Netskope - Excessive Downloads Detection (Spike vs Baseline)

Status: available
Severity: medium
Time window: 7d
Group by: CsUsername
Source: github.com/Azure/Azure-Sentinel

Detects users with excessive download activity compared to their 7-day baseline. Triggers when current download volume exceeds 3x the average.

MITRE ATT&CK coverage

Tactic	Techniques
Collection	`T1074` Data Staged, `T1530` Data from Cloud Storage

Rule body kusto

id: dd0ebd84-ffbe-45df-848b-0615ac446b04
name: Netskope - Excessive Downloads Detection (Spike vs Baseline)
description: |
  Detects users with excessive download activity compared to their 7-day baseline. Triggers when current download volume exceeds 3x the average.
severity: Medium
status: Available
requiredDataConnectors:
  - connectorId: NetskopeWebTxConnector
    dataTypes:
      - NetskopeWebTransactions_CL
queryFrequency: 1h
queryPeriod: 7d
triggerOperator: gt
triggerThreshold: 0
tactics:
  - Exfiltration
  - Collection
relevantTechniques:
  - T1530
  - T1074
query: |
  let lookbackPeriod = 7d;
  let currentPeriod = 1h;
  let threshold = 3;
  let baseline = NetskopeWebTransactions_CL
      | where TimeGenerated between (ago(lookbackPeriod) .. ago(currentPeriod))
      | where isnotempty(CsUsername)
      | where XCsAppActivity =~ 'Download' or ScBytes > 0
      | summarize 
          BaselineAvgBytes = avg(ScBytes),
          BaselineTotalBytes = sum(ScBytes),
          BaselineCount = count()
          by CsUsername
      | extend BaselineDailyAvg = BaselineTotalBytes / 7;
  let current = NetskopeWebTransactions_CL
      | where TimeGenerated > ago(currentPeriod)
      | where isnotempty(CsUsername)
      | where XCsAppActivity =~ 'Download' or ScBytes > 0
      | summarize 
          CurrentTotalBytes = sum(ScBytes),
          CurrentCount = count(),
          Apps = make_set(XCsApp),
          Files = make_set(XCsAppObjectName)
          by CsUsername;
  current
  | join kind=inner baseline on CsUsername
  | where CurrentTotalBytes > (BaselineDailyAvg * threshold)
  | extend 
      SpikeMultiplier = round(CurrentTotalBytes / BaselineDailyAvg, 2),
      CurrentTotalMB = round(CurrentTotalBytes / 1048576.0, 2),
      BaselineDailyMB = round(BaselineDailyAvg / 1048576.0, 2)
  | project 
      TimeGenerated = now(),
      User = CsUsername,
      CurrentDownloadMB = CurrentTotalMB,
      BaselineDailyAvgMB = BaselineDailyMB,
      SpikeMultiplier,
      DownloadCount = CurrentCount,
      ApplicationsUsed = Apps,
      FilesDownloaded = Files
entityMappings:
  - entityType: Account
    fieldMappings:
      - identifier: Name
        columnName: User
version: 1.0.0
kind: Scheduled

Stages and Predicates

Parameters

let lookbackPeriod = 7d;
let currentPeriod = 1h;
let threshold = 3;

Let binding: `baseline`

let baseline = NetskopeWebTransactions_CL
    | where TimeGenerated between (ago(lookbackPeriod) .. ago(currentPeriod))
    | where isnotempty(CsUsername)
    | where XCsAppActivity =~ 'Download' or ScBytes > 0
    | summarize 
        BaselineAvgBytes = avg(ScBytes),
        BaselineTotalBytes = sum(ScBytes),
        BaselineCount = count()
        by CsUsername
    | extend BaselineDailyAvg = BaselineTotalBytes / 7;

Derived from lookbackPeriod, currentPeriod.

The stages below define let current (the rule's main pipeline source).

Stage 1: `source`

NetskopeWebTransactions_CL

Stage 2: `where`

| where TimeGenerated > ago(currentPeriod)

Stage 3: `where`

| where isnotempty(CsUsername)

Stage 4: `where`

| where XCsAppActivity =~ 'Download' or ScBytes > 0

Stage 5: `summarize`

| summarize 
        CurrentTotalBytes = sum(ScBytes),
        CurrentCount = count(),
        Apps = make_set(XCsApp),
        Files = make_set(XCsAppObjectName)
        by CsUsername

The stages below run on current (the outer pipeline).

Stage 6: `join`

current
| join kind=inner baseline on CsUsername

Stage 7: `where`

| where CurrentTotalBytes > (BaselineDailyAvg * threshold)

Stage 8: `extend`

| extend 
    SpikeMultiplier = round(CurrentTotalBytes / BaselineDailyAvg, 2),
    CurrentTotalMB = round(CurrentTotalBytes / 1048576.0, 2),
    BaselineDailyMB = round(BaselineDailyAvg / 1048576.0, 2)

Stage 9: `project`

| project 
    TimeGenerated = now(),
    User = CsUsername,
    CurrentDownloadMB = CurrentTotalMB,
    BaselineDailyAvgMB = BaselineDailyMB,
    SpikeMultiplier,
    DownloadCount = CurrentCount,
    ApplicationsUsed = Apps,
    FilesDownloaded = Files

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
`CsUsername`	is_not_null	(no value, null check)
`CurrentTotalBytes`	cross_field_compare	`BaselineDailyAvg` transforms: `op:gt`, `rhs:mul:3`
`ScBytes`	gt	`0` transforms: `cased`
`XCsAppActivity`	eq	`Download`

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
`ApplicationsUsed`	`project`
`BaselineDailyAvgMB`	`project`
`CurrentDownloadMB`	`project`
`DownloadCount`	`project`
`FilesDownloaded`	`project`
`SpikeMultiplier`	`project`
`TimeGenerated`	`project`
`User`	`project`

`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)

Netskope - Excessive Downloads Detection (Spike vs Baseline)

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Let binding: `baseline`

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `where`

Stage 5: `summarize`

Stage 6: `join`

Stage 7: `where`

Stage 8: `extend`

Stage 9: `project`

Indicators

Output fields

Keyboard shortcuts

Search operators

Netskope - Excessive Downloads Detection (Spike vs Baseline)

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Let binding: baseline

Stage 1: source

Stage 2: where

Stage 3: where

Stage 4: where

Stage 5: summarize

Stage 6: join

Stage 7: where

Stage 8: extend

Stage 9: project

Indicators

Output fields

Let binding: `baseline`

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `where`

Stage 5: `summarize`

Stage 6: `join`

Stage 7: `where`

Stage 8: `extend`

Stage 9: `project`