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SOC Prime Platform Product Release Notes 5.10.1

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Written by Sergey Bayrachny

February 21, 2024

© 2024 SOC Prime Inc.

All rights reserved. This product and documentation related are protected by copyright and distributed under licenses restricting their use, copying, distribution, and decompilation. No part of this product or documentation related may be reproduced in any form or by any means without the prior written authorization of SOC Prime. While every precaution has been taken in the preparation of this book, SOC Prime assumes no responsibility for errors or omissions. This publication and features described herein are subject to change without notice.

Threat Detection Marketplace


Rule Deployment into On-Prem Elastic Stack Environments

We've improved the capabilities of deploying rules into on-prem Elastic Stack environments by adding the possibility to:

  • Create a dedicated Data Plane for on-prem Elastic Stack

  • Set up a Job with a Config, a Preset, and a Custom Field Mapping profile and deploy the rules from the Job via TDM API Integration Tool

Now, the flow of deploying rules is as follows:

  1. Configure a Data Plane (no credentials required).

    1. Go to Account icon > Platform Settings > Data Planes and click Add Data Plane.

    2. In the modal that appears, select Elastic Stack as your platform and enable the On Pem switch.

    3. Name your Data Plane and choose whether to share it to your company.

    4. Select Automation and direct deployment from a Sigma rule page as the place to use the Data Plane.

    5. Click Save Changes

  2. Create a Job.

    1. Go to Threat Detection Marketplace > Automation > Jobs and click Create Job.

    2. Name your Job.

    3. Select Elastic as your platform and set the content type to Detection Rule (Lucene) or Watcher (currently, only these two content types can be deployed into on-prem environments).

    4. Select the Tenant to which the Data Plane created in the previous step belongs, and then select the Data Plane itself.

      Note:

      You can set both on-prem and cloud Data Planes in the same Job. In this case, the deployment into the cloud Data Plane will be carried out by TDM's automation, while deployment into the on-prem Data Plane will be performed by TDM API Integration Tool.

    5. Select the Content Lists from which you want to deploy content.

    6. Choose if you want to Use Default Custom Field Mapping based on Log Source. Optionally select the Config for alternative translations and Presets.

    7. The value of the Schedule dropdown does not matter since it's the TDM API Integration Tool that performs the deployment to on-prem environments.

    8. Click Save Changes.

    9. Enable the Job on the Jobs page.

  3. Install the TDM API Integration Tool and configure deployment into your on-prem Elastic Stack environment.

    1. Download TDM API Integration Tool from the corresponding Content Pack on Threat Detection Marketplace.

    2. Install the Tool following the instructions provided in its Guide (it can be downloaded from the Content Pack page as well).

    3. In the Tool's config file:

      • Set the input type to job and set the job_name parameter to the name of the Job you've created in Threat Detection Marketplace.

      • Set the output type to xpack-watcher (corresponds to the Watcher content type in Job settings) or elasticsearch-rule (corresponds to the Detection Rule (Lucene) content type in Job settings). Set the output parameters according to the TDM API Integration Tool's guide.

      • Set other parameters in the config file according to the TDM API Integration Tool's guide.

    4. Run the TDM API Integration Tool's script to deploy the content linked to the specified Job.

Uncoder AI


Support for Roota

We've added support for translating from Roota, a public-domain language for collective cyber defense, created to make threat detection, incident response, and actor attribution simple. It acts as an open-source wrapper on top of the majority of existing SIEM, EDR, XDR, and Data Lake query languages.

From Roota, you can translate into the following formats:

Platform

Type

Data Schema

AWS Athena

Query

OCSF

AWS OpenSearch

Query (Lucene)

ECS

AWS OpenSearch

Rule (JSON)

ECS

Chronicle Security

Query (UDM)

UDM

Chronicle Security

Rule (YARA-L)

UDM

CrowdStrike Endpoint Security

Query (SPL)

Default

ElastAlert

Alert (Lucene)

ECS

Elastic Stack

Query (Lucene)

ECS

Elastic Stack

Detection Rule (Lucene)

ECS

Elastic Stack

Rule (Watcher)

ECS

Elastic Stack

Kibana SavedSearch (JSON)

ECS

Falcon LogScale

Query

Default

Falcon LogScale

Alert

Default

Graylog

Query

Default

IBM QRadar

Query (AQL)

LEEF

Microsoft Defender for Endpoint

Query (Kusto)

Default

Microsoft Sentinel

Query (Kusto)

Default

Microsoft Sentinel

Rule (Kusto)

Default

Sigma

Sigma

Default

Splunk

Query (SPL)

Default

Splunk

Alert (SPL)

Default

To learn more about Roota's capabilities and check out its specifications, visit the dedicated GitHub repository.

