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  • Examples Library
    • Aggregate Status Codes by count() per Minute
    • Parse JSON Content With Specific Parameters
    • Find Range Between Smallest And Largest Numbers in Field
    • Find Range of CPU Usage by Host
    • Match Multiple Pairs of Event Fields Against Multiple Columns in .CSV Lookup File
    • Return Multiple Matches as Array Fields
    • Access Fields From Single Neighboring Event in a Sequence - Example 1
    • Access Fields From Single Neighboring Event in a Sequence - Example 2
    • Access Fields From Single Neighboring Event in a Sequence - Example 3
    • Add Values From Two Fields
    • Add a Field Based on Values of Another Field - Example 1
    • Add a Field Based on Values of Another Field - Example 2
    • Add a Field Based on Values of Another Field - Example 3
    • Aggregate Array Content
    • Aggregate Status Codes by count() Per Minute
    • Alert Query For Parsers Issues
    • Analyze User Sessions Based on Click Activity
    • Annotate Events With Aggregation - Example 1
    • Annotate Events With Aggregation - Example 2
    • Annotate Events With Aggregation - Example 3
    • Assign Current Time of Search Time Interval to Field
    • Assign End of Search Time Interval to Field - Example 1
    • Assign End of Search Time Interval to Field - Example 2
    • Basic Rounding
    • Bucket Counts When Using bucket()
    • Bucket Events Into Groups
    • Bucket Events Summarized by count()
    • Calculate e Raised to Power
    • Calculate e Raised to Power Minus One
    • Calculate Absolute Value
    • Calculate Angle From Coordinates
    • Calculate Arc Cosine of Value
    • Calculate Arc Sine of Value
    • Calculate Arc Tangent of Value
    • Calculate Average of Field Values in an Array
    • Calculate Base 10 Logarithm of Values
    • Calculate Base 2 Logarithm of Values
    • Calculate Cosine
    • Calculate Distance Between Geographical Coordinates
    • Calculate Edit Distance Between Domain Names
    • Calculate Events per Second by Host
    • Calculate Floor Modulus of Values
    • Calculate Floor Value of a Number
    • Calculate Geohash Value of a Set of Coordinates
    • Calculate HTTP Error Percentages
    • Calculate Hyperbolic Cosine
    • Calculate Hyperbolic Sine
    • Calculate Hyperbolic Tangent Values
    • Calculate Ingest Queue Compression
    • Calculate Median Memory Allocation
    • Calculate Minimum and Maximum Response Times
    • Calculate Multiple Response Time Percentiles
    • Calculate Natural Logarithm of Value Plus One
    • Calculate Natural Logarithm of Values
    • Calculate Power of Values
    • Calculate Query Cost for All Users by Repository
    • Calculate Query Costs by User and Repository in a Single Field
    • Calculate Relationship Between X And Y Variables - Example 1
    • Calculate Relationship Between X And Y Variables - Example 2
    • Calculate Relationship Between X And Y Variables - Example 3
    • Calculate Rounded Square Root Values
    • Calculate Running Average of Field Values
    • Calculate Shannon Entropy Value For String
    • Calculate Sine of a Value
    • Calculate Standard Deviation of Bytes Sent
    • Calculate Subnet with Custom Prefix Length
    • Calculate Sum of Field Values Over Sliding Time-Based Window
    • Calculate Sum of Field Values Over Sliding Window
    • Calculate Tangent Values
    • Calculate Total Network Bandwidth Per Host
    • Calculate a Percentage of Successful Status Codes Over Time
    • Calculate the Mean of CPU Time
    • Call Named Function on a Field - Example 1
    • Call Named Function on a Field - Example 2
    • Categorize Errors in Log Levels
    • Categorize Events Based on Values in More Fields
