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DEVICE INTEGRATION
- Palo Alto (Device Integration)
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CONNECTORS
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- 1Password Connector
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- Cloudflare Logpull Connector Setup Guide
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- GitHub
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- Slack
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DATA INGESTION
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HUNTING WITH WORKBOOKS
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- Your first FIND with the HYPERCLOUD
- Create a Search Block
- Create a Signal Block
- Create a Text Block
- Create an Outlier Block
- Create a DQL Block
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- Create a Call Block
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- Create a Notification Block
- Schedule a Workbook
- Native Workbook
- Workbook Functions
- How to view Workbooks?
- Add Parameters to Workbook
- Working with Pass through Content
- How to create a Workbook?
- Workbooks
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DNIF Query Language (DQL Language)
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SECURITY MONITORING
- Streamline Alert Analysis with Signal Tagging
- Workbook Versioning: Track, Collaborate, and Restore with Ease
- What is Security Monitoring?
- Creating Signal Suppression Rules
- Why EBA
- Signal Suppression Rule
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- What are signals?
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- Source Stream
- Signal Filters
- Signal Data export
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- Signal Confidence Levels
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- Investigate Anywhere
- How to add a signal to a case?
- Graph View for Signals
- Global Signals
- False Positives
- Add Multiple Signals to a Case
- Add comment to the signal
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OPERATIONS
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MANAGE DASHBOARDS
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MANAGE REPORTS
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USER MANAGEMENT & ACCESS CONTROL
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BILLING
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MANAGING YOUR COMPONENTS
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GETTING STARTED
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INSTALLATION
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SOLUTION DESIGN
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AUTOMATION
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TROUBLESHOOTING AND DEBUGGING
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- TLS ( Troubleshooting Procedure)
- TCP (Troubleshooting Procedure)
- Syslog (Troubleshooting Procedure)
- Salesforce ( Troubleshooting Procedure)
- PICO
- Office 365 (Troubleshooting Procedure)
- GSuite
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- Beats (Troubleshooting Procedure)
- Azure NSG ( Troubleshooting Procedure)
- Azure Eventhub
- AWS S3 (Troubleshooting Procedure)
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LICENSE MANAGEMENT
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RELEASE NOTES
- May 27, 2026 - Content Update
- May 6, 2026 - Content Update
- March 31, 2026 - Content Update
- March 16, 2026 - Application Update
- February 26, 2026 - Content Update
- January 19,2026 - Content Update
- December 23, 2025 - Application Update
- December 4,2025 - Content Update
- November 27, 2025 - Application Update
- October 28, 2025 - Content Update
- August 20, 2025 - Content Update
- August 5, 2025 - Application Update
- July 15, 2025 - Content Update
- June 13, 2025 - Content Update
- May 21, 2025 - Content Update
- April 17, 2025- Content Update
- March 25, 2025- Content Update
- March 18, 2025 - Application Update
- March 5, 2025 - Application Update
- January 27, 2025 - Application Update
- January 29, 2025 - Content update
- December 30, 2024 - Content Update
- December 12, 2024 - Content Update
- December 3, 2024 - Application Update
- November 15, 2024 - Content Update
- October 26, 2024- Application Update
- October 23, 2024 - Content Update
- October 16, 2024 - Application Update
- September 04, 2024 - Application Update
- September 04, 2024 - Content Update
- August 27, 2024 - Application Update
- July 30, 2024 - Application Update
- June 04, 2024- Application Update
- April 24, 2024- Application Update
- March 26, 2024 - Application Update
- February 19, 2024 - Application Update
- January 09, 2024 - Content Update
- January 09, 2024 - Application Update
- November 27, 2023 - Content Update
- November 27, 2023 - Application Update
- October 05, 2023 - Application Update (Release Notes v9.3.3)
- May 30, 2023 - Application Update (Release Notes v9.3.2)
- November 29, 2022 - Application Update (Release Notes v9.3.0)
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API
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POLICIES
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SECURITY BULLETINS
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BEST PRACTICES
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DNIF AI
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DNIF LEGAL AND SECURITY COMPLIANCE
UBA: Coalescing User Identities
In an organization, multiple identities could be associated to a specific user.
For Example: An Employee named John Doe might be accessing multiple applications in the organization using different User details.
| Applications | User Details |
| Application 1 | john@example.com |
| Application 2 | john_doe |
| Application 3 | Employee ID 111 |
In the above scenario, the user details look different although they are the same user. Using enrichments, we can coalesce all the multiple identities of the same user into a single identity.
It is possible to maintain an eventstore with details for each user in an organization including the different user ids, email ids, user names of different applications, etc.
Let’s consider another example, the eventstore UserInfo has data imported from a csv file. Displayed below is a sample csv file
Upload a custom eventstore
A custom eventstore called UserInfo can be created by uploading the csv file containing user data. The event store that you created will be listed as shown below:

An enrichment bucket for the field $User can be created to refer values from the UserInfo eventstore.
Define a custom Enrichment Bucket
The enrichment bucket would identify different identities of a specific user observed ($ObservedUser) in the log events coming from different sources and point to a specific user in the $User field.
The yaml format is as follows:
bucket: User
fields:
- User
schema-version: 1.0
source:
- enr_key: '{$UserID1}'
enr_values:
translate:
$User: User
$UserID1: ObservedUser
eventstore: UserInfo
sourcetype: event_store
- enr_key: '{$EmployeeID}'
enr_values:
translate:
$EmployeeID: ObservedUser
$User: User
'{$Department}/{$Designation}': Role
'{$Manager}': Manager
eventstore: UserInfo
sourcetype: event_store
| Field | Description |
| Bucket | Enter the name for the enrichment bucket. |
| Fields | Enter the field names to be enriched. |
| schema-version | Enter the schema version |
| Source | List of sources for the enrichment bucket. Note: There can be multiple sources for one enrichment bucket Source Type: Enter the source type i.e. dql/sql/eventstore Eventstore: For this scenario, enter the eventstore name. Enr_key: Enter the desired values to be detected output representation. For example, ‘{UserID1}’ Enr_values Translate: Allows you to replace the column names of the query result. To replace enter : For example, $EmployeeID: ObservedUser In this case, the column name $EmployeeID is replaced with $ObservedUser. |
Save the enrichment bucket.
Run a Search
To check if enrichment has been added successfully, run a search on data to fetch enriched details. Enrichment will be applied to the field values mentioned in the enrichment bucket of yml file.

In the above screen, the user identities in $ObservedUser field displays the identities that are correlated to the user in $User field.
From the query result, you can click the Information icon to further drill down to each entity in the result and verify the enriched details.


In the above example, the $ObservedUser (shumbham_gilada / NM111) are correlated to the same $User (Shubham Gilada).
