Detect presence of uncommon user agents in web requests (ASIM Web Session)

Status: available
Severity: medium
Time window: 14d
Group by: DstIpAddr, DstPortNumber, HttpUserAgent, SrcHostname, SrcIpAddr, SrcUsername, Url
Source: github.com/Azure/Azure-Sentinel

'This rule assists in detecting rare user agents, which may indicate web browsing activity by an unconventional process different from the usual ones. The rule specifically searches for UserAgent strings that have not been seen in the past 14 days. This query will perform better when run over summarized data'

MITRE ATT&CK coverage

Tactic	Techniques
Initial Access	`T1133` External Remote Services, `T1190` Exploit Public-Facing Application

Rule body kusto

id: 2d50d937-d7f2-4c05-b151-9af7f9ec747e
name: Detect presence of uncommon user agents in web requests (ASIM Web Session)
description: |
  'This rule assists in detecting rare user agents, which may indicate web browsing activity by an unconventional process different from the usual ones. The rule specifically searches for UserAgent strings that have not been seen in the past 14 days. This query will perform better when run over summarized data'
severity: Medium
status: Available 
tags:
  - Schema: WebSession
    SchemaVersion: 0.2.6
requiredDataConnectors: []
queryFrequency: 1h
queryPeriod: 14d
triggerOperator: gt
triggerThreshold: 0
tactics:
  - InitialAccess
relevantTechniques:
  - T1190
  - T1133
query: |
  let lookBack = 14d;
  let timeframe = 1h;
  // calculate avg. eps(events per second)
  let eps = materialize(_Im_WebSession(starttime=ago(1d))
      | project TimeGenerated
      | summarize AvgPerSec = count() / 3600 by bin(TimeGenerated, 1h)
      | summarize round(avg(AvgPerSec))
      );
  let summarizationexist  = (
      union isfuzzy=true 
          (
          WebSession_Summarized_SrcInfo_CL
          | where EventTime_t > ago(1d) 
          | project v = int(2)
          ),
          (
          print int(1) 
          | project v = print_0
          )
      | summarize maxv = max(v)
      | extend sumexist = (maxv > 1)
      );
  let allUserAgents = union isfuzzy=true
          (
          (datatable(exists: int, sumexist: bool)[1, false]
          | where toscalar(eps) > 1000
          | join (summarizationexist) on sumexist)
          | join (
              _Im_WebSession(starttime=todatetime(ago(2d)), endtime=bin(ago(timeframe), 1h), eventresult='Success')
              | where isnotempty(HttpUserAgent)
              | summarize UserAgentsSet =  make_set(HttpUserAgent) // This could contain upto 10,48,576 unique values
              | extend exists=int(1)
              )
              on exists
          | project-away exist*, maxv, sum*
          ),
          (
          (datatable(exists: int, sumexist: bool)[1, false]
          | where toscalar(eps) between (501 .. 1000)
          | join (summarizationexist) on sumexist)
          | join (
              _Im_WebSession(starttime=todatetime(ago(3d)), endtime=bin(ago(timeframe), 1h), eventresult='Success')
              | where isnotempty(HttpUserAgent)
              | summarize UserAgentsSet = make_set(HttpUserAgent) // This could contain upto 10,48,576 unique values
