00.000Z",
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  "created_by_ref": "identity--uuid",
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  "object_refs": [
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    "attack-pattern--uuid1",
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    "intrusion-set--uuid2", 
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    "malware--uuid3"
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  ],
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  "x_mitre_contents": [
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    {
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      "object_ref": "attack-pattern--uuid1",
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      "object_modified": "2023-01-01T00:00:00.000Z"
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    }
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  ]
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}
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```
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The conversion tools handle this format and extract relevant object references for analysis and documentation generation.