    • Check For Existence of Element Contained in Given List of Values
    • Check For Existence of Element Larger Than Given Number
    • Check For Existence of Element Using Complex Conditions
    • Check For Existence of Elements Using Filtering Pipeline
    • Check For Existence of Simple Values in Nested Array Using objectArray:exists()
    • Check for AWS Resources in Vendor Array
    • Check for Values in Array
    • Check if Field Contains Specific Value
    • Check if Field Contains Valid IP Address
    • Check if Fields Contain Same Value
    • Collect and Group Events by Specified Field - Example 1
    • Collect and Group Events by Specified Field - Example 2
    • Combine Values of Multiple Fields
    • Compare Domain Names Using Text Edit Distance Array
    • Compare More Fields and Filter for Specific Events
    • Compare More Fields and Their Respective Values
    • Compare Two Timestamps
    • Compare and Filter Values in Same Table
    • Compute Aggregate Value for Each Array Element With Same Index
    • Compute Average Value for Each Array Element With Same Index
    • Compute Community ID
    • Compute Cumulative Aggregation Across Buckets
    • Compute Cumulative Aggregation For Specific Group
    • Compute an Aggregated Value of an Array on All Events
    • Concatenate Fields and Strings Together
    • Concatenate Multiple CSV Files
    • Concatenate Multiple Tables
    • Concatenate Multiple Values From Nested Array Elements
    • Concatenate Values From Deeply Nested Array Elements
    • Concatenate Values From Nested Array Elements
    • Concatenate Values From Two Nested Array Elements
    • Concatenate Values in Arrays Into New Named Field
    • Concatenate Values in Arrays Using Pipe Separation
    • Concatenate Values in Arrays With a Defined Prefix and Suffix
    • Concatenate Values in Two Fields - Example 1
    • Concatenate Values in Two Fields - Example 2
    • Concatenate Values of All Fields With Same Name in an Array
    • Concatenate a Range of Values in Arrays
    • Convert Decimal Numbers to Hexadecimal Format
    • Convert Decimal Numbers to Prefixed Hexadecimal Format
    • Convert Degrees to Radians
    • Convert Fields to JSON Format
    • Convert Radians to Degrees
    • Convert Rate Values
    • Convert Timestamp Values Into Formatted Strings
    • Convert Timestamps Based on Accuracy
    • Convert Values Between Units
    • Correlate AWS Federation Token Generation with Console Logins
    • Correlate Authentication and Database Errors
    • Correlate Inbound Email URLs with Subsequent Access Attempts
    • Correlate Two Scheduled Task Events
    • Count Array Elements - Example 1
    • Count Array Elements - Example 2
    • Count Characters Including Emojis in String
    • Count Characters in Field
    • Count Events From Each Datasource
    • Count Events Within Partitions Based on Condition
    • Count Events per Repository
    • Count Total Events
    • Count Total of Malware and Nonmalware Events
    • Count Unique Visitors Based on Client IP Addresses
    • Create Data Compatible With Sankey Diagram Widget - Example 1
    • Create Data Compatible With Sankey Diagram Widget - Example 2
    • Create Frequency Count With Formatted Links
    • Create Hash Values from Multiple Fields with Limited Range
    • Create New Array by Appending Expressions
    • Create New Fields
    • Create Sample Groups Using Hash
    • Create Sankey Diagram Calculating Edge Thickness
    • Create Single Array from Object Arrays
    • Create Time Chart Widget for All Events
    • Create Time Chart Widget for Different Events
    • Create Time Chart With Default Percentiles For Multiple Fields
    • Create Time Chart With Fixed Bucket Count
    • Create Time Chart With One-Minute Intervals