              | extend exists=int(1)
              )
              on exists
          | project-away exist*, maxv, sum*
          ),
          (
          (datatable(exists: int, sumexist: bool)[1, false]
          | where toscalar(eps) <= 500
          | join (summarizationexist) on sumexist)
          | join (
              _Im_WebSession(starttime=todatetime(ago(4d)), endtime=bin(ago(timeframe), 1h), eventresult='Success')
              | where isnotempty(HttpUserAgent)
              | summarize UserAgentsSet = make_set(HttpUserAgent) // This could contain upto 10,48,576 unique values
              | extend exists=int(1)
              )
              on exists
          | project-away exist*, maxv, sum*
          ),
          (
          WebSession_Summarized_SrcInfo_CL
          | where EventTime_t between (ago(14d) .. ago(timeframe))
              and isnotempty(HttpUserAgent_s)
              and EventResult_s =~ 'Success'
          | summarize UserAgentsSet = make_set(HttpUserAgent_s) // This could contain upto 10,48,576 unique values
          );
  _Im_WebSession (starttime=bin(ago(timeframe), 1h), eventresult='Success')
  | project
      SrcIpAddr,
      SrcUsername,
      SrcHostname,
      DstIpAddr,
      DstPortNumber,
      Url,
      HttpUserAgent,
      TimeGenerated
  | where isnotempty(HttpUserAgent) and HttpUserAgent !in~ (allUserAgents)
  | summarize
      EventCount=count(),
      EventStartTime=min(TimeGenerated),
      EventEndTime=max(TimeGenerated)
      by
      SrcIpAddr,
      SrcUsername,
      SrcHostname,
      DstIpAddr,
      Url,
      HttpUserAgent,
      DstPortNumber
  | extend Name = iif(SrcUsername contains "@", tostring(split(SrcUsername,'@',0)[0]),SrcUsername), UPNSuffix = iif(SrcUsername contains "@",tostring(split(SrcUsername,'@',1)[0]),"")
entityMappings:
  - entityType: URL
    fieldMappings:
      - identifier: Url
        columnName: Url
  - entityType: IP
    fieldMappings:
      - identifier: Address
        columnName: SrcIpAddr
  - entityType: IP
    fieldMappings:
      - identifier: Address
        columnName: DstIpAddr
  - entityType: Account
    fieldMappings:
      - identifier: Name
        columnName: Name
      - identifier: UPNSuffix
        columnName: UPNSuffix
  - entityType: Host
    fieldMappings:
      - identifier: HostName
        columnName: SrcHostname
eventGroupingSettings:
  aggregationKind: AlertPerResult
customDetails:
  EventCount: EventCount
  EventStartTime: EventStartTime
  EventEndTime: EventEndTime
  HttpUserAgent: HttpUserAgent
  DstPortNumber: DstPortNumber
alertDetailsOverride:
  alertDisplayNameFormat: "User '{{SrcUsername}}' with IP '{{SrcIpAddr}}' has been observed accessing URL '{{Url}}' using a rare user agent."
  alertDescriptionFormat: "The user agent '{{HttpUserAgent}}' has not been observed in the past 14 days. Conduct research on the user agent string to determine if it is associated with a known legitimate bot or if it is potentially linked to malicious activity. The URL is associated with the IP address '{{DstIpAddr}}'."
version: 1.0.1
kind: Scheduled

