pySigma Kusto Query Language (KQL) Backend

Contents

• pySigma Kusto Query Language (KQL) Backend
  • 📖 Overview
  • 🚀 Quick Start
  • 📘 Usage
  • 🛠️ Advanced Features
  • 🔄 Processing Pipelines
  • 🧪 Custom Transformations
  • ❓Frequently Asked Questions
  • 🤝 Contributing
  • 📄 License

📖 Overview

The pySigma Kusto Backend transforms Sigma Rules into queries using Kusto Query Language (KQL). This backend supports multiple Microsoft products, including:

• Microsoft XDR Advanced Hunting Queries (Formally Microsoft 365 Defender Advanced Hunting Queries)
• Azure Sentinel Advanced Security Information Model (ASIM) Queries
• Azure Monitor Queries

Note: This backend was previously named pySigma Microsoft 365 Defender Backend.

🔑 Key Features

• Backend: sigma.backends.kusto with KustoBackend class
• Pipelines: Provides microsoft_xdr_pipeline, sentinelasim_pipeline, and azure_monitor_pipeline for query tables and field renames
• Output: Query strings in Kusto Query Language (KQL)

🧑‍💻 Maintainer

• Stephen Lincoln via AttackIQ

🚀 Quick Start

1. Install the package:

   pip install pysigma-backend-kusto

   Note: This package requires pySigma version 0.10.0 or higher.

2. Convert a Sigma rule to MIcrosoft XDR KQL query using sigma-cli:

   sigma convert -t kusto -p microsoft_xdr path/to/your/rule.yml

3. Or use in a Python script:

   from sigma.rule import SigmaRule
   from sigma.backends.kusto import KustoBackend
   
   # Load your Sigma rule
   rule = SigmaRule.from_yaml("""
     title: Mimikatz CommandLine
     status: test
     logsource:
         category: process_creation
         product: windows
     detection:
         sel:
             CommandLine|contains: mimikatz.exe
         condition: sel
   """)
   
   # Convert the rule
   backend = KustoBackend()
   print(backend.convert_rule(rule)[0])

📘 Usage

🖥️ sigma-cli

Use with sigma-cli per typical sigma-cli usage:

sigma convert -t kusto -p microsoft_xdr -f default -s ~/sigma/rules

🐍 Python Script

Use the backend and pipeline in a standalone Python script. Note, the backend automatically applies the pipeline, but you can manually add it if you would like.

from sigma.rule import SigmaRule
from sigma.backends.kusto import KustoBackend
from sigma.pipelines.microsoftxdr import microsoft_xdr_pipeline

# Define an example rule as a YAML str
sigma_rule = SigmaRule.from_yaml("""
  title: Mimikatz CommandLine
  status: test
  logsource:
      category: process_creation
      product: windows
  detection:
      sel:
          CommandLine|contains: mimikatz.exe
      condition: sel
""")
# Create backend, which automatically adds the pipeline
kusto_backend = KustoBackend()

# Or apply the pipeline manually
pipeline = microsoft_xdr_pipeline()
pipeline.apply(sigma_rule)

# Convert the rule
print(sigma_rule.title + " KQL Query: \n")
print(kusto_backend.convert_rule(sigma_rule)[0])

Output:

Mimikatz CommandLine KQL Query: 

DeviceProcessEvents
| where ProcessCommandLine contains "mimikatz.exe"

🛠️ Advanced Features

🔄 Pipeline & Backend Args (New in 0.2.0)

For the microsoft_xdr_pipeline:

• transform_parent_image: Controls ParentImage field mapping behavior
  • When set to True (default), maps ParentImage to InitiatingProcessParentFileName
  • When set to False, maps ParentImage to InitiatingProcessFileName
  • Useful for adjusting field mappings based on specific rule requirements
  • Example usage:

from sigma.pipelines.microsoftxdr import microsoft_xdr_pipeline
pipeline = microsoft_xdr_pipeline(transform_parent_image=False)

This argument allows fine-tuning of the ParentImage field mapping, which can be crucial for accurate rule conversion in certain scenarios. By default, it follows the behavior of mapping ParentImage to the parent process name, but setting it to False allows for mapping to the initiating process name instead.

🗃️ Custom Table Names (New in 0.3.0) (Beta)

The query_table argument allows users to override table mappings and set custom table names. This is useful for converting Sigma rules where the rule category does not easily map to the default table names.

YAML Pipelines

To set a custom table name, ensure your pipeline has a priority of 9 or lower, as sigma-cli merges pipelines based on priority (default is 10). Field mappings in mappings.py will apply according to your specified table name, along with any custom field mapping transformations.

# test_table_name_pipeline.yml
name: Custom Query Table Pipeline
priority: 1
transformations:
- id: test_name_name
  type: set_state
  key: "query_table"
  val: ["DeviceProcessEvents"]

sigma convert -t kusto -p microsoft_xdr -p test_table_name_pipeline.yml test_rule.yml

Python Pipelines

You can also set the table name in the pipeline via Python by passing the query_table parameter to the pipeline.

from sigma.pipelines.microsoftxdr import microsoft_xdr_pipeline
my_pipeline = microsoft_xdr_pipeline(query_table="DeviceProcessEvents")

🔄 Processing Pipelines

This project includes three main processing pipelines, each designed for a specific Microsoft product:

1. Microsoft XDR Pipeline (formerly Microsoft 365 Defender)

   • Status: Production-ready
   • Supports a wide range of Sigma rule categories
   • All tables supported, but additional field mapping contributions welcome

2. Sentinel ASIM Pipeline

   • Status: Beta
   • Transforms rules for Microsoft Sentinel Advanced Security Information Model (ASIM)
   • All tables supported, but field mappings are limited

3. Azure Monitor Pipeline

   • Status: Alpha
   • Currently supports field mappings for SecurityEvent and SigninLogs tables only
   • All tables supported, but requires custom field mappings for other tables

Each pipeline includes a query_table parameter for setting custom table names.