    • Create Two Temporary Events for Troubleshooting - Example 1
    • Create Two Temporary Events for Troubleshooting - Example 2
    • Create Two Temporary Events for Troubleshooting - Example 3
    • Create a Pivot Table
    • Decode Redirect URLs in Authentication Logs
    • Decode Referrer URLs in Web Access Logs
    • Decode URL-Encoded Strings
    • Decode and Extract true Bits as Arrays
    • Decode and Extract true Bits as Strings - Example 1
    • Decode and Extract true Bits as Strings - Example 2
    • Decode and Extract Bit Flags
    • Deduplicate Compound Field Data With array:union() and split()
    • Deduplicate Content by Field
    • Deduplicate Values in Array
    • Detect All Occurrences of Event A Before Event B
    • Detect Changes And Compute Differences Between Events - Example 1
    • Detect Changes And Compute Differences Between Events - Example 2
    • Detect Continuously Upwards Going Trend
    • Detect Event A Happening X Times Before Event B
    • Detect Event A Happening X Times Before Event B Within a Specific Timespan
    • Detect Two Events Occurring in Quick Succession
    • Determine Autonomous System (AS) Number and IP address/Organization Associated - Example 1
    • Determine Autonomous System (AS) Number and IP address/Organization Associated - Example 2
    • Determine a Score Based on Field Value
    • Differentiate Between Types of Log Levels
    • Display User Account Deletion Events in Table Format
    • Divide Data Into Separate Partitions
    • Divide Values From Two Fields
    • Drop Attributes, Columns/Fields From Result Set - Example 1
    • Drop Attributes, Columns/Fields From Result Set - Example 2
    • Drop Event During Parsing
    • Drop Events Based on Parsing JSON Value
    • Drop Events Based on Specific Field Values or Patterns
    • Drop Fields From Input Array
    • Drop Multiple Fields from Events
    • Drop Single Field from Events
    • Encode Search Query For URL Usage
    • Evaluate Arbitrary Expression as Boolean Value
    • Evaluate Arbitrary Field Values for CPU Time Within Repository
    • Evaluate Field Values Within Repository
    • Evaluate Function Argument on Values in Array
    • Exclude Events With Specific Values From Searches
    • Exclude Production Servers Ending With Specific Prefix
    • Exclude Servers Beginning With Specific Prefix
    • Extract Alert Type From Security Event String Using Substring With Position-based Delimiters
    • Extract Components from Fixed-Length Data
    • Extract Day of Month From Timestamp
    • Extract Day of Week From Timestamp
    • Extract Day of Week Name From Timestamp
    • Extract Day of Year From Timestamp
    • Extract Email Local Part
    • Extract Field Statistics
    • Extract Hour From Timestamp
    • Extract IP Address and Port From Command Line
    • Extract Millisecond From Timestamp
    • Extract Minute From Timestamp
    • Extract Month From Timestamp
    • Extract Month Name From Timestamp
    • Extract Portion of Text From Message
    • Extract Second From Timestamp
    • Extract URL Page Names and Find Most Common Pages
    • Extract Week Number From Timestamp
    • Extract Year From Timestamp
    • Extract a Field From CSV String
    • Extract the Top Most Viewed Pages of a Website
    • Filter Events Using CIDR Subnets - Example 1
    • Filter Events Using CIDR Subnets - Example 2
    • Filter Events Using CIDR Subnets - Example 3
    • Filter Events Using CIDR Subnets - Example 4
    • Filter For Items Not Part of Data Set Using !join()
    • Filter For Items Not Part of Data Set Using !match()
    • Filter For Items Not Part of Data Set Using defineTable()
    • Filter Hostnames Beginning With Specific Prefix
    • Filter Out Based on a Non-Matching Regular Expression (Function Format)