Stages and Predicates

Parameters

let lookBack = 14d;
let timeframe = 1h;

Let binding: `eps`

let eps = materialize(_Im_WebSession(starttime=ago(1d))
    | project TimeGenerated
    | summarize AvgPerSec = count() / 3600 by bin(TimeGenerated, 1h)
    | summarize round(avg(AvgPerSec))
    );

Let binding: `summarizationexist`

let summarizationexist = (
    union isfuzzy=true 
        (
        WebSession_Summarized_SrcInfo_CL
        | where EventTime_t > ago(1d) 
        | project v = int(2)
        ),
        (
        print int(1) 
        | project v = print_0
        )
    | summarize maxv = max(v)
    | extend sumexist = (maxv > 1)
    );

Let binding: `allUserAgents`

let allUserAgents = union isfuzzy=true
        (
        (datatable(exists: int, sumexist: bool)[1, false]
        | where toscalar(eps) > 1000
        | join (summarizationexist) on sumexist)
        | join (
            _Im_WebSession(starttime=todatetime(ago(2d)), endtime=bin(ago(timeframe), 1h), eventresult='Success')
            | where isnotempty(HttpUserAgent)
            | summarize UserAgentsSet =  make_set(HttpUserAgent)
            | extend exists=int(1)
            )
            on exists
        | project-away exist*, maxv, sum*
        ),
        (
        (datatable(exists: int, sumexist: bool)[1, false]
        | where toscalar(eps) between (501 .. 1000)
        | join (summarizationexist) on sumexist)
        | join (
            _Im_WebSession(starttime=todatetime(ago(3d)), endtime=bin(ago(timeframe), 1h), eventresult='Success')
            | where isnotempty(HttpUserAgent)
            | summarize UserAgentsSet = make_set(HttpUserAgent)
            | extend exists=int(1)
            )
            on exists
        | project-away exist*, maxv, sum*
        ),
        (
        (datatable(exists: int, sumexist: bool)[1, false]
        | where toscalar(eps) <= 500
        | join (summarizationexist) on sumexist)
        | join (
            _Im_WebSession(starttime=todatetime(ago(4d)), endtime=bin(ago(timeframe), 1h), eventresult='Success')
            | where isnotempty(HttpUserAgent)
            | summarize UserAgentsSet = make_set(HttpUserAgent)
            | extend exists=int(1)
            )
            on exists
        | project-away exist*, maxv, sum*
        ),
        (
        WebSession_Summarized_SrcInfo_CL
        | where EventTime_t between (ago(14d) .. ago(timeframe))
            and isnotempty(HttpUserAgent_s)
            and EventResult_s =~ 'Success'
        | summarize UserAgentsSet = make_set(HttpUserAgent_s)
        );

Derived from timeframe, eps, summarizationexist.

Stage 1: `source`

_Im_WebSession (starttime=bin(ago(timeframe), 1h), eventresult='Success')

Stage 2: `project`

| project
    SrcIpAddr,
    SrcUsername,
    SrcHostname,
    DstIpAddr,
    DstPortNumber,
    Url,
    HttpUserAgent,
    TimeGenerated

Stage 3: `where`

| where isnotempty(HttpUserAgent) and HttpUserAgent !in~ (allUserAgents)

References allUserAgents (defined above).

Stage 4: `summarize`

| summarize
    EventCount=count(),
    EventStartTime=min(TimeGenerated),
    EventEndTime=max(TimeGenerated)
    by
    SrcIpAddr,
    SrcUsername,
    SrcHostname,
    DstIpAddr,
    Url,
    HttpUserAgent,
    DstPortNumber

Stage 5: `extend`

| extend Name = iif(SrcUsername contains "@", tostring(split(SrcUsername,'@',0)[0]),SrcUsername), UPNSuffix = iif(SrcUsername contains "@",tostring(split(SrcUsername,'@',1)[0]),"")

Exclusions

Top-level NOT(...) conjuncts: predicates this rule actively suppresses.

Field	Kind	Excluded values
`HttpUserAgent`	eq	`allUserAgents`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

Field	Kind	Values
`HttpUserAgent`	is_not_null	(no value, null check)

Output fields

Fields the rule emits when it matches. Chronicle authors list these in the outcome block; they appear on the detection and $risk_score drives alerting. Sentinel / Defender XDR rules build them up through project / summarize / extend stages. Sentinel maps these into alert fields via entityMappings and customDetails; Defender XDR custom detections surface them as alert fields directly.

Field	Source
`DstIpAddr`	`summarize`
`DstPortNumber`	`summarize`
`EventCount`	`summarize`
`EventEndTime`	`summarize`
`EventStartTime`	`summarize`
`HttpUserAgent`	`summarize`
`SrcHostname`	`summarize`
`SrcIpAddr`	`summarize`
`SrcUsername`	`summarize`
`Url`	`summarize`
`Name`	`extend`
`UPNSuffix`	`extend`

`j` / `k`	Scroll down / up
`d` / `u`	Half-page down / up
`gg` / `G`	Top / bottom
`h` / `l`	History back / forward
`f`	Follow link (`Shift` = new tab)
`/`	Focus search
`?`	Toggle this help
`↑` / `↓`	Navigate search results
`Enter`	Open highlighted result
`Esc`	Close results / dialog