📊 Rule Support

Rules are supported if either:

• A valid table name is supplied via the query_table parameter or YAML pipeline
• The rule's logsource category is supported and mapped in the pipeline's mappings.py file

🖥️ Commonly Supported Categories

• process_creation
• image_load
• network_connection
• file_access, file_change, file_delete, file_event, file_rename
• registry_add, registry_delete, registry_event, registry_set

Specific pipelines may support additional categories. Check each pipeline's mappings.py file for details.

🧪 Custom Transformations

This package includes several custom ProcessingPipeline Transformation classes:

1. DynamicFieldMappingTransformation

   • Determines field mappings based on the query_table state parameter

2. GenericFieldMappingTransformation

   • Applies common field mappings across all tables in a pipeline

3. BaseHashesValuesTransformation

   • Transforms the Hashes field, removing hash algorithm prefixes

4. ParentImageValueTransformation

   • Extracts parent process name from Sysmon ParentImage field

5. SplitDomainUserTransformation

   • Splits User field into separate domain and username fields

6. RegistryActionTypeValueTransformation

   • Adjusts registry ActionType values for compatibility

7. InvalidFieldTransformation

   • Identifies unsupported or invalid fields in rules

8. SetQueryTableStateTransformation

   • Manages the query_table state based on rule category or custom settings

📊 Custom Finalizer

1. QueryTableFinalizer

• Adds table name as prefix to each query
• Keeps queries separate for fine-grained control

❓Frequently Asked Questions

How do I set the table name for a rule?

You can set the table name for a rule by adding the query_table parameter to the pipeline and setting it to the table name you want to use.

from sigma.pipelines.microsoftxdr import microsoft_xdr_pipeline
pipeline = microsoft_xdr_pipeline(query_table="DeviceProcessEvents")

How do I set the table name for a rule in YAML?

You can set the table name for a rule in YAML by adding the query_table parameter to the pipeline and setting it to the table name you want to use.

# test_table_name_pipeline.yml
name: 
priority: 1
transformations:
- id: test_name_name
  type: set_state
  key: "query_table"
  val: ["DeviceProcessEvents"]

sigma convert -t kusto -p microsoft_xdr -p test_table_name_pipeline.yml test_rule.yml

How is the table name determined for a rule?

The table name is set by the SetQueryTableStateTransformation transformation, which is the first transformation in each pipeline. It will use the query_table parameter if it is set by either a YAML pipeline or by passing the parameter to the pipeline in a Python script, otherwise it will select the table based on the rule category. The table name to rule category logic is defined in each pipeline's mappings.py file.

How are field mappings determined for a rule?

The field mappings are determined by the DynamicFieldMappingTransformation transformation. It will use the table name from the pipeline state's query_table key. The field mapping logic is defined in each pipeline's mappings.py file for each table. If a field is not found in the table, the GenericFieldMappingTransformation will apply generic field mappings. If a field is not found in the generic field mappings, the field will be kept the same.

What tables are supported for each pipeline?

The tables that are supported for each pipeline are defined in each pipeline's tables.py file. This file is automatically generated by the scripts in the utils folder. These scripts pull documentation from Microsoft to get all documented tables and their fields and schema.

I am receiving an Invalid SigmaDetectionItem field name encountered error. What does this mean?

This error means that the field name(s) provided in the error are not found in the tables fields defined in tables.py for the pipeline you are using. This probably means that a Sigma rule's field was not found in the field mappings for the table. To fix this error, you can supply your own custom field mappings to convert the unsupported field into a supported one. For example, in using YAML:

# custom_field_mapping_pipeline.yml
name: Custom Field Mapping
priority: 1
transformations:
- id: field_mapping
    type: field_name_mapping
    mapping:
        MyNotSupportedField: a_supported_field
    rule_conditions:
    - type: logsource
        service: sysmon

sigma convert -t kusto -p custom_field_mapping_pipeline.yml -p microsoft_xdr test_rule.yml

If you find the field mapping useful, please consider submitting a PR to add it to the pipeline's field mappings :)

My query_table or custom field mapping isn't working

Each pipeline in the project has a priority of 10. If you are trying to set the table name or custom field mappings, your pipeline needs to have a priority of 9 or less. You can set the priority in the YAML pipeline like so:

# test_table_name_pipeline.yml
name: 
priority: 9
transformations:
- id: test_name_name
  type: set_state
  key: "query_table"
  val: ["DeviceProcessEvents"]

🤝 Contributing

Contributions are welcome, especially for table and field mappings! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Please make sure to update tests as appropriate.

📄 License

This project is licensed under the GNU Lesser General Public License v3.0 - see the LICENSE file for details.