    • Filter Out Based on a Non-Matching Regular Expression (Syntax)
    • Filter Out Fields With No Value
    • Filter Servers Ending With Specific suffix
    • Filter an Array on a Given Condition
    • Filter and Collect Values in Same Table
    • Filter on a Single Field for One Specific Value
    • Find Failed Requests
    • Find Fields With Data in Class
    • Find Fields With S3Bucket in Class
    • Find Least Common Values of a Field
    • Find Matches in Array Given a Regular Expression - Example 1
    • Find Matches in Array Given a Regular Expression - Example 2
    • Find Maximum Value in Field
    • Find Minimum And Maximum Values of any Numerical Field in Session
    • Find Minimum Value in Field
    • Find Most Common URLs Returning 404 Errors
    • Find Most Recent (Latest) Value of Field X
    • Find Oldest (First) Value of Field X
    • Find Overlapping User Sessions
    • Find Processes with Low Execution Count
    • Find Set Intersection Within an Array
    • Find Top N Value of Series - Example 1
    • Find Top N Value of Series - Example 2
    • Find Union of Array Over multiple Events
    • Find the First Values in a List of Fields
    • Format Duration Into Human Readable String
    • Format JSON
    • Format Only Valid Input XML in Output String
    • Format Only Valid JSON
    • Format Only Valid XML
    • Format Timestamp Using formatTime()
    • Format Values From Two Array Elements Using :
    • Format XML
    • Format XML String to Certain Line Length and Indentation
    • Format XML in @rawstring Field after Filtering Data
    • Format XML to a Max Line Length
    • Format a String to Upper Case and Lower Case
    • Generate Different But Consistent Hash Values From Same Input Data
    • Generate Temporary Event With Bit Flags For Troubleshooting
    • Get First Events From Result Set
    • Get Integer Part of Number
    • Get List of Status Codes
    • Get the Last Element of an Array
    • Get the Value of a Field Stored in Another Field
    • Group Events by Single Field
    • Group Events by Single Field Without Count
    • Group First Events by Log Level
    • Group HTTP Methods and Count Status Codes
    • Group HTTP Methods and Status Codes Using Nested groupBy()
    • Group Similar Log Lines Using TokenHash
    • Hash Field Values Using hashRewrite()
    • Hash a Field Using Different Seeds
    • Hourly Data Events
    • Identify Potentially Malicious Domains
    • Include All Fields with Any Given Pattern
    • Join Log Events with Reference Data
    • List All EC2 Hosts With FirstSeen Data Within 14 Days
    • List URLs Not Found
    • Look Up IP Addresses with Custom Detection Prefix
    • Look up IP address IOCs
    • Look up URL IOCs
    • MD5 Hash Multiple Fields
    • MD5 Hash a Field With a Given Value
    • Make Copy of Events
    • Make Copy of Events from One Repo to Another Repo
    • Make Data Compatible With Time Chart Widget - Example 1
    • Make Data Compatible With Time Chart Widget - Example 2
    • Make Data Compatible With World Map Widget - Example 1
    • Make Data Compatible With World Map Widget - Example 2
    • Make Data Compatible With World Map Widget - Example 3
    • Match Event Fields Against Lookup Table Values
    • Match Event Fields Against Lookup Table Values Adding Specific Columns
    • Match Event Fields Against Lookup Table Values Allowing All Events to Pass
    • Match Event Fields Against Patterns in Lookup Table Values
    • Match Events Containing Specific Hash Values
    • Match Field to Timespan
    • Match Hashed Values in Specific Fields
    • Modify Existing Fields
    • Multiply Values From Two Fields
    • Narrow the Search Interval
    • Parse Fixed Width-encoded Log Lines Fields
    • Parse ISO8601 Timestamps
    • Parse Key-Value Pairs With Override