`type:`	`events` / `rules` / `providers`
`vendor:`	`sigma` / `elastic` / `splunk` / `kusto` / `chronicle` (vendor name alone also works: `sigma:`, `kql:`, `secops:`…)
`tactic:`	TA-id, slug, or name: `credential_access`, `TA0006`
`technique:`	technique or sub-technique ID: `T1003`, `T1003.001` (alias `tech:`)
`severity:`	`critical` / `high` / `medium` / `low` / `informational` (alias `sev:`)
`risk_score`	Numeric comparison on the Elastic risk score (0 to 100): `risk_score>50`, `risk_score<=20`, `risk_score=99` (alias `risk`; Elastic rules only)
`stages:`	Rules with exactly N pipeline stages
`correlation:`	`single_event` / `sequence` / `alternatives` / `alternatives_cross_log` / `all_required` / `correlated`
`with:`	Co-occurrence event-id; stacks (`with:4624 with:4769`) to require all, while a comma list in one occurrence (`with:4624,4769`) is an either-or group. Implies multi-event
`like:`	Structural neighbors of a rule slug (equivalents + subsumption stricter / broader): `like:comsvcs_lsass_memory_dump-splunk-sysmon`
`groupby:`	Entity-grouping substring match against `group_by_keys`: `groupby:user`, `groupby:host`
`uses:`	Rules whose predicate tree touches the field (any kind, any value): `uses:CommandLine`
`excludes:`	Rules with top-level `not()` clauses on the field (FP whitelists): `excludes:ParentImage`
`field:` / `value:`	Predicate search; narrows rule cards to those with a matching leaf and drives the indicator tier. Unquoted = substring, wildcards allowed (`value:mimikatz`)
`indicator:`	Shorthand for `field:F value:V`: `indicator:Image=*\powershell.exe`
`kind:`	Filter by predicate kind. Narrows rule cards to those carrying a matching predicate leaf (`vendor:elastic kind:cidr_match`) and drives the indicator tier: `contains` / `starts_with` / `ends_with` / `regex` / `cidr` / `eq` / `in` … (operator aliases `op:`/`match:`)
`has:` / `no:`	`sample`, `field`, `notes`, `refs`, `trace`, `thirdparty`, `rule`, `pattern`, `timewindow`, `threshold`, `newterms`, `sigma`/`elastic`/`splunk`/`kusto`/`chronicle`
`-op:val`	Exclude matches; works on most operators but not `type:`/`like:`/`has:`/`no:` (use `no:<flag>` to exclude a rule flag): `tactic:execution -vendor:splunk`. Standalone `-kind:`/`-field:`/`-value:` drop every rule carrying a matching predicate leaf (`type:rules -kind:is_null`)
`field:"…"` / `value:"…"`	Quoted value = anchored exact match (also allows spaces): `value:"net user"`
`a,b`	Comma = OR inside one operator (`vendor:sigma,elastic`, `severity:high,critical`); repeating a facet merges the same way. `field:`/`value:` never split (literal commas)
`vendors:` / `stage:`	Singular and plural spellings fold to the canonical operator and value: `tactics:` = `tactic:`, `type:event` = `type:events`, `correlation:sequences` = `correlation:sequence`, `has:thresholds` = `has:threshold`
`"quoted phrase"`	Exact-match a multi-word phrase (free text)

Detect presence of uncommon user agents in web requests (ASIM Web Session)

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Let binding: `eps`

Let binding: `summarizationexist`

Let binding: `allUserAgents`

Stage 1: `source`

Stage 2: `project`

Stage 3: `where`

Stage 4: `summarize`

Stage 5: `extend`

Exclusions

Indicators

Output fields

Keyboard shortcuts

Search operators

Detect presence of uncommon user agents in web requests (ASIM Web Session)

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Let binding: eps

Let binding: summarizationexist

Let binding: allUserAgents

Stage 1: source

Stage 2: project

Stage 3: where

Stage 4: summarize

Stage 5: extend

Exclusions

Indicators

Output fields

Let binding: `eps`

Let binding: `summarizationexist`

Let binding: `allUserAgents`

Stage 1: `source`

Stage 2: `project`

Stage 3: `where`

Stage 4: `summarize`

Stage 5: `extend`