More Cross-Platform Translations

We've expanded the range of supported cross-platform translation languages (also known as "reverse translations") and improved their quality. Now, the following languages are available for reverse translations:

Platform

Source

Target

AWS Athena:

  • Query with OCSF data schema

AWS OpenSearch:

  • Query (Lucene) with ECS data schema

AWS OpenSearch:

  • Rule (JSON) with ECS data schema

Chronicle Security:

  • Query (UDM) with UDM data schema

  • Rule (YARA-L) with UDM data schema

CrowdStrike Endpoint Security:

  • Query (SPL) with Default data schema

ElastAlert:

  • Alert (Lucene) with ECS data schema

Elastic Stack:

  • Query (Lucene) with ECS data schema

  • Detection Rule (Lucene) with ECS data schema

Elastic Stack:

  • Rule (Watcher) with ECS data schema

  • Kibana SavedSearch (JSON) with ECS data schema

Falcon LogScale:

  • Query with Default data schema

  • Alert with Default data schema

Graylog:

  • Query with Default data schema

IBM QRadar:

  • Query (AQL) with LEEF data schema

Microsoft Defender for Endpoint:

  • Query (Kusto) with Default data schema

Microsoft Sentinel:

  • Query (Kusto) with Default data schema

  • Rule (Kusto) with Default data schema

Sigma:

  • Rule

(Translation from Sigma does not require the reverse translations balance)

Splunk:

  • Query (SPL) with Default data schema

  • Alert (SPL) with Default data schema

Note:

  • A checkmark against a language in the Source column means that this language can be translated into all languages checkmarked in the Target column.

  • A checkmark against a language in the Target column means that translations can be generated into this language from all languages checkmarked in the Source column.

Also, Uncoder AI supports:

  • Translating between different formats of the lame platform (does not require the reverse translations balance):

    • AWS OpenSearch:

      • Query (Lucene) with ECS data schema → Rule (JSON) with ECS data schema

    • Chronicle Security:

      • Query (UDM) with UDM data schema ↔ Rule (YARA-L) with UDM data schema

    • Elastic Stack:

      • Query (Lucene) with ECS data schema ↔ Detection Rule (Lucene) with ECS data schema

      • Query (Lucene) with ECS data schema → Rule (Watcher) with ECS data schema

      • Query (Lucene) with ECS data schema → Kibana SavedSearch (JSON) with ECS data schema

      • Detection Rule (Lucene) with ECS data schema → Rule (Watcher) with ECS data schema

      • Detection Rule (Lucene) with ECS data schema → Kibana SavedSearch (JSON) with ECS data schema

    • Falcon LogScale:

      • Query with Default data schema ↔ Alert with Default data schema

    • Microsoft Sentinel:

      • Query (Kusto) with Default data schema ↔ Rule (Kusto) with Default data schema

    • Splunk:

      • Query (SPL) with Default data schema ↔ Alert (SPL) with Default data schema

  • Remapping to OCSF (does not require the reverse translations balance):

    • AWS OpenSearch Query (Lucene): ECS to OCSF

    • AWS OpenSearch Rule (JSON): ECS to OCSF

    • Elastic Stack Detection Rule (Lucene): ECS to OCSF

    • Elastic Stack Query (Lucene): ECS to OCSF

    • Falcon LogScale Alert: Default to OCSF

    • Falcon LogScale Query: Default to OCSF

    • IBM QRadar Query (AQL): LEEF to OCSF

    • Snowflake Query (SQL): Default to OCSF

    • Splunk Alert (SPL): Default to OCSF

    • Splunk Query (SPL): Default to OCSF

    • Sumo Logic Query: Default to OCSF

Key Bug Fixes & Improvements


With this release, we’ve made the following key bug fixes and improvements to enhance the user experience with the SOC Prime Platform:

  • Improved displaying of rules saved as unstructured JSON. Now, when the user opens such rules in Threat Detection Marketplace, they are automatically presented in a prettified manner while the code stays unstructured. This was implemented for the following platforms:

    • Microsoft Sentinel Rule

    • Elastic Stack Detection Rule (Lucene)

    • Elastic Stack Detection Rule (EQL)

    • Elastic Stack Saved Search

    • Elastic Stack Watcher

    • Sumo Logic CSE Rule

    • Falcon LogScale Alert

  • Fixed a bug where the linked Job was not displayed for some Content Lists on the Lists page

  • Fixed an issue in translations from Sigma into Chronicle Security Rule where an integer in the detection values could be translated as None

  • Fixed a wrong text message on the first step of the Single Sign-On Login flow

  • On the Video Tutorials page, renamed the Copy button to Share and moved it under the video

  • Updated the style of the Close icon on the modals to create/edit Filters, Presets, and Search Profiles

  • Fixed a layout issue where the message about the successful change of the industry was overlapped by the header

  • Fixed the layout of the buttons on the Oh, something went wrong! modal

  • Added to the TDM API proper handling of the error when the user tries to apply a Custom Field Mapping to a rule saved as a non-valid JSON in a custom repository

  • Fixed a bug where alternative translations did not have a proper reference link to the original TDM rule

  • Resolved an issue where updating an Elastic Stack Detection Rule (Lucene) via Inventory sometimes resulted in an error

  • Fixed a bug where the rules automatically unlocked via a Job were deployed only on the second run of the Job

  • Fixed a bug in Uncoder AI where the Custom Field Mapping field was shown as available for Apache Kafka ksqlDB, while actually Custom Field Mapping for this platform is not supported

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