    • Parse String as CSV
    • Parse String as CSV - Example 2
    • Parse Timestamp Without Timezone Information
    • Parse URL Into Components
    • Parse XML Content From Task Triggers
    • Parse XML With Multiple Inner Elements
    • Parse a CSV-encoded Field Into Known Columns
    • Parsers Throttling
    • Perform Base64 Decoding of a Field
    • Perform Base64 Encoding of a Field
    • Perform Case-Insensitive Match on Field
    • Perform Formatting on All Values in an Array
    • Perform a Free-Text Search in Rawstring
    • Perform a Left Join Query to Combine Two Datasets
    • Perform a Nested Join Query to Combine Two Datasets and Two Tables
    • Perform a Right Join Query to Combine Two Datasets
    • Perform an Inner Join Query to Combine Two Datasets
    • Preview And Output Several Lookup Files as Events With readFile()
    • Preview Content in a Lookup File With readFile()
    • Preview Content in a Lookup File With readFile() and Filter With !join()
    • Process Current Time in Live Queries
    • Reduce Large Event Sets to Essential Fields
    • Remove ANSI Escape Codes From Text
    • Remove ANSI Escape Codes from Default Field
    • Remove Fixed-Length Prefix and Suffix From Text
    • Rename Existing Fields in Array
    • Rename Fields
    • Rename a Single Field - Example 1
    • Rename a Single Field - Example 2
    • Replace Word or Substring With Another
    • Request List of Fields
    • Retention Update Per Repository
    • Retrieve Location Data From Specified Field
    • Round Numbers Up to Nearest Integer
    • Rounding Within a Timechart
    • Rounding to n Decimal Places
    • S3 Archiving Backlog
    • SHA-1 Hash Multiple Fields
    • SHA-1 Hash a Field With a Given Value
    • SHA-256 Hash Multiple Fields
    • SHA-256 Hash a Field With a Given Value
    • Sample Event Streams - Example 1
    • Sample Event Streams - example 2
    • Search Accross Multiple Structured Fields
    • Search Fields Through a Given Pattern - Example 1
    • Search Fields Through a Given Pattern - Example 2
    • Search Fields Through a Given Pattern - Example 3
    • Search Fields Through a Given Pattern - Example 4
    • Search Fields Through a Given Pattern - Example 5
    • Search For Events by Number of Fields in Repository
    • Search Multiple Fields Through a Given Pattern
    • Search Relative Time to Query Execution
    • Search Single Field for Multiple Values
    • Search Status Field for All Status Codes Starting With "1" or "2"
    • Search Two Fields for Multiple Values in Either First Field or Second Field
    • Search and Group File Hash Data Using Variables
    • Search for Command Line String
    • Search for Events by Size in Repository
    • Select Fields to Export
    • Set Default Values for Fields - Example 1
    • Set Default Values for Fields - Example 2
    • Set Default Values for Fields - Example 3
    • Set Relative Time Interval From Within Query
    • Set Specific Time Interval Based on Raw Epoch Timestamps From Within Query
    • Set Time Interval From Within Query with defineTable()
    • Set Values for Multiple Fields
    • Set a Field Value Based on Tag Value
    • Set the Value of a Field
    • Show Offline Nodes
    • Show Percentiles Across Multiple Buckets
    • Sort Timestamps With groupBy()
    • Split Comma-Separated Strings in Array Into New Array
    • Square Values in an Array
    • Standardize Values And Combine Into Single Field
    • Subtract Values From Two Fields
    • Take Field Names as Parameters
    • Track Event Size Within a Repository
    • Transpose a Basic Table
    • Truncate a String or Message
    • Use Multiple if() Functions
    • Using Ad-hoc Table With CSV File
Falcon LogScale Documentation
/ LogScale Query Examples

Search and Group File Hash Data Using Variables

Search for specific file hashes across systems using placeholder variables

Query

flowchart LR; %%{init: {"flowchart": {"defaultRenderer": "elk"}} }%% repo{{Events}} 1[/Filter/] 2[/Filter/] 3{{Aggregate}} result{{Result Set}} repo --> 1 1 --> 2 2 --> 3 3 --> result
logscale
MD5HashData=?PutMD5Here FileName=?PutFileNameHere SHA256HashData=?PutSHA256Here
("event_simpleName" = ImageHash OR event_simpleName = ProcessRollup2)
| groupBy([ComputerName, FileName, SHA256HashData])

Introduction

The groupBy() function can be used with placeholder variables to search for specific file hashes across systems, helping security analysts track known malicious files in their environment.

In this example, a query template is used with placeholder variables for hash values and filename, followed by the groupBy() function. This approach allows analysts to quickly search for known malicious files using their hash values and group the results by system, filename, and hash data.

Example incoming data might look like this:

@timestampevent_simpleNameComputerNameFileNameMD5HashDataSHA256HashDataFilePathFileSize
2025-01-15T08:00:00ZImageHashDESKTOP-A1notepad.exe5f356a2f870435769147c6981dd6a0d3e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855C:\Windows\System32\245760
2025-01-15T08:01:00ZProcessRollup2DESKTOP-B2putty.exed41d8cd98f00b204e9800998ecf8427e7b4d6361f3fca7c58a47f54f276197edf6bb698b4dd6d0729f76f271d45735beC:\Program Files\1024000
2025-01-15T08:02:00ZImageHashDESKTOP-A1badfile.exeaaf4c61ddcc5e8a2dabede0f3b482cd9d14a028c2a3a2bc9476102bb288234c415a2b01f828ea62ac5b3e42fC:\Users\Admin\Downloads\506880
2025-01-15T08:03:00ZProcessRollup2DESKTOP-C3cmd.exe5f356a2f870435769147c6981dd6a0d3e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855C:\Windows\System32\323584
2025-01-15T08:04:00ZImageHashDESKTOP-B2badfile.exeaaf4c61ddcc5e8a2dabede0f3b482cd9d14a028c2a3a2bc9476102bb288234c415a2b01f828ea62ac5b3e42fC:\Users\User1\Desktop\506880
2025-01-15T08:05:00ZProcessRollup2DESKTOP-A1winword.exe1234567890abcdef1234567890abcdefa1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6q7r8s9t0u1v2w3x4y5z6a7b8c9d0C:\Program Files\Microsoft Office\2048000
2025-01-15T08:06:00ZImageHashDESKTOP-C3badfile.exeaaf4c61ddcc5e8a2dabede0f3b482cd9d14a028c2a3a2bc9476102bb288234c415a2b01f828ea62ac5b3e42fC:\Users\Admin\Desktop\506880
2025-01-15T08:07:00ZProcessRollup2DESKTOP-B2excel.exe0987654321fedcba0987654321fedcba1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z7a8b9c0C:\Program Files\Microsoft Office\1536000

Step-by-Step

  1. Starting with the source repository events.

  2. flowchart LR; %%{init: {"flowchart": {"defaultRenderer": "elk"}} }%% repo{{Events}} 1[/Filter/] 2[/Filter/] 3{{Aggregate}} result{{Result Set}} repo --> 1 1 --> 2 2 --> 3 3 --> result style 1 fill:#ff0000,stroke-width:4px,stroke:#000;
    logscale
    MD5HashData=?PutMD5Here FileName=?PutFileNameHere SHA256HashData=?PutSHA256Here

    Defines search criteria using placeholder variables that can be replaced with actual values:

    • ?PutMD5Here: Insert a specific MD5 hash value (for example, aaf4c61ddcc5e8a2dabede0f3b482cd9).

    • ?PutFileNameHere: Insert a specific filename (for example, badfile.exe).

    • ?PutSHA256Here: Insert a specific SHA256 hash value (for example, d14a028c2a3a2bc9476102bb288234c415a2b01f828ea62ac5b3e42f).

  3. flowchart LR; %%{init: {"flowchart": {"defaultRenderer": "elk"}} }%% repo{{Events}} 1[/Filter/] 2[/Filter/] 3{{Aggregate}} result{{Result Set}} repo --> 1 1 --> 2 2 --> 3 3 --> result style 2 fill:#ff0000,stroke-width:4px,stroke:#000;
    logscale
    ("event_simpleName" = ImageHash OR event_simpleName = ProcessRollup2)

    Filters for specific event types that contain file hash information:

    • ImageHash: Events generated when DLL or executable images are loaded into memory.

    • ProcessRollup2: Events generated when processes are created or terminated.

  4. flowchart LR; %%{init: {"flowchart": {"defaultRenderer": "elk"}} }%% repo{{Events}} 1[/Filter/] 2[/Filter/] 3{{Aggregate}} result{{Result Set}} repo --> 1 1 --> 2 2 --> 3 3 --> result style 3 fill:#ff0000,stroke-width:4px,stroke:#000;
    logscale
    | groupBy([ComputerName, FileName, SHA256HashData])

    Groups the matching events by three key fields to show the distribution of the searched file across systems:

    • ComputerName: Shows which systems contain the file.

    • FileName: Shows if the same file appears under different names.

    • SHA256HashData: Confirms the file content matches across systems.

  5. Event Result set.

Summary and Results

The query is used to search for specific known files across all systems using their hash values and group the results to show their distribution in the environment.

This query is useful, for example, to track the spread of known malware, verify the presence of legitimate files, or identify renamed malicious files that maintain the same hash value.

Sample output when searching for a specific malicious file:

ComputerNameFileNameSHA256HashDataevent_simpleNameFilePathMD5HashDataFileSize
DESKTOP-A1badfile.exed14a028c2a3a2bc9476102bb288234c415a2b01f828ea62ac5b3e42fImageHashC:\Users\Admin\Downloads\aaf4c61ddcc5e8a2dabede0f3b482cd9506880
DESKTOP-B2badfile.exed14a028c2a3a2bc9476102bb288234c415a2b01f828ea62ac5b3e42fImageHashC:\Users\User1\Desktop\aaf4c61ddcc5e8a2dabede0f3b482cd9506880
DESKTOP-C3badfile.exed14a028c2a3a2bc9476102bb288234c415a2b01f828ea62ac5b3e42fImageHashC:\Users\Admin\Desktop\aaf4c61ddcc5e8a2dabede0f3b482cd9506880

Note how the suspicious file is present on three different systems and maintains consistent hash values and size across systems.

Also, the file appears in different user directories, suggesting possible user-initiated spread.

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  • Related Functions

    • select()
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    • Humio Server 1.56.2 LTS (2022-09-26)
    • Humio Server 1.56.3 LTS (2022-10-05)
    • Humio Server 1.56.4 LTS (2022-12-21)
    • Humio Server 1.60.0 GA (2022-10-04)
  • Breaking Change RN Entries

    • Falcon LogScale 1.120.0 GA (2024-01-09)
    • Falcon LogScale 1.124.1 LTS (2024-02-29)
    • Falcon LogScale 1.124.2 LTS (2024-03-20)
    • Falcon LogScale 1.124.3 LTS (2024-05-14)
  • Related Query Examples

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    • Alert Query For Parsers Issues
    • Analyze User Sessions Based on Click Activity
    • Calculate Events per Second by Host
    • Calculate Query Cost for All Users by Repository
    • Calculate Relationship Between X And Y Variables - Example 3
    • Calculate Total Network Bandwidth Per Host
    • Collect and Group Events by Specified Field - Example 1
    • Collect and Group Events by Specified Field - Example 2
    • Compute Cumulative Aggregation For Specific Group
    • Count Unique Visitors Based on Client IP Addresses
    • Create a Pivot Table
    • Deduplicate Content by Field
    • Detect All Occurrences of Event A Before Event B
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    • Filter Out Fields With No Value
    • Find Fields With Data in Class
    • Find Fields With S3Bucket in Class
    • Find Least Common Values of a Field
    • Find Matches in Array Given a Regular Expression - Example 1
    • Find Minimum And Maximum Values of any Numerical Field in Session
    • Find Overlapping User Sessions
    • Find Processes with Low Execution Count
    • Find Top N Value of Series - Example 1
    • Find Top N Value of Series - Example 2
    • Get List of Status Codes
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    • Group First Events by Log Level
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